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Posted to commits@predictionio.apache.org by do...@apache.org on 2016/07/20 19:09:36 UTC
[01/51] [partial] incubator-predictionio-site git commit: Initial doc
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http://git-wip-us.apache.org/repos/asf/incubator-predictionio-site/blob/92a45fa4/templates/ecommercerecommendation/how-to/index.html
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+fbq('track', "PageView");</script><script src="//use.typekit.net/mut4mjx.js"></script><script>try{Typekit.load();}catch(e){}</script></head><body><div id="global"><header><div class="container" id="header-wrapper"><div class="row"><div class="col-sm-12"><div id="logo-wrapper"><span id="drawer-toggle"></span><a href="#"></a><a href="http://prediction.io/"><img alt="PredictionIO" id="logo" src="/images/logos/logo-ee2b9bb3.png"/></a></div><div id="menu-wrapper"><div id="header-nav-options-wrapper"><ul><li><a href="/">Install & Doc</a></li> <li><a href="/support">Support</a></li> </ul></div><div id="pill-wrapper"><a class="pill left" href="//templates.prediction.io/">TEMPLATES</a> <a class="pill right" href="//github.com/PredictionIO/PredictionIO/">OPEN SOURCE</a></div></div><img class="mobile-search-bar-toggler hidden-md hidden-lg" src="/images/icons/search-glass-704bd4ff.png"/></div></div></div></header><div id="search-bar-row-wrapper"><div class="container-fluid" id="search-bar-row">
<div class="row"><div class="col-md-9 col-sm-11 col-xs-11"><div class="hidden-md hidden-lg" id="mobile-page-heading-wrapper"><p>PredictionIO Docs</p><h4>How-To (E-Commerce Recommendation)</h4></div><h4 class="hidden-sm hidden-xs">PredictionIO Docs</h4></div><div class="col-md-3 col-sm-1 col-xs-1 hidden-md hidden-lg"><img id="left-menu-indicator" src="/images/icons/down-arrow-dfe9f7fe.png"/></div><div class="col-md-3 col-sm-12 col-xs-12 swiftype-wrapper"><div class="swiftype"><form class="search-form"><img class="search-box-toggler hidden-xs hidden-sm" src="/images/icons/search-glass-704bd4ff.png"/><div class="search-box"><img src="/images/icons/search-glass-704bd4ff.png"/><input type="text" id="st-search-input" class="st-search-input" placeholder="Search Doc..."/></div><img class="swiftype-row-hider hidden-md hidden-lg" src="/images/icons/drawer-toggle-active-fcbef12a.png"/></form></div></div><div class="mobile-left-menu-toggler hidden-md hidden-lg"></div></div></div></div><div id="
page" class="container-fluid"><div class="row"><div id="left-menu-wrapper" class="col-md-3"><nav id="nav-main"><ul><li class="level-1"><a class="expandible" href="/"><span>Apache PredictionIO (incubating) Documentation</span></a><ul><li class="level-2"><a class="final" href="/"><span>Welcome to Apache PredictionIO (incubating)</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Getting Started</span></a><ul><li class="level-2"><a class="final" href="/start/"><span>A Quick Intro</span></a></li><li class="level-2"><a class="final" href="/install/"><span>Installing Apache PredictionIO (incubating)</span></a></li><li class="level-2"><a class="final" href="/start/download/"><span>Downloading an Engine Template</span></a></li><li class="level-2"><a class="final" href="/start/deploy/"><span>Deploying Your First Engine</span></a></li><li class="level-2"><a class="final" href="/start/customize/"><span>Customizing the Engine</span></a></li></ul></li><li class="le
vel-1"><a class="expandible" href="#"><span>Integrating with Your App</span></a><ul><li class="level-2"><a class="final" href="/appintegration/"><span>App Integration Overview</span></a></li><li class="level-2"><a class="expandible" href="/sdk/"><span>List of SDKs</span></a><ul><li class="level-3"><a class="final" href="/sdk/java/"><span>Java & Android SDK</span></a></li><li class="level-3"><a class="final" href="/sdk/php/"><span>PHP SDK</span></a></li><li class="level-3"><a class="final" href="/sdk/python/"><span>Python SDK</span></a></li><li class="level-3"><a class="final" href="/sdk/ruby/"><span>Ruby SDK</span></a></li><li class="level-3"><a class="final" href="/sdk/community/"><span>Community Powered SDKs</span></a></li></ul></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Deploying an Engine</span></a><ul><li class="level-2"><a class="final" href="/deploy/"><span>Deploying as a Web Service</span></a></li><li class="level-2"><a class="final" href="/cli/#e
ngine-commands"><span>Engine Command-line Interface</span></a></li><li class="level-2"><a class="final" href="/deploy/engineparams/"><span>Setting Engine Parameters</span></a></li><li class="level-2"><a class="final" href="/deploy/enginevariants/"><span>Deploying Multiple Engine Variants</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Customizing an Engine</span></a><ul><li class="level-2"><a class="final" href="/customize/"><span>Learning DASE</span></a></li><li class="level-2"><a class="final" href="/customize/dase/"><span>Implement DASE</span></a></li><li class="level-2"><a class="final" href="/customize/troubleshooting/"><span>Troubleshooting Engine Development</span></a></li><li class="level-2"><a class="final" href="/api/current/#package"><span>Engine Scala APIs</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Collecting and Analyzing Data</span></a><ul><li class="level-2"><a class="final" href="/datacollection
/"><span>Event Server Overview</span></a></li><li class="level-2"><a class="final" href="/cli/#event-server-commands"><span>Event Server Command-line Interface</span></a></li><li class="level-2"><a class="final" href="/datacollection/eventapi/"><span>Collecting Data with REST/SDKs</span></a></li><li class="level-2"><a class="final" href="/datacollection/eventmodel/"><span>Events Modeling</span></a></li><li class="level-2"><a class="final" href="/datacollection/webhooks/"><span>Unifying Multichannel Data with Webhooks</span></a></li><li class="level-2"><a class="final" href="/datacollection/channel/"><span>Channel</span></a></li><li class="level-2"><a class="final" href="/datacollection/batchimport/"><span>Importing Data in Batch</span></a></li><li class="level-2"><a class="final" href="/datacollection/analytics/"><span>Using Analytics Tools</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Choosing an Algorithm(s)</span></a><ul><li class="level-2"><a
class="final" href="/algorithm/"><span>Built-in Algorithm Libraries</span></a></li><li class="level-2"><a class="final" href="/algorithm/switch/"><span>Switching to Another Algorithm</span></a></li><li class="level-2"><a class="final" href="/algorithm/multiple/"><span>Combining Multiple Algorithms</span></a></li><li class="level-2"><a class="final" href="/algorithm/custom/"><span>Adding Your Own Algorithms</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>ML Tuning and Evaluation</span></a><ul><li class="level-2"><a class="final" href="/evaluation/"><span>Overview</span></a></li><li class="level-2"><a class="final" href="/evaluation/paramtuning/"><span>Hyperparameter Tuning</span></a></li><li class="level-2"><a class="final" href="/evaluation/evaluationdashboard/"><span>Evaluation Dashboard</span></a></li><li class="level-2"><a class="final" href="/evaluation/metricchoose/"><span>Choosing Evaluation Metrics</span></a></li><li class="level-2"><a class=
"final" href="/evaluation/metricbuild/"><span>Building Evaluation Metrics</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>System Architecture</span></a><ul><li class="level-2"><a class="final" href="/system/"><span>Architecture Overview</span></a></li><li class="level-2"><a class="final" href="/system/anotherdatastore/"><span>Using Another Data Store</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Engine Template Gallery</span></a><ul><li class="level-2"><a class="final" href="http://templates.prediction.io"><span>Browse</span></a></li><li class="level-2"><a class="final" href="/community/submit-template/"><span>Submit your Engine as a Template</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Demo Tutorials</span></a><ul><li class="level-2"><a class="final" href="/demo/tapster/"><span>Comics Recommendation Demo</span></a></li><li class="level-2"><a class="final" href="/demo/community
/"><span>Community Contributed Demo</span></a></li><li class="level-2"><a class="final" href="/demo/textclassification/"><span>Text Classification Engine Tutorial</span></a></li></ul></li><li class="level-1"><a class="expandible" href="/community/"><span>Getting Involved</span></a><ul><li class="level-2"><a class="final" href="/community/contribute-code/"><span>Contribute Code</span></a></li><li class="level-2"><a class="final" href="/community/contribute-documentation/"><span>Contribute Documentation</span></a></li><li class="level-2"><a class="final" href="/community/contribute-sdk/"><span>Contribute a SDK</span></a></li><li class="level-2"><a class="final" href="/community/contribute-webhook/"><span>Contribute a Webhook</span></a></li><li class="level-2"><a class="final" href="/community/projects/"><span>Community Projects</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Getting Help</span></a><ul><li class="level-2"><a class="final" href="/resour
ces/faq/"><span>FAQs</span></a></li><li class="level-2"><a class="final" href="/support/"><span>Community Support</span></a></li><li class="level-2"><a class="final" href="/support/#enterprise-support"><span>Enterprise Support</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Resources</span></a><ul><li class="level-2"><a class="final" href="/resources/intellij/"><span>Developing Engines with IntelliJ IDEA</span></a></li><li class="level-2"><a class="final" href="/resources/upgrade/"><span>Upgrade Instructions</span></a></li><li class="level-2"><a class="final" href="/resources/glossary/"><span>Glossary</span></a></li></ul></li></ul></nav></div><div class="col-md-9 col-sm-12"><div class="content-header hidden-md hidden-lg"><div id="page-title"><h1>How-To (E-Commerce Recommendation)</h1></div></div><div id="table-of-content-wrapper"><a id="edit-page-link" href="https://github.com/apache/incubator-predictionio/tree/livedoc/docs/manual/source/templates/e
commercerecommendation/how-to.html.md"><img src="/images/icons/edit-pencil-d6c1bb3d.png"/>Edit this page</a></div><div class="content-header hidden-sm hidden-xs"><div id="page-title"><h1>How-To (E-Commerce Recommendation)</h1></div></div><div class="content"><p>Here are the pages that show you how you can customize the E-Commerce Recommendation engine template.</p> <ul> <li><a href="/templates/ecommercerecommendation/train-with-rate-event/">Train with Rate Event</a></li> </ul> </div></div></div></div><footer><div class="container"><div class="seperator"></div><div class="row"><div class="col-md-4 col-md-push-8 col-xs-12"><div class="subscription-form-wrapper"><h4>Subscribe to our Newsletter</h4><form class="ajax-form" id="subscribe-form" method="POST" action="https://script.google.com/macros/s/AKfycbwhzeKCQJjQ52eVAqNT_vcklH07OITUO7wzOMDXvK6EGAWgaZgF/exec"><input class="required underlined-input" type="email" placeholder="Your email address" name="subscription_email" id="subscription
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[22/51] [partial] incubator-predictionio-site git commit: Initial doc
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Posted by do...@apache.org.
http://git-wip-us.apache.org/repos/asf/incubator-predictionio-site/blob/92a45fa4/resources/glossary/index.html
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<div class="row"><div class="col-md-9 col-sm-11 col-xs-11"><div class="hidden-md hidden-lg" id="mobile-page-heading-wrapper"><p>PredictionIO Docs</p><h4>Glossary</h4></div><h4 class="hidden-sm hidden-xs">PredictionIO Docs</h4></div><div class="col-md-3 col-sm-1 col-xs-1 hidden-md hidden-lg"><img id="left-menu-indicator" src="/images/icons/down-arrow-dfe9f7fe.png"/></div><div class="col-md-3 col-sm-12 col-xs-12 swiftype-wrapper"><div class="swiftype"><form class="search-form"><img class="search-box-toggler hidden-xs hidden-sm" src="/images/icons/search-glass-704bd4ff.png"/><div class="search-box"><img src="/images/icons/search-glass-704bd4ff.png"/><input type="text" id="st-search-input" class="st-search-input" placeholder="Search Doc..."/></div><img class="swiftype-row-hider hidden-md hidden-lg" src="/images/icons/drawer-toggle-active-fcbef12a.png"/></form></div></div><div class="mobile-left-menu-toggler hidden-md hidden-lg"></div></div></div></div><div id="page" class="container-flu
id"><div class="row"><div id="left-menu-wrapper" class="col-md-3"><nav id="nav-main"><ul><li class="level-1"><a class="expandible" href="/"><span>Apache PredictionIO (incubating) Documentation</span></a><ul><li class="level-2"><a class="final" href="/"><span>Welcome to Apache PredictionIO (incubating)</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Getting Started</span></a><ul><li class="level-2"><a class="final" href="/start/"><span>A Quick Intro</span></a></li><li class="level-2"><a class="final" href="/install/"><span>Installing Apache PredictionIO (incubating)</span></a></li><li class="level-2"><a class="final" href="/start/download/"><span>Downloading an Engine Template</span></a></li><li class="level-2"><a class="final" href="/start/deploy/"><span>Deploying Your First Engine</span></a></li><li class="level-2"><a class="final" href="/start/customize/"><span>Customizing the Engine</span></a></li></ul></li><li class="level-1"><a class="expandibl
e" href="#"><span>Integrating with Your App</span></a><ul><li class="level-2"><a class="final" href="/appintegration/"><span>App Integration Overview</span></a></li><li class="level-2"><a class="expandible" href="/sdk/"><span>List of SDKs</span></a><ul><li class="level-3"><a class="final" href="/sdk/java/"><span>Java & Android SDK</span></a></li><li class="level-3"><a class="final" href="/sdk/php/"><span>PHP SDK</span></a></li><li class="level-3"><a class="final" href="/sdk/python/"><span>Python SDK</span></a></li><li class="level-3"><a class="final" href="/sdk/ruby/"><span>Ruby SDK</span></a></li><li class="level-3"><a class="final" href="/sdk/community/"><span>Community Powered SDKs</span></a></li></ul></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Deploying an Engine</span></a><ul><li class="level-2"><a class="final" href="/deploy/"><span>Deploying as a Web Service</span></a></li><li class="level-2"><a class="final" href="/cli/#engine-commands"><span>Engi
ne Command-line Interface</span></a></li><li class="level-2"><a class="final" href="/deploy/engineparams/"><span>Setting Engine Parameters</span></a></li><li class="level-2"><a class="final" href="/deploy/enginevariants/"><span>Deploying Multiple Engine Variants</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Customizing an Engine</span></a><ul><li class="level-2"><a class="final" href="/customize/"><span>Learning DASE</span></a></li><li class="level-2"><a class="final" href="/customize/dase/"><span>Implement DASE</span></a></li><li class="level-2"><a class="final" href="/customize/troubleshooting/"><span>Troubleshooting Engine Development</span></a></li><li class="level-2"><a class="final" href="/api/current/#package"><span>Engine Scala APIs</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Collecting and Analyzing Data</span></a><ul><li class="level-2"><a class="final" href="/datacollection/"><span>Event Server Over
view</span></a></li><li class="level-2"><a class="final" href="/cli/#event-server-commands"><span>Event Server Command-line Interface</span></a></li><li class="level-2"><a class="final" href="/datacollection/eventapi/"><span>Collecting Data with REST/SDKs</span></a></li><li class="level-2"><a class="final" href="/datacollection/eventmodel/"><span>Events Modeling</span></a></li><li class="level-2"><a class="final" href="/datacollection/webhooks/"><span>Unifying Multichannel Data with Webhooks</span></a></li><li class="level-2"><a class="final" href="/datacollection/channel/"><span>Channel</span></a></li><li class="level-2"><a class="final" href="/datacollection/batchimport/"><span>Importing Data in Batch</span></a></li><li class="level-2"><a class="final" href="/datacollection/analytics/"><span>Using Analytics Tools</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Choosing an Algorithm(s)</span></a><ul><li class="level-2"><a class="final" href="/algor
ithm/"><span>Built-in Algorithm Libraries</span></a></li><li class="level-2"><a class="final" href="/algorithm/switch/"><span>Switching to Another Algorithm</span></a></li><li class="level-2"><a class="final" href="/algorithm/multiple/"><span>Combining Multiple Algorithms</span></a></li><li class="level-2"><a class="final" href="/algorithm/custom/"><span>Adding Your Own Algorithms</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>ML Tuning and Evaluation</span></a><ul><li class="level-2"><a class="final" href="/evaluation/"><span>Overview</span></a></li><li class="level-2"><a class="final" href="/evaluation/paramtuning/"><span>Hyperparameter Tuning</span></a></li><li class="level-2"><a class="final" href="/evaluation/evaluationdashboard/"><span>Evaluation Dashboard</span></a></li><li class="level-2"><a class="final" href="/evaluation/metricchoose/"><span>Choosing Evaluation Metrics</span></a></li><li class="level-2"><a class="final" href="/evaluation/
metricbuild/"><span>Building Evaluation Metrics</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>System Architecture</span></a><ul><li class="level-2"><a class="final" href="/system/"><span>Architecture Overview</span></a></li><li class="level-2"><a class="final" href="/system/anotherdatastore/"><span>Using Another Data Store</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Engine Template Gallery</span></a><ul><li class="level-2"><a class="final" href="http://templates.prediction.io"><span>Browse</span></a></li><li class="level-2"><a class="final" href="/community/submit-template/"><span>Submit your Engine as a Template</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Demo Tutorials</span></a><ul><li class="level-2"><a class="final" href="/demo/tapster/"><span>Comics Recommendation Demo</span></a></li><li class="level-2"><a class="final" href="/demo/community/"><span>Community Contrib
uted Demo</span></a></li><li class="level-2"><a class="final" href="/demo/textclassification/"><span>Text Classification Engine Tutorial</span></a></li></ul></li><li class="level-1"><a class="expandible" href="/community/"><span>Getting Involved</span></a><ul><li class="level-2"><a class="final" href="/community/contribute-code/"><span>Contribute Code</span></a></li><li class="level-2"><a class="final" href="/community/contribute-documentation/"><span>Contribute Documentation</span></a></li><li class="level-2"><a class="final" href="/community/contribute-sdk/"><span>Contribute a SDK</span></a></li><li class="level-2"><a class="final" href="/community/contribute-webhook/"><span>Contribute a Webhook</span></a></li><li class="level-2"><a class="final" href="/community/projects/"><span>Community Projects</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Getting Help</span></a><ul><li class="level-2"><a class="final" href="/resources/faq/"><span>FAQs</span
></a></li><li class="level-2"><a class="final" href="/support/"><span>Community Support</span></a></li><li class="level-2"><a class="final" href="/support/#enterprise-support"><span>Enterprise Support</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Resources</span></a><ul><li class="level-2"><a class="final" href="/resources/intellij/"><span>Developing Engines with IntelliJ IDEA</span></a></li><li class="level-2"><a class="final" href="/resources/upgrade/"><span>Upgrade Instructions</span></a></li><li class="level-2"><a class="final active" href="/resources/glossary/"><span>Glossary</span></a></li></ul></li></ul></nav></div><div class="col-md-9 col-sm-12"><div class="content-header hidden-md hidden-lg"><div id="breadcrumbs" class="hidden-sm hidden xs"><ul><li><a href="#">Resources</a><span class="spacer">></span></li><li><span class="last">Glossary</span></li></ul></div><div id="page-title"><h1>Glossary</h1></div></div><div id="table-of-content-w
rapper"><a id="edit-page-link" href="https://github.com/apache/incubator-predictionio/tree/livedoc/docs/manual/source/resources/glossary.html.md"><img src="/images/icons/edit-pencil-d6c1bb3d.png"/>Edit this page</a></div><div class="content-header hidden-sm hidden-xs"><div id="breadcrumbs" class="hidden-sm hidden xs"><ul><li><a href="#">Resources</a><span class="spacer">></span></li><li><span class="last">Glossary</span></li></ul></div><div id="page-title"><h1>Glossary</h1></div></div><div class="content"><p><strong>Data Preparator</strong> - Part of Engine. It reads data from source and transforms it to the desired format.</p><p><strong>Data Source</strong> - Part of Engine. It preprocesses the data and forward it to the algorithm for model training.</p><p><strong>Engine</strong> - An Engine represents a type of prediction, e.g. product recommendation. It is comprised of four components: [D] Data Source and Data Preparator, [A] Algorithm, [S] Serving, [E] Evaluation Metrics.</p>
<p><strong>EngineClient</strong> - Part of PredictionSDK. It sends queries to a deployed engine instance through the Engine API and retrives prediction results.</p><p><strong>Event API</strong> - Please see Event Server.</p><p><strong>Event Server</strong> - Event Server is designed to collect data into PredictionIO in an event-based style. Once the Event Server is launched, your application can send data to it through its Event API with HTTP requests or with the EventClient of PredictionIO's SDKs.</p><p><strong>EventClient</strong> - Please see Event Server.</p><p><strong>Live Evaluation</strong> - Evaluation of prediction results in a production environment. Prediction results are shown to real users. Users do not rate the results explicitly but the system observes user behaviors such as click through rate.</p><p><strong>Offline Evaluation</strong> - The prediction results are compared with pre-compiled offline datasets. Typically, offline evaluations are meant to identify the
most promising approaches.</p><p><strong>Test Data</strong> - Also commonly referred as Test Set. A set of data used to assess the strength and utility of a predictive relationship.</p><p><strong>Training Data</strong> - Also commonly referred as Training Set. A set of data used to discover potentially predictive relationships. In PredictionIO Engine, training data is processed through the Data layer and passed onto algorithm.</p></div></div></div></div><footer><div class="container"><div class="seperator"></div><div class="row"><div class="col-md-4 col-md-push-8 col-xs-12"><div class="subscription-form-wrapper"><h4>Subscribe to our Newsletter</h4><form class="ajax-form" id="subscribe-form" method="POST" action="https://script.google.com/macros/s/AKfycbwhzeKCQJjQ52eVAqNT_vcklH07OITUO7wzOMDXvK6EGAWgaZgF/exec"><input class="required underlined-input" type="email" placeholder="Your email address" name="subscription_email" id="subscription_email"/><input class="pill-button" value="SUBS
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<div class="row"><div class="col-md-9 col-sm-11 col-xs-11"><div class="hidden-md hidden-lg" id="mobile-page-heading-wrapper"><p>PredictionIO Docs</p><h4>Developing Engines with IntelliJ IDEA</h4></div><h4 class="hidden-sm hidden-xs">PredictionIO Docs</h4></div><div class="col-md-3 col-sm-1 col-xs-1 hidden-md hidden-lg"><img id="left-menu-indicator" src="/images/icons/down-arrow-dfe9f7fe.png"/></div><div class="col-md-3 col-sm-12 col-xs-12 swiftype-wrapper"><div class="swiftype"><form class="search-form"><img class="search-box-toggler hidden-xs hidden-sm" src="/images/icons/search-glass-704bd4ff.png"/><div class="search-box"><img src="/images/icons/search-glass-704bd4ff.png"/><input type="text" id="st-search-input" class="st-search-input" placeholder="Search Doc..."/></div><img class="swiftype-row-hider hidden-md hidden-lg" src="/images/icons/drawer-toggle-active-fcbef12a.png"/></form></div></div><div class="mobile-left-menu-toggler hidden-md hidden-lg"></div></div></div></div><div i
d="page" class="container-fluid"><div class="row"><div id="left-menu-wrapper" class="col-md-3"><nav id="nav-main"><ul><li class="level-1"><a class="expandible" href="/"><span>Apache PredictionIO (incubating) Documentation</span></a><ul><li class="level-2"><a class="final" href="/"><span>Welcome to Apache PredictionIO (incubating)</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Getting Started</span></a><ul><li class="level-2"><a class="final" href="/start/"><span>A Quick Intro</span></a></li><li class="level-2"><a class="final" href="/install/"><span>Installing Apache PredictionIO (incubating)</span></a></li><li class="level-2"><a class="final" href="/start/download/"><span>Downloading an Engine Template</span></a></li><li class="level-2"><a class="final" href="/start/deploy/"><span>Deploying Your First Engine</span></a></li><li class="level-2"><a class="final" href="/start/customize/"><span>Customizing the Engine</span></a></li></ul></li><li class=
"level-1"><a class="expandible" href="#"><span>Integrating with Your App</span></a><ul><li class="level-2"><a class="final" href="/appintegration/"><span>App Integration Overview</span></a></li><li class="level-2"><a class="expandible" href="/sdk/"><span>List of SDKs</span></a><ul><li class="level-3"><a class="final" href="/sdk/java/"><span>Java & Android SDK</span></a></li><li class="level-3"><a class="final" href="/sdk/php/"><span>PHP SDK</span></a></li><li class="level-3"><a class="final" href="/sdk/python/"><span>Python SDK</span></a></li><li class="level-3"><a class="final" href="/sdk/ruby/"><span>Ruby SDK</span></a></li><li class="level-3"><a class="final" href="/sdk/community/"><span>Community Powered SDKs</span></a></li></ul></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Deploying an Engine</span></a><ul><li class="level-2"><a class="final" href="/deploy/"><span>Deploying as a Web Service</span></a></li><li class="level-2"><a class="final" href="/cli
/#engine-commands"><span>Engine Command-line Interface</span></a></li><li class="level-2"><a class="final" href="/deploy/engineparams/"><span>Setting Engine Parameters</span></a></li><li class="level-2"><a class="final" href="/deploy/enginevariants/"><span>Deploying Multiple Engine Variants</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Customizing an Engine</span></a><ul><li class="level-2"><a class="final" href="/customize/"><span>Learning DASE</span></a></li><li class="level-2"><a class="final" href="/customize/dase/"><span>Implement DASE</span></a></li><li class="level-2"><a class="final" href="/customize/troubleshooting/"><span>Troubleshooting Engine Development</span></a></li><li class="level-2"><a class="final" href="/api/current/#package"><span>Engine Scala APIs</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Collecting and Analyzing Data</span></a><ul><li class="level-2"><a class="final" href="/datacollect
ion/"><span>Event Server Overview</span></a></li><li class="level-2"><a class="final" href="/cli/#event-server-commands"><span>Event Server Command-line Interface</span></a></li><li class="level-2"><a class="final" href="/datacollection/eventapi/"><span>Collecting Data with REST/SDKs</span></a></li><li class="level-2"><a class="final" href="/datacollection/eventmodel/"><span>Events Modeling</span></a></li><li class="level-2"><a class="final" href="/datacollection/webhooks/"><span>Unifying Multichannel Data with Webhooks</span></a></li><li class="level-2"><a class="final" href="/datacollection/channel/"><span>Channel</span></a></li><li class="level-2"><a class="final" href="/datacollection/batchimport/"><span>Importing Data in Batch</span></a></li><li class="level-2"><a class="final" href="/datacollection/analytics/"><span>Using Analytics Tools</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Choosing an Algorithm(s)</span></a><ul><li class="level-2">
<a class="final" href="/algorithm/"><span>Built-in Algorithm Libraries</span></a></li><li class="level-2"><a class="final" href="/algorithm/switch/"><span>Switching to Another Algorithm</span></a></li><li class="level-2"><a class="final" href="/algorithm/multiple/"><span>Combining Multiple Algorithms</span></a></li><li class="level-2"><a class="final" href="/algorithm/custom/"><span>Adding Your Own Algorithms</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>ML Tuning and Evaluation</span></a><ul><li class="level-2"><a class="final" href="/evaluation/"><span>Overview</span></a></li><li class="level-2"><a class="final" href="/evaluation/paramtuning/"><span>Hyperparameter Tuning</span></a></li><li class="level-2"><a class="final" href="/evaluation/evaluationdashboard/"><span>Evaluation Dashboard</span></a></li><li class="level-2"><a class="final" href="/evaluation/metricchoose/"><span>Choosing Evaluation Metrics</span></a></li><li class="level-2"><a cla
ss="final" href="/evaluation/metricbuild/"><span>Building Evaluation Metrics</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>System Architecture</span></a><ul><li class="level-2"><a class="final" href="/system/"><span>Architecture Overview</span></a></li><li class="level-2"><a class="final" href="/system/anotherdatastore/"><span>Using Another Data Store</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Engine Template Gallery</span></a><ul><li class="level-2"><a class="final" href="http://templates.prediction.io"><span>Browse</span></a></li><li class="level-2"><a class="final" href="/community/submit-template/"><span>Submit your Engine as a Template</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Demo Tutorials</span></a><ul><li class="level-2"><a class="final" href="/demo/tapster/"><span>Comics Recommendation Demo</span></a></li><li class="level-2"><a class="final" href="/demo/commun
ity/"><span>Community Contributed Demo</span></a></li><li class="level-2"><a class="final" href="/demo/textclassification/"><span>Text Classification Engine Tutorial</span></a></li></ul></li><li class="level-1"><a class="expandible" href="/community/"><span>Getting Involved</span></a><ul><li class="level-2"><a class="final" href="/community/contribute-code/"><span>Contribute Code</span></a></li><li class="level-2"><a class="final" href="/community/contribute-documentation/"><span>Contribute Documentation</span></a></li><li class="level-2"><a class="final" href="/community/contribute-sdk/"><span>Contribute a SDK</span></a></li><li class="level-2"><a class="final" href="/community/contribute-webhook/"><span>Contribute a Webhook</span></a></li><li class="level-2"><a class="final" href="/community/projects/"><span>Community Projects</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Getting Help</span></a><ul><li class="level-2"><a class="final" href="/res
ources/faq/"><span>FAQs</span></a></li><li class="level-2"><a class="final" href="/support/"><span>Community Support</span></a></li><li class="level-2"><a class="final" href="/support/#enterprise-support"><span>Enterprise Support</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Resources</span></a><ul><li class="level-2"><a class="final active" href="/resources/intellij/"><span>Developing Engines with IntelliJ IDEA</span></a></li><li class="level-2"><a class="final" href="/resources/upgrade/"><span>Upgrade Instructions</span></a></li><li class="level-2"><a class="final" href="/resources/glossary/"><span>Glossary</span></a></li></ul></li></ul></nav></div><div class="col-md-9 col-sm-12"><div class="content-header hidden-md hidden-lg"><div id="breadcrumbs" class="hidden-sm hidden xs"><ul><li><a href="#">Resources</a><span class="spacer">></span></li><li><span class="last">Developing Engines with IntelliJ IDEA</span></li></ul></div><div id="page-title
"><h1>Developing Engines with IntelliJ IDEA</h1></div></div><div id="table-of-content-wrapper"><h5>On this page</h5><aside id="table-of-contents"><ul> <li> <a href="#prerequisites">Prerequisites</a> </li> <li> <a href="#preparing-intellij-for-engine-development">Preparing IntelliJ for Engine Development</a> </li> <li> <a href="#running-and-debugging-in-intellij-idea">Running and Debugging in IntelliJ IDEA</a> </li> <li> <a href="#loading-a-template-into-intellij-idea">Loading a Template Into Intellij IDEA</a> </li> </ul> </aside><hr/><a id="edit-page-link" href="https://github.com/apache/incubator-predictionio/tree/livedoc/docs/manual/source/resources/intellij.html.md.erb"><img src="/images/icons/edit-pencil-d6c1bb3d.png"/>Edit this page</a></div><div class="content-header hidden-sm hidden-xs"><div id="breadcrumbs" class="hidden-sm hidden xs"><ul><li><a href="#">Resources</a><span class="spacer">></span></li><li><span class="last">Developing Engines with IntelliJ IDEA</span></li>
</ul></div><div id="page-title"><h1>Developing Engines with IntelliJ IDEA</h1></div></div><div class="content"><h2 id='prerequisites' class='header-anchors'>Prerequisites</h2><p>This documentation assumes that you have a fully functional PredictionIO setup. If you have not installed PredictionIO yet, please follow <a href="/install/">these instructions</a>.</p><h2 id='preparing-intellij-for-engine-development' class='header-anchors'>Preparing IntelliJ for Engine Development</h2><h3 id='installing-intellij-scala-plugin' class='header-anchors'>Installing IntelliJ Scala Plugin</h3><p>First of all, you will need to install the <a href="https://plugins.jetbrains.com/plugin/?id=1347">Scala plugin</a> if you have not already done so.</p><p>Go to the <em>Preferences</em> menu item, and look for <em>Plugins</em>. You should see the following screen.</p><p><img alt="IntelliJ Plugins" src="/images/intellij/intelliJ-scala-plugin-09ee074a.png"/></p><p>Click <em>Install JetBrains plugin...</em>,
the search for <em>Scala</em>. You should arrive at something similar to the following.</p><p><img alt="Scala Plugin" src="/images/intellij/intellij-scala-plugin-2-592c697f.png"/></p><p>Click the green <em>Install plugin</em> button to install the plugin. Restart IntelliJ IDEA if asked to do so.</p><h3 id='setting-up-the-engine-directory' class='header-anchors'>Setting Up the Engine Directory</h3><div class="alert-message info"><p>It is very important to run at least <code>pio build</code> once in your engine directory so that the project correctly recognizes the version of PredictionIO that you are using. If you upgraded your PredictionIO installation later, you will need to run <code>pio build</code> again in order for the engine to pick up the latest version of PredictionIO.</p></div><p>Create an engine directory from a template. This requires that you install a template that you wish to start from or modify. Follow template <a href="/start/download">install</a> and <a href="/sta
rt/deploy">deploy</a> instructions or go through the <a href="/templates/recommendation/quickstart/">Quick Start</a> if you are planning to modify a recommender. Make sure to build, train, and deploy the engine to make sure all is configured properly.</p><p>From IntelliJ IDEA, choose <em>File</em> > <em>New</em> > <em>Project from Existing Sources...</em>. When asked to select a directory to import, browse to the engine directory that you downloaded too and proceed. Make sure you pick <em>Import project from external model</em> > <em>SBT</em>, then proceed to finish.</p><p>You should be able to build the project at this point. To run and debug PredictionIO server, continue on to the rest of the steps.</p><div class="alert-message info"><p>If you are running on OS X, you will need to do the following due to this <a href="http://bit.ly/12Abtvn">known issue</a>.</p></div><p>Edit <code>build.sbt</code> and add the following under <code>libraryDependencies</code></p><div class="
highlight shell"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1</pre></td><td class="code"><pre><span class="s2">"org.xerial.snappy"</span> % <span class="s2">"snappy-java"</span> % <span class="s2">"1.1.1.7"</span>
+</pre></td></tr></tbody></table> </div> <p><img alt="Updating build.sbt" src="/images/intellij/intellij-buildsbt-05cfd141.png"/></p><p>When you are done editing, IntelliJ should either refresh the project automatically or prompt you to refresh.</p><h3 id='dependencies' class='header-anchors'>Dependencies</h3><p>IntelliJ has the annoying tendency to drop some dependencies when you refresh your build.sbt after any changes. To avoid this we put any jars that must be available at runtime into a separate empty module in the project then we make the main engine project depend on this dummy module for runtime classes.</p><p>Right click on the project and click <em>Open Module Settings</em>. In the second modules column hit <strong>+</strong> and create a new Scala module. Name it pio-runtime-jars and add these assemblies under the module dependencies tab and remember to change the scope of the jars to <strong>runtime</strong>:</p> <ul> <li><p> <code>pio-assembly-0.9.6.jar</code></p><p>This
JAR can be found inside the <code>assembly</code> or <code>lib</code> directory of your PredictionIO installation directory.</p></li> <li><p> <code>spark-assembly-1.5.2-hadoop2.4.0.jar</code></p><p>This JAR can be found inside the <code>assembly</code> or <code>lib</code> directory of your Apache Spark installation directory.</p></li> </ul> <p><img alt="Create empty module and add dependencies" src="/images/intellij/pio-runtime-jar-deps-3f3c99d9.png"/></p><p>Now make your engine module dependent on the pio-runtime-jars module for scope = runtime. </p><p><img alt="Create empty module and add dependencies" src="/images/intellij/pio-runtime-jars-266e8c1b.png"/></p><h2 id='running-and-debugging-in-intellij-idea' class='header-anchors'>Running and Debugging in IntelliJ IDEA</h2><h3 id='simulating-<code>pio-train</code>' class='header-anchors' >Simulating <code>pio train</code></h3><p>Create a new <em>Run/Debug Configuration</em> by going to <em>Run</em> > <em>Edit Configurations...</
em>. Click on the <strong>+</strong> button and select <em>Application</em>. Name it <code>pio train</code> and put in the following.</p><div class="highlight shell"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1
+2
+3</pre></td><td class="code"><pre>Main class: io.prediction.workflow.CreateWorkflow
+VM options: -Dspark.master<span class="o">=</span><span class="nb">local</span> -Dlog4j.configuration<span class="o">=</span>file:/<span class="k">**</span>replace_with_your_PredictionIO_path<span class="k">**</span>/conf/log4j.properties
+Program arguments: --engine-id dummy --engine-version dummy --engine-variant engine.json
+</pre></td></tr></tbody></table> </div> <p>Click the <strong>...</strong> button to the right of <em>Environment variables</em>, and paste the following.</p><div class="highlight shell"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1
+2
+3
+4
+5
+6
+7
+8
+9
+10
+11
+12
+13
+14
+15
+16
+17
+18
+19
+20
+21</pre></td><td class="code"><pre><span class="nv">SPARK_HOME</span><span class="o">=</span>/<span class="k">**</span>reaplce_w_your_spark_binary_path<span class="k">**</span>
+<span class="nv">PIO_FS_BASEDIR</span><span class="o">=</span>/<span class="k">**</span>replace_w_your_path_to<span class="k">**</span>/.pio_store
+<span class="nv">PIO_FS_ENGINESDIR</span><span class="o">=</span>/<span class="k">**</span>replace_w_your_path_to<span class="k">**</span>/.pio_store/engines
+<span class="nv">PIO_FS_TMPDIR</span><span class="o">=</span>/<span class="k">**</span>replace_w_your_path_to<span class="k">*</span>/.pio_store/tmp
+<span class="nv">PIO_STORAGE_REPOSITORIES_METADATA_NAME</span><span class="o">=</span>predictionio_metadata
+<span class="nv">PIO_STORAGE_REPOSITORIES_METADATA_SOURCE</span><span class="o">=</span>ELASTICSEARCH
+<span class="nv">PIO_STORAGE_REPOSITORIES_MODELDATA_NAME</span><span class="o">=</span>pio_
+<span class="nv">PIO_STORAGE_REPOSITORIES_MODELDATA_SOURCE</span><span class="o">=</span>LOCALFS
+<span class="nv">PIO_STORAGE_REPOSITORIES_APPDATA_NAME</span><span class="o">=</span>predictionio_appdata
+<span class="nv">PIO_STORAGE_REPOSITORIES_APPDATA_SOURCE</span><span class="o">=</span>ELASTICSEARCH
+<span class="nv">PIO_STORAGE_REPOSITORIES_EVENTDATA_NAME</span><span class="o">=</span>predictionio_eventdata
+<span class="nv">PIO_STORAGE_REPOSITORIES_EVENTDATA_SOURCE</span><span class="o">=</span>HBASE
+<span class="nv">PIO_STORAGE_SOURCES_ELASTICSEARCH_TYPE</span><span class="o">=</span>elasticsearch
+<span class="nv">PIO_STORAGE_SOURCES_ELASTICSEARCH_HOSTS</span><span class="o">=</span>localhost
+<span class="nv">PIO_STORAGE_SOURCES_ELASTICSEARCH_PORTS</span><span class="o">=</span>9300
+<span class="nv">PIO_STORAGE_SOURCES_LOCALFS_TYPE</span><span class="o">=</span>localfs
+<span class="nv">PIO_STORAGE_SOURCES_LOCALFS_HOSTS</span><span class="o">=</span>/<span class="k">**</span>replace_w_your_path_to<span class="k">**</span>/.pio_store/models
+<span class="nv">PIO_STORAGE_SOURCES_LOCALFS_PORTS</span><span class="o">=</span>0
+<span class="nv">PIO_STORAGE_SOURCES_HBASE_TYPE</span><span class="o">=</span>hbase
+<span class="nv">PIO_STORAGE_SOURCES_HBASE_HOSTS</span><span class="o">=</span>0
+<span class="nv">PIO_STORAGE_SOURCES_HBASE_PORTS</span><span class="o">=</span>0
+</pre></td></tr></tbody></table> </div> <div class="alert-message info"><p>Remember to replace all paths that start with <code>**replace</code> with actual values. The directory <code>.pio_store</code> typically locates inside your home directory.</p></div><p>The end result should look something similar to this.</p><p><img alt="Run Configuration" src="/images/intellij/intellij-config-48c05039.png"/></p><p>Save and you can run or debug <code>pio train</code> with the new configuration!</p><h3 id='simulating-<code>pio-deploy</code>' class='header-anchors' >Simulating <code>pio deploy</code></h3><p>For <code>pio deploy</code>, simply duplicate the previous configuration and replace with the following.</p><div class="highlight shell"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1
+2</pre></td><td class="code"><pre>Main class: io.prediction.workflow.CreateServer
+Program Arguments: --engineInstanceId <span class="k">**</span>replace_with_the_id_from_pio_train<span class="k">**</span>
+</pre></td></tr></tbody></table> </div> <h3 id='executing-a-query' class='header-anchors'>Executing a Query</h3><p>You can execute a query with the correct SDK. For a recommender that has been trained with the sample MovieLens dataset perhaps the easiest query is a curl one. Start by running or debuging your <code>deploy</code> config so the service is waiting for the query. Then go to the "Terminal" tab at the very bottom of the IDEA window and enter the curl request:</p><p><code>$ curl -H "Content-Type: application/json" -d '{ "user": "1", "num": 4 }' http://localhost:8000/queries.json</code></p><p>This should return something like:</p><div class="highlight shell"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1
+2
+3
+4
+5
+6</pre></td><td class="code"><pre><span class="o">{</span><span class="s2">"itemScores"</span>:[
+ <span class="o">{</span><span class="s2">"item"</span>:<span class="s2">"52"</span>,<span class="s2">"score"</span>:9.582509402541834<span class="o">}</span>,
+ <span class="o">{</span><span class="s2">"item"</span>:<span class="s2">"95"</span>,<span class="s2">"score"</span>:8.017236650368387<span class="o">}</span>,
+ <span class="o">{</span><span class="s2">"item"</span>:<span class="s2">"89"</span>,<span class="s2">"score"</span>:6.975951244053634<span class="o">}</span>,
+ <span class="o">{</span><span class="s2">"item"</span>:<span class="s2">"34"</span>,<span class="s2">"score"</span>:6.857457277981334<span class="o">}</span>
+<span class="o">]}</span>
+</pre></td></tr></tbody></table> </div> <div class="alert-message info"><p>If you hit a breakpoint you are likely to get a connection timeout. To see the data that would have been returned, just place a breakpoint where the response is created or run the query with no breakpoints.</p></div><h2 id='loading-a-template-into-intellij-idea' class='header-anchors'>Loading a Template Into Intellij IDEA</h2><p>To customize an existing <a href="http://templates.prediction.io">template</a> using Intellij IDEA, first pull it from the template gallery:</p><div class="highlight shell"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1</pre></td><td class="code"><pre><span class="gp">$ </span>pio template get <Template Source> <New Engine Directory>
+</pre></td></tr></tbody></table> </div> <p>Now, before opening the template with Intellij, run the following command in the new engine template directory</p><div class="highlight shell"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1</pre></td><td class="code"><pre><span class="gp">$ </span>pio build
+</pre></td></tr></tbody></table> </div> <p>This should update the pioVersion key in SBT to the version of PredictionIO you have installed, so that Intellij loads the correct JARS via its Auto-Import feature. Now, you can go ahead and open the file <code>build.sbt</code> with Intellij IDEA. You are now ready to <a href="/customize/">customize</a> your new engine template.</p></div></div></div></div><footer><div class="container"><div class="seperator"></div><div class="row"><div class="col-md-4 col-md-push-8 col-xs-12"><div class="subscription-form-wrapper"><h4>Subscribe to our Newsletter</h4><form class="ajax-form" id="subscribe-form" method="POST" action="https://script.google.com/macros/s/AKfycbwhzeKCQJjQ52eVAqNT_vcklH07OITUO7wzOMDXvK6EGAWgaZgF/exec"><input class="required underlined-input" type="email" placeholder="Your email address" name="subscription_email" id="subscription_email"/><input class="pill-button" value="SUBSCRIBE" type="submit" data-state-normal="SUBSCRIBE" data-st
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+<!DOCTYPE html><html><head><title>Machine Learning Analytics with Tableau</title><meta charset="utf-8"/><meta content="IE=edge,chrome=1" http-equiv="X-UA-Compatible"/><meta name="viewport" content="width=device-width, initial-scale=1.0"/><meta class="swiftype" name="title" data-type="string" content="Machine Learning Analytics with Tableau"/><link rel="canonical" href="https://docs.prediction.io/datacollection/analytics-tableau/"/><link href="/images/favicon/normal-b330020a.png" rel="shortcut icon"/><link href="/images/favicon/apple-c0febcf2.png" rel="apple-touch-icon"/><link href="//fonts.googleapis.com/css?family=Open+Sans:300italic,400italic,600italic,700italic,800italic,400,300,600,700,800" rel="stylesheet"/><link href="//maxcdn.bootstrapcdn.com/font-awesome/4.2.0/css/font-awesome.min.css" rel="stylesheet"/><link href="/stylesheets/application-3598c7d7.css" rel="stylesheet" type="text/css"/><!--[if lt IE 9]><script src="//cdnjs.cloudflare.com/ajax/libs/html5shiv/3.7.2/html5shiv.
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<div class="row"><div class="col-md-9 col-sm-11 col-xs-11"><div class="hidden-md hidden-lg" id="mobile-page-heading-wrapper"><p>PredictionIO Docs</p><h4>Machine Learning Analytics with Tableau</h4></div><h4 class="hidden-sm hidden-xs">PredictionIO Docs</h4></div><div class="col-md-3 col-sm-1 col-xs-1 hidden-md hidden-lg"><img id="left-menu-indicator" src="/images/icons/down-arrow-dfe9f7fe.png"/></div><div class="col-md-3 col-sm-12 col-xs-12 swiftype-wrapper"><div class="swiftype"><form class="search-form"><img class="search-box-toggler hidden-xs hidden-sm" src="/images/icons/search-glass-704bd4ff.png"/><div class="search-box"><img src="/images/icons/search-glass-704bd4ff.png"/><input type="text" id="st-search-input" class="st-search-input" placeholder="Search Doc..."/></div><img class="swiftype-row-hider hidden-md hidden-lg" src="/images/icons/drawer-toggle-active-fcbef12a.png"/></form></div></div><div class="mobile-left-menu-toggler hidden-md hidden-lg"></div></div></div></div><div
id="page" class="container-fluid"><div class="row"><div id="left-menu-wrapper" class="col-md-3"><nav id="nav-main"><ul><li class="level-1"><a class="expandible" href="/"><span>Apache PredictionIO (incubating) Documentation</span></a><ul><li class="level-2"><a class="final" href="/"><span>Welcome to Apache PredictionIO (incubating)</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Getting Started</span></a><ul><li class="level-2"><a class="final" href="/start/"><span>A Quick Intro</span></a></li><li class="level-2"><a class="final" href="/install/"><span>Installing Apache PredictionIO (incubating)</span></a></li><li class="level-2"><a class="final" href="/start/download/"><span>Downloading an Engine Template</span></a></li><li class="level-2"><a class="final" href="/start/deploy/"><span>Deploying Your First Engine</span></a></li><li class="level-2"><a class="final" href="/start/customize/"><span>Customizing the Engine</span></a></li></ul></li><li clas
s="level-1"><a class="expandible" href="#"><span>Integrating with Your App</span></a><ul><li class="level-2"><a class="final" href="/appintegration/"><span>App Integration Overview</span></a></li><li class="level-2"><a class="expandible" href="/sdk/"><span>List of SDKs</span></a><ul><li class="level-3"><a class="final" href="/sdk/java/"><span>Java & Android SDK</span></a></li><li class="level-3"><a class="final" href="/sdk/php/"><span>PHP SDK</span></a></li><li class="level-3"><a class="final" href="/sdk/python/"><span>Python SDK</span></a></li><li class="level-3"><a class="final" href="/sdk/ruby/"><span>Ruby SDK</span></a></li><li class="level-3"><a class="final" href="/sdk/community/"><span>Community Powered SDKs</span></a></li></ul></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Deploying an Engine</span></a><ul><li class="level-2"><a class="final" href="/deploy/"><span>Deploying as a Web Service</span></a></li><li class="level-2"><a class="final" href="/c
li/#engine-commands"><span>Engine Command-line Interface</span></a></li><li class="level-2"><a class="final" href="/deploy/engineparams/"><span>Setting Engine Parameters</span></a></li><li class="level-2"><a class="final" href="/deploy/enginevariants/"><span>Deploying Multiple Engine Variants</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Customizing an Engine</span></a><ul><li class="level-2"><a class="final" href="/customize/"><span>Learning DASE</span></a></li><li class="level-2"><a class="final" href="/customize/dase/"><span>Implement DASE</span></a></li><li class="level-2"><a class="final" href="/customize/troubleshooting/"><span>Troubleshooting Engine Development</span></a></li><li class="level-2"><a class="final" href="/api/current/#package"><span>Engine Scala APIs</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Collecting and Analyzing Data</span></a><ul><li class="level-2"><a class="final" href="/datacolle
ction/"><span>Event Server Overview</span></a></li><li class="level-2"><a class="final" href="/cli/#event-server-commands"><span>Event Server Command-line Interface</span></a></li><li class="level-2"><a class="final" href="/datacollection/eventapi/"><span>Collecting Data with REST/SDKs</span></a></li><li class="level-2"><a class="final" href="/datacollection/eventmodel/"><span>Events Modeling</span></a></li><li class="level-2"><a class="final" href="/datacollection/webhooks/"><span>Unifying Multichannel Data with Webhooks</span></a></li><li class="level-2"><a class="final" href="/datacollection/channel/"><span>Channel</span></a></li><li class="level-2"><a class="final" href="/datacollection/batchimport/"><span>Importing Data in Batch</span></a></li><li class="level-2"><a class="final" href="/datacollection/analytics/"><span>Using Analytics Tools</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Choosing an Algorithm(s)</span></a><ul><li class="level-2
"><a class="final" href="/algorithm/"><span>Built-in Algorithm Libraries</span></a></li><li class="level-2"><a class="final" href="/algorithm/switch/"><span>Switching to Another Algorithm</span></a></li><li class="level-2"><a class="final" href="/algorithm/multiple/"><span>Combining Multiple Algorithms</span></a></li><li class="level-2"><a class="final" href="/algorithm/custom/"><span>Adding Your Own Algorithms</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>ML Tuning and Evaluation</span></a><ul><li class="level-2"><a class="final" href="/evaluation/"><span>Overview</span></a></li><li class="level-2"><a class="final" href="/evaluation/paramtuning/"><span>Hyperparameter Tuning</span></a></li><li class="level-2"><a class="final" href="/evaluation/evaluationdashboard/"><span>Evaluation Dashboard</span></a></li><li class="level-2"><a class="final" href="/evaluation/metricchoose/"><span>Choosing Evaluation Metrics</span></a></li><li class="level-2"><a c
lass="final" href="/evaluation/metricbuild/"><span>Building Evaluation Metrics</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>System Architecture</span></a><ul><li class="level-2"><a class="final" href="/system/"><span>Architecture Overview</span></a></li><li class="level-2"><a class="final" href="/system/anotherdatastore/"><span>Using Another Data Store</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Engine Template Gallery</span></a><ul><li class="level-2"><a class="final" href="http://templates.prediction.io"><span>Browse</span></a></li><li class="level-2"><a class="final" href="/community/submit-template/"><span>Submit your Engine as a Template</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Demo Tutorials</span></a><ul><li class="level-2"><a class="final" href="/demo/tapster/"><span>Comics Recommendation Demo</span></a></li><li class="level-2"><a class="final" href="/demo/comm
unity/"><span>Community Contributed Demo</span></a></li><li class="level-2"><a class="final" href="/demo/textclassification/"><span>Text Classification Engine Tutorial</span></a></li></ul></li><li class="level-1"><a class="expandible" href="/community/"><span>Getting Involved</span></a><ul><li class="level-2"><a class="final" href="/community/contribute-code/"><span>Contribute Code</span></a></li><li class="level-2"><a class="final" href="/community/contribute-documentation/"><span>Contribute Documentation</span></a></li><li class="level-2"><a class="final" href="/community/contribute-sdk/"><span>Contribute a SDK</span></a></li><li class="level-2"><a class="final" href="/community/contribute-webhook/"><span>Contribute a Webhook</span></a></li><li class="level-2"><a class="final" href="/community/projects/"><span>Community Projects</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Getting Help</span></a><ul><li class="level-2"><a class="final" href="/r
esources/faq/"><span>FAQs</span></a></li><li class="level-2"><a class="final" href="/support/"><span>Community Support</span></a></li><li class="level-2"><a class="final" href="/support/#enterprise-support"><span>Enterprise Support</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Resources</span></a><ul><li class="level-2"><a class="final" href="/resources/intellij/"><span>Developing Engines with IntelliJ IDEA</span></a></li><li class="level-2"><a class="final" href="/resources/upgrade/"><span>Upgrade Instructions</span></a></li><li class="level-2"><a class="final" href="/resources/glossary/"><span>Glossary</span></a></li></ul></li></ul></nav></div><div class="col-md-9 col-sm-12"><div class="content-header hidden-md hidden-lg"><div id="page-title"><h1>Machine Learning Analytics with Tableau</h1></div></div><div id="table-of-content-wrapper"><h5>On this page</h5><aside id="table-of-contents"><ul> <li> <a href="#prerequisites">Prerequisites</a> </li> <
li> <a href="#creating-hive-tables">Creating Hive Tables</a> </li> <li> <a href="#launch-spark-sql-s-thrift-jdbc-odbc-server">Launch Spark SQL's Thrift JDBC/ODBC Server</a> </li> <li> <a href="#performing-analysis-with-tableau">Performing Analysis with Tableau</a> </li> </ul> </aside><hr/><a id="edit-page-link" href="https://github.com/apache/incubator-predictionio/tree/livedoc/docs/manual/source/datacollection/analytics-tableau.html.md.erb"><img src="/images/icons/edit-pencil-d6c1bb3d.png"/>Edit this page</a></div><div class="content-header hidden-sm hidden-xs"><div id="page-title"><h1>Machine Learning Analytics with Tableau</h1></div></div><div class="content"><p>With Spark SQL, it is possible to connect Tableau to Apache PredictionIO (incubating) Event Server for interactive analysis of event data.</p><h2 id='prerequisites' class='header-anchors'>Prerequisites</h2> <ul> <li>Tableau Desktop 8.3+ with a proper license key that supports Spark SQL;</li> <li>Spark ODBC Driver from Dat
abricks (<a href="https://databricks.com/spark/odbc-driver-download">https://databricks.com/spark/odbc-driver-download</a>);</li> <li>Apache Hadoop 2.4+</li> <li>Apache Hive 0.3.1+</li> </ul> <div class="alert-message info"><p>In this article, we will assume that you have a working HDFS, and that your environmental variable <code>HADOOP_HOME</code> has been properly set. This is essential for Apache Hive to function properly. In addition, <code>HADOOP_CONF_DIR</code> in <code>$PIO_HOME/conf/pio-env.sh</code> must also be properly set for the <code>pio export</code> command to write to HDFS instead of the local filesystem.</p></div><p><h2 id='export-events-to-apache-parquet' class='header-anchors'>Export Events to Apache Parquet</h2><p>PredictionIO supports exporting your events to <a href="http://parquet.incubator.apache.org/">Apache Parquet</a>, a columnar storage format that allows you to query quickly.</p><p>Let's export the data we imported in <a href="/templates/recommendat
ion/quickstart/#import-sample-data">Recommendation Engine Template Quick Start</a>, and assume the App ID is 1.</p><div class="highlight shell"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1</pre></td><td class="code"><pre><span class="gp">$ </span><span class="nv">$PIO_HOME</span>/bin/pio <span class="nb">export</span> --appid 1 --output /tmp/movies --format parquet
+</pre></td></tr></tbody></table> </div> <p>After the command has finished successfully, you should see something similar to the following.</p><div class="highlight shell"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1
+2
+3
+4
+5
+6
+7
+8
+9
+10
+11</pre></td><td class="code"><pre>root
+ |-- creationTime: string <span class="o">(</span>nullable <span class="o">=</span> <span class="nb">true</span><span class="o">)</span>
+ |-- entityId: string <span class="o">(</span>nullable <span class="o">=</span> <span class="nb">true</span><span class="o">)</span>
+ |-- entityType: string <span class="o">(</span>nullable <span class="o">=</span> <span class="nb">true</span><span class="o">)</span>
+ |-- event: string <span class="o">(</span>nullable <span class="o">=</span> <span class="nb">true</span><span class="o">)</span>
+ |-- eventId: string <span class="o">(</span>nullable <span class="o">=</span> <span class="nb">true</span><span class="o">)</span>
+ |-- eventTime: string <span class="o">(</span>nullable <span class="o">=</span> <span class="nb">true</span><span class="o">)</span>
+ |-- properties: struct <span class="o">(</span>nullable <span class="o">=</span> <span class="nb">true</span><span class="o">)</span>
+ | |-- rating: double <span class="o">(</span>nullable <span class="o">=</span> <span class="nb">true</span><span class="o">)</span>
+ |-- targetEntityId: string <span class="o">(</span>nullable <span class="o">=</span> <span class="nb">true</span><span class="o">)</span>
+ |-- targetEntityType: string <span class="o">(</span>nullable <span class="o">=</span> <span class="nb">true</span><span class="o">)</span>
+</pre></td></tr></tbody></table> </div></p><h2 id='creating-hive-tables' class='header-anchors'>Creating Hive Tables</h2><p>Before you can use Spark SQL's Thrift JDBC/ODBC Server, you will need to create the table schema in Hive first. Please make sure to replace <code>path_of_hive</code> with the real path.</p><div class="highlight shell"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1
+2
+3
+4</pre></td><td class="code"><pre><span class="gp">$ </span><span class="nb">cd </span>path_of_hive
+<span class="gp">$ </span>bin/hive
+<span class="gp">hive> </span>CREATE EXTERNAL TABLE events <span class="o">(</span>event STRING, entityType STRING, entityId STRING, targetEntityType STRING, targetEntityId STRING, properties STRUCT<rating:DOUBLE><span class="o">)</span> STORED AS parquet LOCATION <span class="s1">'/tmp/movies'</span>;
+<span class="gp">hive> </span><span class="nb">exit</span>;
+</pre></td></tr></tbody></table> </div> <h2 id='launch-spark-sql's-thrift-jdbc/odbc-server' class='header-anchors'>Launch Spark SQL's Thrift JDBC/ODBC Server</h2><p>Once you have created your Hive tables, create a Hive configuration in your Spark installation. If you have a custom <code>hive-site.xml</code>, simply copy or link it to <code>$SPARK_HOME/conf</code>. Otherwise, Hive would have created a local Derby database, and you will need to let Spark knows about it. Create <code>$SPARK_HOME/conf/hive-site.xml</code> from scratch with the following template.</p><div class="alert-message warning"><p>You must change <code>/opt/apache-hive-0.13.1-bin</code> below to a real Hive path.</p></div><div class="highlight xml"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1
+2
+3
+4
+5
+6
+7
+8</pre></td><td class="code"><pre><span class="cp"><?xml version="1.0" encoding="UTF-8" standalone="no"?></span>
+<span class="cp"><?xml-stylesheet type="text/xsl" href="configuration.xsl"?></span>
+<span class="nt"><configuration></span>
+ <span class="nt"><property></span>
+ <span class="nt"><name></span>javax.jdo.option.ConnectionURL<span class="nt"></name></span>
+ <span class="nt"><value></span>jdbc:derby:;databaseName=/opt/apache-hive-0.13.1-bin/metastore_db;create=true<span class="nt"></value></span>
+ <span class="nt"></property></span>
+<span class="nt"></configuration></span>
+</pre></td></tr></tbody></table> </div> <p>Launch Spark SQL's Thift JDBC/ODBC Server by</p><div class="highlight shell"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1</pre></td><td class="code"><pre><span class="gp">$ </span><span class="nv">$SPARK_HOME</span>/sbin/start-thriftserver.sh
+</pre></td></tr></tbody></table> </div> <p>You can test the server using the included Beeline client.</p><div class="highlight shell"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1
+2
+3
+4
+5
+6
+7
+8
+9
+10
+11
+12
+13
+14
+15
+16
+17
+18
+19
+20</pre></td><td class="code"><pre><span class="gp">$ </span><span class="nv">$SPARK_HOME</span>/bin/beeline
+<span class="gp">beeline> </span>!connect jdbc:hive2://localhost:10000
+<span class="o">(</span>Use empty username and password when prompted<span class="o">)</span>
+0: jdbc:hive2://localhost:10000> <span class="k">select</span> <span class="k">*</span> from events limit 10;
++--------+-------------+-----------+-------------------+-----------------+------------------+
+| event | entitytype | entityid | targetentitytype | targetentityid | properties |
++--------+-------------+-----------+-------------------+-----------------+------------------+
+| buy | user | 3 | item | 0 | <span class="o">{</span><span class="s2">"rating"</span>:null<span class="o">}</span> |
+| buy | user | 3 | item | 1 | <span class="o">{</span><span class="s2">"rating"</span>:null<span class="o">}</span> |
+| rate | user | 3 | item | 2 | <span class="o">{</span><span class="s2">"rating"</span>:1.0<span class="o">}</span> |
+| buy | user | 3 | item | 7 | <span class="o">{</span><span class="s2">"rating"</span>:null<span class="o">}</span> |
+| buy | user | 3 | item | 8 | <span class="o">{</span><span class="s2">"rating"</span>:null<span class="o">}</span> |
+| buy | user | 3 | item | 9 | <span class="o">{</span><span class="s2">"rating"</span>:null<span class="o">}</span> |
+| rate | user | 3 | item | 14 | <span class="o">{</span><span class="s2">"rating"</span>:1.0<span class="o">}</span> |
+| buy | user | 3 | item | 15 | <span class="o">{</span><span class="s2">"rating"</span>:null<span class="o">}</span> |
+| buy | user | 3 | item | 16 | <span class="o">{</span><span class="s2">"rating"</span>:null<span class="o">}</span> |
+| buy | user | 3 | item | 18 | <span class="o">{</span><span class="s2">"rating"</span>:null<span class="o">}</span> |
++--------+-------------+-----------+-------------------+-----------------+------------------+
+10 rows selected <span class="o">(</span>0.515 seconds<span class="o">)</span>
+0: jdbc:hive2://localhost:10000>
+</pre></td></tr></tbody></table> </div> <p>Now you are ready to use Tableau!</p><h2 id='performing-analysis-with-tableau' class='header-anchors'>Performing Analysis with Tableau</h2><p>Launch Tableau and Connect to Data. Click on <strong>Spark SQL (Beta)</strong> and enter Spark SQL's Thrift JDBC/ODBC Server information. Make sure to pick <strong>User Name</strong> as <strong>Authentication</strong>. Click <strong>Connect</strong>.</p><p><img alt="Tableau and Spark SQL" src="/images/datacollection/tableau-01-b5a23839.png"/></p><p>On the next page, pick <strong>default</strong> under <strong>Schema</strong>.</p><div class="alert-message info"><p>You may not see any choices when you click on Schema. Simply press Enter and Tableau will try to list all schemas.</p></div><p>Once you see a list of tables that includes <strong>events</strong>, click <strong>New Custom SQL</strong>, then enter the following.</p><div class="highlight sql"><table style="border-spacing: 0"><tbody><tr><td c
lass="gutter gl" style="text-align: right"><pre class="lineno">1</pre></td><td class="code"><pre><span class="k">SELECT</span> <span class="n">event</span><span class="p">,</span> <span class="n">entityType</span><span class="p">,</span> <span class="n">entityId</span><span class="p">,</span> <span class="n">targetEntityType</span><span class="p">,</span> <span class="n">targetEntityId</span><span class="p">,</span> <span class="n">properties</span><span class="p">.</span><span class="n">rating</span> <span class="k">FROM</span> <span class="n">events</span>
+</pre></td></tr></tbody></table> </div> <p>Click <strong>Update Now</strong>. You should see the following screen by now, indicating success in loading data. Using a custom SQL allows you to extract arbitrary fields from within properties.</p><p><img alt="Setting up Tableau" src="/images/datacollection/tableau-02-76e93443.png"/></p><p>Click <strong>Go to Worksheet</strong> and start analyzing. The following shows an example of breaking down different rating values.</p><p><img alt="Rating Values Breakdown" src="/images/datacollection/tableau-03-e389351e.png"/></p><p>The following shows a summary of interactions.</p><p><img alt="Interactions" src="/images/datacollection/tableau-04-c8c31bb7.png"/></p><p>Happy analyzing!</p></div></div></div></div><footer><div class="container"><div class="seperator"></div><div class="row"><div class="col-md-4 col-md-push-8 col-xs-12"><div class="subscription-form-wrapper"><h4>Subscribe to our Newsletter</h4><form class="ajax-form" id="subscribe-form" m
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v id="page" class="container-fluid"><div class="row"><div id="left-menu-wrapper" class="col-md-3"><nav id="nav-main"><ul><li class="level-1"><a class="expandible" href="/"><span>Apache PredictionIO (incubating) Documentation</span></a><ul><li class="level-2"><a class="final" href="/"><span>Welcome to Apache PredictionIO (incubating)</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Getting Started</span></a><ul><li class="level-2"><a class="final" href="/start/"><span>A Quick Intro</span></a></li><li class="level-2"><a class="final" href="/install/"><span>Installing Apache PredictionIO (incubating)</span></a></li><li class="level-2"><a class="final" href="/start/download/"><span>Downloading an Engine Template</span></a></li><li class="level-2"><a class="final" href="/start/deploy/"><span>Deploying Your First Engine</span></a></li><li class="level-2"><a class="final" href="/start/customize/"><span>Customizing the Engine</span></a></li></ul></li><li cla
ss="level-1"><a class="expandible" href="#"><span>Integrating with Your App</span></a><ul><li class="level-2"><a class="final" href="/appintegration/"><span>App Integration Overview</span></a></li><li class="level-2"><a class="expandible" href="/sdk/"><span>List of SDKs</span></a><ul><li class="level-3"><a class="final" href="/sdk/java/"><span>Java & Android SDK</span></a></li><li class="level-3"><a class="final" href="/sdk/php/"><span>PHP SDK</span></a></li><li class="level-3"><a class="final" href="/sdk/python/"><span>Python SDK</span></a></li><li class="level-3"><a class="final" href="/sdk/ruby/"><span>Ruby SDK</span></a></li><li class="level-3"><a class="final" href="/sdk/community/"><span>Community Powered SDKs</span></a></li></ul></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Deploying an Engine</span></a><ul><li class="level-2"><a class="final" href="/deploy/"><span>Deploying as a Web Service</span></a></li><li class="level-2"><a class="final" href="/
cli/#engine-commands"><span>Engine Command-line Interface</span></a></li><li class="level-2"><a class="final" href="/deploy/engineparams/"><span>Setting Engine Parameters</span></a></li><li class="level-2"><a class="final" href="/deploy/enginevariants/"><span>Deploying Multiple Engine Variants</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Customizing an Engine</span></a><ul><li class="level-2"><a class="final" href="/customize/"><span>Learning DASE</span></a></li><li class="level-2"><a class="final" href="/customize/dase/"><span>Implement DASE</span></a></li><li class="level-2"><a class="final" href="/customize/troubleshooting/"><span>Troubleshooting Engine Development</span></a></li><li class="level-2"><a class="final" href="/api/current/#package"><span>Engine Scala APIs</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Collecting and Analyzing Data</span></a><ul><li class="level-2"><a class="final" href="/datacoll
ection/"><span>Event Server Overview</span></a></li><li class="level-2"><a class="final" href="/cli/#event-server-commands"><span>Event Server Command-line Interface</span></a></li><li class="level-2"><a class="final" href="/datacollection/eventapi/"><span>Collecting Data with REST/SDKs</span></a></li><li class="level-2"><a class="final" href="/datacollection/eventmodel/"><span>Events Modeling</span></a></li><li class="level-2"><a class="final" href="/datacollection/webhooks/"><span>Unifying Multichannel Data with Webhooks</span></a></li><li class="level-2"><a class="final" href="/datacollection/channel/"><span>Channel</span></a></li><li class="level-2"><a class="final" href="/datacollection/batchimport/"><span>Importing Data in Batch</span></a></li><li class="level-2"><a class="final" href="/datacollection/analytics/"><span>Using Analytics Tools</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Choosing an Algorithm(s)</span></a><ul><li class="level-
2"><a class="final" href="/algorithm/"><span>Built-in Algorithm Libraries</span></a></li><li class="level-2"><a class="final" href="/algorithm/switch/"><span>Switching to Another Algorithm</span></a></li><li class="level-2"><a class="final" href="/algorithm/multiple/"><span>Combining Multiple Algorithms</span></a></li><li class="level-2"><a class="final" href="/algorithm/custom/"><span>Adding Your Own Algorithms</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>ML Tuning and Evaluation</span></a><ul><li class="level-2"><a class="final" href="/evaluation/"><span>Overview</span></a></li><li class="level-2"><a class="final" href="/evaluation/paramtuning/"><span>Hyperparameter Tuning</span></a></li><li class="level-2"><a class="final" href="/evaluation/evaluationdashboard/"><span>Evaluation Dashboard</span></a></li><li class="level-2"><a class="final" href="/evaluation/metricchoose/"><span>Choosing Evaluation Metrics</span></a></li><li class="level-2"><a
class="final" href="/evaluation/metricbuild/"><span>Building Evaluation Metrics</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>System Architecture</span></a><ul><li class="level-2"><a class="final" href="/system/"><span>Architecture Overview</span></a></li><li class="level-2"><a class="final" href="/system/anotherdatastore/"><span>Using Another Data Store</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Engine Template Gallery</span></a><ul><li class="level-2"><a class="final" href="http://templates.prediction.io"><span>Browse</span></a></li><li class="level-2"><a class="final" href="/community/submit-template/"><span>Submit your Engine as a Template</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Demo Tutorials</span></a><ul><li class="level-2"><a class="final" href="/demo/tapster/"><span>Comics Recommendation Demo</span></a></li><li class="level-2"><a class="final" href="/demo/com
munity/"><span>Community Contributed Demo</span></a></li><li class="level-2"><a class="final" href="/demo/textclassification/"><span>Text Classification Engine Tutorial</span></a></li></ul></li><li class="level-1"><a class="expandible" href="/community/"><span>Getting Involved</span></a><ul><li class="level-2"><a class="final" href="/community/contribute-code/"><span>Contribute Code</span></a></li><li class="level-2"><a class="final" href="/community/contribute-documentation/"><span>Contribute Documentation</span></a></li><li class="level-2"><a class="final" href="/community/contribute-sdk/"><span>Contribute a SDK</span></a></li><li class="level-2"><a class="final" href="/community/contribute-webhook/"><span>Contribute a Webhook</span></a></li><li class="level-2"><a class="final" href="/community/projects/"><span>Community Projects</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Getting Help</span></a><ul><li class="level-2"><a class="final" href="/
resources/faq/"><span>FAQs</span></a></li><li class="level-2"><a class="final" href="/support/"><span>Community Support</span></a></li><li class="level-2"><a class="final" href="/support/#enterprise-support"><span>Enterprise Support</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Resources</span></a><ul><li class="level-2"><a class="final" href="/resources/intellij/"><span>Developing Engines with IntelliJ IDEA</span></a></li><li class="level-2"><a class="final" href="/resources/upgrade/"><span>Upgrade Instructions</span></a></li><li class="level-2"><a class="final" href="/resources/glossary/"><span>Glossary</span></a></li></ul></li></ul></nav></div><div class="col-md-9 col-sm-12"><div class="content-header hidden-md hidden-lg"><div id="page-title"><h1>Machine Learning Analytics with Zeppelin</h1></div></div><div id="table-of-content-wrapper"><h5>On this page</h5><aside id="table-of-contents"><ul> <li> <a href="#prerequisites">Prerequisites</a> </li>
<li> <a href="#building-zeppelin-for-apache-spark-1-2">Building Zeppelin for Apache Spark 1.2+</a> </li> <li> <a href="#preparing-zeppelin">Preparing Zeppelin</a> </li> <li> <a href="#performing-analysis-with-zeppelin">Performing Analysis with Zeppelin</a> </li> </ul> </aside><hr/><a id="edit-page-link" href="https://github.com/apache/incubator-predictionio/tree/livedoc/docs/manual/source/datacollection/analytics-zeppelin.html.md.erb"><img src="/images/icons/edit-pencil-d6c1bb3d.png"/>Edit this page</a></div><div class="content-header hidden-sm hidden-xs"><div id="page-title"><h1>Machine Learning Analytics with Zeppelin</h1></div></div><div class="content"><p><a href="http://zeppelin-project.org/">Apache Zeppelin</a> is an interactive computational environment built on Apache Spark like the IPython Notebook. With <a href="http://predictionio.incubator.apache.org">Apache PredictionIO (incubating)</a> and <a href="https://spark.apache.org/sql/">Spark SQL</a>, you can easily analyze y
our collected events when you are developing or tuning your engine.</p><h2 id='prerequisites' class='header-anchors'>Prerequisites</h2><p>The following instructions assume that you have the command <code>sbt</code> accessible in your shell's search path. Alternatively, you can use the <code>sbt</code> command that comes with Apache PredictionIO (incubating) at <code>$PIO_HOME/sbt/sbt</code>.</p><p><h2 id='export-events-to-apache-parquet' class='header-anchors'>Export Events to Apache Parquet</h2><p>PredictionIO supports exporting your events to <a href="http://parquet.incubator.apache.org/">Apache Parquet</a>, a columnar storage format that allows you to query quickly.</p><p>Let's export the data we imported in <a href="/templates/recommendation/quickstart/#import-sample-data">Recommendation Engine Template Quick Start</a>, and assume the App ID is 1.</p><div class="highlight shell"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><
pre class="lineno">1</pre></td><td class="code"><pre><span class="gp">$ </span><span class="nv">$PIO_HOME</span>/bin/pio <span class="nb">export</span> --appid 1 --output /tmp/movies --format parquet
+</pre></td></tr></tbody></table> </div> <p>After the command has finished successfully, you should see something similar to the following.</p><div class="highlight shell"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1
+2
+3
+4
+5
+6
+7
+8
+9
+10
+11</pre></td><td class="code"><pre>root
+ |-- creationTime: string <span class="o">(</span>nullable <span class="o">=</span> <span class="nb">true</span><span class="o">)</span>
+ |-- entityId: string <span class="o">(</span>nullable <span class="o">=</span> <span class="nb">true</span><span class="o">)</span>
+ |-- entityType: string <span class="o">(</span>nullable <span class="o">=</span> <span class="nb">true</span><span class="o">)</span>
+ |-- event: string <span class="o">(</span>nullable <span class="o">=</span> <span class="nb">true</span><span class="o">)</span>
+ |-- eventId: string <span class="o">(</span>nullable <span class="o">=</span> <span class="nb">true</span><span class="o">)</span>
+ |-- eventTime: string <span class="o">(</span>nullable <span class="o">=</span> <span class="nb">true</span><span class="o">)</span>
+ |-- properties: struct <span class="o">(</span>nullable <span class="o">=</span> <span class="nb">true</span><span class="o">)</span>
+ | |-- rating: double <span class="o">(</span>nullable <span class="o">=</span> <span class="nb">true</span><span class="o">)</span>
+ |-- targetEntityId: string <span class="o">(</span>nullable <span class="o">=</span> <span class="nb">true</span><span class="o">)</span>
+ |-- targetEntityType: string <span class="o">(</span>nullable <span class="o">=</span> <span class="nb">true</span><span class="o">)</span>
+</pre></td></tr></tbody></table> </div></p><h2 id='building-zeppelin-for-apache-spark-1.2+' class='header-anchors'>Building Zeppelin for Apache Spark 1.2+</h2><p>Start by cloning Zeppelin.</p><div class="highlight shell"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1</pre></td><td class="code"><pre><span class="gp">$ </span>git clone https://github.com/apache/incubator-zeppelin.git
+</pre></td></tr></tbody></table> </div> <p>Build Zeppelin with Hadoop 2.4 and Spark 1.2 profiles.</p><div class="highlight shell"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1
+2</pre></td><td class="code"><pre><span class="gp">$ </span><span class="nb">cd </span>zeppelin
+<span class="gp">$ </span>mvn clean package -Pspark-1.2 -Dhadoop.version<span class="o">=</span>2.4.0 -Phadoop-2.4 -DskipTests
+</pre></td></tr></tbody></table> </div> <p>Now you should have working Zeppelin binaries.</p><h2 id='preparing-zeppelin' class='header-anchors'>Preparing Zeppelin</h2><p>First, start Zeppelin.</p><div class="highlight shell"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1</pre></td><td class="code"><pre><span class="gp">$ </span>bin/zeppelin-daemon.sh start
+</pre></td></tr></tbody></table> </div> <p>By default, you should be able to access Zeppelin via web browser at <a href="http://localhost:8080">http://localhost:8080</a>. Create a new notebook and put the following in the first cell.</p><div class="highlight scala"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1</pre></td><td class="code"><pre><span class="n">sqlc</span><span class="o">.</span><span class="n">parquetFile</span><span class="o">(</span><span class="s">"/tmp/movies"</span><span class="o">).</span><span class="n">registerTempTable</span><span class="o">(</span><span class="s">"events"</span><span class="o">)</span>
+</pre></td></tr></tbody></table> </div> <p><img alt="Preparing Zeppelin" src="/images/datacollection/zeppelin-01-1c476081.png"/></p><h2 id='performing-analysis-with-zeppelin' class='header-anchors'>Performing Analysis with Zeppelin</h2><p>If all steps above ran successfully, you should have a ready-to-use analytics environment by now. Let's try a few examples to see if everything is functional.</p><p>In the second cell, put in this piece of code and run it.</p><div class="highlight shell"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1
+2
+3</pre></td><td class="code"><pre>%sql
+SELECT entityType, event, targetEntityType, COUNT<span class="o">(</span><span class="k">*</span><span class="o">)</span> AS c FROM events
+GROUP BY entityType, event, targetEntityType
+</pre></td></tr></tbody></table> </div> <p><img alt="Summary of Events" src="/images/datacollection/zeppelin-02-b3687a33.png"/></p><p>We can also easily plot a pie chart.</p><div class="highlight shell"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1
+2</pre></td><td class="code"><pre>%sql
+SELECT event, COUNT<span class="o">(</span><span class="k">*</span><span class="o">)</span> AS c FROM events GROUP BY event
+</pre></td></tr></tbody></table> </div> <p><img alt="Summary of Event in Pie Chart" src="/images/datacollection/zeppelin-03-15dcefee.png"/></p><p>And see a breakdown of rating values.</p><div class="highlight shell"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1
+2
+3</pre></td><td class="code"><pre>%sql
+SELECT properties.rating AS r, COUNT<span class="o">(</span><span class="k">*</span><span class="o">)</span> AS c FROM events
+WHERE properties.rating IS NOT NULL GROUP BY properties.rating ORDER BY r
+</pre></td></tr></tbody></table> </div> <p><img alt="Breakdown of Rating Values" src="/images/datacollection/zeppelin-04-d646c299.png"/></p><p>Happy analyzing!</p></div></div></div></div><footer><div class="container"><div class="seperator"></div><div class="row"><div class="col-md-4 col-md-push-8 col-xs-12"><div class="subscription-form-wrapper"><h4>Subscribe to our Newsletter</h4><form class="ajax-form" id="subscribe-form" method="POST" action="https://script.google.com/macros/s/AKfycbwhzeKCQJjQ52eVAqNT_vcklH07OITUO7wzOMDXvK6EGAWgaZgF/exec"><input class="required underlined-input" type="email" placeholder="Your email address" name="subscription_email" id="subscription_email"/><input class="pill-button" value="SUBSCRIBE" type="submit" data-state-normal="SUBSCRIBE" data-state-sucess="SUBSCRIBED!" data-state-loading="SENDING..." onclick="t($('#subscription_email').val());"/><p class="result"></p></form></div></div><div class="col-md-2 col-md-pull-4 col-xs-6 footer-link-column"><div c
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<div class="row"><div class="col-md-9 col-sm-11 col-xs-11"><div class="hidden-md hidden-lg" id="mobile-page-heading-wrapper"><p>PredictionIO Docs</p><h4>Building Evaluation Metrics</h4></div><h4 class="hidden-sm hidden-xs">PredictionIO Docs</h4></div><div class="col-md-3 col-sm-1 col-xs-1 hidden-md hidden-lg"><img id="left-menu-indicator" src="/images/icons/down-arrow-dfe9f7fe.png"/></div><div class="col-md-3 col-sm-12 col-xs-12 swiftype-wrapper"><div class="swiftype"><form class="search-form"><img class="search-box-toggler hidden-xs hidden-sm" src="/images/icons/search-glass-704bd4ff.png"/><div class="search-box"><img src="/images/icons/search-glass-704bd4ff.png"/><input type="text" id="st-search-input" class="st-search-input" placeholder="Search Doc..."/></div><img class="swiftype-row-hider hidden-md hidden-lg" src="/images/icons/drawer-toggle-active-fcbef12a.png"/></form></div></div><div class="mobile-left-menu-toggler hidden-md hidden-lg"></div></div></div></div><div id="page" c
lass="container-fluid"><div class="row"><div id="left-menu-wrapper" class="col-md-3"><nav id="nav-main"><ul><li class="level-1"><a class="expandible" href="/"><span>Apache PredictionIO (incubating) Documentation</span></a><ul><li class="level-2"><a class="final" href="/"><span>Welcome to Apache PredictionIO (incubating)</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Getting Started</span></a><ul><li class="level-2"><a class="final" href="/start/"><span>A Quick Intro</span></a></li><li class="level-2"><a class="final" href="/install/"><span>Installing Apache PredictionIO (incubating)</span></a></li><li class="level-2"><a class="final" href="/start/download/"><span>Downloading an Engine Template</span></a></li><li class="level-2"><a class="final" href="/start/deploy/"><span>Deploying Your First Engine</span></a></li><li class="level-2"><a class="final" href="/start/customize/"><span>Customizing the Engine</span></a></li></ul></li><li class="level-1">
<a class="expandible" href="#"><span>Integrating with Your App</span></a><ul><li class="level-2"><a class="final" href="/appintegration/"><span>App Integration Overview</span></a></li><li class="level-2"><a class="expandible" href="/sdk/"><span>List of SDKs</span></a><ul><li class="level-3"><a class="final" href="/sdk/java/"><span>Java & Android SDK</span></a></li><li class="level-3"><a class="final" href="/sdk/php/"><span>PHP SDK</span></a></li><li class="level-3"><a class="final" href="/sdk/python/"><span>Python SDK</span></a></li><li class="level-3"><a class="final" href="/sdk/ruby/"><span>Ruby SDK</span></a></li><li class="level-3"><a class="final" href="/sdk/community/"><span>Community Powered SDKs</span></a></li></ul></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Deploying an Engine</span></a><ul><li class="level-2"><a class="final" href="/deploy/"><span>Deploying as a Web Service</span></a></li><li class="level-2"><a class="final" href="/cli/#engine-c
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n>Event Server Overview</span></a></li><li class="level-2"><a class="final" href="/cli/#event-server-commands"><span>Event Server Command-line Interface</span></a></li><li class="level-2"><a class="final" href="/datacollection/eventapi/"><span>Collecting Data with REST/SDKs</span></a></li><li class="level-2"><a class="final" href="/datacollection/eventmodel/"><span>Events Modeling</span></a></li><li class="level-2"><a class="final" href="/datacollection/webhooks/"><span>Unifying Multichannel Data with Webhooks</span></a></li><li class="level-2"><a class="final" href="/datacollection/channel/"><span>Channel</span></a></li><li class="level-2"><a class="final" href="/datacollection/batchimport/"><span>Importing Data in Batch</span></a></li><li class="level-2"><a class="final" href="/datacollection/analytics/"><span>Using Analytics Tools</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Choosing an Algorithm(s)</span></a><ul><li class="level-2"><a class="
final" href="/algorithm/"><span>Built-in Algorithm Libraries</span></a></li><li class="level-2"><a class="final" href="/algorithm/switch/"><span>Switching to Another Algorithm</span></a></li><li class="level-2"><a class="final" href="/algorithm/multiple/"><span>Combining Multiple Algorithms</span></a></li><li class="level-2"><a class="final" href="/algorithm/custom/"><span>Adding Your Own Algorithms</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>ML Tuning and Evaluation</span></a><ul><li class="level-2"><a class="final" href="/evaluation/"><span>Overview</span></a></li><li class="level-2"><a class="final" href="/evaluation/paramtuning/"><span>Hyperparameter Tuning</span></a></li><li class="level-2"><a class="final" href="/evaluation/evaluationdashboard/"><span>Evaluation Dashboard</span></a></li><li class="level-2"><a class="final" href="/evaluation/metricchoose/"><span>Choosing Evaluation Metrics</span></a></li><li class="level-2"><a class="final
active" href="/evaluation/metricbuild/"><span>Building Evaluation Metrics</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>System Architecture</span></a><ul><li class="level-2"><a class="final" href="/system/"><span>Architecture Overview</span></a></li><li class="level-2"><a class="final" href="/system/anotherdatastore/"><span>Using Another Data Store</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Engine Template Gallery</span></a><ul><li class="level-2"><a class="final" href="http://templates.prediction.io"><span>Browse</span></a></li><li class="level-2"><a class="final" href="/community/submit-template/"><span>Submit your Engine as a Template</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Demo Tutorials</span></a><ul><li class="level-2"><a class="final" href="/demo/tapster/"><span>Comics Recommendation Demo</span></a></li><li class="level-2"><a class="final" href="/demo/community
/"><span>Community Contributed Demo</span></a></li><li class="level-2"><a class="final" href="/demo/textclassification/"><span>Text Classification Engine Tutorial</span></a></li></ul></li><li class="level-1"><a class="expandible" href="/community/"><span>Getting Involved</span></a><ul><li class="level-2"><a class="final" href="/community/contribute-code/"><span>Contribute Code</span></a></li><li class="level-2"><a class="final" href="/community/contribute-documentation/"><span>Contribute Documentation</span></a></li><li class="level-2"><a class="final" href="/community/contribute-sdk/"><span>Contribute a SDK</span></a></li><li class="level-2"><a class="final" href="/community/contribute-webhook/"><span>Contribute a Webhook</span></a></li><li class="level-2"><a class="final" href="/community/projects/"><span>Community Projects</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Getting Help</span></a><ul><li class="level-2"><a class="final" href="/resour
ces/faq/"><span>FAQs</span></a></li><li class="level-2"><a class="final" href="/support/"><span>Community Support</span></a></li><li class="level-2"><a class="final" href="/support/#enterprise-support"><span>Enterprise Support</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Resources</span></a><ul><li class="level-2"><a class="final" href="/resources/intellij/"><span>Developing Engines with IntelliJ IDEA</span></a></li><li class="level-2"><a class="final" href="/resources/upgrade/"><span>Upgrade Instructions</span></a></li><li class="level-2"><a class="final" href="/resources/glossary/"><span>Glossary</span></a></li></ul></li></ul></nav></div><div class="col-md-9 col-sm-12"><div class="content-header hidden-md hidden-lg"><div id="breadcrumbs" class="hidden-sm hidden xs"><ul><li><a href="#">ML Tuning and Evaluation</a><span class="spacer">></span></li><li><span class="last">Building Evaluation Metrics</span></li></ul></div><div id="page-title"><h1
>Building Evaluation Metrics</h1></div></div><div id="table-of-content-wrapper"><h5>On this page</h5><aside id="table-of-contents"><ul> <li> <a href="#overview">Overview</a> </li> <li> <a href="#example-1-accuracy-metric">Example 1: Accuracy Metric</a> </li> <li> <a href="#example-2-precision-metric">Example 2: Precision Metric</a> </li> </ul> </aside><hr/><a id="edit-page-link" href="https://github.com/apache/incubator-predictionio/tree/livedoc/docs/manual/source/evaluation/metricbuild.html.md"><img src="/images/icons/edit-pencil-d6c1bb3d.png"/>Edit this page</a></div><div class="content-header hidden-sm hidden-xs"><div id="breadcrumbs" class="hidden-sm hidden xs"><ul><li><a href="#">ML Tuning and Evaluation</a><span class="spacer">></span></li><li><span class="last">Building Evaluation Metrics</span></li></ul></div><div id="page-title"><h1>Building Evaluation Metrics</h1></div></div><div class="content"><p>PredictionIO enables developer to implement evaluation custom evaluation
metric with just a few lines of code. We illustrate it with <a href="/templates/classification/quickstart/">the classification template</a>.</p><h2 id='overview' class='header-anchors'>Overview</h2><p>A simplistic form of metric is a function which takes a <code>(Query, PredictedResult, ActualResult)</code>-tuple (<em>QPA-tuple</em>) as input and return a score. Exploiting this properties allows us to implement custom metric with a single line of code (plus some boilerplates). We demonstate this with two metrics: accuracy and precision.</p> <h2 id='example-1:-accuracy-metric' class='header-anchors'>Example 1: Accuracy Metric</h2><p>Accuracy is a metric capturing the portion of correct prediction among all test data points. A way to model this is for each correct QPA-tuple, we give a score of 1.0 and otherwise 0.0, then we take an average of all tuple scores.</p><p>PredictionIO has a [[AverageMetric]] helper class which provides this feature. This class takes 4 type parameters, [[Ev
alInfo]], [[Query]], [[PredictedResult]], and [[ActualResult]], these types can be found from the engine's signature. Line 5 below is the custom calculation.</p><div class="highlight scala"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1
+2
+3
+4
+5
+6</pre></td><td class="code"><pre><span class="k">case</span> <span class="k">class</span> <span class="nc">Accuracy</span>
+ <span class="k">extends</span> <span class="nc">AverageMetric</span><span class="o">[</span><span class="kt">EmptyEvaluationInfo</span>, <span class="kt">Query</span>, <span class="kt">PredictedResult</span>, <span class="kt">ActualResult</span><span class="o">]</span> <span class="o">{</span>
+ <span class="k">def</span> <span class="n">calculate</span><span class="o">(</span><span class="n">query</span><span class="k">:</span> <span class="kt">Query</span><span class="o">,</span> <span class="n">predicted</span><span class="k">:</span> <span class="kt">PredictedResult</span><span class="o">,</span> <span class="n">actual</span><span class="k">:</span> <span class="kt">ActualResult</span><span class="o">)</span>
+ <span class="k">:</span> <span class="kt">Double</span> <span class="o">=</span>
+ <span class="o">(</span><span class="k">if</span> <span class="o">(</span><span class="n">predicted</span><span class="o">.</span><span class="n">label</span> <span class="o">==</span> <span class="n">actual</span><span class="o">.</span><span class="n">label</span><span class="o">)</span> <span class="mf">1.0</span> <span class="k">else</span> <span class="mf">0.0</span><span class="o">)</span>
+<span class="o">}</span>
+</pre></td></tr></tbody></table> </div> <p>Once we define a metric, we tell PredictionIO we are using it in the <code>Evaluation</code> object. We can run the following command to kick start the evaluation.</p><div class="highlight shell"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1
+2
+3
+4
+5</pre></td><td class="code"><pre><span class="gp">$ </span>pio build
+...
+<span class="gp">$ </span>pio <span class="nb">eval </span>org.template.classification.AccuracyEvaluation <span class="se">\</span>
+ org.template.classification.EngineParamsList
+...
+</pre></td></tr></tbody></table> </div> <p>(See MyClassification/src/main/scala/<strong><em>Evaluation.scala</em></strong> for full usage.)</p><h2 id='example-2:-precision-metric' class='header-anchors'>Example 2: Precision Metric</h2><p>Precision is a metric for binary classifier capturing the portion of correction prediction among all <em>positive</em> predictions. We don't care about the cases where the QPA-tuple gives a negative prediction. (Recall that a binary classifier only provide two output values: <em>positive</em> and <em>negative</em>.) The following table illustrates all four cases:</p> <table><thead> <tr> <th style="text-align: center">PredictedResult</th> <th style="text-align: center">ActualResult</th> <th style="text-align: center">Value</th> </tr> </thead><tbody> <tr> <td style="text-align: center">Positive</td> <td style="text-align: center">Positive</td> <td style="text-align: center">1.0</td> </tr> <tr> <td style="text-align: center">Positive</td> <td style
="text-align: center">Negative</td> <td style="text-align: center">0.0</td> </tr> <tr> <td style="text-align: center">Negative</td> <td style="text-align: center">Positive</td> <td style="text-align: center">Don't care</td> </tr> <tr> <td style="text-align: center">Negative</td> <td style="text-align: center">Negative</td> <td style="text-align: center">Don't care</td> </tr> </tbody></table> <p>Calculating the precision metric is a slightly more involved procedure than calculating the accuracy metric as we have to specially handle the <em>don't care</em> negative cases.</p><p>PredictionIO provides a helper class <code>OptionAverageMetric</code> allows user to specify <em>don't care</em> values as <code>None</code>. It only aggregates the non-None values. Lines 3 to 4 is the method signature of <code>calcuate</code> method. The key difference is that the return value is a <code>Option[Double]</code>, in contrast to <code>Double</code> for <code>AverageMetric</code>. T
his class only computes the average of <code>Some(.)</code> results. Lines 5 to 13 are the actual logic. The first <code>if</code> factors out the positively predicted case, and the computation is simliar to the accuracy metric. The negatively predicted case are the <em>don't cares</em>, which we return <code>None</code>.</p><div class="highlight scala"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1
+2
+3
+4
+5
+6
+7
+8
+9
+10
+11
+12
+13
+14
+15</pre></td><td class="code"><pre><span class="k">case</span> <span class="k">class</span> <span class="nc">Precision</span><span class="o">(</span><span class="n">label</span><span class="k">:</span> <span class="kt">Double</span><span class="o">)</span>
+ <span class="k">extends</span> <span class="nc">OptionAverageMetric</span><span class="o">[</span><span class="kt">EmptyEvaluationInfo</span>, <span class="kt">Query</span>, <span class="kt">PredictedResult</span>, <span class="kt">ActualResult</span><span class="o">]</span> <span class="o">{</span>
+ <span class="k">def</span> <span class="n">calculate</span><span class="o">(</span><span class="n">query</span><span class="k">:</span> <span class="kt">Query</span><span class="o">,</span> <span class="n">predicted</span><span class="k">:</span> <span class="kt">PredictedResult</span><span class="o">,</span> <span class="n">actual</span><span class="k">:</span> <span class="kt">ActualResult</span><span class="o">)</span>
+ <span class="k">:</span> <span class="kt">Option</span><span class="o">[</span><span class="kt">Double</span><span class="o">]</span> <span class="k">=</span> <span class="o">{</span>
+ <span class="k">if</span> <span class="o">(</span><span class="n">predicted</span><span class="o">.</span><span class="n">label</span> <span class="o">==</span> <span class="n">label</span><span class="o">)</span> <span class="o">{</span>
+ <span class="k">if</span> <span class="o">(</span><span class="n">predicted</span><span class="o">.</span><span class="n">label</span> <span class="o">==</span> <span class="n">actual</span><span class="o">.</span><span class="n">label</span><span class="o">)</span> <span class="o">{</span>
+ <span class="nc">Some</span><span class="o">(</span><span class="mf">1.0</span><span class="o">)</span> <span class="c1">// True positive
+</span> <span class="o">}</span> <span class="k">else</span> <span class="o">{</span>
+ <span class="nc">Some</span><span class="o">(</span><span class="mf">0.0</span><span class="o">)</span> <span class="c1">// False positive
+</span> <span class="o">}</span>
+ <span class="o">}</span> <span class="k">else</span> <span class="o">{</span>
+ <span class="nc">None</span> <span class="c1">// Unrelated case for calcuating precision
+</span> <span class="o">}</span>
+ <span class="o">}</span>
+<span class="o">}</span>
+</pre></td></tr></tbody></table> </div> <p>We define a new <code>Evaluation</code> object to tell PredictionIO how to use this new precision metric.</p><div class="highlight shell"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1
+2
+3</pre></td><td class="code"><pre>object PrecisionEvaluation extends Evaluation <span class="o">{</span>
+ engineMetric <span class="o">=</span> <span class="o">(</span>ClassificationEngine<span class="o">()</span>, new Precision<span class="o">(</span>label <span class="o">=</span> 1.0<span class="o">))</span>
+<span class="o">}</span>
+</pre></td></tr></tbody></table> </div> <p>We can kickstarts the evaluation with the following command, notice that we are reusing the same engine params list as before. This address the separation of concern when we conduct hyperparameter tuning.</p><div class="highlight shell"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1
+2
+3
+4
+5
+6
+7
+8
+9
+10
+11
+12
+13
+14
+15
+16
+17
+18
+19
+20
+21
+22
+23
+24
+25
+26
+27
+28
+29
+30
+31
+32
+33
+34
+35
+36
+37
+38
+39
+40
+41
+42
+43
+44
+45
+46</pre></td><td class="code"><pre><span class="gp">$ </span>pio build
+...
+<span class="gp">$ </span>pio <span class="nb">eval </span>org.template.classification.PrecisionEvaluation <span class="se">\</span>
+ org.template.classification.EngineParamsList
+...
+<span class="o">[</span>INFO] <span class="o">[</span>CoreWorkflow<span class="nv">$]</span> Starting evaluation instance ID: SMhzYbJ9QgKkD0fQzTA7MA
+...
+<span class="o">[</span>INFO] <span class="o">[</span>MetricEvaluator] Iteration 0
+<span class="o">[</span>INFO] <span class="o">[</span>MetricEvaluator] EngineParams: <span class="o">{</span><span class="s2">"dataSourceParams"</span>:<span class="o">{</span><span class="s2">""</span>:<span class="o">{</span><span class="s2">"appId"</span>:19,<span class="s2">"evalK"</span>:5<span class="o">}}</span>,<span class="s2">"preparatorParams"</span>:<span class="o">{</span><span class="s2">""</span>:<span class="o">{}}</span>,<span class="s2">"algorithmParamsList"</span>:[<span class="o">{</span><span class="s2">"naive"</span>:<span class="o">{</span><span class="s2">"lambda"</span>:10.0<span class="o">}}]</span>,<span class="s2">"servingParams"</span>:<span class="o">{</span><span class="s2">""</span>:<span class="o">{}}}</span>
+<span class="o">[</span>INFO] <span class="o">[</span>MetricEvaluator] Result: MetricScores<span class="o">(</span>0.8846153846153846,List<span class="o">())</span>
+<span class="o">[</span>INFO] <span class="o">[</span>MetricEvaluator] Iteration 1
+<span class="o">[</span>INFO] <span class="o">[</span>MetricEvaluator] EngineParams: <span class="o">{</span><span class="s2">"dataSourceParams"</span>:<span class="o">{</span><span class="s2">""</span>:<span class="o">{</span><span class="s2">"appId"</span>:19,<span class="s2">"evalK"</span>:5<span class="o">}}</span>,<span class="s2">"preparatorParams"</span>:<span class="o">{</span><span class="s2">""</span>:<span class="o">{}}</span>,<span class="s2">"algorithmParamsList"</span>:[<span class="o">{</span><span class="s2">"naive"</span>:<span class="o">{</span><span class="s2">"lambda"</span>:100.0<span class="o">}}]</span>,<span class="s2">"servingParams"</span>:<span class="o">{</span><span class="s2">""</span>:<span class="o">{}}}</span>
+<span class="o">[</span>INFO] <span class="o">[</span>MetricEvaluator] Result: MetricScores<span class="o">(</span>0.7936507936507936,List<span class="o">())</span>
+<span class="o">[</span>INFO] <span class="o">[</span>MetricEvaluator] Iteration 2
+<span class="o">[</span>INFO] <span class="o">[</span>MetricEvaluator] EngineParams: <span class="o">{</span><span class="s2">"dataSourceParams"</span>:<span class="o">{</span><span class="s2">""</span>:<span class="o">{</span><span class="s2">"appId"</span>:19,<span class="s2">"evalK"</span>:5<span class="o">}}</span>,<span class="s2">"preparatorParams"</span>:<span class="o">{</span><span class="s2">""</span>:<span class="o">{}}</span>,<span class="s2">"algorithmParamsList"</span>:[<span class="o">{</span><span class="s2">"naive"</span>:<span class="o">{</span><span class="s2">"lambda"</span>:1000.0<span class="o">}}]</span>,<span class="s2">"servingParams"</span>:<span class="o">{</span><span class="s2">""</span>:<span class="o">{}}}</span>
+<span class="o">[</span>INFO] <span class="o">[</span>MetricEvaluator] Result: MetricScores<span class="o">(</span>0.37593984962406013,List<span class="o">())</span>
+<span class="o">[</span>INFO] <span class="o">[</span>CoreWorkflow<span class="nv">$]</span> Updating evaluation instance with result: MetricEvaluatorResult:
+ <span class="c"># engine params evaluated: 3</span>
+Optimal Engine Params:
+ <span class="o">{</span>
+ <span class="s2">"dataSourceParams"</span>:<span class="o">{</span>
+ <span class="s2">""</span>:<span class="o">{</span>
+ <span class="s2">"appId"</span>:19,
+ <span class="s2">"evalK"</span>:5
+ <span class="o">}</span>
+ <span class="o">}</span>,
+ <span class="s2">"preparatorParams"</span>:<span class="o">{</span>
+ <span class="s2">""</span>:<span class="o">{</span>
+
+ <span class="o">}</span>
+ <span class="o">}</span>,
+ <span class="s2">"algorithmParamsList"</span>:[
+ <span class="o">{</span>
+ <span class="s2">"naive"</span>:<span class="o">{</span>
+ <span class="s2">"lambda"</span>:10.0
+ <span class="o">}</span>
+ <span class="o">}</span>
+ <span class="o">]</span>,
+ <span class="s2">"servingParams"</span>:<span class="o">{</span>
+ <span class="s2">""</span>:<span class="o">{</span>
+
+ <span class="o">}</span>
+ <span class="o">}</span>
+<span class="o">}</span>
+Metrics:
+ org.template.classification.Precision: 0.8846153846153846
+</pre></td></tr></tbody></table> </div> <p>(See MyClassification/src/main/scala/<strong><em>PrecisionEvaluation.scala</em></strong> for the full usage.)</p></div></div></div></div><footer><div class="container"><div class="seperator"></div><div class="row"><div class="col-md-4 col-md-push-8 col-xs-12"><div class="subscription-form-wrapper"><h4>Subscribe to our Newsletter</h4><form class="ajax-form" id="subscribe-form" method="POST" action="https://script.google.com/macros/s/AKfycbwhzeKCQJjQ52eVAqNT_vcklH07OITUO7wzOMDXvK6EGAWgaZgF/exec"><input class="required underlined-input" type="email" placeholder="Your email address" name="subscription_email" id="subscription_email"/><input class="pill-button" value="SUBSCRIBE" type="submit" data-state-normal="SUBSCRIBE" data-state-sucess="SUBSCRIBED!" data-state-loading="SENDING..." onclick="t($('#subscription_email').val());"/><p class="result"></p></form></div></div><div class="col-md-2 col-md-pull-4 col-xs-6 footer-link-column"><div class="f
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<a class="expandible" href="#"><span>Integrating with Your App</span></a><ul><li class="level-2"><a class="final" href="/appintegration/"><span>App Integration Overview</span></a></li><li class="level-2"><a class="expandible" href="/sdk/"><span>List of SDKs</span></a><ul><li class="level-3"><a class="final" href="/sdk/java/"><span>Java & Android SDK</span></a></li><li class="level-3"><a class="final" href="/sdk/php/"><span>PHP SDK</span></a></li><li class="level-3"><a class="final" href="/sdk/python/"><span>Python SDK</span></a></li><li class="level-3"><a class="final" href="/sdk/ruby/"><span>Ruby SDK</span></a></li><li class="level-3"><a class="final" href="/sdk/community/"><span>Community Powered SDKs</span></a></li></ul></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Deploying an Engine</span></a><ul><li class="level-2"><a class="final" href="/deploy/"><span>Deploying as a Web Service</span></a></li><li class="level-2"><a class="final" href="/cli/#engine-c
ommands"><span>Engine Command-line Interface</span></a></li><li class="level-2"><a class="final" href="/deploy/engineparams/"><span>Setting Engine Parameters</span></a></li><li class="level-2"><a class="final" href="/deploy/enginevariants/"><span>Deploying Multiple Engine Variants</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Customizing an Engine</span></a><ul><li class="level-2"><a class="final" href="/customize/"><span>Learning DASE</span></a></li><li class="level-2"><a class="final" href="/customize/dase/"><span>Implement DASE</span></a></li><li class="level-2"><a class="final" href="/customize/troubleshooting/"><span>Troubleshooting Engine Development</span></a></li><li class="level-2"><a class="final" href="/api/current/#package"><span>Engine Scala APIs</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Collecting and Analyzing Data</span></a><ul><li class="level-2"><a class="final" href="/datacollection/"><spa
n>Event Server Overview</span></a></li><li class="level-2"><a class="final" href="/cli/#event-server-commands"><span>Event Server Command-line Interface</span></a></li><li class="level-2"><a class="final" href="/datacollection/eventapi/"><span>Collecting Data with REST/SDKs</span></a></li><li class="level-2"><a class="final" href="/datacollection/eventmodel/"><span>Events Modeling</span></a></li><li class="level-2"><a class="final" href="/datacollection/webhooks/"><span>Unifying Multichannel Data with Webhooks</span></a></li><li class="level-2"><a class="final" href="/datacollection/channel/"><span>Channel</span></a></li><li class="level-2"><a class="final" href="/datacollection/batchimport/"><span>Importing Data in Batch</span></a></li><li class="level-2"><a class="final" href="/datacollection/analytics/"><span>Using Analytics Tools</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Choosing an Algorithm(s)</span></a><ul><li class="level-2"><a class="
final" href="/algorithm/"><span>Built-in Algorithm Libraries</span></a></li><li class="level-2"><a class="final" href="/algorithm/switch/"><span>Switching to Another Algorithm</span></a></li><li class="level-2"><a class="final" href="/algorithm/multiple/"><span>Combining Multiple Algorithms</span></a></li><li class="level-2"><a class="final" href="/algorithm/custom/"><span>Adding Your Own Algorithms</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>ML Tuning and Evaluation</span></a><ul><li class="level-2"><a class="final" href="/evaluation/"><span>Overview</span></a></li><li class="level-2"><a class="final" href="/evaluation/paramtuning/"><span>Hyperparameter Tuning</span></a></li><li class="level-2"><a class="final" href="/evaluation/evaluationdashboard/"><span>Evaluation Dashboard</span></a></li><li class="level-2"><a class="final active" href="/evaluation/metricchoose/"><span>Choosing Evaluation Metrics</span></a></li><li class="level-2"><a class=
"final" href="/evaluation/metricbuild/"><span>Building Evaluation Metrics</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>System Architecture</span></a><ul><li class="level-2"><a class="final" href="/system/"><span>Architecture Overview</span></a></li><li class="level-2"><a class="final" href="/system/anotherdatastore/"><span>Using Another Data Store</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Engine Template Gallery</span></a><ul><li class="level-2"><a class="final" href="http://templates.prediction.io"><span>Browse</span></a></li><li class="level-2"><a class="final" href="/community/submit-template/"><span>Submit your Engine as a Template</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Demo Tutorials</span></a><ul><li class="level-2"><a class="final" href="/demo/tapster/"><span>Comics Recommendation Demo</span></a></li><li class="level-2"><a class="final" href="/demo/community
/"><span>Community Contributed Demo</span></a></li><li class="level-2"><a class="final" href="/demo/textclassification/"><span>Text Classification Engine Tutorial</span></a></li></ul></li><li class="level-1"><a class="expandible" href="/community/"><span>Getting Involved</span></a><ul><li class="level-2"><a class="final" href="/community/contribute-code/"><span>Contribute Code</span></a></li><li class="level-2"><a class="final" href="/community/contribute-documentation/"><span>Contribute Documentation</span></a></li><li class="level-2"><a class="final" href="/community/contribute-sdk/"><span>Contribute a SDK</span></a></li><li class="level-2"><a class="final" href="/community/contribute-webhook/"><span>Contribute a Webhook</span></a></li><li class="level-2"><a class="final" href="/community/projects/"><span>Community Projects</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Getting Help</span></a><ul><li class="level-2"><a class="final" href="/resour
ces/faq/"><span>FAQs</span></a></li><li class="level-2"><a class="final" href="/support/"><span>Community Support</span></a></li><li class="level-2"><a class="final" href="/support/#enterprise-support"><span>Enterprise Support</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Resources</span></a><ul><li class="level-2"><a class="final" href="/resources/intellij/"><span>Developing Engines with IntelliJ IDEA</span></a></li><li class="level-2"><a class="final" href="/resources/upgrade/"><span>Upgrade Instructions</span></a></li><li class="level-2"><a class="final" href="/resources/glossary/"><span>Glossary</span></a></li></ul></li></ul></nav></div><div class="col-md-9 col-sm-12"><div class="content-header hidden-md hidden-lg"><div id="breadcrumbs" class="hidden-sm hidden xs"><ul><li><a href="#">ML Tuning and Evaluation</a><span class="spacer">></span></li><li><span class="last">Choosing Evaluation Metrics</span></li></ul></div><div id="page-title"><h1
>Choosing Evaluation Metrics</h1></div></div><div id="table-of-content-wrapper"><h5>On this page</h5><aside id="table-of-contents"><ul> <li> <a href="#defining-metric">Defining Metric</a> </li> <li> <a href="#common-metrics">Common Metrics</a> </li> </ul> </aside><hr/><a id="edit-page-link" href="https://github.com/apache/incubator-predictionio/tree/livedoc/docs/manual/source/evaluation/metricchoose.html.md"><img src="/images/icons/edit-pencil-d6c1bb3d.png"/>Edit this page</a></div><div class="content-header hidden-sm hidden-xs"><div id="breadcrumbs" class="hidden-sm hidden xs"><ul><li><a href="#">ML Tuning and Evaluation</a><span class="spacer">></span></li><li><span class="last">Choosing Evaluation Metrics</span></li></ul></div><div id="page-title"><h1>Choosing Evaluation Metrics</h1></div></div><div class="content"><p>The <a href="/evaluation/paramtuning/">hyperparameter tuning module</a> allows us to select the optimal engine parameter defined by a <code>Metric</code>. <code>
Metric</code> determines the quality of an engine variant. We have skimmmed through the process of choosing the right <code>Metric</code> in previous sections.</p><p>This secion discusses basic evaluation metrics commonly used for classification problems. If you are more interested in knowing how to <em>implement</em> a custom metric, please skip to <a href="/evaluation/metricbuild/">the next section</a>.</p><h2 id='defining-metric' class='header-anchors'>Defining Metric</h2><p>Metric evaluates the quality of an engine by comparing engine's output (predicted result) with the original label (actual result). A engine serving better prediction should yield a higher metric score, the tuning module returns the engine parameter with the highest score. It is sometimes called <a href="http://en.wikipedia.org/wiki/Loss_function"><em>loss function</em></a> in literature, where the goal is to minimize the loss function. </p><p>During tuning, it is important for us to understand the definit
ion of the metric, to make sure it is aligned with the prediction engine's goal.</p><p>In the classificaiton template, we use <em>Accuracy</em> as our metric. <em>Accuracy</em> is defined as: the percentage of queries which the engine is able to predict the correct label. </p><h2 id='common-metrics' class='header-anchors'>Common Metrics</h2><p>We illustrate the choice of metric with the following confusion matrix. Row represents the engine predicted label, column represents the acutal label. The second row means that of the 200 testing data points, the engine predicted 60 (15 + 35 + 10) of them as label 2.0, among which 35 are correct prediction (i.e. actual label is 2.0, matches with the prediction), and 25 are wrong.</p> <table><thead> <tr> <th style="text-align: center"></th> <th style="text-align: center">Actual = 1.0</th> <th style="text-align: center">Actual = 2.0</th> <th style="text-align: center">Actual = 3.0</th> </tr> </thead><tbody> <tr> <td style="text-align: center
"><strong>Predicted = 1.0</strong></td> <td style="text-align: center">30</td> <td style="text-align: center">0</td> <td style="text-align: center">60</td> </tr> <tr> <td style="text-align: center"><strong>Predicted = 2.0</strong></td> <td style="text-align: center">15</td> <td style="text-align: center">35</td> <td style="text-align: center">10</td> </tr> <tr> <td style="text-align: center"><strong>Predicted = 3.0</strong></td> <td style="text-align: center">0</td> <td style="text-align: center">0</td> <td style="text-align: center">50</td> </tr> </tbody></table> <h3 id='accuracy' class='header-anchors'>Accuracy</h3><p>Accuracy means that how many data points are predicted correctly. It is one of the simplest form of evaluation metrics. The accuracy score is # of correct points / # total = (30 + 35 + 50) / 200 = 0.575.</p><h3 id='precision' class='header-anchors'>Precision</h3><p>Precision is a metric for binary classifier which measures the correctness among all positive labels. A
binary classifier gives only two output values (i.e. positive and negative). For problem where there are multiple values (3 in our example), we first have to tranform our problem into a binary classification problem. For example, we can have problem whether label = 1.0. The confusion matrix now becomes:</p> <table><thead> <tr> <th style="text-align: center"></th> <th style="text-align: center">Actual = 1.0</th> <th style="text-align: center">Actual != 1.0</th> </tr> </thead><tbody> <tr> <td style="text-align: center"><strong>Predicted = 1.0</strong></td> <td style="text-align: center">30</td> <td style="text-align: center">60</td> </tr> <tr> <td style="text-align: center"><strong>Predicted != 1.0</strong></td> <td style="text-align: center">15</td> <td style="text-align: center">95</td> </tr> </tbody></table> <p>Precision is the ratio between the number of correct positive answer (true positive) and the sum of correct positive answer (true positive) and wrong but positively labeled
answer (false positive). In this case, the precision is 30 / (30 + 60) = ~0.3333.</p><h3 id='recall' class='header-anchors'>Recall</h3><p>Recall is a metric for binary classifier which measures how many positive labels are successfully predicted amongst all positive labels. Formally, it is the ratio between the number of correct positive answer (true positive) and the sum of correct positive answer (true positive) and wrongly negatively labeled asnwer (false negative). In this case, the recall is 30 / (30 + 15) = ~0.6667.</p><p>As we have discussed several common metrics for classification problem, we can implement them using the <code>Metric</code> class in <a href="/evaluation/metricbuild">the next section</a>.</p></div></div></div></div><footer><div class="container"><div class="seperator"></div><div class="row"><div class="col-md-4 col-md-push-8 col-xs-12"><div class="subscription-form-wrapper"><h4>Subscribe to our Newsletter</h4><form class="ajax-form" id="subscribe-form" meth
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+fbq('track', "PageView");</script><script src="//use.typekit.net/mut4mjx.js"></script><script>try{Typekit.load();}catch(e){}</script></head><body><div id="global"><header><div class="container" id="header-wrapper"><div class="row"><div class="col-sm-12"><div id="logo-wrapper"><span id="drawer-toggle"></span><a href="#"></a><a href="http://prediction.io/"><img alt="PredictionIO" id="logo" src="/images/logos/logo-ee2b9bb3.png"/></a></div><div id="menu-wrapper"><div id="header-nav-options-wrapper"><ul><li><a href="/">Install & Doc</a></li> <li><a href="/support">Support</a></li> </ul></div><div id="pill-wrapper"><a class="pill left" href="//templates.prediction.io/">TEMPLATES</a> <a class="pill right" href="//github.com/PredictionIO/PredictionIO/">OPEN SOURCE</a></div></div><img class="mobile-search-bar-toggler hidden-md hidden-lg" src="/images/icons/search-glass-704bd4ff.png"/></div></div></div></header><div id="search-bar-row-wrapper"><div class="container-fluid" id="search-bar-row">
<div class="row"><div class="col-md-9 col-sm-11 col-xs-11"><div class="hidden-md hidden-lg" id="mobile-page-heading-wrapper"><p>PredictionIO Docs</p><h4>Quick Start - Classification Engine Template</h4></div><h4 class="hidden-sm hidden-xs">PredictionIO Docs</h4></div><div class="col-md-3 col-sm-1 col-xs-1 hidden-md hidden-lg"><img id="left-menu-indicator" src="/images/icons/down-arrow-dfe9f7fe.png"/></div><div class="col-md-3 col-sm-12 col-xs-12 swiftype-wrapper"><div class="swiftype"><form class="search-form"><img class="search-box-toggler hidden-xs hidden-sm" src="/images/icons/search-glass-704bd4ff.png"/><div class="search-box"><img src="/images/icons/search-glass-704bd4ff.png"/><input type="text" id="st-search-input" class="st-search-input" placeholder="Search Doc..."/></div><img class="swiftype-row-hider hidden-md hidden-lg" src="/images/icons/drawer-toggle-active-fcbef12a.png"/></form></div></div><div class="mobile-left-menu-toggler hidden-md hidden-lg"></div></div></div></div
><div id="page" class="container-fluid"><div class="row"><div id="left-menu-wrapper" class="col-md-3"><nav id="nav-main"><ul><li class="level-1"><a class="expandible" href="/"><span>Apache PredictionIO (incubating) Documentation</span></a><ul><li class="level-2"><a class="final" href="/"><span>Welcome to Apache PredictionIO (incubating)</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Getting Started</span></a><ul><li class="level-2"><a class="final" href="/start/"><span>A Quick Intro</span></a></li><li class="level-2"><a class="final" href="/install/"><span>Installing Apache PredictionIO (incubating)</span></a></li><li class="level-2"><a class="final" href="/start/download/"><span>Downloading an Engine Template</span></a></li><li class="level-2"><a class="final" href="/start/deploy/"><span>Deploying Your First Engine</span></a></li><li class="level-2"><a class="final" href="/start/customize/"><span>Customizing the Engine</span></a></li></ul></li><li
class="level-1"><a class="expandible" href="#"><span>Integrating with Your App</span></a><ul><li class="level-2"><a class="final" href="/appintegration/"><span>App Integration Overview</span></a></li><li class="level-2"><a class="expandible" href="/sdk/"><span>List of SDKs</span></a><ul><li class="level-3"><a class="final" href="/sdk/java/"><span>Java & Android SDK</span></a></li><li class="level-3"><a class="final" href="/sdk/php/"><span>PHP SDK</span></a></li><li class="level-3"><a class="final" href="/sdk/python/"><span>Python SDK</span></a></li><li class="level-3"><a class="final" href="/sdk/ruby/"><span>Ruby SDK</span></a></li><li class="level-3"><a class="final" href="/sdk/community/"><span>Community Powered SDKs</span></a></li></ul></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Deploying an Engine</span></a><ul><li class="level-2"><a class="final" href="/deploy/"><span>Deploying as a Web Service</span></a></li><li class="level-2"><a class="final" hre
f="/cli/#engine-commands"><span>Engine Command-line Interface</span></a></li><li class="level-2"><a class="final" href="/deploy/engineparams/"><span>Setting Engine Parameters</span></a></li><li class="level-2"><a class="final" href="/deploy/enginevariants/"><span>Deploying Multiple Engine Variants</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Customizing an Engine</span></a><ul><li class="level-2"><a class="final" href="/customize/"><span>Learning DASE</span></a></li><li class="level-2"><a class="final" href="/customize/dase/"><span>Implement DASE</span></a></li><li class="level-2"><a class="final" href="/customize/troubleshooting/"><span>Troubleshooting Engine Development</span></a></li><li class="level-2"><a class="final" href="/api/current/#package"><span>Engine Scala APIs</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Collecting and Analyzing Data</span></a><ul><li class="level-2"><a class="final" href="/data
collection/"><span>Event Server Overview</span></a></li><li class="level-2"><a class="final" href="/cli/#event-server-commands"><span>Event Server Command-line Interface</span></a></li><li class="level-2"><a class="final" href="/datacollection/eventapi/"><span>Collecting Data with REST/SDKs</span></a></li><li class="level-2"><a class="final" href="/datacollection/eventmodel/"><span>Events Modeling</span></a></li><li class="level-2"><a class="final" href="/datacollection/webhooks/"><span>Unifying Multichannel Data with Webhooks</span></a></li><li class="level-2"><a class="final" href="/datacollection/channel/"><span>Channel</span></a></li><li class="level-2"><a class="final" href="/datacollection/batchimport/"><span>Importing Data in Batch</span></a></li><li class="level-2"><a class="final" href="/datacollection/analytics/"><span>Using Analytics Tools</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Choosing an Algorithm(s)</span></a><ul><li class="le
vel-2"><a class="final" href="/algorithm/"><span>Built-in Algorithm Libraries</span></a></li><li class="level-2"><a class="final" href="/algorithm/switch/"><span>Switching to Another Algorithm</span></a></li><li class="level-2"><a class="final" href="/algorithm/multiple/"><span>Combining Multiple Algorithms</span></a></li><li class="level-2"><a class="final" href="/algorithm/custom/"><span>Adding Your Own Algorithms</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>ML Tuning and Evaluation</span></a><ul><li class="level-2"><a class="final" href="/evaluation/"><span>Overview</span></a></li><li class="level-2"><a class="final" href="/evaluation/paramtuning/"><span>Hyperparameter Tuning</span></a></li><li class="level-2"><a class="final" href="/evaluation/evaluationdashboard/"><span>Evaluation Dashboard</span></a></li><li class="level-2"><a class="final" href="/evaluation/metricchoose/"><span>Choosing Evaluation Metrics</span></a></li><li class="level-2"
><a class="final" href="/evaluation/metricbuild/"><span>Building Evaluation Metrics</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>System Architecture</span></a><ul><li class="level-2"><a class="final" href="/system/"><span>Architecture Overview</span></a></li><li class="level-2"><a class="final" href="/system/anotherdatastore/"><span>Using Another Data Store</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Engine Template Gallery</span></a><ul><li class="level-2"><a class="final" href="http://templates.prediction.io"><span>Browse</span></a></li><li class="level-2"><a class="final" href="/community/submit-template/"><span>Submit your Engine as a Template</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Demo Tutorials</span></a><ul><li class="level-2"><a class="final" href="/demo/tapster/"><span>Comics Recommendation Demo</span></a></li><li class="level-2"><a class="final" href="/demo
/community/"><span>Community Contributed Demo</span></a></li><li class="level-2"><a class="final" href="/demo/textclassification/"><span>Text Classification Engine Tutorial</span></a></li></ul></li><li class="level-1"><a class="expandible" href="/community/"><span>Getting Involved</span></a><ul><li class="level-2"><a class="final" href="/community/contribute-code/"><span>Contribute Code</span></a></li><li class="level-2"><a class="final" href="/community/contribute-documentation/"><span>Contribute Documentation</span></a></li><li class="level-2"><a class="final" href="/community/contribute-sdk/"><span>Contribute a SDK</span></a></li><li class="level-2"><a class="final" href="/community/contribute-webhook/"><span>Contribute a Webhook</span></a></li><li class="level-2"><a class="final" href="/community/projects/"><span>Community Projects</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Getting Help</span></a><ul><li class="level-2"><a class="final" hre
f="/resources/faq/"><span>FAQs</span></a></li><li class="level-2"><a class="final" href="/support/"><span>Community Support</span></a></li><li class="level-2"><a class="final" href="/support/#enterprise-support"><span>Enterprise Support</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Resources</span></a><ul><li class="level-2"><a class="final" href="/resources/intellij/"><span>Developing Engines with IntelliJ IDEA</span></a></li><li class="level-2"><a class="final" href="/resources/upgrade/"><span>Upgrade Instructions</span></a></li><li class="level-2"><a class="final" href="/resources/glossary/"><span>Glossary</span></a></li></ul></li></ul></nav></div><div class="col-md-9 col-sm-12"><div class="content-header hidden-md hidden-lg"><div id="page-title"><h1>Quick Start - Classification Engine Template</h1></div></div><div id="table-of-content-wrapper"><h5>On this page</h5><aside id="table-of-contents"><ul> <li> <a href="#overview">Overview</a> </li> <
li> <a href="#usage">Usage</a> </li> <li> <a href="#1-install-and-run-predictionio">1. Install and Run PredictionIO</a> </li> <li> <a href="#2-create-a-new-engine-from-an-engine-template">2. Create a new Engine from an Engine Template</a> </li> <li> <a href="#3-generate-an-app-id-and-access-key">3. Generate an App ID and Access Key</a> </li> <li> <a href="#4-collecting-data">4. Collecting Data</a> </li> <li> <a href="#5-deploy-the-engine-as-a-service">5. Deploy the Engine as a Service</a> </li> <li> <a href="#6-use-the-engine">6. Use the Engine</a> </li> </ul> </aside><hr/><a id="edit-page-link" href="https://github.com/apache/incubator-predictionio/tree/livedoc/docs/manual/source/templates/classification/quickstart.html.md.erb"><img src="/images/icons/edit-pencil-d6c1bb3d.png"/>Edit this page</a></div><div class="content-header hidden-sm hidden-xs"><div id="page-title"><h1>Quick Start - Classification Engine Template</h1></div></div><div class="content"><h2 id='overview' class='hea
der-anchors'>Overview</h2><p>An engine template is an almost-complete implementation of an engine. PredictionIO's Classification Engine Template has integrated <strong>Apache Spark MLlib</strong>'s Naive Bayes algorithm by default.</p><p>The default use case of Classification Engine Template is to predict the service plan (<em>plan</em>) a user will subscribe to based on his 3 properties: <em>attr0</em>, <em>attr1</em> and <em>attr2</em>.</p><p>You can customize it easily to fit your specific use case and needs.</p><p>We are going to show you how to create your own classification engine for production use based on this template.</p><h2 id='usage' class='header-anchors'>Usage</h2><h3 id='event-data-requirements' class='header-anchors'>Event Data Requirements</h3><p>By default, the template requires the following events to be collected:</p> <ul> <li>user $set event, which set the attributes of the user</li> </ul> <div class="alert-message note"><p>You can customize to use othe
r event.</p></div><h3 id='input-query' class='header-anchors'>Input Query</h3> <ul> <li>individual attributes values (for version >= v0.3.1)</li> </ul> <div class="alert-message warning"><p>for version < v0.3.1, it is array of features values</p></div><h3 id='output-predictedresult' class='header-anchors'>Output PredictedResult</h3> <ul> <li>the predicted label</li> </ul> <h2 id='1.-install-and-run-predictionio' class='header-anchors'>1. Install and Run PredictionIO</h2><p>First you need to <a href="/install">install PredictionIO 0.9.6</a> (if you haven't done it).</p><p>Let's say you have installed PredictionIO at <code>/home/yourname/PredictionIO/</code>. For convenience, add PredictionIO's binary command path to your <code>PATH</code>, i.e. <code>/home/yourname/PredictionIO/bin</code>:</p><div class="highlight shell"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1</pre></td><td class="code"><pre><
span class="gp">$ </span><span class="nv">PATH</span><span class="o">=</span><span class="nv">$PATH</span>:/home/yourname/PredictionIO/bin; <span class="nb">export </span>PATH
+</pre></td></tr></tbody></table> </div> <div class="alert-message note"><p>If you launched <strong>PredictionIO AWS instance</strong>, the path is located at <code>/opt/PredictionIO/bin</code>.</p></div><p>Once you have completed the installation process, please make sure all the components (PredictionIO Event Server, Elasticsearch, and HBase) are up and running.</p><div class="alert-message note"><p>If you launched <strong>PredictionIO AWS instance</strong>, you can skip <code>pio-start-all</code>. All components should have been started automatically.</p></div><p>If you are using PostgreSQL or MySQL, run the following to start PredictionIO Event Server:</p><div class="highlight shell"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1</pre></td><td class="code"><pre><span class="gp">$ </span>pio eventserver &
+</pre></td></tr></tbody></table> </div> <p>If instead you are running HBase and Elasticsearch, run the following to start all PredictionIO Event Server, HBase, and Elasticsearch:</p><div class="highlight shell"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1</pre></td><td class="code"><pre><span class="gp">$ </span>pio-start-all
+</pre></td></tr></tbody></table> </div> <p>You can check the status by running:</p><div class="highlight shell"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1</pre></td><td class="code"><pre><span class="gp">$ </span>pio status
+</pre></td></tr></tbody></table> </div> <p>If everything is OK, you should see the following outputs:</p><div class="highlight shell"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1
+2
+3
+4</pre></td><td class="code"><pre>...
+
+<span class="o">(</span>sleeping 5 seconds <span class="k">for </span>all messages to show up...<span class="o">)</span>
+Your system is all ready to go.
+</pre></td></tr></tbody></table> </div> <div class="alert-message note"><p>To further troubleshoot, please see <a href="/resources/faq/#using-predictionio">FAQ - Using PredictionIO</a>.</p></div> <p><a href="#"></a></p> <h2 id='2.-create-a-new-engine-from-an-engine-template' class='header-anchors'>2. Create a new Engine from an Engine Template</h2><p>Now let's create a new engine called <em>MyClassification</em> by downloading the Classification Engine Template. Go to a directory where you want to put your engine and run the following:</p><div class="highlight shell"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1
+2</pre></td><td class="code"><pre><span class="gp">$ </span>pio template get PredictionIO/template-scala-parallel-classification MyClassification
+<span class="gp">$ </span><span class="nb">cd </span>MyClassification
+</pre></td></tr></tbody></table> </div> <p>A new directory <em>MyClassification</em> is created, where you can find the downloaded engine template.</p> <p><a href="#"></a></p> <h2 id='3.-generate-an-app-id-and-access-key' class='header-anchors'>3. Generate an App ID and Access Key</h2><p>You will need to create a new App in PredictionIO to store all the data of your app. The data collected will be used for machine learning modeling.</p><p>Let's assume you want to use this engine in an application named "MyApp1". Run the following to create a new app "MyApp1":</p><div class="highlight shell"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1</pre></td><td class="code"><pre><span class="gp">$ </span>pio app new MyApp1
+</pre></td></tr></tbody></table> </div> <p>You should find the following in the console output:</p><div class="highlight shell"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1
+2
+3
+4
+5
+6</pre></td><td class="code"><pre>...
+<span class="o">[</span>INFO] <span class="o">[</span>App<span class="nv">$]</span> Initialized Event Store <span class="k">for </span>this app ID: 1.
+<span class="o">[</span>INFO] <span class="o">[</span>App<span class="nv">$]</span> Created new app:
+<span class="o">[</span>INFO] <span class="o">[</span>App<span class="nv">$]</span> Name: MyApp1
+<span class="o">[</span>INFO] <span class="o">[</span>App<span class="nv">$]</span> ID: 1
+<span class="o">[</span>INFO] <span class="o">[</span>App<span class="nv">$]</span> Access Key: 3mZWDzci2D5YsqAnqNnXH9SB6Rg3dsTBs8iHkK6X2i54IQsIZI1eEeQQyMfs7b3F
+</pre></td></tr></tbody></table> </div> <p>Note that <em>App ID</em><em>, **Access Key</em>* are created for this App "MyApp1". You will need the <strong>Access Key</strong> when you collect data with EventServer for this App.</p><p>You can list all of the apps created its corresponding ID and Access Key by running the following command:</p><div class="highlight shell"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1</pre></td><td class="code"><pre><span class="gp">$ </span>pio app list
+</pre></td></tr></tbody></table> </div> <p>You should see a list of apps created. For example:</p><div class="highlight shell"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1
+2
+3
+4</pre></td><td class="code"><pre><span class="o">[</span>INFO] <span class="o">[</span>App<span class="nv">$]</span> Name | ID | Access Key | Allowed Event<span class="o">(</span>s<span class="o">)</span>
+<span class="o">[</span>INFO] <span class="o">[</span>App<span class="nv">$]</span> MyApp1 | 1 | 3mZWDzci2D5YsqAnqNnXH9SB6Rg3dsTBs8iHkK6X2i54IQsIZI1eEeQQyMfs7b3F | <span class="o">(</span>all<span class="o">)</span>
+<span class="o">[</span>INFO] <span class="o">[</span>App<span class="nv">$]</span> MyApp2 | 2 | io5lz6Eg4m3Xe4JZTBFE13GMAf1dhFl6ZteuJfrO84XpdOz9wRCrDU44EUaYuXq5 | <span class="o">(</span>all<span class="o">)</span>
+<span class="o">[</span>INFO] <span class="o">[</span>App<span class="nv">$]</span> Finished listing 2 app<span class="o">(</span>s<span class="o">)</span>.
+</pre></td></tr></tbody></table> </div> <p><a href="#"></a></p> <h2 id='4.-collecting-data' class='header-anchors'>4. Collecting Data</h2><p>Next, let's collect some training data. By default, the Classification Engine Template reads 4 properties of a user record: attr0, attr1, attr2 and plan. This templates requires '$set' user events.</p><div class="alert-message info"><p>This template can easily be customized to use different or more number of attributes.</p></div><p>You can send these events to PredictionIO Event Server in real-time easily by making a HTTP request or through the provided SDK. Please see <a href="/appintegration/">App Integration Overview</a> for more details how to integrate your app with SDK.</p><p>Let's try sending events to EventServer with the following <code>curl</code> commands (The corresponding SDK code is showed in other tabs).</p><p>Replace <code><ACCCESS_KEY></code> by the Access Key generated in above steps. Note that <code>loca
lhost:7070</code> is the default URL of the Event Server.</p><p>For convenience, set your access key to the shell variable, run:</p><p><code>$ ACCESS_KEY=<ACCESS_KEY></code></p> <p><a href="#"></a></p> <p>To set properties "attr0", "attr1", "attr2" and "plan" for user "u0" on time <code>2014-11-02T09:39:45.618-08:00</code> (current time will be used if eventTime is not specified), you can send <code>$set</code> event for the user. To send this event, run the following <code>curl</code> command:</p><div class="tabs"> <ul class="control"> <li data-lang="json"><a href="#tab-8379eb6c-a349-4450-af38-b4c0f4172242">REST API</a></li> <li data-lang="python"><a href="#tab-90c64ba8-ad3c-4767-a7d4-30c713a756c0">Python SDK</a></li> <li data-lang="php"><a href="#tab-80cd65cb-f968-4933-966f-1fae4510513e">PHP SDK</a></li> <li data-lang="ruby"><a href="#tab-8b7bbba8-1e88-417a-8286-058f04f00dfe">Ruby SDK</a></li> <li data-lang="java"><a href="#t
ab-45e13392-b2b0-4095-bf33-4c586fe33a32">Java SDK</a></li> </ul> <div data-tab="REST API" data-lang="json" id="tab-8379eb6c-a349-4450-af38-b4c0f4172242"> <div class="highlight shell"> <table style="border-spacing: 0"><tbody><tr> <td class="gutter gl" style="text-align: right"><pre class="lineno">1
+2
+3
+4
+5
+6
+7
+8
+9
+10
+11
+12
+13
+14</pre></td> <td class="code"><pre><span class="gp">$ </span>curl -i -X POST http://localhost:7070/events.json?accessKey<span class="o">=</span><span class="nv">$ACCESS_KEY</span> <span class="se">\</span>
+-H <span class="s2">"Content-Type: application/json"</span> <span class="se">\</span>
+-d <span class="s1">'{
+ "event" : "$set",
+ "entityType" : "user"
+ "entityId" : "u0",
+ "properties" : {
+ "attr0" : 0,
+ "attr1" : 1,
+ "attr2" : 0,
+ "plan" : 1
+ }
+ "eventTime" : "2014-11-02T09:39:45.618-08:00"
+}'</span>
+</pre></td> </tr></tbody></table> </div> </div> <div data-tab="Python SDK" data-lang="python" id="tab-90c64ba8-ad3c-4767-a7d4-30c713a756c0"> <div class="highlight python"> <table style="border-spacing: 0"><tbody><tr> <td class="gutter gl" style="text-align: right"><pre class="lineno">1
+2
+3
+4
+5
+6
+7
+8
+9
+10
+11
+12
+13
+14
+15
+16
+17
+18
+19
+20
+21</pre></td> <td class="code"><pre><span class="kn">import</span> <span class="nn">predictionio</span>
+
+<span class="n">client</span> <span class="o">=</span> <span class="n">predictionio</span><span class="o">.</span><span class="n">EventClient</span><span class="p">(</span>
+ <span class="n">access_key</span><span class="o">=<</span><span class="n">ACCESS</span> <span class="n">KEY</span><span class="o">></span><span class="p">,</span>
+ <span class="n">url</span><span class="o">=<</span><span class="n">URL</span> <span class="n">OF</span> <span class="n">EVENTSERVER</span><span class="o">></span><span class="p">,</span>
+ <span class="n">threads</span><span class="o">=</span><span class="mi">5</span><span class="p">,</span>
+ <span class="n">qsize</span><span class="o">=</span><span class="mi">500</span>
+<span class="p">)</span>
+
+<span class="c"># Set the 4 properties for a user</span>
+<span class="n">client</span><span class="o">.</span><span class="n">create_event</span><span class="p">(</span>
+ <span class="n">event</span><span class="o">=</span><span class="s">"$set"</span><span class="p">,</span>
+ <span class="n">entity_type</span><span class="o">=</span><span class="s">"user"</span><span class="p">,</span>
+ <span class="n">entity_id</span><span class="o">=<</span><span class="n">USER</span> <span class="n">ID</span><span class="o">></span><span class="p">,</span>
+ <span class="n">properties</span><span class="o">=</span> <span class="p">{</span>
+ <span class="s">"attr0"</span> <span class="p">:</span> <span class="nb">int</span><span class="p">(</span><span class="o"><</span><span class="n">VALUE</span> <span class="n">OF</span> <span class="n">ATTR0</span><span class="o">></span><span class="p">),</span>
+ <span class="s">"attr1"</span> <span class="p">:</span> <span class="nb">int</span><span class="p">(</span><span class="o"><</span><span class="n">VALUE</span> <span class="n">OF</span> <span class="n">ATTR1</span><span class="o">></span><span class="p">),</span>
+ <span class="s">"attr2"</span> <span class="p">:</span> <span class="nb">int</span><span class="p">(</span><span class="o"><</span><span class="n">VALUE</span> <span class="n">OF</span> <span class="n">ATTR2</span><span class="o">></span><span class="p">),</span>
+ <span class="s">"plan"</span> <span class="p">:</span> <span class="nb">int</span><span class="p">(</span><span class="o"><</span><span class="n">VALUE</span> <span class="n">OF</span> <span class="n">PLAN</span><span class="o">></span><span class="p">)</span>
+ <span class="p">}</span>
+<span class="p">)</span>
+</pre></td> </tr></tbody></table> </div> </div> <div data-tab="PHP SDK" data-lang="php" id="tab-80cd65cb-f968-4933-966f-1fae4510513e"> <div class="highlight php"> <table style="border-spacing: 0"><tbody><tr> <td class="gutter gl" style="text-align: right"><pre class="lineno">1
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+<span class="k">require_once</span><span class="p">(</span><span class="s2">"vendor/autoload.php"</span><span class="p">);</span>
+<span class="k">use</span> <span class="nx">predictionio\EventClient</span><span class="p">;</span>
+
+<span class="nv">$client</span> <span class="o">=</span> <span class="k">new</span> <span class="nx">EventClient</span><span class="p">(</span><span class="o"><</span><span class="nx">ACCESS</span> <span class="nx">KEY</span><span class="o">></span><span class="p">,</span> <span class="o"><</span><span class="nx">URL</span> <span class="nx">OF</span> <span class="nx">EVENTSERVER</span><span class="o">></span><span class="p">);</span>
+
+<span class="c1">// Set the 4 properties for a user
+</span><span class="nv">$client</span><span class="o">-></span><span class="na">createEvent</span><span class="p">(</span><span class="k">array</span><span class="p">(</span>
+ <span class="s1">'event'</span> <span class="o">=></span> <span class="s1">'$set'</span><span class="p">,</span>
+ <span class="s1">'entityType'</span> <span class="o">=></span> <span class="s1">'user'</span><span class="p">,</span>
+ <span class="s1">'entityId'</span> <span class="o">=></span> <span class="o"><</span><span class="nx">USER</span> <span class="nx">ID</span><span class="o">></span><span class="p">,</span>
+ <span class="s1">'properties'</span> <span class="o">=></span> <span class="k">array</span><span class="p">(</span>
+ <span class="s1">'attr0'</span> <span class="o">=></span> <span class="o"><</span><span class="nx">VALUE</span> <span class="nx">OF</span> <span class="nx">ATTR0</span><span class="o">></span><span class="p">,</span>
+ <span class="s1">'attr1'</span> <span class="o">=></span> <span class="o"><</span><span class="nx">VALUE</span> <span class="nx">OF</span> <span class="nx">ATTR1</span><span class="o">></span><span class="p">,</span>
+ <span class="s1">'attr2'</span> <span class="o">=></span> <span class="o"><</span><span class="nx">VALUE</span> <span class="nx">OF</span> <span class="nx">ATTR2</span><span class="o">></span><span class="p">,</span>
+ <span class="s1">'plan'</span> <span class="o">=></span> <span class="o"><</span><span class="nx">VALUE</span> <span class="nx">OF</span> <span class="nx">PLAN</span><span class="o">></span>
+ <span class="p">)</span>
+<span class="p">));</span>
+<span class="cp">?></span>
+</pre></td> </tr></tbody></table> </div> </div> <div data-tab="Ruby SDK" data-lang="ruby" id="tab-8b7bbba8-1e88-417a-8286-058f04f00dfe"> <div class="highlight ruby"> <table style="border-spacing: 0"><tbody><tr> <td class="gutter gl" style="text-align: right"><pre class="lineno">1
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+<span class="n">client</span> <span class="o">=</span> <span class="no">PredictionIO</span><span class="o">::</span><span class="no">EventClient</span><span class="p">.</span><span class="nf">new</span><span class="p">(</span><span class="o"><</span><span class="no">ACCESS</span> <span class="no">KEY</span><span class="o">></span><span class="p">,</span> <span class="o"><</span><span class="no">URL</span> <span class="no">OF</span> <span class="no">EVENTSERVER</span><span class="o">></span><span class="p">)</span>
+
+<span class="c1"># Set the 4 properties for a user.</span>
+<span class="n">client</span><span class="p">.</span><span class="nf">create_event</span><span class="p">(</span>
+ <span class="s1">'$set'</span><span class="p">,</span>
+ <span class="s1">'user'</span><span class="p">,</span>
+ <span class="o"><</span><span class="no">USER</span> <span class="no">ID</span><span class="o">></span><span class="p">,</span> <span class="p">{</span>
+ <span class="s1">'properties'</span> <span class="o">=></span> <span class="p">{</span>
+ <span class="s1">'attr0'</span> <span class="o">=></span> <span class="o"><</span><span class="no">VALUE</span> <span class="no">OF</span> <span class="no">ATTR0</span> <span class="p">(</span><span class="n">integer</span><span class="p">)</span><span class="o">></span><span class="p">,</span>
+ <span class="s1">'attr1'</span> <span class="o">=></span> <span class="o"><</span><span class="no">VALUE</span> <span class="no">OF</span> <span class="no">ATTR1</span> <span class="p">(</span><span class="n">integer</span><span class="p">)</span><span class="o">></span><span class="p">,</span>
+ <span class="s1">'attr2'</span> <span class="o">=></span> <span class="o"><</span><span class="no">VALUE</span> <span class="no">OF</span> <span class="no">ATTR2</span> <span class="p">(</span><span class="n">integer</span><span class="p">)</span><span class="o">></span><span class="p">,</span>
+ <span class="s1">'plan'</span> <span class="o">=></span> <span class="o"><</span><span class="no">VALUE</span> <span class="no">OF</span> <span class="no">PLAN</span> <span class="p">(</span><span class="n">integer</span><span class="p">)</span><span class="o">></span><span class="p">,</span>
+ <span class="p">}</span>
+ <span class="p">}</span>
+<span class="p">)</span>
+</pre></td> </tr></tbody></table> </div> </div> <div data-tab="Java SDK" data-lang="java" id="tab-45e13392-b2b0-4095-bf33-4c586fe33a32"> <div class="highlight java"> <table style="border-spacing: 0"><tbody><tr> <td class="gutter gl" style="text-align: right"><pre class="lineno">1
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+<span class="kn">import</span> <span class="nn">io.prediction.Event</span><span class="o">;</span>
+<span class="kn">import</span> <span class="nn">io.prediction.EventClient</span><span class="o">;</span>
+
+<span class="n">EventClient</span> <span class="n">client</span> <span class="o">=</span> <span class="k">new</span> <span class="n">EventClient</span><span class="o">(<</span><span class="n">ACCESS</span> <span class="n">KEY</span><span class="o">>,</span> <span class="o"><</span><span class="n">URL</span> <span class="n">OF</span> <span class="n">EVENTSERVER</span><span class="o">>);</span>
+
+<span class="c1">// set the 4 properties for a user</span>
+<span class="n">Event</span> <span class="n">event</span> <span class="o">=</span> <span class="k">new</span> <span class="n">Event</span><span class="o">()</span>
+ <span class="o">.</span><span class="na">event</span><span class="o">(</span><span class="s">"$set"</span><span class="o">)</span>
+ <span class="o">.</span><span class="na">entityType</span><span class="o">(</span><span class="s">"user"</span><span class="o">)</span>
+ <span class="o">.</span><span class="na">entityId</span><span class="o">(<</span><span class="n">USER</span> <span class="n">ID</span><span class="o">>)</span>
+ <span class="o">.</span><span class="na">properties</span><span class="o">(</span><span class="n">ImmutableMap</span><span class="o">.<</span><span class="n">String</span><span class="o">,</span> <span class="n">Object</span><span class="o">></span><span class="n">of</span><span class="o">(</span>
+ <span class="s">"attr0"</span><span class="o">,</span> <span class="o"><</span><span class="n">VALUE</span> <span class="n">OF</span> <span class="n">ATTR0</span><span class="o">>,</span>
+ <span class="s">"attr1"</span><span class="o">,</span> <span class="o"><</span><span class="n">VALUE</span> <span class="n">OF</span> <span class="n">ATTR1</span><span class="o">>,</span>
+ <span class="s">"attr2"</span><span class="o">,</span> <span class="o"><</span><span class="n">VALUE</span> <span class="n">OF</span> <span class="n">ATTR2</span><span class="o">>,</span>
+ <span class="s">"plan"</span><span class="o">,</span> <span class="o"><</span><span class="n">VALUE</span> <span class="n">OF</span> <span class="n">PLAN</span><span class="o">></span>
+ <span class="o">));</span>
+<span class="n">client</span><span class="o">.</span><span class="na">createEvent</span><span class="o">(</span><span class="n">event</span><span class="o">);</span>
+</pre></td> </tr></tbody></table> </div> </div> </div> <p>Note that you can also set the properties for the user with multiple <code>$set</code> events (They will be aggregated during engine training).</p><p>To set properties "attr0", "attr1" and "attr2", and "plan" for user "u1" at different time, you can send follwing <code>$set</code> events for the user. To send these events, run the following <code>curl</code> command:</p><div class="tabs"> <ul class="control"> <li data-lang="json"><a href="#tab-7fb39be4-e550-4706-97c2-8a8f5869895f">REST API</a></li> <li data-lang="python"><a href="#tab-1f907cb6-be4c-4411-90fc-18c441ab06d9">Python SDK</a></li> <li data-lang="php"><a href="#tab-d4d47040-77b0-4d1c-8438-846c59b0e812">PHP SDK</a></li> <li data-lang="ruby"><a href="#tab-3c8dd7bc-0990-4a47-9437-deaacb7ba270">Ruby SDK</a></li> <li data-lang="java"><a href="#tab-b8376a13-843e-4c90-982b-911a2c71472a">Java SDK</a></li> </ul> <div data-tab
="REST API" data-lang="json" id="tab-7fb39be4-e550-4706-97c2-8a8f5869895f"> <div class="highlight shell"> <table style="border-spacing: 0"><tbody><tr> <td class="gutter gl" style="text-align: right"><pre class="lineno">1
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+-H <span class="s2">"Content-Type: application/json"</span> <span class="se">\</span>
+-d <span class="s1">'{
+ "event" : "$set",
+ "entityType" : "user"
+ "entityId" : "u1",
+ "properties" : {
+ "attr0" : 0
+ }
+ "eventTime" : "2014-11-02T09:39:45.618-08:00"
+}'</span>
+
+<span class="gp">$ </span>curl -i -X POST http://localhost:7070/events.json?accessKey<span class="o">=</span><span class="nv">$ACCESS_KEY</span> <span class="se">\</span>
+-H <span class="s2">"Content-Type: application/json"</span> <span class="se">\</span>
+-d <span class="s1">'{
+ "event" : "$set",
+ "entityType" : "user"
+ "entityId" : "u1",
+ "properties" : {
+ "attr1" : 1,
+ "attr2": 0
+ }
+ "eventTime" : "2014-11-02T09:39:45.618-08:00"
+}'</span>
+
+<span class="gp">$ </span>curl -i -X POST http://localhost:7070/events.json?accessKey<span class="o">=</span><span class="nv">$ACCESS_KEY</span> <span class="se">\</span>
+-H <span class="s2">"Content-Type: application/json"</span> <span class="se">\</span>
+-d <span class="s1">'{
+ "event" : "$set",
+ "entityType" : "user"
+ "entityId" : "u1",
+ "properties" : {
+ "plan" : 1
+ }
+ "eventTime" : "2014-11-02T09:39:45.618-08:00"
+}'</span>
+</pre></td> </tr></tbody></table> </div> </div> <div data-tab="Python SDK" data-lang="python" id="tab-1f907cb6-be4c-4411-90fc-18c441ab06d9"> <div class="highlight python"> <table style="border-spacing: 0"><tbody><tr> <td class="gutter gl" style="text-align: right"><pre class="lineno">1
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+<span class="n">client</span><span class="o">.</span><span class="n">create_event</span><span class="p">(</span>
+ <span class="n">event</span><span class="o">=</span><span class="s">"$set"</span><span class="p">,</span>
+ <span class="n">entity_type</span><span class="o">=</span><span class="s">"user"</span><span class="p">,</span>
+ <span class="n">entity_id</span><span class="o">=<</span><span class="n">USER</span> <span class="n">ID</span><span class="o">></span><span class="p">,</span>
+ <span class="n">properties</span><span class="o">=</span> <span class="p">{</span>
+ <span class="s">"attr0"</span> <span class="p">:</span> <span class="nb">int</span><span class="p">(</span><span class="o"><</span><span class="n">VALUE</span> <span class="n">OF</span> <span class="n">ATTR0</span><span class="o">></span><span class="p">)</span>
+ <span class="p">}</span>
+<span class="p">)</span>
+<span class="n">client</span><span class="o">.</span><span class="n">create_event</span><span class="p">(</span>
+ <span class="n">event</span><span class="o">=</span><span class="s">"$set"</span><span class="p">,</span>
+ <span class="n">entity_type</span><span class="o">=</span><span class="s">"user"</span><span class="p">,</span>
+ <span class="n">entity_id</span><span class="o">=<</span><span class="n">USER</span> <span class="n">ID</span><span class="o">></span><span class="p">,</span>
+ <span class="n">properties</span><span class="o">=</span> <span class="p">{</span>
+ <span class="s">"attr1"</span> <span class="p">:</span> <span class="nb">int</span><span class="p">(</span><span class="o"><</span><span class="n">VALUE</span> <span class="n">OF</span> <span class="n">ATTR1</span><span class="o">></span><span class="p">),</span>
+ <span class="s">"attr2"</span> <span class="p">:</span> <span class="nb">int</span><span class="p">(</span><span class="o"><</span><span class="n">VALUE</span> <span class="n">OF</span> <span class="n">ATTR2</span><span class="o">></span><span class="p">)</span>
+ <span class="p">}</span>
+<span class="p">)</span>
+
+<span class="n">client</span><span class="o">.</span><span class="n">create_event</span><span class="p">(</span>
+ <span class="n">event</span><span class="o">=</span><span class="s">"$set"</span><span class="p">,</span>
+ <span class="n">entity_type</span><span class="o">=</span><span class="s">"user"</span><span class="p">,</span>
+ <span class="n">entity_id</span><span class="o">=<</span><span class="n">USER</span> <span class="n">ID</span><span class="o">></span><span class="p">,</span>
+ <span class="n">properties</span><span class="o">=</span> <span class="p">{</span>
+ <span class="s">"plan"</span> <span class="p">:</span> <span class="nb">int</span><span class="p">(</span><span class="o"><</span><span class="n">VALUE</span> <span class="n">OF</span> <span class="n">PLAN</span><span class="o">></span><span class="p">)</span>
+ <span class="p">}</span>
+<span class="p">)</span>
+</pre></td> </tr></tbody></table> </div> </div> <div data-tab="PHP SDK" data-lang="php" id="tab-d4d47040-77b0-4d1c-8438-846c59b0e812"> <div class="highlight php"> <table style="border-spacing: 0"><tbody><tr> <td class="gutter gl" style="text-align: right"><pre class="lineno">1
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+
+<span class="c1">// You may also set the properties one by one
+</span><span class="nv">$client</span><span class="o">-></span><span class="na">createEvent</span><span class="p">(</span><span class="k">array</span><span class="p">(</span>
+ <span class="s1">'event'</span> <span class="o">=></span> <span class="s1">'$set'</span><span class="p">,</span>
+ <span class="s1">'entityType'</span> <span class="o">=></span> <span class="s1">'user'</span><span class="p">,</span>
+ <span class="s1">'entityId'</span> <span class="o">=></span> <span class="o"><</span><span class="nx">USER</span> <span class="nx">ID</span><span class="o">></span><span class="p">,</span>
+ <span class="s1">'properties'</span> <span class="o">=></span> <span class="k">array</span><span class="p">(</span>
+ <span class="s1">'attr0'</span> <span class="o">=></span> <span class="o"><</span><span class="nx">VALUE</span> <span class="nx">OF</span> <span class="nx">ATTR0</span><span class="o">></span>
+ <span class="p">)</span>
+<span class="p">));</span>
+
+<span class="nv">$client</span><span class="o">-></span><span class="na">createEvent</span><span class="p">(</span><span class="k">array</span><span class="p">(</span>
+ <span class="s1">'event'</span> <span class="o">=></span> <span class="s1">'$set'</span><span class="p">,</span>
+ <span class="s1">'entityType'</span> <span class="o">=></span> <span class="s1">'user'</span><span class="p">,</span>
+ <span class="s1">'entityId'</span> <span class="o">=></span> <span class="o"><</span><span class="nx">USER</span> <span class="nx">ID</span><span class="o">></span><span class="p">,</span>
+ <span class="s1">'properties'</span> <span class="o">=></span> <span class="k">array</span><span class="p">(</span>
+ <span class="s1">'attr1'</span> <span class="o">=></span> <span class="o"><</span><span class="nx">VALUE</span> <span class="nx">OF</span> <span class="nx">ATTR1</span><span class="o">></span><span class="p">,</span>
+ <span class="s1">'attr2'</span> <span class="o">=></span> <span class="o"><</span><span class="nx">VALUE</span> <span class="nx">OF</span> <span class="nx">ATTR2</span><span class="o">></span>
+ <span class="p">)</span>
+<span class="p">));</span>
+
+<span class="nv">$client</span><span class="o">-></span><span class="na">createEvent</span><span class="p">(</span><span class="k">array</span><span class="p">(</span>
+ <span class="s1">'event'</span> <span class="o">=></span> <span class="s1">'$set'</span><span class="p">,</span>
+ <span class="s1">'entityType'</span> <span class="o">=></span> <span class="s1">'user'</span><span class="p">,</span>
+ <span class="s1">'entityId'</span> <span class="o">=></span> <span class="o"><</span><span class="nx">USER</span> <span class="nx">ID</span><span class="o">></span><span class="p">,</span>
+ <span class="s1">'properties'</span> <span class="o">=></span> <span class="k">array</span><span class="p">(</span>
+ <span class="s1">'plan'</span> <span class="o">=></span> <span class="o"><</span><span class="nx">VALUE</span> <span class="nx">OF</span> <span class="nx">PLAN</span><span class="o">></span>
+ <span class="p">)</span>
+<span class="p">));</span>
+
+<span class="cp">?></span>
+</pre></td> </tr></tbody></table> </div> </div> <div data-tab="Ruby SDK" data-lang="ruby" id="tab-3c8dd7bc-0990-4a47-9437-deaacb7ba270"> <div class="highlight ruby"> <table style="border-spacing: 0"><tbody><tr> <td class="gutter gl" style="text-align: right"><pre class="lineno">1
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+<span class="n">client</span><span class="p">.</span><span class="nf">create_event</span><span class="p">(</span>
+ <span class="s1">'$set'</span><span class="p">,</span>
+ <span class="s1">'user'</span><span class="p">,</span>
+ <span class="o"><</span><span class="no">USER</span> <span class="no">ID</span><span class="o">></span><span class="p">,</span> <span class="p">{</span>
+ <span class="s1">'properties'</span> <span class="o">=></span> <span class="p">{</span>
+ <span class="s1">'attr0'</span> <span class="o">=></span> <span class="o"><</span><span class="no">VALUE</span> <span class="no">OF</span> <span class="no">ATTR0</span> <span class="p">(</span><span class="n">integer</span><span class="p">)</span><span class="o">></span>
+ <span class="p">}</span>
+ <span class="p">}</span>
+<span class="p">)</span>
+
+<span class="n">client</span><span class="p">.</span><span class="nf">create_event</span><span class="p">(</span>
+ <span class="s1">'$set'</span><span class="p">,</span>
+ <span class="s1">'user'</span><span class="p">,</span>
+ <span class="o"><</span><span class="no">USER</span> <span class="no">ID</span><span class="o">></span><span class="p">,</span> <span class="p">{</span>
+ <span class="s1">'properties'</span> <span class="o">=></span> <span class="p">{</span>
+ <span class="s1">'attr1'</span> <span class="o">=></span> <span class="o"><</span><span class="no">VALUE</span> <span class="no">OF</span> <span class="no">ATTR1</span> <span class="p">(</span><span class="n">integer</span><span class="p">)</span><span class="o">></span><span class="p">,</span>
+ <span class="p">}</span>
+ <span class="p">}</span>
+<span class="p">)</span>
+
+<span class="c1"># Etc...</span>
+</pre></td> </tr></tbody></table> </div> </div> <div data-tab="Java SDK" data-lang="java" id="tab-b8376a13-843e-4c90-982b-911a2c71472a"> <div class="highlight java"> <table style="border-spacing: 0"><tbody><tr> <td class="gutter gl" style="text-align: right"><pre class="lineno">1
+2
+3
+4
+5
+6
+7
+8
+9
+10
+11
+12
+13
+14
+15
+16
+17</pre></td> <td class="code"><pre><span class="c1">// you may also set the properties one by one</span>
+<span class="n">client</span><span class="o">.</span><span class="na">createEvent</span><span class="o">(</span><span class="k">new</span> <span class="n">Event</span><span class="o">()</span>
+ <span class="o">.</span><span class="na">event</span><span class="o">(</span><span class="s">"$set"</span><span class="o">)</span>
+ <span class="o">.</span><span class="na">entityType</span><span class="o">(</span><span class="s">"user"</span><span class="o">)</span>
+ <span class="o">.</span><span class="na">entityId</span><span class="o">(<</span><span class="n">USER</span> <span class="n">ID</span><span class="o">>)</span>
+ <span class="o">.</span><span class="na">property</span><span class="o">(</span><span class="s">"attr0"</span><span class="o">,</span> <span class="o"><</span><span class="n">VALUE</span> <span class="n">OF</span> <span class="n">ATTR0</span><span class="o">>));</span>
+<span class="n">client</span><span class="o">.</span><span class="na">createEvent</span><span class="o">(</span><span class="k">new</span> <span class="n">Event</span><span class="o">()</span>
+ <span class="o">.</span><span class="na">event</span><span class="o">(</span><span class="s">"$set"</span><span class="o">)</span>
+ <span class="o">.</span><span class="na">entityType</span><span class="o">(</span><span class="s">"user"</span><span class="o">)</span>
+ <span class="o">.</span><span class="na">entityId</span><span class="o">(<</span><span class="n">USER</span> <span class="n">ID</span><span class="o">>)</span>
+ <span class="o">.</span><span class="na">property</span><span class="o">(</span><span class="s">"attr1"</span><span class="o">,</span> <span class="o"><</span><span class="n">VALUE</span> <span class="n">OF</span> <span class="n">ATTR1</span><span class="o">>)</span>
+ <span class="o">.</span><span class="na">property</span><span class="o">(</span><span class="s">"attr2"</span><span class="o">,</span> <span class="o"><</span><span class="n">VALUE</span> <span class="n">OF</span> <span class="n">ATTR2</span><span class="o">>));</span>
+<span class="n">client</span><span class="o">.</span><span class="na">createEvent</span><span class="o">(</span><span class="k">new</span> <span class="n">Event</span><span class="o">()</span>
+ <span class="o">.</span><span class="na">event</span><span class="o">(</span><span class="s">"$set"</span><span class="o">)</span>
+ <span class="o">.</span><span class="na">entityType</span><span class="o">(</span><span class="s">"user"</span><span class="o">)</span>
+ <span class="o">.</span><span class="na">entityId</span><span class="o">(<</span><span class="n">USER</span> <span class="n">ID</span><span class="o">>)</span>
+ <span class="o">.</span><span class="na">property</span><span class="o">(</span><span class="s">"plan"</span><span class="o">,</span> <span class="o"><</span><span class="n">VALUE</span> <span class="n">OF</span> <span class="n">PLAN</span><span class="o">>));</span>
+</pre></td> </tr></tbody></table> </div> </div> </div> <p>The properties of the <code>user</code> can be set, unset, or delete by special events <strong>$set</strong>, <strong>$unset</strong> and <strong>$delete</strong>. Please refer to <a href="/datacollection/eventapi/#note-about-properties">Event API</a> for more details of using these events.</p><p><h3 id='query-event-server' class='header-anchors'>Query Event Server</h3><p>Now let's query the EventServer and see if these events are imported successfully.</p><p>Go to following URL with your browser:</p><p><code><a href="http://localhost:7070/events.json?accessKey=&lt;YOUR_ACCESS_KEY">http://localhost:7070/events.json?accessKey=&lt;YOUR_ACCESS_KEY</a>></code></p><p>or run the following command in terminal:</p><div class="highlight shell"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1</pre></td><td class="code"><pre><span class="gp">$ </span>curl -i
-X GET <span class="s2">"<a href="http://localhost:7070/events.json?accessKey=">http://localhost:7070/events.json?accessKey=</a></span><span class="nv">$ACCESS_KEY</span><span class="s2">"</span>
+</pre></td></tr></tbody></table> </div> <div class="alert-message note"><p>Note that you should quote the entire URL by using single or double quotes when you run the <code>curl</code> command.</p></div><p>It should return the imported events in JSON format. You can refer to <a href="/datacollection/eventapi/#debugging-recipes">Event Server Debugging Recipes</a> for more different ways to query Event Server.</p></p><h3 id='import-more-sample-data' class='header-anchors'>Import More Sample Data</h3><p>This engine requires more data in order to train a useful model. Instead of sending more events one by one in real time, for quickstart demonstration purpose, we are going to use a script to import more events in batch.</p> <p>A Python import script <code>import_eventserver.py</code> is provided to import the data to Event Server using Python SDK. Please upgrade to the latest Python SDK.</p><p>First, you will need to install Python SDK in order to run the sample data import script. To i
nstall Python SDK, run:</p><div class="highlight shell"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1</pre></td><td class="code"><pre><span class="gp">$ </span>pip install predictionio
+</pre></td></tr></tbody></table> </div> <p>or</p><div class="highlight shell"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1</pre></td><td class="code"><pre><span class="gp">$ </span>easy_install predictionio
+</pre></td></tr></tbody></table> </div> <div class="alert-message note"><p>You may need <code>sudo</code> access if you have permission issue. (ie. <code>sudo pip install predictionio</code>)</p></div> <p><a href="#"></a></p> <p>Make sure you are under the <code>MyClassification</code> directory. Replace the value of access_key parameter by your <strong>Access Key</strong> and run:</p><div class="highlight shell"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1
+2</pre></td><td class="code"><pre><span class="gp">$ </span><span class="nb">cd </span>MyClassification
+<span class="gp">$ </span>python data/import_eventserver.py --access_key obbiTuSOiMzyFKsvjjkDnWk1vcaHjcjrv9oT3mtN3y6fOlpJoVH459O1bPmDzCdv
+</pre></td></tr></tbody></table> </div> <p>You should see the following output:</p><div class="highlight shell"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1
+2</pre></td><td class="code"><pre>Importing data...
+6 events are imported.
+</pre></td></tr></tbody></table> </div> <p>Now the training data is stored as events inside the Event Store.</p> <p><a href="#"></a></p><div class="alert-message warning"><p>If you see error <strong>TypeError: <strong>init</strong>() got an unexpected keyword argument 'access_key'</strong>, please update the Python SDK to the latest version.</p></div><p>You can query the event server again as described previously to check the imported events.</p> <h2 id='5.-deploy-the-engine-as-a-service' class='header-anchors'>5. Deploy the Engine as a Service</h2><p>Now you can build, train, and deploy the engine. First, make sure you are under the <code>MyClassification</code> directory.</p><div class="highlight shell"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1</pre></td><td class="code"><pre><span class="gp">$ </span><span class="nb">cd </span>MyClassification
+</pre></td></tr></tbody></table> </div> <h3 id='engine.json' class='header-anchors'>Engine.json</h3><p>Under the directory, you should find an <code>engine.json</code> file; this is where you specify parameters for the engine.</p><div class="alert-message warning"><p>Modify this file to make sure the <code>appName</code> parameter match your <strong>App Name</strong> you created earlier (e.g. "MyApp1" if you follow the quickstart).</p></div><div class="highlight shell"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1
+2
+3
+4
+5
+6
+7</pre></td><td class="code"><pre> ...
+ <span class="s2">"datasource"</span>: <span class="o">{</span>
+ <span class="s2">"params"</span> : <span class="o">{</span>
+ <span class="s2">"appName"</span>: <span class="s2">"MyApp1"</span>
+ <span class="o">}</span>
+ <span class="o">}</span>,
+ ...
+</pre></td></tr></tbody></table> </div> <div class="alert-message note"><p>You may see <code>appId</code> in engine.json instead, which means you are using old template. In this case, make sure the <code>appId</code> defined in the file match your <strong>App ID</strong>. Alternatively, you can download the latest version of the template or follow our <a href="/resources/upgrade/#upgrade-to-0.9.2">upgrade instructions</a> to modify the template to use <code>appName</code> as parameter.</p></div> <p><a href="#"></a></p> <p><h3 id='building' class='header-anchors'>Building</h3><p>Start with building your <em>MyClassification</em> engine. Run the following command:</p><div class="highlight shell"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1</pre></td><td class="code"><pre><span class="gp">$ </span>pio build --verbose
+</pre></td></tr></tbody></table> </div> <p>This command should take few minutes for the first time; all subsequent builds should be less than a minute. You can also run it without <code>--verbose</code> if you don't want to see all the log messages.</p><p>Upon successful build, you should see a console message similar to the following.</p><div class="highlight shell"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1</pre></td><td class="code"><pre><span class="o">[</span>INFO] <span class="o">[</span>Console<span class="nv">$]</span> Your engine is ready <span class="k">for </span>training.
+</pre></td></tr></tbody></table> </div> <h3 id='training-the-predictive-model' class='header-anchors'>Training the Predictive Model</h3><p>To train your engine, run the following command:</p><div class="highlight shell"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1</pre></td><td class="code"><pre><span class="gp">$ </span>pio train
+</pre></td></tr></tbody></table> </div> <p>When your engine is trained successfully, you should see a console message similar to the following.</p><div class="highlight shell"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1</pre></td><td class="code"><pre><span class="o">[</span>INFO] <span class="o">[</span>CoreWorkflow<span class="nv">$]</span> Training completed successfully.
+</pre></td></tr></tbody></table> </div> <h3 id='deploying-the-engine' class='header-anchors'>Deploying the Engine</h3><p>Now your engine is ready to deploy. Run:</p><div class="highlight shell"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1</pre></td><td class="code"><pre><span class="gp">$ </span>pio deploy
+</pre></td></tr></tbody></table> </div> <p>When the engine is deployed successfully and running, you should see a console message similar to the following:</p><div class="highlight shell"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1
+2</pre></td><td class="code"><pre><span class="o">[</span>INFO] <span class="o">[</span>HttpListener] Bound to /0.0.0.0:8000
+<span class="o">[</span>INFO] <span class="o">[</span>MasterActor] Bind successful. Ready to serve.
+</pre></td></tr></tbody></table> </div> <p>Do not kill the deployed engine process.</p><p>By default, the deployed engine binds to <a href="http://localhost:8000"><a href="http://localhost:8000">http://localhost:8000</a></a>. You can visit that page in your web browser to check its status.</p><p><img alt="Engine Status" src="/images/engine-server-3246414b.png"/></p></p><h2 id='6.-use-the-engine' class='header-anchors'>6. Use the Engine</h2><p>Now, You can try to retrieve predicted results. For example, to predict the label (i.e. <em>plan</em> in this case) of a user with attr0=2, attr1=0 and attr2=0, you send this JSON <code>{ "attr0":2, "attr1":0, "attr2":0 }</code> to the deployed engine and it will return a JSON of the predicted plan. Simply send a query by making a HTTP request or through the <code>EngineClient</code> of an SDK.</p><p>With the deployed engine running, open another temrinal and run the following <code>curl</code> command or use SDK t
o send the query:</p><div class="tabs"> <ul class="control"> <li data-lang="bash"><a href="#tab-f6485d00-c570-4e7d-acca-43df3cd9a041">REST API</a></li> <li data-lang="python"><a href="#tab-8ead9892-571c-4030-9c2b-4372e6490e2d">Python SDK</a></li> <li data-lang="php"><a href="#tab-af7f9d5d-d306-4aa4-8c4b-7d376f861e91">PHP SDK</a></li> <li data-lang="ruby"><a href="#tab-d8653460-d0e3-4d44-b943-2d2b7e032a64">Ruby SDK</a></li> <li data-lang="java"><a href="#tab-d7932e52-7ea1-4222-8186-ae4f04b34c7e">Java SDK</a></li> </ul> <div data-tab="REST API" data-lang="bash" id="tab-f6485d00-c570-4e7d-acca-43df3cd9a041"> <div class="highlight shell"> <table style="border-spacing: 0"><tbody><tr> <td class="gutter gl" style="text-align: right"><pre class="lineno">1
+2
+3</pre></td> <td class="code"><pre><span class="gp">$ </span>curl -H <span class="s2">"Content-Type: application/json"</span> <span class="se">\</span>
+-d <span class="s1">'{ "attr0":2, "attr1":0, "attr2":0 }'</span> http://localhost:8000/queries.json
+
+</pre></td> </tr></tbody></table> </div> </div> <div data-tab="Python SDK" data-lang="python" id="tab-8ead9892-571c-4030-9c2b-4372e6490e2d"> <div class="highlight python"> <table style="border-spacing: 0"><tbody><tr> <td class="gutter gl" style="text-align: right"><pre class="lineno">1
+2
+3</pre></td> <td class="code"><pre><span class="kn">import</span> <span class="nn">predictionio</span>
+<span class="n">engine_client</span> <span class="o">=</span> <span class="n">predictionio</span><span class="o">.</span><span class="n">EngineClient</span><span class="p">(</span><span class="n">url</span><span class="o">=</span><span class="s">"http://localhost:8000"</span><span class="p">)</span>
+<span class="k">print</span> <span class="n">engine_client</span><span class="o">.</span><span class="n">send_query</span><span class="p">({</span><span class="s">"attr0"</span><span class="p">:</span><span class="mi">2</span><span class="p">,</span> <span class="s">"attr1"</span><span class="p">:</span><span class="mi">0</span><span class="p">,</span> <span class="s">"attr2"</span><span class="p">:</span><span class="mi">0</span><span class="p">})</span>
+</pre></td> </tr></tbody></table> </div> </div> <div data-tab="PHP SDK" data-lang="php" id="tab-af7f9d5d-d306-4aa4-8c4b-7d376f861e91"> <div class="highlight php"> <table style="border-spacing: 0"><tbody><tr> <td class="gutter gl" style="text-align: right"><pre class="lineno">1
+2
+3
+4
+5
+6
+7
+8
+9
+10</pre></td> <td class="code"><pre><span class="cp"><?php</span>
+<span class="k">require_once</span><span class="p">(</span><span class="s2">"vendor/autoload.php"</span><span class="p">);</span>
+<span class="k">use</span> <span class="nx">predictionio\EngineClient</span><span class="p">;</span>
+
+<span class="nv">$client</span> <span class="o">=</span> <span class="k">new</span> <span class="nx">EngineClient</span><span class="p">(</span><span class="s1">'http://localhost:8000'</span><span class="p">);</span>
+
+<span class="nv">$response</span> <span class="o">=</span> <span class="nv">$client</span><span class="o">-></span><span class="na">sendQuery</span><span class="p">(</span><span class="k">array</span><span class="p">(</span><span class="s1">'attr0'</span><span class="o">=></span> <span class="mi">2</span><span class="p">,</span> <span class="s1">'attr1'</span> <span class="o">=></span> <span class="mi">0</span><span class="p">,</span> <span class="s1">'attr2'</span> <span class="o">=></span> <span class="mi">0</span><span class="p">));</span>
+<span class="nb">print_r</span><span class="p">(</span><span class="nv">$response</span><span class="p">);</span>
+
+<span class="cp">?></span>
+</pre></td> </tr></tbody></table> </div> </div> <div data-tab="Ruby SDK" data-lang="ruby" id="tab-d8653460-d0e3-4d44-b943-2d2b7e032a64"> <div class="highlight ruby"> <table style="border-spacing: 0"><tbody><tr> <td class="gutter gl" style="text-align: right"><pre class="lineno">1
+2
+3
+4
+5
+6
+7</pre></td> <td class="code"><pre><span class="c1"># Create client object.</span>
+<span class="n">client</span> <span class="o">=</span> <span class="no">PredictionIO</span><span class="o">::</span><span class="no">EngineClient</span><span class="p">.</span><span class="nf">new</span><span class="p">(</span><span class="o"><</span><span class="no">ENGINE</span> <span class="no">DEPLOY</span> <span class="no">URL</span><span class="o">></span><span class="p">)</span>
+
+<span class="c1"># Query PredictionIO.</span>
+<span class="n">response</span> <span class="o">=</span> <span class="n">client</span><span class="p">.</span><span class="nf">send_query</span><span class="p">(</span><span class="s1">'attr0'</span> <span class="o">=></span> <span class="mi">2</span><span class="p">,</span> <span class="s1">'attr1'</span> <span class="o">=></span> <span class="mi">0</span><span class="p">,</span> <span class="s1">'attr2'</span> <span class="o">=></span> <span class="mi">0</span><span class="p">)</span>
+
+<span class="nb">puts</span> <span class="n">response</span>
+</pre></td> </tr></tbody></table> </div> </div> <div data-tab="Java SDK" data-lang="java" id="tab-d7932e52-7ea1-4222-8186-ae4f04b34c7e"> <div class="highlight java"> <table style="border-spacing: 0"><tbody><tr> <td class="gutter gl" style="text-align: right"><pre class="lineno">1
+2
+3
+4
+5
+6
+7
+8
+9
+10
+11
+12
+13</pre></td> <td class="code"><pre><span class="kn">import</span> <span class="nn">com.google.common.collect.ImmutableList</span><span class="o">;</span>
+<span class="kn">import</span> <span class="nn">com.google.common.collect.ImmutableMap</span><span class="o">;</span>
+<span class="kn">import</span> <span class="nn">com.google.gson.JsonObject</span><span class="o">;</span>
+
+<span class="kn">import</span> <span class="nn">io.prediction.EngineClient</span><span class="o">;</span>
+
+<span class="n">EngineClient</span> <span class="n">engineClient</span> <span class="o">=</span> <span class="k">new</span> <span class="n">EngineClient</span><span class="o">(<</span><span class="n">ENGINE</span> <span class="n">DEPLOY</span> <span class="n">URL</span><span class="o">>);</span>
+
+<span class="n">JsonObject</span> <span class="n">response</span> <span class="o">=</span> <span class="n">engineClient</span><span class="o">.</span><span class="na">sendQuery</span><span class="o">(</span><span class="n">ImmutableMap</span><span class="o">.<</span><span class="n">String</span><span class="o">,</span> <span class="n">Object</span><span class="o">></span><span class="n">of</span><span class="o">(</span>
+ <span class="s">"attr0"</span><span class="o">,</span> <span class="mi">2</span><span class="o">,</span>
+ <span class="s">"attr1"</span><span class="o">,</span> <span class="mi">0</span><span class="o">,</span>
+ <span class="s">"attr2"</span><span class="o">,</span> <span class="mi">0</span>
+ <span class="o">));</span>
+</pre></td> </tr></tbody></table> </div> </div> </div> <div class="alert-message warning"><p>The Query format is changed since version v0.3.1. If you are using old Classification template version v0.3.0 or earlier, the query format is array of feature values instead: <code>{ "features": [2, 0, 0] }</code>.</p></div><p>The following is sample JSON response:</p><div class="highlight shell"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1</pre></td><td class="code"><pre><span class="o">{</span><span class="s2">"label"</span>:0.0<span class="o">}</span>
+</pre></td></tr></tbody></table> </div> <p>Similarly, to predict the label (i.e. <em>plan</em> in this case) of a user with attr0=4, attr1=3 and attr2=8, you send this JSON <code>{ "attr0": 4, "attr1": 3, "attr2": 8] }</code> to the deployed engine and it will return a JSON of the predicted plan.</p><div class="alert-message warning"><p>For classification template version v0.3.0 or earlier, the query JSON would be <code>{ "features": [4, 3, 8] }</code>.</p></div><p><em>MyClassification</em> is now running.</p><div class="alert-message info"><p>To update the model periodically with new data, simply set up a cron job to call <code>pio train</code> and <code>pio deploy</code>. The engine will continue to serve prediction results during the re-train process. After the training is completed, <code>pio deploy</code> will automatically shutdown the existing engine server and bring up a new process on the same port.</p></div><div class="alert-message
info"><p><strong>Note that if you import a <em>large</em> data set</strong> and the training seems to be taking forever or getting stuck, it's likely that there is not enough executor memory. It's recommended to setup a Spark standalone cluster, you'll need to specify more driver and executor memory when training with a large data set. Please see <a href="/resources/faq/#engine-training">FAQ here</a> for instructions.</p></div> <p>Next, we are going to take a look at the engine architecture and explain how you can customize it completely.</p><h4 id='<a-href="/templates/classification/dase/">next:-dase-components-explained</a>' class='header-anchors' ><a href="/templates/classification/dase/">Next: DASE Components Explained</a></h4></div></div></div></div><footer><div class="container"><div class="seperator"></div><div class="row"><div class="col-md-4 col-md-push-8 col-xs-12"><div class="subscription-form-wrapper"><h4>Subscribe to our Newsletter</h4><form class="ajax-form
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<div class="row"><div class="col-md-9 col-sm-11 col-xs-11"><div class="hidden-md hidden-lg" id="mobile-page-heading-wrapper"><p>PredictionIO Docs</p><h4>Language Samples</h4></div><h4 class="hidden-sm hidden-xs">PredictionIO Docs</h4></div><div class="col-md-3 col-sm-1 col-xs-1 hidden-md hidden-lg"><img id="left-menu-indicator" src="/images/icons/down-arrow-dfe9f7fe.png"/></div><div class="col-md-3 col-sm-12 col-xs-12 swiftype-wrapper"><div class="swiftype"><form class="search-form"><img class="search-box-toggler hidden-xs hidden-sm" src="/images/icons/search-glass-704bd4ff.png"/><div class="search-box"><img src="/images/icons/search-glass-704bd4ff.png"/><input type="text" id="st-search-input" class="st-search-input" placeholder="Search Doc..."/></div><img class="swiftype-row-hider hidden-md hidden-lg" src="/images/icons/drawer-toggle-active-fcbef12a.png"/></form></div></div><div class="mobile-left-menu-toggler hidden-md hidden-lg"></div></div></div></div><div id="page" class="conta
iner-fluid"><div class="row"><div id="left-menu-wrapper" class="col-md-3"><nav id="nav-main"><ul><li class="level-1"><a class="expandible" href="/"><span>Apache PredictionIO (incubating) Documentation</span></a><ul><li class="level-2"><a class="final" href="/"><span>Welcome to Apache PredictionIO (incubating)</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Getting Started</span></a><ul><li class="level-2"><a class="final" href="/start/"><span>A Quick Intro</span></a></li><li class="level-2"><a class="final" href="/install/"><span>Installing Apache PredictionIO (incubating)</span></a></li><li class="level-2"><a class="final" href="/start/download/"><span>Downloading an Engine Template</span></a></li><li class="level-2"><a class="final" href="/start/deploy/"><span>Deploying Your First Engine</span></a></li><li class="level-2"><a class="final" href="/start/customize/"><span>Customizing the Engine</span></a></li></ul></li><li class="level-1"><a class="e
xpandible" href="#"><span>Integrating with Your App</span></a><ul><li class="level-2"><a class="final" href="/appintegration/"><span>App Integration Overview</span></a></li><li class="level-2"><a class="expandible" href="/sdk/"><span>List of SDKs</span></a><ul><li class="level-3"><a class="final" href="/sdk/java/"><span>Java & Android SDK</span></a></li><li class="level-3"><a class="final" href="/sdk/php/"><span>PHP SDK</span></a></li><li class="level-3"><a class="final" href="/sdk/python/"><span>Python SDK</span></a></li><li class="level-3"><a class="final" href="/sdk/ruby/"><span>Ruby SDK</span></a></li><li class="level-3"><a class="final" href="/sdk/community/"><span>Community Powered SDKs</span></a></li></ul></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Deploying an Engine</span></a><ul><li class="level-2"><a class="final" href="/deploy/"><span>Deploying as a Web Service</span></a></li><li class="level-2"><a class="final" href="/cli/#engine-commands"><s
pan>Engine Command-line Interface</span></a></li><li class="level-2"><a class="final" href="/deploy/engineparams/"><span>Setting Engine Parameters</span></a></li><li class="level-2"><a class="final" href="/deploy/enginevariants/"><span>Deploying Multiple Engine Variants</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Customizing an Engine</span></a><ul><li class="level-2"><a class="final" href="/customize/"><span>Learning DASE</span></a></li><li class="level-2"><a class="final" href="/customize/dase/"><span>Implement DASE</span></a></li><li class="level-2"><a class="final" href="/customize/troubleshooting/"><span>Troubleshooting Engine Development</span></a></li><li class="level-2"><a class="final" href="/api/current/#package"><span>Engine Scala APIs</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Collecting and Analyzing Data</span></a><ul><li class="level-2"><a class="final" href="/datacollection/"><span>Event Ser
ver Overview</span></a></li><li class="level-2"><a class="final" href="/cli/#event-server-commands"><span>Event Server Command-line Interface</span></a></li><li class="level-2"><a class="final" href="/datacollection/eventapi/"><span>Collecting Data with REST/SDKs</span></a></li><li class="level-2"><a class="final" href="/datacollection/eventmodel/"><span>Events Modeling</span></a></li><li class="level-2"><a class="final" href="/datacollection/webhooks/"><span>Unifying Multichannel Data with Webhooks</span></a></li><li class="level-2"><a class="final" href="/datacollection/channel/"><span>Channel</span></a></li><li class="level-2"><a class="final" href="/datacollection/batchimport/"><span>Importing Data in Batch</span></a></li><li class="level-2"><a class="final" href="/datacollection/analytics/"><span>Using Analytics Tools</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Choosing an Algorithm(s)</span></a><ul><li class="level-2"><a class="final" href
="/algorithm/"><span>Built-in Algorithm Libraries</span></a></li><li class="level-2"><a class="final" href="/algorithm/switch/"><span>Switching to Another Algorithm</span></a></li><li class="level-2"><a class="final" href="/algorithm/multiple/"><span>Combining Multiple Algorithms</span></a></li><li class="level-2"><a class="final" href="/algorithm/custom/"><span>Adding Your Own Algorithms</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>ML Tuning and Evaluation</span></a><ul><li class="level-2"><a class="final" href="/evaluation/"><span>Overview</span></a></li><li class="level-2"><a class="final" href="/evaluation/paramtuning/"><span>Hyperparameter Tuning</span></a></li><li class="level-2"><a class="final" href="/evaluation/evaluationdashboard/"><span>Evaluation Dashboard</span></a></li><li class="level-2"><a class="final" href="/evaluation/metricchoose/"><span>Choosing Evaluation Metrics</span></a></li><li class="level-2"><a class="final" href="/eva
luation/metricbuild/"><span>Building Evaluation Metrics</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>System Architecture</span></a><ul><li class="level-2"><a class="final" href="/system/"><span>Architecture Overview</span></a></li><li class="level-2"><a class="final" href="/system/anotherdatastore/"><span>Using Another Data Store</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Engine Template Gallery</span></a><ul><li class="level-2"><a class="final" href="http://templates.prediction.io"><span>Browse</span></a></li><li class="level-2"><a class="final" href="/community/submit-template/"><span>Submit your Engine as a Template</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Demo Tutorials</span></a><ul><li class="level-2"><a class="final" href="/demo/tapster/"><span>Comics Recommendation Demo</span></a></li><li class="level-2"><a class="final" href="/demo/community/"><span>Community
Contributed Demo</span></a></li><li class="level-2"><a class="final" href="/demo/textclassification/"><span>Text Classification Engine Tutorial</span></a></li></ul></li><li class="level-1"><a class="expandible" href="/community/"><span>Getting Involved</span></a><ul><li class="level-2"><a class="final" href="/community/contribute-code/"><span>Contribute Code</span></a></li><li class="level-2"><a class="final" href="/community/contribute-documentation/"><span>Contribute Documentation</span></a></li><li class="level-2"><a class="final" href="/community/contribute-sdk/"><span>Contribute a SDK</span></a></li><li class="level-2"><a class="final" href="/community/contribute-webhook/"><span>Contribute a Webhook</span></a></li><li class="level-2"><a class="final" href="/community/projects/"><span>Community Projects</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Getting Help</span></a><ul><li class="level-2"><a class="final" href="/resources/faq/"><span>FA
Qs</span></a></li><li class="level-2"><a class="final" href="/support/"><span>Community Support</span></a></li><li class="level-2"><a class="final" href="/support/#enterprise-support"><span>Enterprise Support</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Resources</span></a><ul><li class="level-2"><a class="final" href="/resources/intellij/"><span>Developing Engines with IntelliJ IDEA</span></a></li><li class="level-2"><a class="final" href="/resources/upgrade/"><span>Upgrade Instructions</span></a></li><li class="level-2"><a class="final" href="/resources/glossary/"><span>Glossary</span></a></li></ul></li></ul></nav></div><div class="col-md-9 col-sm-12"><div class="content-header hidden-md hidden-lg"><div id="page-title"><h1>Language Samples</h1></div></div><div id="table-of-content-wrapper"><h5>On this page</h5><aside id="table-of-contents"><ul> <li> <a href="#plain-text">Plain Text</a> </li> <li> <a href="#scala">Scala</a> </li> <li> <a href="#
ruby">Ruby</a> </li> <li> <a href="#json">JSON</a> </li> <li> <a href="#php">PHP</a> </li> <li> <a href="#python">Python</a> </li> </ul> </aside><hr/><a id="edit-page-link" href="https://github.com/apache/incubator-predictionio/tree/livedoc/docs/manual/source/samples/languages.html.md"><img src="/images/icons/edit-pencil-d6c1bb3d.png"/>Edit this page</a></div><div class="content-header hidden-sm hidden-xs"><div id="page-title"><h1>Language Samples</h1></div></div><div class="content"><h2 id='plain-text' class='header-anchors'>Plain Text</h2><p>This is a sample code block with no language.</p><div class="highlight shell"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1
+2
+3
+4</pre></td><td class="code"><pre><span class="gp">$ </span><span class="nv">$PIO_HOME</span>/bin/pio eventserver
+<span class="gp">$ </span><span class="nb">cd</span> /path/to/engine
+<span class="gp">$ </span>../bin/pio train
+<span class="gp">$ </span>../bin/pio deploy
+</pre></td></tr></tbody></table> </div> <h2 id='scala' class='header-anchors'>Scala</h2><p>This is a sample Scala code block:</p><div class="highlight scala"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1
+2
+3
+4
+5
+6
+7
+8
+9
+10
+11</pre></td><td class="code"><pre><span class="k">class</span> <span class="nc">Preparator</span>
+ <span class="k">extends</span> <span class="nc">PPreparator</span><span class="o">[</span><span class="kt">TrainingData</span>, <span class="kt">PreparedData</span><span class="o">]</span> <span class="o">{</span>
+
+ <span class="k">def</span> <span class="n">prepare</span><span class="o">(</span><span class="n">sc</span><span class="k">:</span> <span class="kt">SparkContext</span><span class="o">,</span> <span class="n">trainingData</span><span class="k">:</span> <span class="kt">TrainingData</span><span class="o">)</span><span class="k">:</span> <span class="kt">PreparedData</span> <span class="o">=</span> <span class="o">{</span>
+ <span class="k">new</span> <span class="nc">PreparedData</span><span class="o">(</span><span class="n">ratings</span> <span class="k">=</span> <span class="n">trainingData</span><span class="o">.</span><span class="n">ratings</span><span class="o">)</span>
+ <span class="o">}</span>
+<span class="o">}</span>
+
+<span class="k">class</span> <span class="nc">PreparedData</span><span class="o">(</span>
+ <span class="k">val</span> <span class="n">ratings</span><span class="k">:</span> <span class="kt">RDD</span><span class="o">[</span><span class="kt">Rating</span><span class="o">]</span>
+<span class="o">)</span>
+</pre></td></tr></tbody></table> </div> <h2 id='ruby' class='header-anchors'>Ruby</h2><p>This is a sample Ruby code block:</p><div class="highlight ruby"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1
+2
+3
+4
+5</pre></td><td class="code"><pre><span class="k">class</span> <span class="nc">UsersController</span> <span class="o"><</span> <span class="no">ApplicationController</span>
+ <span class="k">def</span> <span class="nf">index</span>
+ <span class="vi">@users</span> <span class="o">=</span> <span class="no">User</span><span class="p">.</span><span class="nf">order</span><span class="p">(</span><span class="s1">'reviews_count DESC'</span><span class="p">).</span><span class="nf">limit</span><span class="p">(</span><span class="mi">20</span><span class="p">)</span>
+ <span class="k">end</span>
+<span class="k">end</span>
+</pre></td></tr></tbody></table> </div> <h2 id='json' class='header-anchors'>JSON</h2><p>This is a sample JSON code block:</p><div class="highlight json"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1
+2
+3
+4
+5
+6
+7
+8
+9
+10
+11
+12
+13
+14</pre></td><td class="code"><pre><span class="p">{</span><span class="w">
+ </span><span class="err">...</span><span class="w">
+ </span><span class="s2">"algorithms"</span><span class="p">:</span><span class="w"> </span><span class="p">[</span><span class="w">
+ </span><span class="p">{</span><span class="w">
+ </span><span class="s2">"name"</span><span class="p">:</span><span class="w"> </span><span class="s2">"als"</span><span class="p">,</span><span class="w">
+ </span><span class="s2">"params"</span><span class="p">:</span><span class="w"> </span><span class="p">{</span><span class="w">
+ </span><span class="s2">"rank"</span><span class="p">:</span><span class="w"> </span><span class="mi">10</span><span class="p">,</span><span class="w">
+ </span><span class="s2">"numIterations"</span><span class="p">:</span><span class="w"> </span><span class="mi">20</span><span class="p">,</span><span class="w">
+ </span><span class="s2">"lambda"</span><span class="p">:</span><span class="w"> </span><span class="mf">0.01</span><span class="w">
+ </span><span class="p">}</span><span class="w">
+ </span><span class="p">}</span><span class="w">
+ </span><span class="p">]</span><span class="w">
+ </span><span class="err">...</span><span class="w">
+</span><span class="p">}</span><span class="w">
+</span></pre></td></tr></tbody></table> </div> <h2 id='php' class='header-anchors'>PHP</h2><p>This is a sample PHP code block:</p><div class="highlight php"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1
+2
+3
+4
+5
+6
+7
+8
+9
+10
+11
+12
+13
+14
+15
+16
+17
+18
+19</pre></td><td class="code"><pre><span class="cp"><?php</span>
+<span class="k">require_once</span><span class="p">(</span><span class="s2">"vendor/autoload.php"</span><span class="p">);</span>
+<span class="k">use</span> <span class="nx">predictionio\EventClient</span><span class="p">;</span>
+
+<span class="nv">$client</span> <span class="o">=</span> <span class="k">new</span> <span class="nx">EventClient</span><span class="p">(</span><span class="o"><</span><span class="nx">ACCESS</span> <span class="nx">KEY</span><span class="o">></span><span class="p">,</span> <span class="o"><</span><span class="nx">URL</span> <span class="nx">OF</span> <span class="nx">EVENTSERVER</span><span class="o">></span><span class="p">);</span>
+
+<span class="c1">// Set the 4 properties for a user
+</span><span class="nv">$client</span><span class="o">-></span><span class="na">createEvent</span><span class="p">(</span><span class="k">array</span><span class="p">(</span>
+ <span class="s1">'event'</span> <span class="o">=></span> <span class="s1">'$set'</span><span class="p">,</span>
+ <span class="s1">'entityType'</span> <span class="o">=></span> <span class="s1">'user'</span><span class="p">,</span>
+ <span class="s1">'entityId'</span> <span class="o">=></span> <span class="o"><</span><span class="nx">USER</span> <span class="nx">ID</span><span class="o">></span><span class="p">,</span>
+ <span class="s1">'properties'</span> <span class="o">=></span> <span class="k">array</span><span class="p">(</span>
+ <span class="s1">'attr0'</span> <span class="o">=></span> <span class="o"><</span><span class="nx">VALUE</span> <span class="nx">OF</span> <span class="nx">ATTR0</span><span class="o">></span><span class="p">,</span>
+ <span class="s1">'attr1'</span> <span class="o">=></span> <span class="o"><</span><span class="nx">VALUE</span> <span class="nx">OF</span> <span class="nx">ATTR1</span><span class="o">></span><span class="p">,</span>
+ <span class="s1">'attr2'</span> <span class="o">=></span> <span class="o"><</span><span class="nx">VALUE</span> <span class="nx">OF</span> <span class="nx">ATTR2</span><span class="o">></span><span class="p">,</span>
+ <span class="s1">'plan'</span> <span class="o">=></span> <span class="o"><</span><span class="nx">VALUE</span> <span class="nx">OF</span> <span class="nx">PLAN</span><span class="o">></span>
+ <span class="p">)</span>
+ <span class="p">));</span>
+<span class="cp">?></span>
+</pre></td></tr></tbody></table> </div> <h2 id='python' class='header-anchors'>Python</h2><p>This is a sample Python code block:</p><div class="highlight python"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1
+2
+3
+4
+5
+6
+7
+8
+9
+10
+11
+12
+13
+14
+15
+16
+17
+18
+19
+20
+21
+22</pre></td><td class="code"><pre><span class="kn">from</span> <span class="nn">predictionio</span> <span class="kn">import</span> <span class="n">EventClient</span>
+<span class="kn">from</span> <span class="nn">datetime</span> <span class="kn">import</span> <span class="n">datetime</span>
+<span class="kn">import</span> <span class="nn">pytz</span>
+<span class="n">client</span> <span class="o">=</span> <span class="n">EventClient</span><span class="p">(</span><span class="n">app_id</span><span class="o">=</span><span class="mi">4</span><span class="p">,</span> <span class="n">url</span><span class="o">=</span><span class="s">"http://localhost:7070"</span><span class="p">)</span>
+
+<span class="n">first_event_properties</span> <span class="o">=</span> <span class="p">{</span>
+ <span class="s">"prop1"</span> <span class="p">:</span> <span class="mi">1</span><span class="p">,</span>
+ <span class="s">"prop2"</span> <span class="p">:</span> <span class="s">"value2"</span><span class="p">,</span>
+ <span class="s">"prop3"</span> <span class="p">:</span> <span class="p">[</span><span class="mi">1</span><span class="p">,</span> <span class="mi">2</span><span class="p">,</span> <span class="mi">3</span><span class="p">],</span>
+ <span class="s">"prop4"</span> <span class="p">:</span> <span class="bp">True</span><span class="p">,</span>
+ <span class="s">"prop5"</span> <span class="p">:</span> <span class="p">[</span><span class="s">"a"</span><span class="p">,</span> <span class="s">"b"</span><span class="p">,</span> <span class="s">"c"</span><span class="p">],</span>
+ <span class="s">"prop6"</span> <span class="p">:</span> <span class="mf">4.56</span> <span class="p">,</span>
+ <span class="p">}</span>
+<span class="n">first_event_time</span> <span class="o">=</span> <span class="n">datetime</span><span class="p">(</span>
+ <span class="mi">2004</span><span class="p">,</span> <span class="mi">12</span><span class="p">,</span> <span class="mi">13</span><span class="p">,</span> <span class="mi">21</span><span class="p">,</span> <span class="mi">39</span><span class="p">,</span> <span class="mi">45</span><span class="p">,</span> <span class="mi">618000</span><span class="p">,</span> <span class="n">pytz</span><span class="o">.</span><span class="n">timezone</span><span class="p">(</span><span class="s">'US/Mountain'</span><span class="p">))</span>
+<span class="n">first_event_response</span> <span class="o">=</span> <span class="n">client</span><span class="o">.</span><span class="n">create_event</span><span class="p">(</span>
+ <span class="n">event</span><span class="o">=</span><span class="s">"my_event"</span><span class="p">,</span>
+ <span class="n">entity_type</span><span class="o">=</span><span class="s">"user"</span><span class="p">,</span>
+ <span class="n">entity_id</span><span class="o">=</span><span class="s">"uid"</span><span class="p">,</span>
+ <span class="n">properties</span><span class="o">=</span><span class="n">first_event_properties</span><span class="p">,</span>
+ <span class="n">event_time</span><span class="o">=</span><span class="n">first_event_time</span><span class="p">,</span>
+<span class="p">)</span>
+</pre></td></tr></tbody></table> </div> </div></div></div></div><footer><div class="container"><div class="seperator"></div><div class="row"><div class="col-md-4 col-md-push-8 col-xs-12"><div class="subscription-form-wrapper"><h4>Subscribe to our Newsletter</h4><form class="ajax-form" id="subscribe-form" method="POST" action="https://script.google.com/macros/s/AKfycbwhzeKCQJjQ52eVAqNT_vcklH07OITUO7wzOMDXvK6EGAWgaZgF/exec"><input class="required underlined-input" type="email" placeholder="Your email address" name="subscription_email" id="subscription_email"/><input class="pill-button" value="SUBSCRIBE" type="submit" data-state-normal="SUBSCRIBE" data-state-sucess="SUBSCRIBED!" data-state-loading="SENDING..." onclick="t($('#subscription_email').val());"/><p class="result"></p></form></div></div><div class="col-md-2 col-md-pull-4 col-xs-6 footer-link-column"><div class="footer-link-column-row"><h4>Community</h4><ul><li><a href="//docs.prediction.io/install/" target="blank">Download</a>
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+++ b/samples/level-1/index.html
@@ -0,0 +1,55 @@
+<!DOCTYPE html><html><head><title>Level 1</title><meta charset="utf-8"/><meta content="IE=edge,chrome=1" http-equiv="X-UA-Compatible"/><meta name="viewport" content="width=device-width, initial-scale=1.0"/><meta class="swiftype" name="title" data-type="string" content="Level 1"/><link rel="canonical" href="https://docs.prediction.io/samples/level-1/"/><link href="/images/favicon/normal-b330020a.png" rel="shortcut icon"/><link href="/images/favicon/apple-c0febcf2.png" rel="apple-touch-icon"/><link href="//fonts.googleapis.com/css?family=Open+Sans:300italic,400italic,600italic,700italic,800italic,400,300,600,700,800" rel="stylesheet"/><link href="//maxcdn.bootstrapcdn.com/font-awesome/4.2.0/css/font-awesome.min.css" rel="stylesheet"/><link href="/stylesheets/application-3598c7d7.css" rel="stylesheet" type="text/css"/><!--[if lt IE 9]><script src="//cdnjs.cloudflare.com/ajax/libs/html5shiv/3.7.2/html5shiv.min.js"></script><![endif]--><script src="//cdn.mathjax.org/mathjax/latest/MathJa
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<div class="row"><div class="col-md-9 col-sm-11 col-xs-11"><div class="hidden-md hidden-lg" id="mobile-page-heading-wrapper"><p>PredictionIO Docs</p><h4>Level 1</h4></div><h4 class="hidden-sm hidden-xs">PredictionIO Docs</h4></div><div class="col-md-3 col-sm-1 col-xs-1 hidden-md hidden-lg"><img id="left-menu-indicator" src="/images/icons/down-arrow-dfe9f7fe.png"/></div><div class="col-md-3 col-sm-12 col-xs-12 swiftype-wrapper"><div class="swiftype"><form class="search-form"><img class="search-box-toggler hidden-xs hidden-sm" src="/images/icons/search-glass-704bd4ff.png"/><div class="search-box"><img src="/images/icons/search-glass-704bd4ff.png"/><input type="text" id="st-search-input" class="st-search-input" placeholder="Search Doc..."/></div><img class="swiftype-row-hider hidden-md hidden-lg" src="/images/icons/drawer-toggle-active-fcbef12a.png"/></form></div></div><div class="mobile-left-menu-toggler hidden-md hidden-lg"></div></div></div></div><div id="page" class="container-flui
d"><div class="row"><div id="left-menu-wrapper" class="col-md-3"><nav id="nav-main"><ul><li class="level-1"><a class="expandible" href="/"><span>Apache PredictionIO (incubating) Documentation</span></a><ul><li class="level-2"><a class="final" href="/"><span>Welcome to Apache PredictionIO (incubating)</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Getting Started</span></a><ul><li class="level-2"><a class="final" href="/start/"><span>A Quick Intro</span></a></li><li class="level-2"><a class="final" href="/install/"><span>Installing Apache PredictionIO (incubating)</span></a></li><li class="level-2"><a class="final" href="/start/download/"><span>Downloading an Engine Template</span></a></li><li class="level-2"><a class="final" href="/start/deploy/"><span>Deploying Your First Engine</span></a></li><li class="level-2"><a class="final" href="/start/customize/"><span>Customizing the Engine</span></a></li></ul></li><li class="level-1"><a class="expandible
" href="#"><span>Integrating with Your App</span></a><ul><li class="level-2"><a class="final" href="/appintegration/"><span>App Integration Overview</span></a></li><li class="level-2"><a class="expandible" href="/sdk/"><span>List of SDKs</span></a><ul><li class="level-3"><a class="final" href="/sdk/java/"><span>Java & Android SDK</span></a></li><li class="level-3"><a class="final" href="/sdk/php/"><span>PHP SDK</span></a></li><li class="level-3"><a class="final" href="/sdk/python/"><span>Python SDK</span></a></li><li class="level-3"><a class="final" href="/sdk/ruby/"><span>Ruby SDK</span></a></li><li class="level-3"><a class="final" href="/sdk/community/"><span>Community Powered SDKs</span></a></li></ul></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Deploying an Engine</span></a><ul><li class="level-2"><a class="final" href="/deploy/"><span>Deploying as a Web Service</span></a></li><li class="level-2"><a class="final" href="/cli/#engine-commands"><span>Engin
e Command-line Interface</span></a></li><li class="level-2"><a class="final" href="/deploy/engineparams/"><span>Setting Engine Parameters</span></a></li><li class="level-2"><a class="final" href="/deploy/enginevariants/"><span>Deploying Multiple Engine Variants</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Customizing an Engine</span></a><ul><li class="level-2"><a class="final" href="/customize/"><span>Learning DASE</span></a></li><li class="level-2"><a class="final" href="/customize/dase/"><span>Implement DASE</span></a></li><li class="level-2"><a class="final" href="/customize/troubleshooting/"><span>Troubleshooting Engine Development</span></a></li><li class="level-2"><a class="final" href="/api/current/#package"><span>Engine Scala APIs</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Collecting and Analyzing Data</span></a><ul><li class="level-2"><a class="final" href="/datacollection/"><span>Event Server Overv
iew</span></a></li><li class="level-2"><a class="final" href="/cli/#event-server-commands"><span>Event Server Command-line Interface</span></a></li><li class="level-2"><a class="final" href="/datacollection/eventapi/"><span>Collecting Data with REST/SDKs</span></a></li><li class="level-2"><a class="final" href="/datacollection/eventmodel/"><span>Events Modeling</span></a></li><li class="level-2"><a class="final" href="/datacollection/webhooks/"><span>Unifying Multichannel Data with Webhooks</span></a></li><li class="level-2"><a class="final" href="/datacollection/channel/"><span>Channel</span></a></li><li class="level-2"><a class="final" href="/datacollection/batchimport/"><span>Importing Data in Batch</span></a></li><li class="level-2"><a class="final" href="/datacollection/analytics/"><span>Using Analytics Tools</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Choosing an Algorithm(s)</span></a><ul><li class="level-2"><a class="final" href="/algori
thm/"><span>Built-in Algorithm Libraries</span></a></li><li class="level-2"><a class="final" href="/algorithm/switch/"><span>Switching to Another Algorithm</span></a></li><li class="level-2"><a class="final" href="/algorithm/multiple/"><span>Combining Multiple Algorithms</span></a></li><li class="level-2"><a class="final" href="/algorithm/custom/"><span>Adding Your Own Algorithms</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>ML Tuning and Evaluation</span></a><ul><li class="level-2"><a class="final" href="/evaluation/"><span>Overview</span></a></li><li class="level-2"><a class="final" href="/evaluation/paramtuning/"><span>Hyperparameter Tuning</span></a></li><li class="level-2"><a class="final" href="/evaluation/evaluationdashboard/"><span>Evaluation Dashboard</span></a></li><li class="level-2"><a class="final" href="/evaluation/metricchoose/"><span>Choosing Evaluation Metrics</span></a></li><li class="level-2"><a class="final" href="/evaluation/m
etricbuild/"><span>Building Evaluation Metrics</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>System Architecture</span></a><ul><li class="level-2"><a class="final" href="/system/"><span>Architecture Overview</span></a></li><li class="level-2"><a class="final" href="/system/anotherdatastore/"><span>Using Another Data Store</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Engine Template Gallery</span></a><ul><li class="level-2"><a class="final" href="http://templates.prediction.io"><span>Browse</span></a></li><li class="level-2"><a class="final" href="/community/submit-template/"><span>Submit your Engine as a Template</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Demo Tutorials</span></a><ul><li class="level-2"><a class="final" href="/demo/tapster/"><span>Comics Recommendation Demo</span></a></li><li class="level-2"><a class="final" href="/demo/community/"><span>Community Contribu
ted Demo</span></a></li><li class="level-2"><a class="final" href="/demo/textclassification/"><span>Text Classification Engine Tutorial</span></a></li></ul></li><li class="level-1"><a class="expandible" href="/community/"><span>Getting Involved</span></a><ul><li class="level-2"><a class="final" href="/community/contribute-code/"><span>Contribute Code</span></a></li><li class="level-2"><a class="final" href="/community/contribute-documentation/"><span>Contribute Documentation</span></a></li><li class="level-2"><a class="final" href="/community/contribute-sdk/"><span>Contribute a SDK</span></a></li><li class="level-2"><a class="final" href="/community/contribute-webhook/"><span>Contribute a Webhook</span></a></li><li class="level-2"><a class="final" href="/community/projects/"><span>Community Projects</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Getting Help</span></a><ul><li class="level-2"><a class="final" href="/resources/faq/"><span>FAQs</span>
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ubator-predictionio/tree/livedoc/docs/manual/source/samples/level-1.html.md"><img src="/images/icons/edit-pencil-d6c1bb3d.png"/>Edit this page</a></div><div class="content-header hidden-sm hidden-xs"><div id="page-title"><h1>Level 1</h1></div></div><div class="content"><h2 id='level-1' class='header-anchors'>Level 1</h2></div></div></div></div><footer><div class="container"><div class="seperator"></div><div class="row"><div class="col-md-4 col-md-push-8 col-xs-12"><div class="subscription-form-wrapper"><h4>Subscribe to our Newsletter</h4><form class="ajax-form" id="subscribe-form" method="POST" action="https://script.google.com/macros/s/AKfycbwhzeKCQJjQ52eVAqNT_vcklH07OITUO7wzOMDXvK6EGAWgaZgF/exec"><input class="required underlined-input" type="email" placeholder="Your email address" name="subscription_email" id="subscription_email"/><input class="pill-button" value="SUBSCRIBE" type="submit" data-state-normal="SUBSCRIBE" data-state-sucess="SUBSCRIBED!" data-state-loading="SENDING...
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<div class="row"><div class="col-md-9 col-sm-11 col-xs-11"><div class="hidden-md hidden-lg" id="mobile-page-heading-wrapper"><p>PredictionIO Docs</p><h4>Level 2.1</h4></div><h4 class="hidden-sm hidden-xs">PredictionIO Docs</h4></div><div class="col-md-3 col-sm-1 col-xs-1 hidden-md hidden-lg"><img id="left-menu-indicator" src="/images/icons/down-arrow-dfe9f7fe.png"/></div><div class="col-md-3 col-sm-12 col-xs-12 swiftype-wrapper"><div class="swiftype"><form class="search-form"><img class="search-box-toggler hidden-xs hidden-sm" src="/images/icons/search-glass-704bd4ff.png"/><div class="search-box"><img src="/images/icons/search-glass-704bd4ff.png"/><input type="text" id="st-search-input" class="st-search-input" placeholder="Search Doc..."/></div><img class="swiftype-row-hider hidden-md hidden-lg" src="/images/icons/drawer-toggle-active-fcbef12a.png"/></form></div></div><div class="mobile-left-menu-toggler hidden-md hidden-lg"></div></div></div></div><div id="page" class="container-fl
uid"><div class="row"><div id="left-menu-wrapper" class="col-md-3"><nav id="nav-main"><ul><li class="level-1"><a class="expandible" href="/"><span>Apache PredictionIO (incubating) Documentation</span></a><ul><li class="level-2"><a class="final" href="/"><span>Welcome to Apache PredictionIO (incubating)</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Getting Started</span></a><ul><li class="level-2"><a class="final" href="/start/"><span>A Quick Intro</span></a></li><li class="level-2"><a class="final" href="/install/"><span>Installing Apache PredictionIO (incubating)</span></a></li><li class="level-2"><a class="final" href="/start/download/"><span>Downloading an Engine Template</span></a></li><li class="level-2"><a class="final" href="/start/deploy/"><span>Deploying Your First Engine</span></a></li><li class="level-2"><a class="final" href="/start/customize/"><span>Customizing the Engine</span></a></li></ul></li><li class="level-1"><a class="expandib
le" href="#"><span>Integrating with Your App</span></a><ul><li class="level-2"><a class="final" href="/appintegration/"><span>App Integration Overview</span></a></li><li class="level-2"><a class="expandible" href="/sdk/"><span>List of SDKs</span></a><ul><li class="level-3"><a class="final" href="/sdk/java/"><span>Java & Android SDK</span></a></li><li class="level-3"><a class="final" href="/sdk/php/"><span>PHP SDK</span></a></li><li class="level-3"><a class="final" href="/sdk/python/"><span>Python SDK</span></a></li><li class="level-3"><a class="final" href="/sdk/ruby/"><span>Ruby SDK</span></a></li><li class="level-3"><a class="final" href="/sdk/community/"><span>Community Powered SDKs</span></a></li></ul></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Deploying an Engine</span></a><ul><li class="level-2"><a class="final" href="/deploy/"><span>Deploying as a Web Service</span></a></li><li class="level-2"><a class="final" href="/cli/#engine-commands"><span>Eng
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rview</span></a></li><li class="level-2"><a class="final" href="/cli/#event-server-commands"><span>Event Server Command-line Interface</span></a></li><li class="level-2"><a class="final" href="/datacollection/eventapi/"><span>Collecting Data with REST/SDKs</span></a></li><li class="level-2"><a class="final" href="/datacollection/eventmodel/"><span>Events Modeling</span></a></li><li class="level-2"><a class="final" href="/datacollection/webhooks/"><span>Unifying Multichannel Data with Webhooks</span></a></li><li class="level-2"><a class="final" href="/datacollection/channel/"><span>Channel</span></a></li><li class="level-2"><a class="final" href="/datacollection/batchimport/"><span>Importing Data in Batch</span></a></li><li class="level-2"><a class="final" href="/datacollection/analytics/"><span>Using Analytics Tools</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Choosing an Algorithm(s)</span></a><ul><li class="level-2"><a class="final" href="/algo
rithm/"><span>Built-in Algorithm Libraries</span></a></li><li class="level-2"><a class="final" href="/algorithm/switch/"><span>Switching to Another Algorithm</span></a></li><li class="level-2"><a class="final" href="/algorithm/multiple/"><span>Combining Multiple Algorithms</span></a></li><li class="level-2"><a class="final" href="/algorithm/custom/"><span>Adding Your Own Algorithms</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>ML Tuning and Evaluation</span></a><ul><li class="level-2"><a class="final" href="/evaluation/"><span>Overview</span></a></li><li class="level-2"><a class="final" href="/evaluation/paramtuning/"><span>Hyperparameter Tuning</span></a></li><li class="level-2"><a class="final" href="/evaluation/evaluationdashboard/"><span>Evaluation Dashboard</span></a></li><li class="level-2"><a class="final" href="/evaluation/metricchoose/"><span>Choosing Evaluation Metrics</span></a></li><li class="level-2"><a class="final" href="/evaluation
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n></a></li><li class="level-2"><a class="final" href="/support/"><span>Community Support</span></a></li><li class="level-2"><a class="final" href="/support/#enterprise-support"><span>Enterprise Support</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Resources</span></a><ul><li class="level-2"><a class="final" href="/resources/intellij/"><span>Developing Engines with IntelliJ IDEA</span></a></li><li class="level-2"><a class="final" href="/resources/upgrade/"><span>Upgrade Instructions</span></a></li><li class="level-2"><a class="final" href="/resources/glossary/"><span>Glossary</span></a></li></ul></li></ul></nav></div><div class="col-md-9 col-sm-12"><div class="content-header hidden-md hidden-lg"><div id="page-title"><h1>Level 2.1</h1></div></div><div id="table-of-content-wrapper"><h5>On this page</h5><aside id="table-of-contents"><ul> <li> <a href="#level-2-1">Level 2.1</a> </li> </ul> </aside><hr/><a id="edit-page-link" href="https://github.com/ap
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uid"><div class="row"><div id="left-menu-wrapper" class="col-md-3"><nav id="nav-main"><ul><li class="level-1"><a class="expandible" href="/"><span>Apache PredictionIO (incubating) Documentation</span></a><ul><li class="level-2"><a class="final" href="/"><span>Welcome to Apache PredictionIO (incubating)</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Getting Started</span></a><ul><li class="level-2"><a class="final" href="/start/"><span>A Quick Intro</span></a></li><li class="level-2"><a class="final" href="/install/"><span>Installing Apache PredictionIO (incubating)</span></a></li><li class="level-2"><a class="final" href="/start/download/"><span>Downloading an Engine Template</span></a></li><li class="level-2"><a class="final" href="/start/deploy/"><span>Deploying Your First Engine</span></a></li><li class="level-2"><a class="final" href="/start/customize/"><span>Customizing the Engine</span></a></li></ul></li><li class="level-1"><a class="expandib
le" href="#"><span>Integrating with Your App</span></a><ul><li class="level-2"><a class="final" href="/appintegration/"><span>App Integration Overview</span></a></li><li class="level-2"><a class="expandible" href="/sdk/"><span>List of SDKs</span></a><ul><li class="level-3"><a class="final" href="/sdk/java/"><span>Java & Android SDK</span></a></li><li class="level-3"><a class="final" href="/sdk/php/"><span>PHP SDK</span></a></li><li class="level-3"><a class="final" href="/sdk/python/"><span>Python SDK</span></a></li><li class="level-3"><a class="final" href="/sdk/ruby/"><span>Ruby SDK</span></a></li><li class="level-3"><a class="final" href="/sdk/community/"><span>Community Powered SDKs</span></a></li></ul></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Deploying an Engine</span></a><ul><li class="level-2"><a class="final" href="/deploy/"><span>Deploying as a Web Service</span></a></li><li class="level-2"><a class="final" href="/cli/#engine-commands"><span>Eng
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rview</span></a></li><li class="level-2"><a class="final" href="/cli/#event-server-commands"><span>Event Server Command-line Interface</span></a></li><li class="level-2"><a class="final" href="/datacollection/eventapi/"><span>Collecting Data with REST/SDKs</span></a></li><li class="level-2"><a class="final" href="/datacollection/eventmodel/"><span>Events Modeling</span></a></li><li class="level-2"><a class="final" href="/datacollection/webhooks/"><span>Unifying Multichannel Data with Webhooks</span></a></li><li class="level-2"><a class="final" href="/datacollection/channel/"><span>Channel</span></a></li><li class="level-2"><a class="final" href="/datacollection/batchimport/"><span>Importing Data in Batch</span></a></li><li class="level-2"><a class="final" href="/datacollection/analytics/"><span>Using Analytics Tools</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Choosing an Algorithm(s)</span></a><ul><li class="level-2"><a class="final" href="/algo
rithm/"><span>Built-in Algorithm Libraries</span></a></li><li class="level-2"><a class="final" href="/algorithm/switch/"><span>Switching to Another Algorithm</span></a></li><li class="level-2"><a class="final" href="/algorithm/multiple/"><span>Combining Multiple Algorithms</span></a></li><li class="level-2"><a class="final" href="/algorithm/custom/"><span>Adding Your Own Algorithms</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>ML Tuning and Evaluation</span></a><ul><li class="level-2"><a class="final" href="/evaluation/"><span>Overview</span></a></li><li class="level-2"><a class="final" href="/evaluation/paramtuning/"><span>Hyperparameter Tuning</span></a></li><li class="level-2"><a class="final" href="/evaluation/evaluationdashboard/"><span>Evaluation Dashboard</span></a></li><li class="level-2"><a class="final" href="/evaluation/metricchoose/"><span>Choosing Evaluation Metrics</span></a></li><li class="level-2"><a class="final" href="/evaluation
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d"><div class="row"><div id="left-menu-wrapper" class="col-md-3"><nav id="nav-main"><ul><li class="level-1"><a class="expandible" href="/"><span>Apache PredictionIO (incubating) Documentation</span></a><ul><li class="level-2"><a class="final" href="/"><span>Welcome to Apache PredictionIO (incubating)</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Getting Started</span></a><ul><li class="level-2"><a class="final" href="/start/"><span>A Quick Intro</span></a></li><li class="level-2"><a class="final" href="/install/"><span>Installing Apache PredictionIO (incubating)</span></a></li><li class="level-2"><a class="final" href="/start/download/"><span>Downloading an Engine Template</span></a></li><li class="level-2"><a class="final" href="/start/deploy/"><span>Deploying Your First Engine</span></a></li><li class="level-2"><a class="final" href="/start/customize/"><span>Customizing the Engine</span></a></li></ul></li><li class="level-1"><a class="expandible
" href="#"><span>Integrating with Your App</span></a><ul><li class="level-2"><a class="final" href="/appintegration/"><span>App Integration Overview</span></a></li><li class="level-2"><a class="expandible" href="/sdk/"><span>List of SDKs</span></a><ul><li class="level-3"><a class="final" href="/sdk/java/"><span>Java & Android SDK</span></a></li><li class="level-3"><a class="final" href="/sdk/php/"><span>PHP SDK</span></a></li><li class="level-3"><a class="final" href="/sdk/python/"><span>Python SDK</span></a></li><li class="level-3"><a class="final" href="/sdk/ruby/"><span>Ruby SDK</span></a></li><li class="level-3"><a class="final" href="/sdk/community/"><span>Community Powered SDKs</span></a></li></ul></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Deploying an Engine</span></a><ul><li class="level-2"><a class="final" href="/deploy/"><span>Deploying as a Web Service</span></a></li><li class="level-2"><a class="final" href="/cli/#engine-commands"><span>Engin
e Command-line Interface</span></a></li><li class="level-2"><a class="final" href="/deploy/engineparams/"><span>Setting Engine Parameters</span></a></li><li class="level-2"><a class="final" href="/deploy/enginevariants/"><span>Deploying Multiple Engine Variants</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Customizing an Engine</span></a><ul><li class="level-2"><a class="final" href="/customize/"><span>Learning DASE</span></a></li><li class="level-2"><a class="final" href="/customize/dase/"><span>Implement DASE</span></a></li><li class="level-2"><a class="final" href="/customize/troubleshooting/"><span>Troubleshooting Engine Development</span></a></li><li class="level-2"><a class="final" href="/api/current/#package"><span>Engine Scala APIs</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Collecting and Analyzing Data</span></a><ul><li class="level-2"><a class="final" href="/datacollection/"><span>Event Server Overv
iew</span></a></li><li class="level-2"><a class="final" href="/cli/#event-server-commands"><span>Event Server Command-line Interface</span></a></li><li class="level-2"><a class="final" href="/datacollection/eventapi/"><span>Collecting Data with REST/SDKs</span></a></li><li class="level-2"><a class="final" href="/datacollection/eventmodel/"><span>Events Modeling</span></a></li><li class="level-2"><a class="final" href="/datacollection/webhooks/"><span>Unifying Multichannel Data with Webhooks</span></a></li><li class="level-2"><a class="final" href="/datacollection/channel/"><span>Channel</span></a></li><li class="level-2"><a class="final" href="/datacollection/batchimport/"><span>Importing Data in Batch</span></a></li><li class="level-2"><a class="final" href="/datacollection/analytics/"><span>Using Analytics Tools</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Choosing an Algorithm(s)</span></a><ul><li class="level-2"><a class="final" href="/algori
thm/"><span>Built-in Algorithm Libraries</span></a></li><li class="level-2"><a class="final" href="/algorithm/switch/"><span>Switching to Another Algorithm</span></a></li><li class="level-2"><a class="final" href="/algorithm/multiple/"><span>Combining Multiple Algorithms</span></a></li><li class="level-2"><a class="final" href="/algorithm/custom/"><span>Adding Your Own Algorithms</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>ML Tuning and Evaluation</span></a><ul><li class="level-2"><a class="final" href="/evaluation/"><span>Overview</span></a></li><li class="level-2"><a class="final" href="/evaluation/paramtuning/"><span>Hyperparameter Tuning</span></a></li><li class="level-2"><a class="final" href="/evaluation/evaluationdashboard/"><span>Evaluation Dashboard</span></a></li><li class="level-2"><a class="final" href="/evaluation/metricchoose/"><span>Choosing Evaluation Metrics</span></a></li><li class="level-2"><a class="final" href="/evaluation/m
etricbuild/"><span>Building Evaluation Metrics</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>System Architecture</span></a><ul><li class="level-2"><a class="final" href="/system/"><span>Architecture Overview</span></a></li><li class="level-2"><a class="final" href="/system/anotherdatastore/"><span>Using Another Data Store</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Engine Template Gallery</span></a><ul><li class="level-2"><a class="final" href="http://templates.prediction.io"><span>Browse</span></a></li><li class="level-2"><a class="final" href="/community/submit-template/"><span>Submit your Engine as a Template</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Demo Tutorials</span></a><ul><li class="level-2"><a class="final" href="/demo/tapster/"><span>Comics Recommendation Demo</span></a></li><li class="level-2"><a class="final" href="/demo/community/"><span>Community Contribu
ted Demo</span></a></li><li class="level-2"><a class="final" href="/demo/textclassification/"><span>Text Classification Engine Tutorial</span></a></li></ul></li><li class="level-1"><a class="expandible" href="/community/"><span>Getting Involved</span></a><ul><li class="level-2"><a class="final" href="/community/contribute-code/"><span>Contribute Code</span></a></li><li class="level-2"><a class="final" href="/community/contribute-documentation/"><span>Contribute Documentation</span></a></li><li class="level-2"><a class="final" href="/community/contribute-sdk/"><span>Contribute a SDK</span></a></li><li class="level-2"><a class="final" href="/community/contribute-webhook/"><span>Contribute a Webhook</span></a></li><li class="level-2"><a class="final" href="/community/projects/"><span>Community Projects</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Getting Help</span></a><ul><li class="level-2"><a class="final" href="/resources/faq/"><span>FAQs</span>
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uid"><div class="row"><div id="left-menu-wrapper" class="col-md-3"><nav id="nav-main"><ul><li class="level-1"><a class="expandible" href="/"><span>Apache PredictionIO (incubating) Documentation</span></a><ul><li class="level-2"><a class="final" href="/"><span>Welcome to Apache PredictionIO (incubating)</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Getting Started</span></a><ul><li class="level-2"><a class="final" href="/start/"><span>A Quick Intro</span></a></li><li class="level-2"><a class="final" href="/install/"><span>Installing Apache PredictionIO (incubating)</span></a></li><li class="level-2"><a class="final" href="/start/download/"><span>Downloading an Engine Template</span></a></li><li class="level-2"><a class="final" href="/start/deploy/"><span>Deploying Your First Engine</span></a></li><li class="level-2"><a class="final" href="/start/customize/"><span>Customizing the Engine</span></a></li></ul></li><li class="level-1"><a class="expandib
le" href="#"><span>Integrating with Your App</span></a><ul><li class="level-2"><a class="final" href="/appintegration/"><span>App Integration Overview</span></a></li><li class="level-2"><a class="expandible" href="/sdk/"><span>List of SDKs</span></a><ul><li class="level-3"><a class="final" href="/sdk/java/"><span>Java & Android SDK</span></a></li><li class="level-3"><a class="final" href="/sdk/php/"><span>PHP SDK</span></a></li><li class="level-3"><a class="final" href="/sdk/python/"><span>Python SDK</span></a></li><li class="level-3"><a class="final" href="/sdk/ruby/"><span>Ruby SDK</span></a></li><li class="level-3"><a class="final" href="/sdk/community/"><span>Community Powered SDKs</span></a></li></ul></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Deploying an Engine</span></a><ul><li class="level-2"><a class="final" href="/deploy/"><span>Deploying as a Web Service</span></a></li><li class="level-2"><a class="final" href="/cli/#engine-commands"><span>Eng
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rview</span></a></li><li class="level-2"><a class="final" href="/cli/#event-server-commands"><span>Event Server Command-line Interface</span></a></li><li class="level-2"><a class="final" href="/datacollection/eventapi/"><span>Collecting Data with REST/SDKs</span></a></li><li class="level-2"><a class="final" href="/datacollection/eventmodel/"><span>Events Modeling</span></a></li><li class="level-2"><a class="final" href="/datacollection/webhooks/"><span>Unifying Multichannel Data with Webhooks</span></a></li><li class="level-2"><a class="final" href="/datacollection/channel/"><span>Channel</span></a></li><li class="level-2"><a class="final" href="/datacollection/batchimport/"><span>Importing Data in Batch</span></a></li><li class="level-2"><a class="final" href="/datacollection/analytics/"><span>Using Analytics Tools</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Choosing an Algorithm(s)</span></a><ul><li class="level-2"><a class="final" href="/algo
rithm/"><span>Built-in Algorithm Libraries</span></a></li><li class="level-2"><a class="final" href="/algorithm/switch/"><span>Switching to Another Algorithm</span></a></li><li class="level-2"><a class="final" href="/algorithm/multiple/"><span>Combining Multiple Algorithms</span></a></li><li class="level-2"><a class="final" href="/algorithm/custom/"><span>Adding Your Own Algorithms</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>ML Tuning and Evaluation</span></a><ul><li class="level-2"><a class="final" href="/evaluation/"><span>Overview</span></a></li><li class="level-2"><a class="final" href="/evaluation/paramtuning/"><span>Hyperparameter Tuning</span></a></li><li class="level-2"><a class="final" href="/evaluation/evaluationdashboard/"><span>Evaluation Dashboard</span></a></li><li class="level-2"><a class="final" href="/evaluation/metricchoose/"><span>Choosing Evaluation Metrics</span></a></li><li class="level-2"><a class="final" href="/evaluation
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uid"><div class="row"><div id="left-menu-wrapper" class="col-md-3"><nav id="nav-main"><ul><li class="level-1"><a class="expandible" href="/"><span>Apache PredictionIO (incubating) Documentation</span></a><ul><li class="level-2"><a class="final" href="/"><span>Welcome to Apache PredictionIO (incubating)</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Getting Started</span></a><ul><li class="level-2"><a class="final" href="/start/"><span>A Quick Intro</span></a></li><li class="level-2"><a class="final" href="/install/"><span>Installing Apache PredictionIO (incubating)</span></a></li><li class="level-2"><a class="final" href="/start/download/"><span>Downloading an Engine Template</span></a></li><li class="level-2"><a class="final" href="/start/deploy/"><span>Deploying Your First Engine</span></a></li><li class="level-2"><a class="final" href="/start/customize/"><span>Customizing the Engine</span></a></li></ul></li><li class="level-1"><a class="expandib
le" href="#"><span>Integrating with Your App</span></a><ul><li class="level-2"><a class="final" href="/appintegration/"><span>App Integration Overview</span></a></li><li class="level-2"><a class="expandible" href="/sdk/"><span>List of SDKs</span></a><ul><li class="level-3"><a class="final" href="/sdk/java/"><span>Java & Android SDK</span></a></li><li class="level-3"><a class="final" href="/sdk/php/"><span>PHP SDK</span></a></li><li class="level-3"><a class="final" href="/sdk/python/"><span>Python SDK</span></a></li><li class="level-3"><a class="final" href="/sdk/ruby/"><span>Ruby SDK</span></a></li><li class="level-3"><a class="final" href="/sdk/community/"><span>Community Powered SDKs</span></a></li></ul></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Deploying an Engine</span></a><ul><li class="level-2"><a class="final" href="/deploy/"><span>Deploying as a Web Service</span></a></li><li class="level-2"><a class="final" href="/cli/#engine-commands"><span>Eng
ine Command-line Interface</span></a></li><li class="level-2"><a class="final" href="/deploy/engineparams/"><span>Setting Engine Parameters</span></a></li><li class="level-2"><a class="final" href="/deploy/enginevariants/"><span>Deploying Multiple Engine Variants</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Customizing an Engine</span></a><ul><li class="level-2"><a class="final" href="/customize/"><span>Learning DASE</span></a></li><li class="level-2"><a class="final" href="/customize/dase/"><span>Implement DASE</span></a></li><li class="level-2"><a class="final" href="/customize/troubleshooting/"><span>Troubleshooting Engine Development</span></a></li><li class="level-2"><a class="final" href="/api/current/#package"><span>Engine Scala APIs</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Collecting and Analyzing Data</span></a><ul><li class="level-2"><a class="final" href="/datacollection/"><span>Event Server Ove
rview</span></a></li><li class="level-2"><a class="final" href="/cli/#event-server-commands"><span>Event Server Command-line Interface</span></a></li><li class="level-2"><a class="final" href="/datacollection/eventapi/"><span>Collecting Data with REST/SDKs</span></a></li><li class="level-2"><a class="final" href="/datacollection/eventmodel/"><span>Events Modeling</span></a></li><li class="level-2"><a class="final" href="/datacollection/webhooks/"><span>Unifying Multichannel Data with Webhooks</span></a></li><li class="level-2"><a class="final" href="/datacollection/channel/"><span>Channel</span></a></li><li class="level-2"><a class="final" href="/datacollection/batchimport/"><span>Importing Data in Batch</span></a></li><li class="level-2"><a class="final" href="/datacollection/analytics/"><span>Using Analytics Tools</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Choosing an Algorithm(s)</span></a><ul><li class="level-2"><a class="final" href="/algo
rithm/"><span>Built-in Algorithm Libraries</span></a></li><li class="level-2"><a class="final" href="/algorithm/switch/"><span>Switching to Another Algorithm</span></a></li><li class="level-2"><a class="final" href="/algorithm/multiple/"><span>Combining Multiple Algorithms</span></a></li><li class="level-2"><a class="final" href="/algorithm/custom/"><span>Adding Your Own Algorithms</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>ML Tuning and Evaluation</span></a><ul><li class="level-2"><a class="final" href="/evaluation/"><span>Overview</span></a></li><li class="level-2"><a class="final" href="/evaluation/paramtuning/"><span>Hyperparameter Tuning</span></a></li><li class="level-2"><a class="final" href="/evaluation/evaluationdashboard/"><span>Evaluation Dashboard</span></a></li><li class="level-2"><a class="final" href="/evaluation/metricchoose/"><span>Choosing Evaluation Metrics</span></a></li><li class="level-2"><a class="final" href="/evaluation
/metricbuild/"><span>Building Evaluation Metrics</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>System Architecture</span></a><ul><li class="level-2"><a class="final" href="/system/"><span>Architecture Overview</span></a></li><li class="level-2"><a class="final" href="/system/anotherdatastore/"><span>Using Another Data Store</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Engine Template Gallery</span></a><ul><li class="level-2"><a class="final" href="http://templates.prediction.io"><span>Browse</span></a></li><li class="level-2"><a class="final" href="/community/submit-template/"><span>Submit your Engine as a Template</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Demo Tutorials</span></a><ul><li class="level-2"><a class="final" href="/demo/tapster/"><span>Comics Recommendation Demo</span></a></li><li class="level-2"><a class="final" href="/demo/community/"><span>Community Contri
buted Demo</span></a></li><li class="level-2"><a class="final" href="/demo/textclassification/"><span>Text Classification Engine Tutorial</span></a></li></ul></li><li class="level-1"><a class="expandible" href="/community/"><span>Getting Involved</span></a><ul><li class="level-2"><a class="final" href="/community/contribute-code/"><span>Contribute Code</span></a></li><li class="level-2"><a class="final" href="/community/contribute-documentation/"><span>Contribute Documentation</span></a></li><li class="level-2"><a class="final" href="/community/contribute-sdk/"><span>Contribute a SDK</span></a></li><li class="level-2"><a class="final" href="/community/contribute-webhook/"><span>Contribute a Webhook</span></a></li><li class="level-2"><a class="final" href="/community/projects/"><span>Community Projects</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Getting Help</span></a><ul><li class="level-2"><a class="final" href="/resources/faq/"><span>FAQs</spa
n></a></li><li class="level-2"><a class="final" href="/support/"><span>Community Support</span></a></li><li class="level-2"><a class="final" href="/support/#enterprise-support"><span>Enterprise Support</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Resources</span></a><ul><li class="level-2"><a class="final" href="/resources/intellij/"><span>Developing Engines with IntelliJ IDEA</span></a></li><li class="level-2"><a class="final" href="/resources/upgrade/"><span>Upgrade Instructions</span></a></li><li class="level-2"><a class="final" href="/resources/glossary/"><span>Glossary</span></a></li></ul></li></ul></nav></div><div class="col-md-9 col-sm-12"><div class="content-header hidden-md hidden-lg"><div id="page-title"><h1>Level 3.2</h1></div></div><div id="table-of-content-wrapper"><h5>On this page</h5><aside id="table-of-contents"><ul> <li> <a href="#level-3-2">Level 3.2</a> </li> </ul> </aside><hr/><a id="edit-page-link" href="https://github.com/ap
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<div class="row"><div class="col-md-9 col-sm-11 col-xs-11"><div class="hidden-md hidden-lg" id="mobile-page-heading-wrapper"><p>PredictionIO Docs</p><h4>Contribute a SDK</h4></div><h4 class="hidden-sm hidden-xs">PredictionIO Docs</h4></div><div class="col-md-3 col-sm-1 col-xs-1 hidden-md hidden-lg"><img id="left-menu-indicator" src="/images/icons/down-arrow-dfe9f7fe.png"/></div><div class="col-md-3 col-sm-12 col-xs-12 swiftype-wrapper"><div class="swiftype"><form class="search-form"><img class="search-box-toggler hidden-xs hidden-sm" src="/images/icons/search-glass-704bd4ff.png"/><div class="search-box"><img src="/images/icons/search-glass-704bd4ff.png"/><input type="text" id="st-search-input" class="st-search-input" placeholder="Search Doc..."/></div><img class="swiftype-row-hider hidden-md hidden-lg" src="/images/icons/drawer-toggle-active-fcbef12a.png"/></form></div></div><div class="mobile-left-menu-toggler hidden-md hidden-lg"></div></div></div></div><div id="page" class="conta
iner-fluid"><div class="row"><div id="left-menu-wrapper" class="col-md-3"><nav id="nav-main"><ul><li class="level-1"><a class="expandible" href="/"><span>Apache PredictionIO (incubating) Documentation</span></a><ul><li class="level-2"><a class="final" href="/"><span>Welcome to Apache PredictionIO (incubating)</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Getting Started</span></a><ul><li class="level-2"><a class="final" href="/start/"><span>A Quick Intro</span></a></li><li class="level-2"><a class="final" href="/install/"><span>Installing Apache PredictionIO (incubating)</span></a></li><li class="level-2"><a class="final" href="/start/download/"><span>Downloading an Engine Template</span></a></li><li class="level-2"><a class="final" href="/start/deploy/"><span>Deploying Your First Engine</span></a></li><li class="level-2"><a class="final" href="/start/customize/"><span>Customizing the Engine</span></a></li></ul></li><li class="level-1"><a class="e
xpandible" href="#"><span>Integrating with Your App</span></a><ul><li class="level-2"><a class="final" href="/appintegration/"><span>App Integration Overview</span></a></li><li class="level-2"><a class="expandible" href="/sdk/"><span>List of SDKs</span></a><ul><li class="level-3"><a class="final" href="/sdk/java/"><span>Java & Android SDK</span></a></li><li class="level-3"><a class="final" href="/sdk/php/"><span>PHP SDK</span></a></li><li class="level-3"><a class="final" href="/sdk/python/"><span>Python SDK</span></a></li><li class="level-3"><a class="final" href="/sdk/ruby/"><span>Ruby SDK</span></a></li><li class="level-3"><a class="final" href="/sdk/community/"><span>Community Powered SDKs</span></a></li></ul></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Deploying an Engine</span></a><ul><li class="level-2"><a class="final" href="/deploy/"><span>Deploying as a Web Service</span></a></li><li class="level-2"><a class="final" href="/cli/#engine-commands"><s
pan>Engine Command-line Interface</span></a></li><li class="level-2"><a class="final" href="/deploy/engineparams/"><span>Setting Engine Parameters</span></a></li><li class="level-2"><a class="final" href="/deploy/enginevariants/"><span>Deploying Multiple Engine Variants</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Customizing an Engine</span></a><ul><li class="level-2"><a class="final" href="/customize/"><span>Learning DASE</span></a></li><li class="level-2"><a class="final" href="/customize/dase/"><span>Implement DASE</span></a></li><li class="level-2"><a class="final" href="/customize/troubleshooting/"><span>Troubleshooting Engine Development</span></a></li><li class="level-2"><a class="final" href="/api/current/#package"><span>Engine Scala APIs</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Collecting and Analyzing Data</span></a><ul><li class="level-2"><a class="final" href="/datacollection/"><span>Event Ser
ver Overview</span></a></li><li class="level-2"><a class="final" href="/cli/#event-server-commands"><span>Event Server Command-line Interface</span></a></li><li class="level-2"><a class="final" href="/datacollection/eventapi/"><span>Collecting Data with REST/SDKs</span></a></li><li class="level-2"><a class="final" href="/datacollection/eventmodel/"><span>Events Modeling</span></a></li><li class="level-2"><a class="final" href="/datacollection/webhooks/"><span>Unifying Multichannel Data with Webhooks</span></a></li><li class="level-2"><a class="final" href="/datacollection/channel/"><span>Channel</span></a></li><li class="level-2"><a class="final" href="/datacollection/batchimport/"><span>Importing Data in Batch</span></a></li><li class="level-2"><a class="final" href="/datacollection/analytics/"><span>Using Analytics Tools</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Choosing an Algorithm(s)</span></a><ul><li class="level-2"><a class="final" href
="/algorithm/"><span>Built-in Algorithm Libraries</span></a></li><li class="level-2"><a class="final" href="/algorithm/switch/"><span>Switching to Another Algorithm</span></a></li><li class="level-2"><a class="final" href="/algorithm/multiple/"><span>Combining Multiple Algorithms</span></a></li><li class="level-2"><a class="final" href="/algorithm/custom/"><span>Adding Your Own Algorithms</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>ML Tuning and Evaluation</span></a><ul><li class="level-2"><a class="final" href="/evaluation/"><span>Overview</span></a></li><li class="level-2"><a class="final" href="/evaluation/paramtuning/"><span>Hyperparameter Tuning</span></a></li><li class="level-2"><a class="final" href="/evaluation/evaluationdashboard/"><span>Evaluation Dashboard</span></a></li><li class="level-2"><a class="final" href="/evaluation/metricchoose/"><span>Choosing Evaluation Metrics</span></a></li><li class="level-2"><a class="final" href="/eva
luation/metricbuild/"><span>Building Evaluation Metrics</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>System Architecture</span></a><ul><li class="level-2"><a class="final" href="/system/"><span>Architecture Overview</span></a></li><li class="level-2"><a class="final" href="/system/anotherdatastore/"><span>Using Another Data Store</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Engine Template Gallery</span></a><ul><li class="level-2"><a class="final" href="http://templates.prediction.io"><span>Browse</span></a></li><li class="level-2"><a class="final" href="/community/submit-template/"><span>Submit your Engine as a Template</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Demo Tutorials</span></a><ul><li class="level-2"><a class="final" href="/demo/tapster/"><span>Comics Recommendation Demo</span></a></li><li class="level-2"><a class="final" href="/demo/community/"><span>Community
Contributed Demo</span></a></li><li class="level-2"><a class="final" href="/demo/textclassification/"><span>Text Classification Engine Tutorial</span></a></li></ul></li><li class="level-1"><a class="expandible" href="/community/"><span>Getting Involved</span></a><ul><li class="level-2"><a class="final" href="/community/contribute-code/"><span>Contribute Code</span></a></li><li class="level-2"><a class="final" href="/community/contribute-documentation/"><span>Contribute Documentation</span></a></li><li class="level-2"><a class="final active" href="/community/contribute-sdk/"><span>Contribute a SDK</span></a></li><li class="level-2"><a class="final" href="/community/contribute-webhook/"><span>Contribute a Webhook</span></a></li><li class="level-2"><a class="final" href="/community/projects/"><span>Community Projects</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Getting Help</span></a><ul><li class="level-2"><a class="final" href="/resources/faq/"><
span>FAQs</span></a></li><li class="level-2"><a class="final" href="/support/"><span>Community Support</span></a></li><li class="level-2"><a class="final" href="/support/#enterprise-support"><span>Enterprise Support</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Resources</span></a><ul><li class="level-2"><a class="final" href="/resources/intellij/"><span>Developing Engines with IntelliJ IDEA</span></a></li><li class="level-2"><a class="final" href="/resources/upgrade/"><span>Upgrade Instructions</span></a></li><li class="level-2"><a class="final" href="/resources/glossary/"><span>Glossary</span></a></li></ul></li></ul></nav></div><div class="col-md-9 col-sm-12"><div class="content-header hidden-md hidden-lg"><div id="breadcrumbs" class="hidden-sm hidden xs"><ul><li><a href="/community/">Getting Involved</a><span class="spacer">></span></li><li><span class="last">Contribute a SDK</span></li></ul></div><div id="page-title"><h1>Contribute a SDK</h
1></div></div><div id="table-of-content-wrapper"><h5>On this page</h5><aside id="table-of-contents"><ul> <li> <a href="#event-client">Event Client</a> </li> <li> <a href="#engine-client">Engine Client</a> </li> <li> <a href="#testing-your-sdk">Testing Your SDK</a> </li> </ul> </aside><hr/><a id="edit-page-link" href="https://github.com/apache/incubator-predictionio/tree/livedoc/docs/manual/source/community/contribute-sdk.html.md"><img src="/images/icons/edit-pencil-d6c1bb3d.png"/>Edit this page</a></div><div class="content-header hidden-sm hidden-xs"><div id="breadcrumbs" class="hidden-sm hidden xs"><ul><li><a href="/community/">Getting Involved</a><span class="spacer">></span></li><li><span class="last">Contribute a SDK</span></li></ul></div><div id="page-title"><h1>Contribute a SDK</h1></div></div><div class="content"><p>A SDK should provide convenient methods for client applications to easily record users' behaviors in Apache PredictionIO (incubating)'s Event Server an
d also query recommendations from the ML Engines. Therefore, a SDK typically has 2 corresponding clients: <code>Event Client</code> and <code>Engine Client</code>.</p><p>The following guideline bases on the REST API provided by Apache PredictionIO (incubating)'s Event Client which details can be found <a href="http://docs.prediction.io/datacollection/eventapi/">here</a>.</p><h2 id='event-client' class='header-anchors'>Event Client</h2><p>Because the Event Server has only 1 connection point, the <code>Event Client</code> needs to implement this core request first. The core request has the following rules.</p> <ul> <li><p><strong>URL</strong>: <code><base URL>/events.json?accessKey=<your access key></code> (e.g. <a href="http://localhost:7070/events.json?accessKey=1234567890">http://localhost:7070/events.json?accessKey=1234567890</a>)</p></li> <li><p><strong>Request</strong>: <code>POST</code> + JSON data. Please refer to the <a href="http://docs.prediction.io/datacoll
ection/eventapi/">Event Creation API</a> for the details on the fields of the JSON data object.</p></li> <li><p><strong>Response</strong>:</p> <ul> <li><strong>Success</strong>: status code <code>201</code> with a JSON result containing the <code>eventId</code>.</li> <li><strong>Failure</strong>: a JSON result containing a <code>message</code> field describing the error. <ul> <li>Status code <code>401</code>: invalid access key.</li> <li>Status code <code>400</code>: fail to parse the JSON request e.g. missing required fields like <code>event</code>, or invalid <code>eventTime</code> format.</li> </ul></li> </ul></li> </ul> <p>Other convenient methods are just shortcut. They could simply build the event's parameters and call the core request. <code>Event Client</code> should support the following 7 shorthand operations:</p> <ul> <li><p><strong>User entities</strong></p> <ul> <li><p><strong>Sets properties of a user</strong>: with the JSON object</p><div class="highlight json"><t
able style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1
+2
+3
+4
+5
+6</pre></td><td class="code"><pre><span class="p">{</span><span class="w">
+ </span><span class="s2">"event"</span><span class="p">:</span><span class="w"> </span><span class="s2">"$set"</span><span class="p">,</span><span class="w">
+ </span><span class="s2">"entityType"</span><span class="p">:</span><span class="w"> </span><span class="s2">"user"</span><span class="p">,</span><span class="w">
+ </span><span class="s2">"entityId"</span><span class="p">:</span><span class="w"> </span><span class="err"><user_ID></span><span class="p">,</span><span class="w">
+ </span><span class="s2">"properties"</span><span class="p">:</span><span class="w"> </span><span class="err"><properties></span><span class="w">
+</span><span class="p">}</span><span class="w">
+</span></pre></td></tr></tbody></table> </div></li> <li><p><strong>Unsets some properties of a user</strong>: with the JSON object</p><div class="highlight json"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1
+2
+3
+4
+5
+6</pre></td><td class="code"><pre><span class="p">{</span><span class="w">
+ </span><span class="s2">"event"</span><span class="p">:</span><span class="w"> </span><span class="s2">"$unset"</span><span class="p">,</span><span class="w">
+ </span><span class="s2">"entityType"</span><span class="p">:</span><span class="w"> </span><span class="s2">"user"</span><span class="p">,</span><span class="w">
+ </span><span class="s2">"entityId"</span><span class="p">:</span><span class="w"> </span><span class="err"><user_ID></span><span class="p">,</span><span class="w">
+ </span><span class="s2">"properties"</span><span class="p">:</span><span class="w"> </span><span class="err"><properties></span><span class="w">
+</span><span class="p">}</span><span class="w">
+</span></pre></td></tr></tbody></table> </div></li> <li><p><strong>Delete a user</strong>: with the JSON object</p><div class="highlight json"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1
+2
+3
+4
+5</pre></td><td class="code"><pre><span class="p">{</span><span class="w">
+ </span><span class="s2">"event"</span><span class="p">:</span><span class="w"> </span><span class="s2">"$delete"</span><span class="p">,</span><span class="w">
+ </span><span class="s2">"entityType"</span><span class="p">:</span><span class="w"> </span><span class="s2">"user"</span><span class="p">,</span><span class="w">
+ </span><span class="s2">"entityId"</span><span class="p">:</span><span class="w"> </span><span class="err"><user_ID></span><span class="w">
+</span><span class="p">}</span><span class="w">
+</span></pre></td></tr></tbody></table> </div></li> </ul></li> <li><p><strong>Item entities</strong></p> <ul> <li><p><strong>Sets properties of an item</strong>: with the JSON object</p><div class="highlight json"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1
+2
+3
+4
+5
+6</pre></td><td class="code"><pre><span class="p">{</span><span class="w">
+ </span><span class="s2">"event"</span><span class="p">:</span><span class="w"> </span><span class="s2">"$set"</span><span class="p">,</span><span class="w">
+ </span><span class="s2">"entityType"</span><span class="p">:</span><span class="w"> </span><span class="s2">"item"</span><span class="p">,</span><span class="w">
+ </span><span class="s2">"entityId"</span><span class="p">:</span><span class="w"> </span><span class="err"><item_ID></span><span class="p">,</span><span class="w">
+ </span><span class="s2">"properties"</span><span class="p">:</span><span class="w"> </span><span class="err"><properties></span><span class="w">
+</span><span class="p">}</span><span class="w">
+</span></pre></td></tr></tbody></table> </div></li> <li><p><strong>Unsets some properties of an item</strong>: with the JSON object</p><div class="highlight json"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1
+2
+3
+4
+5
+6</pre></td><td class="code"><pre><span class="p">{</span><span class="w">
+ </span><span class="s2">"event"</span><span class="p">:</span><span class="w"> </span><span class="s2">"$unset"</span><span class="p">,</span><span class="w">
+ </span><span class="s2">"entityType"</span><span class="p">:</span><span class="w"> </span><span class="s2">"item"</span><span class="p">,</span><span class="w">
+ </span><span class="s2">"entityId"</span><span class="p">:</span><span class="w"> </span><span class="err"><item_ID></span><span class="p">,</span><span class="w">
+ </span><span class="s2">"properties"</span><span class="p">:</span><span class="w"> </span><span class="err"><properties></span><span class="w">
+</span><span class="p">}</span><span class="w">
+</span></pre></td></tr></tbody></table> </div></li> <li><p><strong>Delete an item</strong>: with the JSON object</p><div class="highlight json"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1
+2
+3
+4
+5</pre></td><td class="code"><pre><span class="p">{</span><span class="w">
+ </span><span class="s2">"event"</span><span class="p">:</span><span class="w"> </span><span class="s2">"$delete"</span><span class="p">,</span><span class="w">
+ </span><span class="s2">"entityType"</span><span class="p">:</span><span class="w"> </span><span class="s2">"item"</span><span class="p">,</span><span class="w">
+ </span><span class="s2">"entityId"</span><span class="p">:</span><span class="w"> </span><span class="err"><item_ID></span><span class="w">
+</span><span class="p">}</span><span class="w">
+</span></pre></td></tr></tbody></table> </div></li> </ul></li> <li><p><strong>Others</strong></p> <ul> <li><p><strong>Record a user's action on some item</strong>: with the JSON object</p><div class="highlight json"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1
+2
+3
+4
+5
+6
+7
+8</pre></td><td class="code"><pre><span class="p">{</span><span class="w">
+ </span><span class="s2">"event"</span><span class="p">:</span><span class="w"> </span><span class="err"><event_name></span><span class="p">,</span><span class="w">
+ </span><span class="s2">"entityType"</span><span class="p">:</span><span class="w"> </span><span class="s2">"user"</span><span class="p">,</span><span class="w">
+ </span><span class="s2">"entityId"</span><span class="p">:</span><span class="w"> </span><span class="err"><user_ID></span><span class="p">,</span><span class="w">
+ </span><span class="s2">"targetEntityType"</span><span class="p">:</span><span class="w"> </span><span class="s2">"item"</span><span class="p">,</span><span class="w">
+ </span><span class="s2">"targetEntityId"</span><span class="p">:</span><span class="w"> </span><span class="err"><item_ID></span><span class="p">,</span><span class="w">
+ </span><span class="s2">"properties"</span><span class="p">:</span><span class="w"> </span><span class="err"><properties></span><span class="w">
+</span><span class="p">}</span><span class="w">
+</span></pre></td></tr></tbody></table> </div></li> </ul></li> </ul> <p>Again, please refer to the <a href="http://docs.prediction.io/datacollection/eventapi/">API documentation</a> for explanations on the reversed events like <code>$set</code>, <code>$unset</code> or <code>$delete</code>.</p><div class="alert-message info"><p>The <code>eventTime</code> is optional but it is recommended that the client application should include time in the request. Therefore, it is best that the <code>Event Client</code> includes the time field if missing, before sending the event to the server.</p></div><h2 id='engine-client' class='header-anchors'>Engine Client</h2><p><code>Engine Client</code>'s main job is to retrieve recommendation or prediction results from Apache PredictionIO (incubating)'s Engines. It has only a few rules on the request and response type.</p> <ul> <li><p><strong>URL</strong>: <code><base URL>/queries.json</code> (e.g. <a href="http://localhost:8000/queries.jso
n">http://localhost:8000/queries.json</a>)</p></li> <li><p><strong>Request</strong>: <code>POST</code> + JSON data. For example,</p><div class="highlight json"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1
+2
+3
+4</pre></td><td class="code"><pre><span class="p">{</span><span class="w">
+ </span><span class="s2">"user"</span><span class="p">:</span><span class="w"> </span><span class="mi">1</span><span class="p">,</span><span class="w">
+ </span><span class="s2">"num"</span><span class="p">:</span><span class="w"> </span><span class="mi">4</span><span class="w">
+</span><span class="p">}</span><span class="w">
+</span></pre></td></tr></tbody></table> </div></li> <li><p><strong>Response</strong>:</p> <ul> <li><p><strong>Success</strong>: status code <code>200</code> with a JSON result object. For example,</p><div class="highlight json"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1
+2
+3
+4
+5
+6
+7
+8
+9
+10
+11
+12
+13</pre></td><td class="code"><pre><span class="p">{</span><span class="w">
+ </span><span class="s2">"itemScores"</span><span class="p">:</span><span class="w"> </span><span class="p">[</span><span class="w">
+ </span><span class="p">{</span><span class="w">
+ </span><span class="s2">"item"</span><span class="p">:</span><span class="w"> </span><span class="mi">39</span><span class="p">,</span><span class="w">
+ </span><span class="s2">"score"</span><span class="p">:</span><span class="w"> </span><span class="s2">"6.177719297832409"</span><span class="w">
+ </span><span class="p">},</span><span class="w">
+ </span><span class="p">{</span><span class="w">
+ </span><span class="s2">"item"</span><span class="p">:</span><span class="w"> </span><span class="mi">79</span><span class="p">,</span><span class="w">
+ </span><span class="s2">"score"</span><span class="p">:</span><span class="w"> </span><span class="s2">"5.931687319083594"</span><span class="w">
+ </span><span class="p">},</span><span class="w">
+ </span><span class="err">...</span><span class="w">
+ </span><span class="p">]</span><span class="w">
+</span><span class="p">}</span><span class="w">
+</span></pre></td></tr></tbody></table> </div></li> <li><p><strong>Failure</strong>: status code <code>400</code> e.g. fail to parse the query.</p></li> </ul></li> </ul> <p>The formats of JSON objects in both the request and response must be defined by the Apache PredictionIO (incubating)'s Engine and are different across applications. The above examples are taken from the Recommendation Engine template in which the query and prediction results are defined as following.</p><div class="highlight scala"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1
+2
+3
+4
+5
+6
+7
+8</pre></td><td class="code"><pre><span class="k">case</span> <span class="k">class</span> <span class="nc">Query</span><span class="o">(</span>
+ <span class="n">user</span><span class="k">:</span> <span class="kt">String</span><span class="o">,</span>
+ <span class="n">num</span><span class="k">:</span> <span class="kt">Int</span>
+<span class="o">)</span> <span class="k">extends</span> <span class="nc">Serializable</span>
+
+<span class="k">case</span> <span class="k">class</span> <span class="nc">PredictedResult</span><span class="o">(</span>
+ <span class="n">itemScores</span><span class="k">:</span> <span class="kt">Array</span><span class="o">[</span><span class="kt">ItemScore</span><span class="o">]</span>
+<span class="o">)</span> <span class="k">extends</span> <span class="nc">Serializable</span>
+</pre></td></tr></tbody></table> </div> <h2 id='testing-your-sdk' class='header-anchors'>Testing Your SDK</h2><p>You can set up a local host Apache PredictionIO (incubating) environment to test your SDK. However, it is hard to set it up online to test your SDK automatically using services like Travis CI. In that case, you should consider using these lightweight <a href="https://github.com/minhtule/PredictionIO-Mock-Server">mock servers</a>. Please see the instructions in the repo how to use it. It takes less than 5 minutes!</p><p>That's it! We are looking forward to see your SDK!</p></div></div></div></div><footer><div class="container"><div class="seperator"></div><div class="row"><div class="col-md-4 col-md-push-8 col-xs-12"><div class="subscription-form-wrapper"><h4>Subscribe to our Newsletter</h4><form class="ajax-form" id="subscribe-form" method="POST" action="https://script.google.com/macros/s/AKfycbwhzeKCQJjQ52eVAqNT_vcklH07OITUO7wzOMDXvK6EGAWgaZgF/exec"><input class="req
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Server Overview</span></a></li><li class="level-2"><a class="final" href="/cli/#event-server-commands"><span>Event Server Command-line Interface</span></a></li><li class="level-2"><a class="final" href="/datacollection/eventapi/"><span>Collecting Data with REST/SDKs</span></a></li><li class="level-2"><a class="final" href="/datacollection/eventmodel/"><span>Events Modeling</span></a></li><li class="level-2"><a class="final" href="/datacollection/webhooks/"><span>Unifying Multichannel Data with Webhooks</span></a></li><li class="level-2"><a class="final" href="/datacollection/channel/"><span>Channel</span></a></li><li class="level-2"><a class="final" href="/datacollection/batchimport/"><span>Importing Data in Batch</span></a></li><li class="level-2"><a class="final" href="/datacollection/analytics/"><span>Using Analytics Tools</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Choosing an Algorithm(s)</span></a><ul><li class="level-2"><a class="final"
href="/algorithm/"><span>Built-in Algorithm Libraries</span></a></li><li class="level-2"><a class="final" href="/algorithm/switch/"><span>Switching to Another Algorithm</span></a></li><li class="level-2"><a class="final" href="/algorithm/multiple/"><span>Combining Multiple Algorithms</span></a></li><li class="level-2"><a class="final" href="/algorithm/custom/"><span>Adding Your Own Algorithms</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>ML Tuning and Evaluation</span></a><ul><li class="level-2"><a class="final" href="/evaluation/"><span>Overview</span></a></li><li class="level-2"><a class="final" href="/evaluation/paramtuning/"><span>Hyperparameter Tuning</span></a></li><li class="level-2"><a class="final" href="/evaluation/evaluationdashboard/"><span>Evaluation Dashboard</span></a></li><li class="level-2"><a class="final" href="/evaluation/metricchoose/"><span>Choosing Evaluation Metrics</span></a></li><li class="level-2"><a class="final" href="
/evaluation/metricbuild/"><span>Building Evaluation Metrics</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>System Architecture</span></a><ul><li class="level-2"><a class="final" href="/system/"><span>Architecture Overview</span></a></li><li class="level-2"><a class="final" href="/system/anotherdatastore/"><span>Using Another Data Store</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Engine Template Gallery</span></a><ul><li class="level-2"><a class="final" href="http://templates.prediction.io"><span>Browse</span></a></li><li class="level-2"><a class="final" href="/community/submit-template/"><span>Submit your Engine as a Template</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Demo Tutorials</span></a><ul><li class="level-2"><a class="final" href="/demo/tapster/"><span>Comics Recommendation Demo</span></a></li><li class="level-2"><a class="final" href="/demo/community/"><span>Commu
nity Contributed Demo</span></a></li><li class="level-2"><a class="final" href="/demo/textclassification/"><span>Text Classification Engine Tutorial</span></a></li></ul></li><li class="level-1"><a class="expandible" href="/community/"><span>Getting Involved</span></a><ul><li class="level-2"><a class="final" href="/community/contribute-code/"><span>Contribute Code</span></a></li><li class="level-2"><a class="final" href="/community/contribute-documentation/"><span>Contribute Documentation</span></a></li><li class="level-2"><a class="final" href="/community/contribute-sdk/"><span>Contribute a SDK</span></a></li><li class="level-2"><a class="final active" href="/community/contribute-webhook/"><span>Contribute a Webhook</span></a></li><li class="level-2"><a class="final" href="/community/projects/"><span>Community Projects</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Getting Help</span></a><ul><li class="level-2"><a class="final" href="/resources/faq
/"><span>FAQs</span></a></li><li class="level-2"><a class="final" href="/support/"><span>Community Support</span></a></li><li class="level-2"><a class="final" href="/support/#enterprise-support"><span>Enterprise Support</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Resources</span></a><ul><li class="level-2"><a class="final" href="/resources/intellij/"><span>Developing Engines with IntelliJ IDEA</span></a></li><li class="level-2"><a class="final" href="/resources/upgrade/"><span>Upgrade Instructions</span></a></li><li class="level-2"><a class="final" href="/resources/glossary/"><span>Glossary</span></a></li></ul></li></ul></nav></div><div class="col-md-9 col-sm-12"><div class="content-header hidden-md hidden-lg"><div id="breadcrumbs" class="hidden-sm hidden xs"><ul><li><a href="/community/">Getting Involved</a><span class="spacer">></span></li><li><span class="last">Contribute a Webhook</span></li></ul></div><div id="page-title"><h1>Contribute
a Webhooks Connector</h1></div></div><div id="table-of-content-wrapper"><h5>On this page</h5><aside id="table-of-contents"><ul> <li> <a href="#example">Example</a> <ul> <li> <a href="#1-implement-webhooks-connector">1. Implement Webhooks Connector</a> </li> <li> <a href="#2-integrate-the-connector-into-event-server">2. Integrate the Connector into Event Server</a> </li> </ul> </li> </ul> </aside><hr/><a id="edit-page-link" href="https://github.com/apache/incubator-predictionio/tree/livedoc/docs/manual/source/community/contribute-webhook.html.md"><img src="/images/icons/edit-pencil-d6c1bb3d.png"/>Edit this page</a></div><div class="content-header hidden-sm hidden-xs"><div id="breadcrumbs" class="hidden-sm hidden xs"><ul><li><a href="/community/">Getting Involved</a><span class="spacer">></span></li><li><span class="last">Contribute a Webhook</span></li></ul></div><div id="page-title"><h1>Contribute a Webhooks Connector</h1></div></div><div class="content"><div class="alert-message
note"><p>Please check out the <a href="https://github.com/apache/incubator-predictionio">latest develop branch</a>.</p></div><p>Event server can collect data from other third-party sites or software through their webhooks services (for example, SegmentIO, MailChimp). To support that, a <em>Webhooks Connector</em> for the third-party data is needed to be integrated into Event Server. The job of the <em>Webhooks Connector</em> is as simply as converting the third-party data into Event JSON. You can find an example below.</p><p>Currently we support two types of connectors: <code>JsonConnector</code> and <code>FormConnector</code>, which is responsible for accepting <em>JSON</em> data and <em>Form-submission</em> data, respectively.</p><p><strong>JsonConnector</strong>:</p><div class="highlight scala"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1
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+
+<span class="cm">/** Connector for Webhooks connection */</span>
+<span class="k">private</span><span class="o">[</span><span class="kt">prediction</span><span class="o">]</span> <span class="k">trait</span> <span class="nc">JsonConnector</span> <span class="o">{</span>
+
+ <span class="cm">/** Convert from original JObject to Event JObject
+ * @param data original JObject recevived through webhooks
+ * @return Event JObject
+ */</span>
+ <span class="k">def</span> <span class="n">toEventJson</span><span class="o">(</span><span class="n">data</span><span class="k">:</span> <span class="kt">JObject</span><span class="o">)</span><span class="k">:</span> <span class="kt">JObject</span>
+
+<span class="o">}</span>
+
+</pre></td></tr></tbody></table> </div> <p>The EventServer URL path to collect webhooks JSON data:</p><div class="highlight shell"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1</pre></td><td class="code"><pre>http://<EVENT SERVER URL>/webhooks/<CONNECTOR_NAME>.json?accessKey<span class="o">=</span><YOUR_ACCESS_KEY>&channel<span class="o">=</span><CHANNEL_NAME>
+</pre></td></tr></tbody></table> </div> <p>Note that you may collect Webhooks data into default channel (without the <code>channel</code> parameter in the URL) but it's highly recommended to create dedicated <a href="/datacollection/channel/">Channel</a> to collect specific Webhooks data (e.g. create one channel "segmentio" for SegmentIO and another channel "mailchimp" for Mailchimp data) because it allows you to manage and query data more easily, and the Webhooks data won't be mixed with your other normal app data.</p><p><strong>FormConnector</strong>:</p><div class="highlight scala"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1
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+
+<span class="cm">/** Connector for Webhooks connection with Form submission data format
+ */</span>
+<span class="k">private</span><span class="o">[</span><span class="kt">prediction</span><span class="o">]</span> <span class="k">trait</span> <span class="nc">FormConnector</span> <span class="o">{</span>
+
+ <span class="cm">/** Convert from original Form submission data to Event JObject
+ * @param data Map of key-value pairs in String type received through webhooks
+ * @return Event JObject
+ */</span>
+ <span class="k">def</span> <span class="n">toEventJson</span><span class="o">(</span><span class="n">data</span><span class="k">:</span> <span class="kt">Map</span><span class="o">[</span><span class="kt">String</span>, <span class="kt">String</span><span class="o">])</span><span class="k">:</span> <span class="kt">JObject</span>
+
+<span class="o">}</span>
+
+</pre></td></tr></tbody></table> </div> <p>The EventServer URL path to collect webhooks form-subimssion data (no .json):</p><div class="highlight shell"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1</pre></td><td class="code"><pre>http://<EVENT SERVER URL>/webhooks/<CONNECTOR_NAME>?accessKey<span class="o">=</span><YOUR_ACCESS_KEY>&channel<span class="o">=</span><CHANNEL_NAME>
+</pre></td></tr></tbody></table> </div> <p>Note that you may collect Webhooks data into default channel (without the <code>channel</code> parameter in the URL) but it's highly recommended to create dedicated <a href="/datacollection/channel/">Channel</a> to collect specific Webhooks data (e.g. create one channel "segmentio" for SegmentIO and another channel "mailchimp" for Mailchimp data) because it allows you to manage and query data more easily, and the Webhooks data won't be mixed with your other normal app data.</p><h1 id='example' class='header-anchors'>Example</h1><p>For example, let's say there is a third-party website (say, it is named "ExampleJson") which can send the following JSON data through its webhooks service and we would like to collect it into Event Store.</p><p><strong>UserActionItem</strong>:</p><div class="highlight json"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre cla
ss="lineno">1
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+ </span><span class="s2">"type"</span><span class="p">:</span><span class="w"> </span><span class="s2">"userActionItem"</span><span class="p">,</span><span class="w">
+ </span><span class="s2">"userId"</span><span class="p">:</span><span class="w"> </span><span class="s2">"as34smg4"</span><span class="p">,</span><span class="w">
+ </span><span class="s2">"event"</span><span class="p">:</span><span class="w"> </span><span class="s2">"do_something_on"</span><span class="p">,</span><span class="w">
+ </span><span class="s2">"itemId"</span><span class="p">:</span><span class="w"> </span><span class="s2">"kfjd312bc"</span><span class="p">,</span><span class="w">
+ </span><span class="s2">"context"</span><span class="p">:</span><span class="w"> </span><span class="p">{</span><span class="w">
+ </span><span class="s2">"ip"</span><span class="p">:</span><span class="w"> </span><span class="s2">"1.23.4.56"</span><span class="p">,</span><span class="w">
+ </span><span class="s2">"prop1"</span><span class="p">:</span><span class="w"> </span><span class="mf">2.345</span><span class="p">,</span><span class="w">
+ </span><span class="s2">"prop2"</span><span class="p">:</span><span class="w"> </span><span class="s2">"value1"</span><span class="w">
+ </span><span class="p">},</span><span class="w">
+ </span><span class="s2">"anotherPropertyA"</span><span class="p">:</span><span class="w"> </span><span class="mf">4.567</span><span class="p">,</span><span class="w">
+ </span><span class="s2">"anotherPropertyB"</span><span class="p">:</span><span class="w"> </span><span class="kc">false</span><span class="p">,</span><span class="w">
+ </span><span class="s2">"timestamp"</span><span class="p">:</span><span class="w"> </span><span class="s2">"2015-01-15T04:20:23.567Z"</span><span class="w">
+</span><span class="p">}</span><span class="w">
+</span></pre></td></tr></tbody></table> </div> <h2 id='1.-implement-webhooks-connector' class='header-anchors'>1. Implement Webhooks Connector</h2><p>Because the data sent by this third-party "ExampleJson" site is in JSON format, we implement an object <code>ExampleJsonConnector</code> which extends <code>JsonConnector</code>:</p><div class="highlight scala"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1
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+
+ <span class="k">implicit</span> <span class="k">val</span> <span class="n">json4sFormats</span><span class="k">:</span> <span class="kt">Formats</span> <span class="o">=</span> <span class="nc">DefaultFormats</span>
+
+ <span class="k">override</span> <span class="k">def</span> <span class="n">toEventJson</span><span class="o">(</span><span class="n">data</span><span class="k">:</span> <span class="kt">JObject</span><span class="o">)</span><span class="k">:</span> <span class="kt">JObject</span> <span class="o">=</span> <span class="o">{</span>
+ <span class="k">val</span> <span class="n">common</span> <span class="k">=</span> <span class="k">try</span> <span class="o">{</span>
+ <span class="n">data</span><span class="o">.</span><span class="n">extract</span><span class="o">[</span><span class="kt">Common</span><span class="o">]</span>
+ <span class="o">}</span> <span class="k">catch</span> <span class="o">{</span>
+ <span class="k">case</span> <span class="n">e</span><span class="k">:</span> <span class="kt">Exception</span> <span class="o">=></span> <span class="k">throw</span> <span class="k">new</span> <span class="nc">ConnectorException</span><span class="o">(</span>
+ <span class="n">s</span><span class="s">"Cannot extract Common field from ${data}. ${e.getMessage()}"</span><span class="o">,</span> <span class="n">e</span><span class="o">)</span>
+ <span class="o">}</span>
+
+ <span class="k">val</span> <span class="n">json</span> <span class="k">=</span> <span class="k">try</span> <span class="o">{</span>
+ <span class="n">common</span><span class="o">.</span><span class="n">`type`</span> <span class="k">match</span> <span class="o">{</span>
+ <span class="k">case</span> <span class="s">"userActionItem"</span> <span class="k">=></span>
+ <span class="n">toEventJson</span><span class="o">(</span><span class="n">common</span> <span class="k">=</span> <span class="n">common</span><span class="o">,</span> <span class="n">userActionItem</span> <span class="k">=</span> <span class="n">data</span><span class="o">.</span><span class="n">extract</span><span class="o">[</span><span class="kt">UserActionItem</span><span class="o">])</span>
+ <span class="k">case</span> <span class="n">x</span><span class="k">:</span> <span class="kt">String</span> <span class="o">=></span>
+ <span class="k">throw</span> <span class="k">new</span> <span class="nc">ConnectorException</span><span class="o">(</span>
+ <span class="n">s</span><span class="s">"Cannot convert unknown type '${x}' to Event JSON."</span><span class="o">)</span>
+ <span class="o">}</span>
+ <span class="o">}</span> <span class="k">catch</span> <span class="o">{</span>
+ <span class="k">case</span> <span class="n">e</span><span class="k">:</span> <span class="kt">ConnectorException</span> <span class="o">=></span> <span class="k">throw</span> <span class="n">e</span>
+ <span class="k">case</span> <span class="n">e</span><span class="k">:</span> <span class="kt">Exception</span> <span class="o">=></span> <span class="k">throw</span> <span class="k">new</span> <span class="nc">ConnectorException</span><span class="o">(</span>
+ <span class="n">s</span><span class="s">"Cannot convert ${data} to eventJson. ${e.getMessage()}"</span><span class="o">,</span> <span class="n">e</span><span class="o">)</span>
+ <span class="o">}</span>
+
+ <span class="n">json</span>
+ <span class="o">}</span>
+
+ <span class="c1">// Convert the UserActionItem JSON to Event JSON
+</span> <span class="k">def</span> <span class="n">toEventJson</span><span class="o">(</span><span class="n">common</span><span class="k">:</span> <span class="kt">Common</span><span class="o">,</span> <span class="n">userActionItem</span><span class="k">:</span> <span class="kt">UserActionItem</span><span class="o">)</span><span class="k">:</span> <span class="kt">JObject</span> <span class="o">=</span> <span class="o">{</span>
+ <span class="k">import</span> <span class="nn">org.json4s.JsonDSL._</span>
+
+ <span class="c1">// map to EventAPI JSON
+</span> <span class="k">val</span> <span class="n">json</span> <span class="k">=</span>
+ <span class="o">(</span><span class="s">"event"</span> <span class="o">-></span> <span class="n">userActionItem</span><span class="o">.</span><span class="n">event</span><span class="o">)</span> <span class="o">~</span>
+ <span class="o">(</span><span class="s">"entityType"</span> <span class="o">-></span> <span class="s">"user"</span><span class="o">)</span> <span class="o">~</span>
+ <span class="o">(</span><span class="s">"entityId"</span> <span class="o">-></span> <span class="n">userActionItem</span><span class="o">.</span><span class="n">userId</span><span class="o">)</span> <span class="o">~</span>
+ <span class="o">(</span><span class="s">"targetEntityType"</span> <span class="o">-></span> <span class="s">"item"</span><span class="o">)</span> <span class="o">~</span>
+ <span class="o">(</span><span class="s">"targetEntityId"</span> <span class="o">-></span> <span class="n">userActionItem</span><span class="o">.</span><span class="n">itemId</span><span class="o">)</span> <span class="o">~</span>
+ <span class="o">(</span><span class="s">"eventTime"</span> <span class="o">-></span> <span class="n">userActionItem</span><span class="o">.</span><span class="n">timestamp</span><span class="o">)</span> <span class="o">~</span>
+ <span class="o">(</span><span class="s">"properties"</span> <span class="o">-></span> <span class="o">(</span>
+ <span class="o">(</span><span class="s">"context"</span> <span class="o">-></span> <span class="n">userActionItem</span><span class="o">.</span><span class="n">context</span><span class="o">)</span> <span class="o">~</span>
+ <span class="o">(</span><span class="s">"anotherPropertyA"</span> <span class="o">-></span> <span class="n">userActionItem</span><span class="o">.</span><span class="n">anotherPropertyA</span><span class="o">)</span> <span class="o">~</span>
+ <span class="o">(</span><span class="s">"anotherPropertyB"</span> <span class="o">-></span> <span class="n">userActionItem</span><span class="o">.</span><span class="n">anotherPropertyB</span><span class="o">)</span>
+ <span class="o">))</span>
+ <span class="n">json</span>
+ <span class="o">}</span>
+
+ <span class="c1">// Common required fields
+</span> <span class="k">case</span> <span class="k">class</span> <span class="nc">Common</span><span class="o">(</span>
+ <span class="n">`type`</span><span class="k">:</span> <span class="kt">String</span>
+ <span class="o">)</span>
+
+ <span class="c1">// UserActionItem fields
+</span> <span class="k">case</span> <span class="k">class</span> <span class="nc">UserActionItem</span> <span class="o">(</span>
+ <span class="n">userId</span><span class="k">:</span> <span class="kt">String</span><span class="o">,</span>
+ <span class="n">event</span><span class="k">:</span> <span class="kt">String</span><span class="o">,</span>
+ <span class="n">itemId</span><span class="k">:</span> <span class="kt">String</span><span class="o">,</span>
+ <span class="n">context</span><span class="k">:</span> <span class="kt">JObject</span><span class="o">,</span>
+ <span class="n">anotherPropertyA</span><span class="k">:</span> <span class="kt">Option</span><span class="o">[</span><span class="kt">Double</span><span class="o">],</span>
+ <span class="n">anotherPropertyB</span><span class="k">:</span> <span class="kt">Option</span><span class="o">[</span><span class="kt">Boolean</span><span class="o">],</span>
+ <span class="n">timestamp</span><span class="k">:</span> <span class="kt">String</span>
+ <span class="o">)</span>
+
+<span class="o">}</span>
+</pre></td></tr></tbody></table> </div> <p>You can find the complete example in <a href="https://github.com/apache/incubator-predictionio/blob/develop/data/src/main/scala/io/prediction/data/webhooks/examplejson/ExampleJsonConnector.scala">the GitHub repo</a> and how to write <a href="https://github.com/apache/incubator-predictionio/blob/develop/data/src/test/scala/io/prediction/data/webhooks/examplejson/ExampleJsonConnectorSpec.scala">tests for the connector</a>.</p><p>Please put the connector code in a separate directory for each site. For example, code for segmentio connector should be in</p><div class="highlight shell"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1</pre></td><td class="code"><pre>data/src/main/scala/io/prediction/data/webhooks/segmentio/
+</pre></td></tr></tbody></table> </div> <p>and tests should be in</p><div class="highlight shell"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1</pre></td><td class="code"><pre>data/src/test/scala/io/prediction/data/webhooks/segmentio/
+</pre></td></tr></tbody></table> </div> <p><strong>For form-submission data</strong>, you can find the comple example <a href="https://github.com/apache/incubator-predictionio/blob/develop/data/src/main/scala/io/prediction/data/webhooks/exampleform/ExampleFormConnector.scala">the GitHub repo</a> and how to write <a href="https://github.com/apache/incubator-predictionio/blob/develop/data/src/test/scala/io/prediction/data/webhooks/exampleform/ExampleFormConnectorSpec.scala">tests for the connector</a>.</p><h2 id='2.-integrate-the-connector-into-event-server' class='header-anchors'>2. Integrate the Connector into Event Server</h2><p>Once we have the connector implemented, we can add this to the EventServer so we can collect real-time data.</p><p>Add the connector to <a href="https://github.com/apache/incubator-predictionio/blob/develop/data/src/main/scala/io/prediction/data/api/WebhooksConnectors.scala"><code>WebhooksConnectors</code> object</a>:</p><div class="highlight scala"><table
style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1
+2
+3
+4
+5
+6
+7
+8
+9
+10
+11
+12
+13
+14
+15
+16
+17</pre></td><td class="code"><pre>
+<span class="k">import</span> <span class="nn">io.prediction.data.webhooks.examplejson.ExampleJsonConnector</span> <span class="c1">// ADDED
+</span>
+<span class="k">private</span><span class="o">[</span><span class="kt">prediction</span><span class="o">]</span> <span class="k">object</span> <span class="nc">WebhooksConnectors</span> <span class="o">{</span>
+
+ <span class="c1">// Map of Connector Name to Connector
+</span> <span class="k">val</span> <span class="n">json</span><span class="k">:</span> <span class="kt">Map</span><span class="o">[</span><span class="kt">String</span>, <span class="kt">JsonConnector</span><span class="o">]</span> <span class="k">=</span> <span class="nc">Map</span><span class="o">(</span>
+ <span class="s">"segmentio"</span> <span class="o">-></span> <span class="nc">SegmentIOConnector</span><span class="o">,</span>
+ <span class="s">"examplejson"</span> <span class="o">-></span> <span class="nc">ExampleJsonConnector</span> <span class="c1">// ADDED
+</span> <span class="o">)</span>
+
+ <span class="c1">// Map of Connector Name to Connector
+</span> <span class="k">val</span> <span class="n">form</span><span class="k">:</span> <span class="kt">Map</span><span class="o">[</span><span class="kt">String</span>, <span class="kt">FormConnector</span><span class="o">]</span> <span class="k">=</span> <span class="nc">Map</span><span class="o">(</span>
+ <span class="s">"mailchimp"</span> <span class="o">-></span> <span class="nc">MailChimpConnector</span>
+ <span class="o">)</span>
+
+<span class="o">}</span>
+</pre></td></tr></tbody></table> </div> <p>Note that the name of the connectors (e.g. "examplejson", "segmentio") will be used as the webhooks URL. In this example, the event server URL to collect data from "ExampleJson" would be:</p><div class="highlight shell"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1</pre></td><td class="code"><pre>http://<EVENT SERVER URL>/webhooks/examplejson.json?accessKey<span class="o">=</span><YOUR_ACCESS_KEY>&channel<span class="o">=</span><CHANNEL_NAME>
+</pre></td></tr></tbody></table> </div> <p>For <code>FormConnector</code>, the URL doesn't have <code>.json</code>. For example,</p><div class="highlight shell"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1</pre></td><td class="code"><pre>http://<EVENT SERVER URL>/webhooks/mailchimp?accessKey<span class="o">=</span><YOUR_ACCESS_KEY>&channel<span class="o">=</span><CHANNEL_NAME>
+</pre></td></tr></tbody></table> </div> <p>That's it. Once you re-compile Apache PredictionIO (incubating), you can send the ExampleJson data to the following URL and the data will be stored to the App of the corresponding Access Key.</p></div></div></div></div><footer><div class="container"><div class="seperator"></div><div class="row"><div class="col-md-4 col-md-push-8 col-xs-12"><div class="subscription-form-wrapper"><h4>Subscribe to our Newsletter</h4><form class="ajax-form" id="subscribe-form" method="POST" action="https://script.google.com/macros/s/AKfycbwhzeKCQJjQ52eVAqNT_vcklH07OITUO7wzOMDXvK6EGAWgaZgF/exec"><input class="required underlined-input" type="email" placeholder="Your email address" name="subscription_email" id="subscription_email"/><input class="pill-button" value="SUBSCRIBE" type="submit" data-state-normal="SUBSCRIBE" data-state-sucess="SUBSCRIBED!" data-state-loading="SENDING..." onclick="t($('#subscription_email').val());"/><p class="result"></p></form></d
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+fbq('track', "PageView");</script><script src="//use.typekit.net/mut4mjx.js"></script><script>try{Typekit.load();}catch(e){}</script></head><body><div id="global"><header><div class="container" id="header-wrapper"><div class="row"><div class="col-sm-12"><div id="logo-wrapper"><span id="drawer-toggle"></span><a href="#"></a><a href="http://prediction.io/"><img alt="PredictionIO" id="logo" src="/images/logos/logo-ee2b9bb3.png"/></a></div><div id="menu-wrapper"><div id="header-nav-options-wrapper"><ul><li><a href="/">Install & Doc</a></li> <li><a href="/support">Support</a></li> </ul></div><div id="pill-wrapper"><a class="pill left" href="//templates.prediction.io/">TEMPLATES</a> <a class="pill right" href="//github.com/PredictionIO/PredictionIO/">OPEN SOURCE</a></div></div><img class="mobile-search-bar-toggler hidden-md hidden-lg" src="/images/icons/search-glass-704bd4ff.png"/></div></div></div></header><div id="search-bar-row-wrapper"><div class="container-fluid" id="search-bar-row">
<div class="row"><div class="col-md-9 col-sm-11 col-xs-11"><div class="hidden-md hidden-lg" id="mobile-page-heading-wrapper"><p>PredictionIO Docs</p><h4>Machine Learning With PredictionIO</h4></div><h4 class="hidden-sm hidden-xs">PredictionIO Docs</h4></div><div class="col-md-3 col-sm-1 col-xs-1 hidden-md hidden-lg"><img id="left-menu-indicator" src="/images/icons/down-arrow-dfe9f7fe.png"/></div><div class="col-md-3 col-sm-12 col-xs-12 swiftype-wrapper"><div class="swiftype"><form class="search-form"><img class="search-box-toggler hidden-xs hidden-sm" src="/images/icons/search-glass-704bd4ff.png"/><div class="search-box"><img src="/images/icons/search-glass-704bd4ff.png"/><input type="text" id="st-search-input" class="st-search-input" placeholder="Search Doc..."/></div><img class="swiftype-row-hider hidden-md hidden-lg" src="/images/icons/drawer-toggle-active-fcbef12a.png"/></form></div></div><div class="mobile-left-menu-toggler hidden-md hidden-lg"></div></div></div></div><div id="
page" class="container-fluid"><div class="row"><div id="left-menu-wrapper" class="col-md-3"><nav id="nav-main"><ul><li class="level-1"><a class="expandible" href="/"><span>Apache PredictionIO (incubating) Documentation</span></a><ul><li class="level-2"><a class="final" href="/"><span>Welcome to Apache PredictionIO (incubating)</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Getting Started</span></a><ul><li class="level-2"><a class="final" href="/start/"><span>A Quick Intro</span></a></li><li class="level-2"><a class="final" href="/install/"><span>Installing Apache PredictionIO (incubating)</span></a></li><li class="level-2"><a class="final" href="/start/download/"><span>Downloading an Engine Template</span></a></li><li class="level-2"><a class="final" href="/start/deploy/"><span>Deploying Your First Engine</span></a></li><li class="level-2"><a class="final" href="/start/customize/"><span>Customizing the Engine</span></a></li></ul></li><li class="le
vel-1"><a class="expandible" href="#"><span>Integrating with Your App</span></a><ul><li class="level-2"><a class="final" href="/appintegration/"><span>App Integration Overview</span></a></li><li class="level-2"><a class="expandible" href="/sdk/"><span>List of SDKs</span></a><ul><li class="level-3"><a class="final" href="/sdk/java/"><span>Java & Android SDK</span></a></li><li class="level-3"><a class="final" href="/sdk/php/"><span>PHP SDK</span></a></li><li class="level-3"><a class="final" href="/sdk/python/"><span>Python SDK</span></a></li><li class="level-3"><a class="final" href="/sdk/ruby/"><span>Ruby SDK</span></a></li><li class="level-3"><a class="final" href="/sdk/community/"><span>Community Powered SDKs</span></a></li></ul></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Deploying an Engine</span></a><ul><li class="level-2"><a class="final" href="/deploy/"><span>Deploying as a Web Service</span></a></li><li class="level-2"><a class="final" href="/cli/#e
ngine-commands"><span>Engine Command-line Interface</span></a></li><li class="level-2"><a class="final" href="/deploy/engineparams/"><span>Setting Engine Parameters</span></a></li><li class="level-2"><a class="final" href="/deploy/enginevariants/"><span>Deploying Multiple Engine Variants</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Customizing an Engine</span></a><ul><li class="level-2"><a class="final" href="/customize/"><span>Learning DASE</span></a></li><li class="level-2"><a class="final" href="/customize/dase/"><span>Implement DASE</span></a></li><li class="level-2"><a class="final" href="/customize/troubleshooting/"><span>Troubleshooting Engine Development</span></a></li><li class="level-2"><a class="final" href="/api/current/#package"><span>Engine Scala APIs</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Collecting and Analyzing Data</span></a><ul><li class="level-2"><a class="final" href="/datacollection
/"><span>Event Server Overview</span></a></li><li class="level-2"><a class="final" href="/cli/#event-server-commands"><span>Event Server Command-line Interface</span></a></li><li class="level-2"><a class="final" href="/datacollection/eventapi/"><span>Collecting Data with REST/SDKs</span></a></li><li class="level-2"><a class="final" href="/datacollection/eventmodel/"><span>Events Modeling</span></a></li><li class="level-2"><a class="final" href="/datacollection/webhooks/"><span>Unifying Multichannel Data with Webhooks</span></a></li><li class="level-2"><a class="final" href="/datacollection/channel/"><span>Channel</span></a></li><li class="level-2"><a class="final" href="/datacollection/batchimport/"><span>Importing Data in Batch</span></a></li><li class="level-2"><a class="final" href="/datacollection/analytics/"><span>Using Analytics Tools</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Choosing an Algorithm(s)</span></a><ul><li class="level-2"><a
class="final" href="/algorithm/"><span>Built-in Algorithm Libraries</span></a></li><li class="level-2"><a class="final" href="/algorithm/switch/"><span>Switching to Another Algorithm</span></a></li><li class="level-2"><a class="final" href="/algorithm/multiple/"><span>Combining Multiple Algorithms</span></a></li><li class="level-2"><a class="final" href="/algorithm/custom/"><span>Adding Your Own Algorithms</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>ML Tuning and Evaluation</span></a><ul><li class="level-2"><a class="final" href="/evaluation/"><span>Overview</span></a></li><li class="level-2"><a class="final" href="/evaluation/paramtuning/"><span>Hyperparameter Tuning</span></a></li><li class="level-2"><a class="final" href="/evaluation/evaluationdashboard/"><span>Evaluation Dashboard</span></a></li><li class="level-2"><a class="final" href="/evaluation/metricchoose/"><span>Choosing Evaluation Metrics</span></a></li><li class="level-2"><a class=
"final" href="/evaluation/metricbuild/"><span>Building Evaluation Metrics</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>System Architecture</span></a><ul><li class="level-2"><a class="final" href="/system/"><span>Architecture Overview</span></a></li><li class="level-2"><a class="final" href="/system/anotherdatastore/"><span>Using Another Data Store</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Engine Template Gallery</span></a><ul><li class="level-2"><a class="final" href="http://templates.prediction.io"><span>Browse</span></a></li><li class="level-2"><a class="final" href="/community/submit-template/"><span>Submit your Engine as a Template</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Demo Tutorials</span></a><ul><li class="level-2"><a class="final" href="/demo/tapster/"><span>Comics Recommendation Demo</span></a></li><li class="level-2"><a class="final" href="/demo/community
/"><span>Community Contributed Demo</span></a></li><li class="level-2"><a class="final" href="/demo/textclassification/"><span>Text Classification Engine Tutorial</span></a></li></ul></li><li class="level-1"><a class="expandible" href="/community/"><span>Getting Involved</span></a><ul><li class="level-2"><a class="final" href="/community/contribute-code/"><span>Contribute Code</span></a></li><li class="level-2"><a class="final" href="/community/contribute-documentation/"><span>Contribute Documentation</span></a></li><li class="level-2"><a class="final" href="/community/contribute-sdk/"><span>Contribute a SDK</span></a></li><li class="level-2"><a class="final" href="/community/contribute-webhook/"><span>Contribute a Webhook</span></a></li><li class="level-2"><a class="final" href="/community/projects/"><span>Community Projects</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Getting Help</span></a><ul><li class="level-2"><a class="final" href="/resour
ces/faq/"><span>FAQs</span></a></li><li class="level-2"><a class="final" href="/support/"><span>Community Support</span></a></li><li class="level-2"><a class="final" href="/support/#enterprise-support"><span>Enterprise Support</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Resources</span></a><ul><li class="level-2"><a class="final" href="/resources/intellij/"><span>Developing Engines with IntelliJ IDEA</span></a></li><li class="level-2"><a class="final" href="/resources/upgrade/"><span>Upgrade Instructions</span></a></li><li class="level-2"><a class="final" href="/resources/glossary/"><span>Glossary</span></a></li></ul></li></ul></nav></div><div class="col-md-9 col-sm-12"><div class="content-header hidden-md hidden-lg"><div id="page-title"><h1>Machine Learning With PredictionIO</h1></div></div><div id="table-of-content-wrapper"><h5>On this page</h5><aside id="table-of-contents"><ul> <li> <a href="#introduction-to-supervised-learning">Introduction
to Supervised Learning</a> </li> <li> <a href="#predictionio-and-supervised-learning">PredictionIO and Supervised Learning</a> </li> </ul> </aside><hr/><a id="edit-page-link" href="https://github.com/apache/incubator-predictionio/tree/livedoc/docs/manual/source/demo/supervisedlearning.html.md"><img src="/images/icons/edit-pencil-d6c1bb3d.png"/>Edit this page</a></div><div class="content-header hidden-sm hidden-xs"><div id="page-title"><h1>Machine Learning With PredictionIO</h1></div></div><div class="content"><p>This guide is designed to give developers a brief introduction to fundamental concepts in machine learning, as well as an explanation of how these concept tie into PredictionIO's engine development platform. This particular guide will largely deal with giving some </p><h2 id='introduction-to-supervised-learning' class='header-anchors'>Introduction to Supervised Learning</h2><p>The first question we must ask is: what is machine learning? <strong>Machine learning</strong>
is the field of study at the intersection of computer science, engineering, mathematics, and statistics which seeks to discover or infer patterns hidden within a set of observations, which we call our data. Some examples of problems that machine learning seeks to solve are:</p> <ul> <li>Predict whether a patient has breast cancer based on their mammogram results.</li> <li>Predict whether an e-mail is spam or not based on the e-mail's content.</li> <li>Predict today's temperature based on climate variables collected for the previous week.</li> </ul> <h3 id='thinking-about-data' class='header-anchors'>Thinking About Data</h3><p>In the latter examples, we are trying to predict an outcome \(Y\), or <strong>response</strong>, based on some recorded or observed variables \(X\), or <strong>features</strong>. For example: in the third problem each observation is a patient, the response variable \(Y\) is equal to 1 if this patient has breast cancer and 0 otherwise, and \(X\) represen
ts the mammogram results. </p><p>When we say we want to predict \(Y\) using \(X\), we are trying to answer the question: how does a response \(Y\) depend on a set of features \(X\) affect the response \(Y\)? To do this we need a set of observations, which we call our <strong>training data</strong>, consisting of observations for which we have observed both \(Y\) and \(X\), in order to make inference about this relationship. </p><h3 id='different-types-of-supervised-learning-problems' class='header-anchors'>Different Types of Supervised Learning Problems</h3><p>Note that in the first two examples, the outcome \(Y\) can only take on two values (1 : cancer/spam, 0: no cancer/ no spam). Whenever the outcome variable \(Y\) denotes a label associated to a particular group of observations (i.e. cancer group), the <strong>supervised learning</strong> problem is also called a <strong>classification</strong> problem. In the third example, however, \(Y\) can take on any numerical value since i
t denotes some temperature reading (i.e. 25.143, 25.14233, 32.0). These types of supervised learning problems are also called <strong>regression</strong> problems.</p><h3 id='training-a-predictive-model' class='header-anchors'>Training a Predictive Model</h3><p>A predictive model should be thought of as a function \(f\) that takes as input a set of features, and outputs a predicted outcome (i.e. \(f(X) = Y\)). The phrase <strong>training a model</strong> simply refers to the process of using the training data to estimate such a function. </p><h2 id='predictionio-and-supervised-learning' class='header-anchors'>PredictionIO and Supervised Learning</h2><p>Machine learning methods generally assume that our observation responses and features are numeric vectors. We will say that observations in this format are in <strong>standard form</strong>. However, when you are working with real-life data this will often not be the case. The data will often be formatted in a manner that is specific
to the application's needs. As an example, let's suppose our application is <a href="http://stackoverflow.com">StackOverFlow</a>. The data we want to analyze are questions, and we want to predict based on a question's content whether or not it is related to Scala. </p><p><strong>Self-check:</strong> Is this a classification or regression problem?</p><h3 id='thinking-about-data-with-predictionio' class='header-anchors'>Thinking About Data With PredictionIO</h3><p>PredictionIO's predictive engine development platform allows you to easily incorporate observations that are not in standard form. Continuing with our example, we can import the observations, or StackOverFlow questions, into <a href="/datacollection/">PredictionIO's Event Server</a> as events with the following properties:</p><p><code>properties = {question : String, topic : String}</code></p><p>The value <code>question</code> is the actual question stored as a <code>String</code>, and topic is also a str
ing equal to either <code>"Scala"</code> or <code>"Other"</code>. Our outcome here is <code>topic</code>, and <code>question</code> will provide a source for extracting features. That is, we will be using <code>question</code> to predict the outcome <code>topic</code>.</p><p>Once the observations are loaded as events into the Event Server, the engine's <a href="/customize/">Data Source</a> component is able to read them, which allows you to treat them as objects in a Scala project. The engine's Preparator component is in charge of converting these observations into standard form. To do this, we can first map the topic values as follows:</p><p><code>Map("Other" -> 0, "Scala" -> 1)</code>.</p><p>We can then vectorize the observation's associated question text to obtain a numeric feature vector for each of our observations. This text vectorization procedure is an example of a general concept in machine learning called <strong>fe
ature extraction</strong>. After performing these transformations of our observations, they are now in standard form and can be used for training a large quantity of machine learning models.</p><h3 id='training-the-model-with-predictionio' class='header-anchors'>Training the Model With PredictionIO</h3><p>The Algorithm engine component serves two purposes: outputting a predictive model \(f\) and using this to predict the outcome variable. Here \(f\) takes as input a vectorized question and outputs either 0 or 1. However, our <code>Query</code> input will be again a question, and our <code>PredictedResult</code> the topic associated to the predicted label (0 or 1):</p><p><code>Query = {question : String}</code> <code>PredictedResult = {topic : String}</code></p><p>With PredictionIO's engine development platform, you can easily automate the vectorization of the Query question, as well as mapping the predicted label to the appropriate topic output format.</p></div></div></div></div
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ass="container-fluid"><div class="row"><div id="left-menu-wrapper" class="col-md-3"><nav id="nav-main"><ul><li class="level-1"><a class="expandible" href="/"><span>Apache PredictionIO (incubating) Documentation</span></a><ul><li class="level-2"><a class="final" href="/"><span>Welcome to Apache PredictionIO (incubating)</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Getting Started</span></a><ul><li class="level-2"><a class="final" href="/start/"><span>A Quick Intro</span></a></li><li class="level-2"><a class="final" href="/install/"><span>Installing Apache PredictionIO (incubating)</span></a></li><li class="level-2"><a class="final" href="/start/download/"><span>Downloading an Engine Template</span></a></li><li class="level-2"><a class="final" href="/start/deploy/"><span>Deploying Your First Engine</span></a></li><li class="level-2"><a class="final" href="/start/customize/"><span>Customizing the Engine</span></a></li></ul></li><li class="level-1"><
a class="expandible" href="#"><span>Integrating with Your App</span></a><ul><li class="level-2"><a class="final" href="/appintegration/"><span>App Integration Overview</span></a></li><li class="level-2"><a class="expandible" href="/sdk/"><span>List of SDKs</span></a><ul><li class="level-3"><a class="final" href="/sdk/java/"><span>Java & Android SDK</span></a></li><li class="level-3"><a class="final" href="/sdk/php/"><span>PHP SDK</span></a></li><li class="level-3"><a class="final" href="/sdk/python/"><span>Python SDK</span></a></li><li class="level-3"><a class="final" href="/sdk/ruby/"><span>Ruby SDK</span></a></li><li class="level-3"><a class="final" href="/sdk/community/"><span>Community Powered SDKs</span></a></li></ul></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Deploying an Engine</span></a><ul><li class="level-2"><a class="final" href="/deploy/"><span>Deploying as a Web Service</span></a></li><li class="level-2"><a class="final" href="/cli/#engine-co
mmands"><span>Engine Command-line Interface</span></a></li><li class="level-2"><a class="final" href="/deploy/engineparams/"><span>Setting Engine Parameters</span></a></li><li class="level-2"><a class="final" href="/deploy/enginevariants/"><span>Deploying Multiple Engine Variants</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Customizing an Engine</span></a><ul><li class="level-2"><a class="final" href="/customize/"><span>Learning DASE</span></a></li><li class="level-2"><a class="final" href="/customize/dase/"><span>Implement DASE</span></a></li><li class="level-2"><a class="final" href="/customize/troubleshooting/"><span>Troubleshooting Engine Development</span></a></li><li class="level-2"><a class="final" href="/api/current/#package"><span>Engine Scala APIs</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Collecting and Analyzing Data</span></a><ul><li class="level-2"><a class="final" href="/datacollection/"><span
>Event Server Overview</span></a></li><li class="level-2"><a class="final" href="/cli/#event-server-commands"><span>Event Server Command-line Interface</span></a></li><li class="level-2"><a class="final" href="/datacollection/eventapi/"><span>Collecting Data with REST/SDKs</span></a></li><li class="level-2"><a class="final" href="/datacollection/eventmodel/"><span>Events Modeling</span></a></li><li class="level-2"><a class="final" href="/datacollection/webhooks/"><span>Unifying Multichannel Data with Webhooks</span></a></li><li class="level-2"><a class="final" href="/datacollection/channel/"><span>Channel</span></a></li><li class="level-2"><a class="final" href="/datacollection/batchimport/"><span>Importing Data in Batch</span></a></li><li class="level-2"><a class="final" href="/datacollection/analytics/"><span>Using Analytics Tools</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Choosing an Algorithm(s)</span></a><ul><li class="level-2"><a class="f
inal" href="/algorithm/"><span>Built-in Algorithm Libraries</span></a></li><li class="level-2"><a class="final" href="/algorithm/switch/"><span>Switching to Another Algorithm</span></a></li><li class="level-2"><a class="final" href="/algorithm/multiple/"><span>Combining Multiple Algorithms</span></a></li><li class="level-2"><a class="final" href="/algorithm/custom/"><span>Adding Your Own Algorithms</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>ML Tuning and Evaluation</span></a><ul><li class="level-2"><a class="final" href="/evaluation/"><span>Overview</span></a></li><li class="level-2"><a class="final" href="/evaluation/paramtuning/"><span>Hyperparameter Tuning</span></a></li><li class="level-2"><a class="final" href="/evaluation/evaluationdashboard/"><span>Evaluation Dashboard</span></a></li><li class="level-2"><a class="final" href="/evaluation/metricchoose/"><span>Choosing Evaluation Metrics</span></a></li><li class="level-2"><a class="final"
href="/evaluation/metricbuild/"><span>Building Evaluation Metrics</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>System Architecture</span></a><ul><li class="level-2"><a class="final" href="/system/"><span>Architecture Overview</span></a></li><li class="level-2"><a class="final" href="/system/anotherdatastore/"><span>Using Another Data Store</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Engine Template Gallery</span></a><ul><li class="level-2"><a class="final" href="http://templates.prediction.io"><span>Browse</span></a></li><li class="level-2"><a class="final" href="/community/submit-template/"><span>Submit your Engine as a Template</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Demo Tutorials</span></a><ul><li class="level-2"><a class="final active" href="/demo/tapster/"><span>Comics Recommendation Demo</span></a></li><li class="level-2"><a class="final" href="/demo/community/
"><span>Community Contributed Demo</span></a></li><li class="level-2"><a class="final" href="/demo/textclassification/"><span>Text Classification Engine Tutorial</span></a></li></ul></li><li class="level-1"><a class="expandible" href="/community/"><span>Getting Involved</span></a><ul><li class="level-2"><a class="final" href="/community/contribute-code/"><span>Contribute Code</span></a></li><li class="level-2"><a class="final" href="/community/contribute-documentation/"><span>Contribute Documentation</span></a></li><li class="level-2"><a class="final" href="/community/contribute-sdk/"><span>Contribute a SDK</span></a></li><li class="level-2"><a class="final" href="/community/contribute-webhook/"><span>Contribute a Webhook</span></a></li><li class="level-2"><a class="final" href="/community/projects/"><span>Community Projects</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Getting Help</span></a><ul><li class="level-2"><a class="final" href="/resourc
es/faq/"><span>FAQs</span></a></li><li class="level-2"><a class="final" href="/support/"><span>Community Support</span></a></li><li class="level-2"><a class="final" href="/support/#enterprise-support"><span>Enterprise Support</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Resources</span></a><ul><li class="level-2"><a class="final" href="/resources/intellij/"><span>Developing Engines with IntelliJ IDEA</span></a></li><li class="level-2"><a class="final" href="/resources/upgrade/"><span>Upgrade Instructions</span></a></li><li class="level-2"><a class="final" href="/resources/glossary/"><span>Glossary</span></a></li></ul></li></ul></nav></div><div class="col-md-9 col-sm-12"><div class="content-header hidden-md hidden-lg"><div id="breadcrumbs" class="hidden-sm hidden xs"><ul><li><a href="#">Demo Tutorials</a><span class="spacer">></span></li><li><span class="last">Comics Recommendation Demo</span></li></ul></div><div id="page-title"><h1>Comics Reco
mmendation Demo</h1></div></div><div id="table-of-content-wrapper"><h5>On this page</h5><aside id="table-of-contents"><ul> <li> <a href="#introduction">Introduction</a> </li> <li> <a href="#tapster-demo-application">Tapster Demo Application</a> </li> <li> <a href="#apache-predictionio-incubating-setup">Apache PredictionIO (incubating) Setup</a> </li> <li> <a href="#import-data">Import Data</a> </li> <li> <a href="#connect-demo-app-with-apache-predictionio-incubating">Connect Demo app with Apache PredictionIO (incubating)</a> </li> <li> <a href="#links">Links</a> </li> <li> <a href="#conclusion">Conclusion</a> </li> </ul> </aside><hr/><a id="edit-page-link" href="https://github.com/apache/incubator-predictionio/tree/livedoc/docs/manual/source/demo/tapster.html.md"><img src="/images/icons/edit-pencil-d6c1bb3d.png"/>Edit this page</a></div><div class="content-header hidden-sm hidden-xs"><div id="breadcrumbs" class="hidden-sm hidden xs"><ul><li><a href="#">Demo Tutorials</a><span class=
"spacer">></span></li><li><span class="last">Comics Recommendation Demo</span></li></ul></div><div id="page-title"><h1>Comics Recommendation Demo</h1></div></div><div class="content"><h2 id='introduction' class='header-anchors'>Introduction</h2><p>In this demo, we will show you how to build a Tinder-style web application (named "Tapster") recommending comics to users based on their likes/dislikes of episodes interactively.</p><p>The demo will use <a href="https://docs.prediction.io/templates/similarproduct/quickstart/">Similar Product Template</a>. Similar Product Template is a great choice if you want to make recommendations based on immediate user activities or for new users with limited history. It uses MLLib Alternating Least Squares (ALS) recommendation algorithm, a <a href="http://en.wikipedia.org/wiki/Recommender_system#Collaborative_filtering">Collaborative filtering</a> (CF) algorithm commonly used for recommender systems. These techniques aim to fill in the mi
ssing entries of a user-item association matrix. Users and products are described by a small set of latent factors that can be used to predict missing entries. A layman's interpretation of Collaborative Filtering is "People who like this comic, also like these comics."</p><p>All the code and data is on GitHub at: <a href="https://github.com/PredictionIO/Demo-Tapster">github.com/PredictionIO/Demo-Tapster</a>.</p><h3 id='data' class='header-anchors'>Data</h3><p>The source of the data is from <a href="http://tapastic.com/">Tapastic</a>. You can find the data files <a href="https://github.com/PredictionIO/Demo-Tapster/tree/master/data">here</a>.</p><p>The data structure looks like this:</p><p><a href="https://github.com/PredictionIO/Demo-Tapster/blob/master/data/episode_list.csv">Episode List</a> <code>data/episode_list.csv</code></p><p><strong>Fields:</strong> episodeId | episodeTitle | episodeCategories | episodeUrl | episodeImageUrls</p><p>1,000 rows. Each row represent
s one episode.</p><p><a href="https://github.com/PredictionIO/Demo-Tapster/blob/master/data/user_list.csv">User Like Event List</a> <code>data/user_list.csv</code></p><p><strong>Fields:</strong> userId | episodeId | likedTimestamp</p><p>192,587 rows. Each row represents one user like for the given episode.</p><p>The tutorial has four major steps: - Demo application setup - PredictionIO installation and setup - Import data into database and PredictionIO - Integrate demo application with PredictionIO</p><h2 id='tapster-demo-application' class='header-anchors'>Tapster Demo Application</h2><p>The demo application is built using Rails.</p><p>You can clone the existing application with:</p><div class="highlight shell"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1
+2
+3</pre></td><td class="code"><pre><span class="gp">$ </span>git clone https://github.com/PredictionIO/Demo-Tapster.git
+<span class="gp">$ </span><span class="nb">cd </span>Demo-Tapster
+<span class="gp">$ </span>bundle install
+</pre></td></tr></tbody></table> </div> <p>You will need to edit <code>config/database.yml</code> to match your local database settings. We have provided some sensible defaults for PostgreSQL, MySQL, and SQLite.</p><p>Setup the database with:</p><div class="highlight shell"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1
+2</pre></td><td class="code"><pre><span class="gp">$ </span>rake db:create
+<span class="gp">$ </span>rake db:migrate
+</pre></td></tr></tbody></table> </div> <p>At this point, you should have the demo application ready but with an empty database. Lets import the episodes data into our database. We will do this with: <code>$ rake import:episodes</code>. An "Episode" is a single <a href="http://en.wikipedia.org/wiki/Comic_strip">comic strip</a>.</p><p><a href="https://github.com/PredictionIO/Demo-Tapster/blob/master/lib/tasks/import/episodes.rake">View on GitHub</a></p><p>This script is pretty simple. It loops through the CSV file and creates a new episode for each line in the file in our local database.</p><p>You can start the app and point your browser to <a href="http://localhost:3000">http://localhost:3000</a></p><div class="highlight shell"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1</pre></td><td class="code"><pre><span class="nv">$rails</span> server
+</pre></td></tr></tbody></table> </div> <p><img alt="Rails Server" src="/images/demo/tapster/rails-server-997d690e.png"/></p><h2 id='apache-predictionio-(incubating)-setup' class='header-anchors'>Apache PredictionIO (incubating) Setup</h2><h3 id='install-apache-predictionio-(incubating)' class='header-anchors'>Install Apache PredictionIO (incubating)</h3><p>Follow the installation instructions <a href="http://predictionio.incubator.apache.org/install/">here</a> or simply run:</p><div class="highlight shell"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1</pre></td><td class="code"><pre><span class="gp">$ </span>bash -c <span class="s2">"</span><span class="k">$(</span>curl -s https://raw.githubusercontent.com/apache/incubator-predictionio/master/bin/install.sh<span class="k">)</span><span class="s2">"</span>
+</pre></td></tr></tbody></table> </div> <p><img alt="PIO Install" src="/images/demo/tapster/pio-install-2d870aed.png"/></p><h3 id='create-a-new-app' class='header-anchors'>Create a New App</h3><p>You will need to create a new app on Apache PredictionIO (incubating) to house the Tapster demo. You can do this with:</p><div class="highlight shell"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1</pre></td><td class="code"><pre><span class="gp">$ </span>pio app new tapster
+</pre></td></tr></tbody></table> </div> <p>Take note of the App ID and Access Key.</p><p><img alt="PIO App New" src="/images/demo/tapster/pio-app-new-5a8ae503.png"/></p><h3 id='setup-engine' class='header-anchors'>Setup Engine</h3><p>We are going to copy the Similar Product Template into the PIO directory.</p><div class="highlight shell"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1
+2</pre></td><td class="code"><pre><span class="gp">$ </span><span class="nb">cd </span>PredictionIO
+<span class="gp">$ </span>pio template get PredictionIO/template-scala-parallel-similarproduct tapster-episode-similar
+</pre></td></tr></tbody></table> </div> <p>Next we are going to update the App ID in the \u2018engine.json\u2019 file to match the App ID we just created.</p><div class="highlight shell"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1
+2
+3</pre></td><td class="code"><pre><span class="gp">$ </span><span class="nb">cd </span>tapster-episode-similar
+<span class="gp">$ </span>nano engine.json
+<span class="gp">$ </span><span class="nb">cd</span> ..
+</pre></td></tr></tbody></table> </div> <p><img alt="Engine Setup" src="/images/demo/tapster/pio-engine-setup-88e25cc0.png"/></p><h3 id='modify--engine-template' class='header-anchors'>Modify Engine Template</h3><p>By the default, the engine template reads the \u201cview\u201d events. We can easily to change it to read \u201clike\u201d events.</p> <p>Modify <code>readTraining()</code> in DataSource.scala:</p><div class="highlight scala"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1
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+36</pre></td><td class="code"><pre>
+ <span class="k">override</span>
+ <span class="k">def</span> <span class="n">readTraining</span><span class="o">(</span><span class="n">sc</span><span class="k">:</span> <span class="kt">SparkContext</span><span class="o">)</span><span class="k">:</span> <span class="kt">TrainingData</span> <span class="o">=</span> <span class="o">{</span>
+
+ <span class="o">...</span>
+
+ <span class="k">val</span> <span class="n">viewEventsRDD</span><span class="k">:</span> <span class="kt">RDD</span><span class="o">[</span><span class="kt">ViewEvent</span><span class="o">]</span> <span class="k">=</span> <span class="n">eventsDb</span><span class="o">.</span><span class="n">find</span><span class="o">(</span>
+ <span class="n">appId</span> <span class="k">=</span> <span class="n">dsp</span><span class="o">.</span><span class="n">appId</span><span class="o">,</span>
+ <span class="n">entityType</span> <span class="k">=</span> <span class="nc">Some</span><span class="o">(</span><span class="s">"user"</span><span class="o">),</span>
+ <span class="n">eventNames</span> <span class="k">=</span> <span class="nc">Some</span><span class="o">(</span><span class="nc">List</span><span class="o">(</span><span class="s">"like"</span><span class="o">)),</span> <span class="c1">// MODIFIED
+</span> <span class="c1">// targetEntityType is optional field of an event.
+</span> <span class="n">targetEntityType</span> <span class="k">=</span> <span class="nc">Some</span><span class="o">(</span><span class="nc">Some</span><span class="o">(</span><span class="s">"item"</span><span class="o">)))(</span><span class="n">sc</span><span class="o">)</span>
+ <span class="c1">// eventsDb.find() returns RDD[Event]
+</span> <span class="o">.</span><span class="n">map</span> <span class="o">{</span> <span class="n">event</span> <span class="k">=></span>
+ <span class="k">val</span> <span class="n">viewEvent</span> <span class="k">=</span> <span class="k">try</span> <span class="o">{</span>
+ <span class="n">event</span><span class="o">.</span><span class="n">event</span> <span class="k">match</span> <span class="o">{</span>
+ <span class="k">case</span> <span class="s">"like"</span> <span class="k">=></span> <span class="nc">ViewEvent</span><span class="o">(</span> <span class="c1">// MODIFIED
+</span> <span class="n">user</span> <span class="k">=</span> <span class="n">event</span><span class="o">.</span><span class="n">entityId</span><span class="o">,</span>
+ <span class="n">item</span> <span class="k">=</span> <span class="n">event</span><span class="o">.</span><span class="n">targetEntityId</span><span class="o">.</span><span class="n">get</span><span class="o">,</span>
+ <span class="n">t</span> <span class="k">=</span> <span class="n">event</span><span class="o">.</span><span class="n">eventTime</span><span class="o">.</span><span class="n">getMillis</span><span class="o">)</span>
+ <span class="k">case</span> <span class="k">_</span> <span class="k">=></span> <span class="k">throw</span> <span class="k">new</span> <span class="nc">Exception</span><span class="o">(</span><span class="n">s</span><span class="s">"Unexpected event ${event} is read."</span><span class="o">)</span>
+ <span class="o">}</span>
+ <span class="o">}</span> <span class="k">catch</span> <span class="o">{</span>
+ <span class="k">case</span> <span class="n">e</span><span class="k">:</span> <span class="kt">Exception</span> <span class="o">=></span> <span class="o">{</span>
+ <span class="n">logger</span><span class="o">.</span><span class="n">error</span><span class="o">(</span><span class="n">s</span><span class="s">"Cannot convert ${event} to ViewEvent."</span> <span class="o">+</span>
+ <span class="n">s</span><span class="s">" Exception: ${e}."</span><span class="o">)</span>
+ <span class="k">throw</span> <span class="n">e</span>
+ <span class="o">}</span>
+ <span class="o">}</span>
+ <span class="n">viewEvent</span>
+ <span class="o">}</span>
+
+ <span class="o">...</span>
+ <span class="o">}</span>
+<span class="o">}</span>
+
+</pre></td></tr></tbody></table> </div> <p>Finally to build the engine we will run:</p><div class="highlight shell"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1
+2
+3</pre></td><td class="code"><pre><span class="gp">$ </span><span class="nb">cd </span>tapster-episode-similar
+<span class="gp">$ </span>pio build
+<span class="gp">$ </span><span class="nb">cd</span> ..
+</pre></td></tr></tbody></table> </div> <p><img alt="PIO Build" src="/images/demo/tapster/pio-build-e6eb1d7c.png"/></p><h2 id='import-data' class='header-anchors'>Import Data</h2><p>Once everything is installed, start the event server by running: <code>$ pio eventserver</code></p><p><img alt="Event Server" src="/images/demo/tapster/pio-eventserver-88889ec0.png"/></p><div class="alert-message info"><p>You can check the status of Apache PredictionIO (incubating) at any time by running: <code>$ pio status</code></p></div><p>ALERT: If your laptop goes to sleep you might manually need to restart HBase with:</p><div class="highlight shell"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1
+2
+3</pre></td><td class="code"><pre><span class="gp">$ </span><span class="nb">cd </span>PredictionIO/venders/hbase-0.98.6/bin
+<span class="gp">$ </span>./stop-hbase.sh
+<span class="gp">$ </span>./start-hbase.sh
+</pre></td></tr></tbody></table> </div> <p>The key event we are importing into Apache PredictionIO (incubating) event server is the "Like" event (for example, user X likes episode Y).</p><p>We will send this data to Apache PredictionIO (incubating) by executing <code>$ rake import:predictionio</code> command.</p><p><a href="https://github.com/PredictionIO/Demo-Tapster/blob/master/lib/tasks/import/predictionio.rake">View on GitHub</a></p><p>This script is a little more complex. First we need to connect to the Event Server.</p><div class="highlight shell"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1</pre></td><td class="code"><pre>client <span class="o">=</span> PredictionIO::EventClient.new<span class="o">(</span>ENV[<span class="s1">'PIO_ACCESS_KEY'</span><span class="o">]</span>, ENV[<span class="s1">'PIO_EVENT_SERVER_URL'</span><span class="o">]</span>, THREADS<span class="o">)</span>
+</pre></td></tr></tbody></table> </div> <p>You will need to create the environmental variables <code>PIO_ACCESS_KEY</code> and <code>PIO_EVENT_SERVER_URL</code>. The default Event Server URL is: <a href="http://localhost:7070">http://localhost:7070</a>.</p><div class="alert-message info"><p>If you forget your <strong>Access Key</strong> you can always run: <code>$ pio app list</code></p></div><p>You can set these values in the <code>.env</code> file located in the application root directory and it will be automatically loaded into your environment each time Rails is run.</p><p>The next part of the script loops through each line of the <code>data/user_list.csv</code> file and returns an array of unique user and episode IDs. Once we have those we can send the data to Apache PredictionIO (incubating) like this.</p><p>First the users:</p><div class="highlight shell"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1
+2
+3
+4
+5</pre></td><td class="code"><pre>user_ids.each_with_index <span class="k">do</span> |id, i|
+ <span class="c"># Send unique user IDs to PredictionIO.</span>
+ client.aset_user<span class="o">(</span>id<span class="o">)</span>
+ puts <span class="s2">"Sent user ID #{id} to PredictionIO. Action #{i + 1} of #{user_count}"</span>
+end
+</pre></td></tr></tbody></table> </div> <p>And now the episodes:</p><div class="highlight shell"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1
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+ <span class="c"># Load episode from database - we will need this to include the categories!</span>
+ episode <span class="o">=</span> Episode.where<span class="o">(</span>episode_id: id<span class="o">)</span>.take
+
+ <span class="k">if </span>episode
+ <span class="c"># Send unique episode IDs to PredictionIO.</span>
+ client.acreate_event<span class="o">(</span>
+ <span class="s1">'$set'</span>,
+ <span class="s1">'item'</span>,
+ id,
+ properties: <span class="o">{</span> categories: episode.categories <span class="o">}</span>
+ <span class="o">)</span>
+ puts <span class="s2">"Sent episode ID #{id} to PredictionIO. Action #{i + 1} of #{episode_count}"</span>
+ <span class="k">else
+ </span>puts <span class="s2">"Episode ID #{id} not found in database! Skipping!"</span>.color<span class="o">(</span>:red<span class="o">)</span>
+ end
+end
+</pre></td></tr></tbody></table> </div> <p>Finally we loop through the <code>data/user_list.csv</code> file a final time to send the like events:</p><div class="highlight shell"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1
+2
+3
+4
+5
+6
+7
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+10
+11
+12
+13
+14</pre></td><td class="code"><pre>CSV.foreach<span class="o">(</span>USER_LIST, headers: <span class="nb">true</span><span class="o">)</span> <span class="k">do</span> |row|
+ user_id <span class="o">=</span> row[0] <span class="c"># userId</span>
+ episode_id <span class="o">=</span> row[1] <span class="c"># episodeId</span>
+
+ <span class="c"># Send like to PredictionIO.</span>
+ client.acreate_event<span class="o">(</span>
+ <span class="s1">'like'</span>,
+ <span class="s1">'user'</span>,
+ user_id,
+ <span class="o">{</span> <span class="s1">'targetEntityType'</span> <span class="o">=</span>> <span class="s1">'item'</span>, <span class="s1">'targetEntityId'</span> <span class="o">=</span>> episode_id <span class="o">}</span>
+ <span class="o">)</span>
+
+ puts <span class="s2">"Sent user ID #{user_id} liked episode ID #{episode_id} to PredictionIO. Action #{</span><span class="nv">$INPUT_LINE_NUMBER</span><span class="s2">} of #{line_count}."</span>
+end
+</pre></td></tr></tbody></table> </div> <p>In total the script takes about 4 minutes to run on a basic laptop. At this point all the data is now imported to Apache PredictionIO (incubating).</p><p><img alt="Import" src="/images/demo/tapster/pio-import-predictionio-1ecd11fd.png"/></p><h3 id='engine-training' class='header-anchors'>Engine Training</h3><p>We train the engine with the following command:</p><div class="highlight shell"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1
+2</pre></td><td class="code"><pre><span class="gp">$ </span><span class="nb">cd </span>tapster-episode-similar
+<span class="gp">$ </span>pio train -- --driver-memory 4g
+</pre></td></tr></tbody></table> </div> <p><img alt="PIO Train" src="/images/demo/tapster/pio-train-7edffad4.png"/></p><p>Using the --driver-memory option to limit the memory used by Apache PredictionIO (incubating). Without this Apache PredictionIO (incubating) can consume too much memory leading to a crash. You can adjust the 4g up or down depending on your system specs.</p><p>You can set up a job to periodically retrain the engine so the model is updated with the latest dataset.</p><h3 id='deploy-model' class='header-anchors'>Deploy Model</h3><p>You can deploy the model with: <code>$ pio deploy</code> from the <code>tapster-episode-similar</code> directory.</p><p>At this point, you have an demo app with data and a Apache PredictionIO (incubating) server with a trained model all setup. Next, we will connect the two so you can log the live interaction (likes) events into Apache PredictionIO (incubating) event server and query the engine server for recommendation.</p><h2 id='connect
-demo-app-with-apache-predictionio-(incubating)' class='header-anchors'>Connect Demo app with Apache PredictionIO (incubating)</h2><h3 id='overview' class='header-anchors'>Overview</h3><p>On a high level the application keeps a record of each like and dislike. It uses jQuery to send an array of both likes and dislikes to the server on each click. The server then queries Apache PredictionIO (incubating) for a similar episode which is relayed to jQuery and displayed to the user.</p><p>Data flow:</p> <ul> <li>The user likes an episode.</li> <li>Tapster sends the "Like" event to Apache PredictionIO (incubating) event server.</li> <li>Tapster queries Apache PredictionIO (incubating) engine with all the episodes the user has rated (likes and dislikes) in this session.</li> <li>Apache PredictionIO (incubating) returns 1 recommended episode.</li> </ul> <h3 id='javascript' class='header-anchors'>JavaScript</h3><p>All the important code lives in <code>app/assets/javascripts/applicat
ion.js</code> <a href="https://github.com/PredictionIO/Demo-Tapster/blob/master/app/assets/javascripts/application.js">View on GitHub</a></p><p>Most of this file is just handlers for click things, displaying the loading dialog and other such things.</p><p>The most important function is to query the Rails server for results from Apache PredictionIO (incubating).</p><div class="highlight shell"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1
+2
+3
+4
+5
+6
+7
+8
+9
+10
+11
+12
+13
+14</pre></td><td class="code"><pre>// Query the server <span class="k">for </span>a comic based on previous likes. See episodes#query.
+queryPIO: <span class="k">function</span><span class="o">()</span> <span class="o">{</span>
+ var _this <span class="o">=</span> this; // For closure.
+ <span class="nv">$.</span>ajax<span class="o">({</span>
+ url: <span class="s1">'/episodes/query'</span>,
+ <span class="nb">type</span>: <span class="s1">'POST'</span>,
+ data: <span class="o">{</span>
+ likes: JSON.stringify<span class="o">(</span>_this.likes<span class="o">)</span>,
+ dislikes: JSON.stringify<span class="o">(</span>_this.dislikes<span class="o">)</span>,
+ <span class="o">}</span>
+ <span class="o">})</span>.done<span class="o">(</span><span class="k">function</span><span class="o">(</span>data<span class="o">)</span> <span class="o">{</span>
+ _this.setComic<span class="o">(</span>data<span class="o">)</span>;
+ <span class="o">})</span>;
+<span class="o">}</span>
+</pre></td></tr></tbody></table> </div> <h3 id='rails' class='header-anchors'>Rails</h3><p>On the Rails side all the fun things happen in the episodes controller locates at: <code>app/controllers/episodes_controller</code> <a href="https://github.com/PredictionIO/Demo-Tapster/blob/master/app/controllers/episodes_controller.rb">View on GitHub</a>.</p><div class="highlight shell"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1
+2
+3
+4
+5
+6
+7
+8
+9
+10
+11
+12
+13
+14
+15
+16
+17
+18
+19
+20
+21
+22
+23
+24
+25
+26
+27
+28
+29
+30
+31
+32</pre></td><td class="code"><pre>def query
+ <span class="c"># Create PredictionIO client.</span>
+ client <span class="o">=</span> PredictionIO::EngineClient.new<span class="o">(</span>ENV[<span class="s1">'PIO_ENGINE_URL'</span><span class="o">])</span>
+
+ <span class="c"># Get posted likes and dislikes.</span>
+ likes <span class="o">=</span> ActiveSupport::JSON.decode<span class="o">(</span>params[:likes]<span class="o">)</span>
+ dislikes <span class="o">=</span> ActiveSupport::JSON.decode<span class="o">(</span>params[:dislikes]<span class="o">)</span>
+
+ <span class="k">if </span>likes.empty?
+ <span class="c"># We can't query PredictionIO with no likes so</span>
+ <span class="c"># we will return a random comic instead.</span>
+ @episode <span class="o">=</span> random_episode
+
+ render json: @episode
+ <span class="k">return
+ </span>end
+
+ <span class="c"># Query PredictionIO.</span>
+ <span class="c"># Here we black list the disliked items so they are not shown again!</span>
+ response <span class="o">=</span> client.send_query<span class="o">(</span>items: likes, blackList: dislikes, num: 1<span class="o">)</span>
+
+ <span class="c"># With a real application you would want to do some</span>
+ <span class="c"># better sanity checking of the response here!</span>
+
+ <span class="c"># Get ID of response.</span>
+ id <span class="o">=</span> response[<span class="s1">'itemScores'</span><span class="o">][</span>0][<span class="s1">'item'</span><span class="o">]</span>
+
+ <span class="c"># Find episode in database.</span>
+ @episode <span class="o">=</span> Episode.where<span class="o">(</span>episode_id: id<span class="o">)</span>.take
+
+ render json: @episode
+end
+</pre></td></tr></tbody></table> </div> <p>On the first line we make a connection to Apache PredictionIO (incubating). You will need to set the <code>PIO_ENGINE_URL</code>. This can be done in the <code>.env</code> file. The default URL is: <a href="http://localhost:8000">http://localhost:8000</a>.</p><p>Next we decode the JSON sent from the browser.</p><p>After that we check to see if the user has liked anything yet. If not we just return a random episode.</p><p>If the user has likes then we can send that data to Apache PredictionIO (incubating) event server.</p><p>We also blacklist the dislikes so that they are not returned.</p><p>With our response from Apache PredictionIO (incubating) it\u2019s just a matter of looking it up in the database and rendering that object as JSON.</p><p>Once the response is sent to the browser JavaScript is used to replace the existing comic and hide the loading message.</p><p>Thats it. You\u2019re done! If Ruby is not your language of choice check out our o
ther <a href="http://docs.prediction.io/sdk/">SDKs</a> and remember you can always interact with the Event Server though it\u2019s native JSON API.</p><h2 id='links' class='header-anchors'>Links</h2><p>Source code is on GitHub at: <a href="https://github.com/PredictionIO/Demo-Tapster">github.com/PredictionIO/Demo-Tapster</a></p><h2 id='conclusion' class='header-anchors'>Conclusion</h2><p>Love this tutorial and Apache PredictionIO (incubating)? Both are open source (Apache 2 License). <a href="https://github.com/PredictionIO/Demo-Tapster">Fork</a> this demo and build upon it. If you produce something cool shoot us an email and we will link to it from here.</p><p>Found a typo? Think something should be explained better? This tutorial (and all our other documenation) live in the main repo <a href="https://github.com/apache/incubator-predictionio/blob/livedoc/docs/manual/source/demo/tapster.html.md">here</a>. Our documentation is in the <code>livedoc</code> branch. Find out how to contribu
te documentation at <a href="http://predictionio.incubator.apache.org/community/contribute-documentation/">http://predictionio.incubator.apache.org/community/contribute-documentation/</a>].</p><p>We ♥ pull requests!</p></div></div></div></div><footer><div class="container"><div class="seperator"></div><div class="row"><div class="col-md-4 col-md-push-8 col-xs-12"><div class="subscription-form-wrapper"><h4>Subscribe to our Newsletter</h4><form class="ajax-form" id="subscribe-form" method="POST" action="https://script.google.com/macros/s/AKfycbwhzeKCQJjQ52eVAqNT_vcklH07OITUO7wzOMDXvK6EGAWgaZgF/exec"><input class="required underlined-input" type="email" placeholder="Your email address" name="subscription_email" id="subscription_email"/><input class="pill-button" value="SUBSCRIBE" type="submit" data-state-normal="SUBSCRIBE" data-state-sucess="SUBSCRIBED!" data-state-loading="SENDING..." onclick="t($('#subscription_email').val());"/><p class="result"></p></form></div></div><div cl
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[09/51] [partial] incubator-predictionio-site git commit: Initial doc
site
Posted by do...@apache.org.
http://git-wip-us.apache.org/repos/asf/incubator-predictionio-site/blob/92a45fa4/system/deploy-cloudformation/index.html
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+fbq('track', "PageView");</script><script src="//use.typekit.net/mut4mjx.js"></script><script>try{Typekit.load();}catch(e){}</script></head><body><div id="global"><header><div class="container" id="header-wrapper"><div class="row"><div class="col-sm-12"><div id="logo-wrapper"><span id="drawer-toggle"></span><a href="#"></a><a href="http://prediction.io/"><img alt="PredictionIO" id="logo" src="/images/logos/logo-ee2b9bb3.png"/></a></div><div id="menu-wrapper"><div id="header-nav-options-wrapper"><ul><li><a href="/">Install & Doc</a></li> <li><a href="/support">Support</a></li> </ul></div><div id="pill-wrapper"><a class="pill left" href="//templates.prediction.io/">TEMPLATES</a> <a class="pill right" href="//github.com/PredictionIO/PredictionIO/">OPEN SOURCE</a></div></div><img class="mobile-search-bar-toggler hidden-md hidden-lg" src="/images/icons/search-glass-704bd4ff.png"/></div></div></div></header><div id="search-bar-row-wrapper"><div class="container-fluid" id="search-bar-row">
<div class="row"><div class="col-md-9 col-sm-11 col-xs-11"><div class="hidden-md hidden-lg" id="mobile-page-heading-wrapper"><p>PredictionIO Docs</p><h4>Deploying with AWS CloudFormation</h4></div><h4 class="hidden-sm hidden-xs">PredictionIO Docs</h4></div><div class="col-md-3 col-sm-1 col-xs-1 hidden-md hidden-lg"><img id="left-menu-indicator" src="/images/icons/down-arrow-dfe9f7fe.png"/></div><div class="col-md-3 col-sm-12 col-xs-12 swiftype-wrapper"><div class="swiftype"><form class="search-form"><img class="search-box-toggler hidden-xs hidden-sm" src="/images/icons/search-glass-704bd4ff.png"/><div class="search-box"><img src="/images/icons/search-glass-704bd4ff.png"/><input type="text" id="st-search-input" class="st-search-input" placeholder="Search Doc..."/></div><img class="swiftype-row-hider hidden-md hidden-lg" src="/images/icons/drawer-toggle-active-fcbef12a.png"/></form></div></div><div class="mobile-left-menu-toggler hidden-md hidden-lg"></div></div></div></div><div id="p
age" class="container-fluid"><div class="row"><div id="left-menu-wrapper" class="col-md-3"><nav id="nav-main"><ul><li class="level-1"><a class="expandible" href="/"><span>Apache PredictionIO (incubating) Documentation</span></a><ul><li class="level-2"><a class="final" href="/"><span>Welcome to Apache PredictionIO (incubating)</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Getting Started</span></a><ul><li class="level-2"><a class="final" href="/start/"><span>A Quick Intro</span></a></li><li class="level-2"><a class="final" href="/install/"><span>Installing Apache PredictionIO (incubating)</span></a></li><li class="level-2"><a class="final" href="/start/download/"><span>Downloading an Engine Template</span></a></li><li class="level-2"><a class="final" href="/start/deploy/"><span>Deploying Your First Engine</span></a></li><li class="level-2"><a class="final" href="/start/customize/"><span>Customizing the Engine</span></a></li></ul></li><li class="lev
el-1"><a class="expandible" href="#"><span>Integrating with Your App</span></a><ul><li class="level-2"><a class="final" href="/appintegration/"><span>App Integration Overview</span></a></li><li class="level-2"><a class="expandible" href="/sdk/"><span>List of SDKs</span></a><ul><li class="level-3"><a class="final" href="/sdk/java/"><span>Java & Android SDK</span></a></li><li class="level-3"><a class="final" href="/sdk/php/"><span>PHP SDK</span></a></li><li class="level-3"><a class="final" href="/sdk/python/"><span>Python SDK</span></a></li><li class="level-3"><a class="final" href="/sdk/ruby/"><span>Ruby SDK</span></a></li><li class="level-3"><a class="final" href="/sdk/community/"><span>Community Powered SDKs</span></a></li></ul></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Deploying an Engine</span></a><ul><li class="level-2"><a class="final" href="/deploy/"><span>Deploying as a Web Service</span></a></li><li class="level-2"><a class="final" href="/cli/#en
gine-commands"><span>Engine Command-line Interface</span></a></li><li class="level-2"><a class="final" href="/deploy/engineparams/"><span>Setting Engine Parameters</span></a></li><li class="level-2"><a class="final" href="/deploy/enginevariants/"><span>Deploying Multiple Engine Variants</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Customizing an Engine</span></a><ul><li class="level-2"><a class="final" href="/customize/"><span>Learning DASE</span></a></li><li class="level-2"><a class="final" href="/customize/dase/"><span>Implement DASE</span></a></li><li class="level-2"><a class="final" href="/customize/troubleshooting/"><span>Troubleshooting Engine Development</span></a></li><li class="level-2"><a class="final" href="/api/current/#package"><span>Engine Scala APIs</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Collecting and Analyzing Data</span></a><ul><li class="level-2"><a class="final" href="/datacollection/
"><span>Event Server Overview</span></a></li><li class="level-2"><a class="final" href="/cli/#event-server-commands"><span>Event Server Command-line Interface</span></a></li><li class="level-2"><a class="final" href="/datacollection/eventapi/"><span>Collecting Data with REST/SDKs</span></a></li><li class="level-2"><a class="final" href="/datacollection/eventmodel/"><span>Events Modeling</span></a></li><li class="level-2"><a class="final" href="/datacollection/webhooks/"><span>Unifying Multichannel Data with Webhooks</span></a></li><li class="level-2"><a class="final" href="/datacollection/channel/"><span>Channel</span></a></li><li class="level-2"><a class="final" href="/datacollection/batchimport/"><span>Importing Data in Batch</span></a></li><li class="level-2"><a class="final" href="/datacollection/analytics/"><span>Using Analytics Tools</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Choosing an Algorithm(s)</span></a><ul><li class="level-2"><a c
lass="final" href="/algorithm/"><span>Built-in Algorithm Libraries</span></a></li><li class="level-2"><a class="final" href="/algorithm/switch/"><span>Switching to Another Algorithm</span></a></li><li class="level-2"><a class="final" href="/algorithm/multiple/"><span>Combining Multiple Algorithms</span></a></li><li class="level-2"><a class="final" href="/algorithm/custom/"><span>Adding Your Own Algorithms</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>ML Tuning and Evaluation</span></a><ul><li class="level-2"><a class="final" href="/evaluation/"><span>Overview</span></a></li><li class="level-2"><a class="final" href="/evaluation/paramtuning/"><span>Hyperparameter Tuning</span></a></li><li class="level-2"><a class="final" href="/evaluation/evaluationdashboard/"><span>Evaluation Dashboard</span></a></li><li class="level-2"><a class="final" href="/evaluation/metricchoose/"><span>Choosing Evaluation Metrics</span></a></li><li class="level-2"><a class="
final" href="/evaluation/metricbuild/"><span>Building Evaluation Metrics</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>System Architecture</span></a><ul><li class="level-2"><a class="final" href="/system/"><span>Architecture Overview</span></a></li><li class="level-2"><a class="final" href="/system/anotherdatastore/"><span>Using Another Data Store</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Engine Template Gallery</span></a><ul><li class="level-2"><a class="final" href="http://templates.prediction.io"><span>Browse</span></a></li><li class="level-2"><a class="final" href="/community/submit-template/"><span>Submit your Engine as a Template</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Demo Tutorials</span></a><ul><li class="level-2"><a class="final" href="/demo/tapster/"><span>Comics Recommendation Demo</span></a></li><li class="level-2"><a class="final" href="/demo/community/
"><span>Community Contributed Demo</span></a></li><li class="level-2"><a class="final" href="/demo/textclassification/"><span>Text Classification Engine Tutorial</span></a></li></ul></li><li class="level-1"><a class="expandible" href="/community/"><span>Getting Involved</span></a><ul><li class="level-2"><a class="final" href="/community/contribute-code/"><span>Contribute Code</span></a></li><li class="level-2"><a class="final" href="/community/contribute-documentation/"><span>Contribute Documentation</span></a></li><li class="level-2"><a class="final" href="/community/contribute-sdk/"><span>Contribute a SDK</span></a></li><li class="level-2"><a class="final" href="/community/contribute-webhook/"><span>Contribute a Webhook</span></a></li><li class="level-2"><a class="final" href="/community/projects/"><span>Community Projects</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Getting Help</span></a><ul><li class="level-2"><a class="final" href="/resourc
es/faq/"><span>FAQs</span></a></li><li class="level-2"><a class="final" href="/support/"><span>Community Support</span></a></li><li class="level-2"><a class="final" href="/support/#enterprise-support"><span>Enterprise Support</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Resources</span></a><ul><li class="level-2"><a class="final" href="/resources/intellij/"><span>Developing Engines with IntelliJ IDEA</span></a></li><li class="level-2"><a class="final" href="/resources/upgrade/"><span>Upgrade Instructions</span></a></li><li class="level-2"><a class="final" href="/resources/glossary/"><span>Glossary</span></a></li></ul></li></ul></nav></div><div class="col-md-9 col-sm-12"><div class="content-header hidden-md hidden-lg"><div id="page-title"><h1>Deploying with AWS CloudFormation</h1></div></div><div id="table-of-content-wrapper"><h5>On this page</h5><aside id="table-of-contents"><ul> <li> <a href="#overview">Overview</a> </li> <li> <a href="#step-by-
step">Step-by-Step</a> </li> <li> <a href="#using-the-cluster">Using the Cluster</a> </li> <li> <a href="#scaling-the-cluster">Scaling the Cluster</a> </li> <li> <a href="#support-and-pricing">Support and Pricing</a> </li> </ul> </aside><hr/><a id="edit-page-link" href="https://github.com/apache/incubator-predictionio/tree/livedoc/docs/manual/source/system/deploy-cloudformation.html.md.erb"><img src="/images/icons/edit-pencil-d6c1bb3d.png"/>Edit this page</a></div><div class="content-header hidden-sm hidden-xs"><div id="page-title"><h1>Deploying with AWS CloudFormation</h1></div></div><div class="content"><h2 id='overview' class='header-anchors'>Overview</h2><p>You can scale PredictionIO on AWS with <a href="http://aws.amazon.com/cloudformation/">CloudFormation</a>. Here we have defined a PredictionIO CloudFormation stack that you can deploy a functional, fully distributed PredictionIO cluster in minutes.</p><h3 id='instances' class='header-anchors'>Instances</h3><p>The PredictionIO
CloudFormation stack creates two types of instance: <strong>compute and storage</strong>. By default, the stack will launch <strong>1 compute Instance and 3 Storage instances</strong>.</p><p>The compute instance <em>(ComputeInstance)</em> acts as Spark master. You can launch extra compute instances <em>(ComputeInstanceExtra)</em> by updating the stack. The storage instances <em>(StorageInstance)</em> form the core of the HDFS, ZooKeeper quorum, and HBase storage. Extra storage instances <em>(StorageInstanceExtra)</em> can be added to the cluster by updating the stack. They cannot be removed once they are spinned up.</p><p>PredictionIO Event Server will be launched on all storage instances.</p><h3 id='networking' class='header-anchors'>Networking</h3><p>The stack will automatically create a VPC and a subnet with an Internet gateway. All cluster instances will be launched inside this subnet using a single security group that enables all TCP communications among all instances within t
he same group. All compute instances (including those that are launched after stack creation) will receive public IPs. All core storage instances will receive public Elastic IPs.</p><h2 id='step-by-step' class='header-anchors'>Step-by-Step</h2><p>First, you need to have an active Amazon Web Services account with permissions to use the following services:</p> <ul> <li>Auto Scaling</li> <li>CloudFormation</li> <li>EC2</li> <li>VPC</li> </ul> <h3 id='subscribe-to-predictionio-cluster' class='header-anchors'>Subscribe to PredictionIO Cluster</h3><p>Before you can start using PredictionIO CloudFormation template, you will need to subscribe to PredictionIO Cluster AMI through AWS Marketplace. To subscribe, go to this <a href="https://aws.amazon.com/marketplace/pp/B00S74CY0A">link</a>. Click the yellow "Continue" button on the next screen.</p><p><img alt="AWS Marketplace Subscription Page" src="/images/cloudformation/awsmp-1-609eb919.png"/></p><p>In the next screen, click the &qu
ot;Manual Launch" tab, then select your preferred pricing model. Pick your desired version, then click "Accept Terms".</p><p><img alt="AWS Marketplace Term Page" src="/images/cloudformation/awsmp-2-7dd613ba.png"/></p><p>Once your subscription is in place, you may proceed to the next section.</p><h3 id='start-using-cloudformation' class='header-anchors'>Start Using CloudFormation</h3><p>From your main AWS console, locate CloudFormation and click on it.</p><p><img alt="CloudFormation on AWS Console" src="/images/cloudformation/cf-01-13c7f924.png"/></p><p>This will bring you to the CloudFormation console below.</p><p><img alt="CloudFormation Console" src="/images/cloudformation/cf-02-61cd8e67.png"/></p><h3 id='select-the-predictionio-cloudformation-stack-template' class='header-anchors'>Select the PredictionIO CloudFormation Stack Template</h3><p>From the CloudFormation console, click on the <strong>Create New Stack</strong> blue button as shown above. This will bring up
the <strong>Select Template</strong> screen. Name your stack as you like. Within the <em>Template</em> section, choose <strong>Specify an Amazon S3 template URL</strong>, and put <a href="https://s3.amazonaws.com/cloudformation.prediction.io/0.9.6/pio.json">https://s3.amazonaws.com/cloudformation.prediction.io/0.9.6/pio.json</a> as the value.</p><p><img alt="CloudFormation Stack Template Selection" src="/images/cloudformation/cf-03-d017fa2d.png"/></p><p>Click <strong>Next</strong> when you are done.</p><h3 id='specify-stack-parameters' class='header-anchors'>Specify Stack Parameters</h3><p>The next screen shows the stack parameters. You must enter your AWS SSH key pair. For the other parameters, you can change them to meet your needs or simply use the default values.</p><p><img alt="Stack Parameters" src="/images/cloudformation/cf-04-6b545f50.png"/></p> <table><thead> <tr> <th>Parameter</th> <th>Description</th> </tr> </thead><tbody> <tr> <td>AWS-KeyPair</td> <td>The AWS SSH key pa
ir name that can be used to access all instances in the cluster.</td> </tr> <tr> <td>AvailabilityZone</td> <td>Specify the availability zone that the PredictionIO cluster will be launched in. All instances of the cluster will be launched into the same zone for optimal network performance between one another.</td> </tr> <tr> <td>ComputeInstanceType</td> <td>The EC2 instance type of all compute instances. Memory-optimized EC2 instances are recommended.</td> </tr> <tr> <td>ComputeInstanceExtra</td> <td>Number of extra compute instances besides the core compute instance. This can be increased and decreased.</td> </tr> <tr> <td>StorageInstanceExtra</td> <td>Number of extra storage instances besides core storage instances. <strong>Never decrease this value or you will risk data corruption.</strong></td> </tr> <tr> <td>StorageInstanceExtraSize</td> <td>Size in GB of each extra storage instance. This can be changed when you add an extra storage instance.</td> </tr> <tr> <td>StorageInstanceE
xtraVolumeType</td> <td>The EBS volume type of each extra storage instance. Valid values are <em>standard</em> and <em>gp2</em>. This can be changed when you add an extra storage instance.</td> </tr> <tr> <td>StorageInstanceType</td> <td>The EC2 instance type of all storage instances. General purpose EC2 instances are recommended.</td> </tr> <tr> <td>StorageInstanceSize</td> <td>Size in GB of each core storage instance. This cannot be changed once the cluster is launched.</td> </tr> <tr> <td>StorageInstanceVolumeType</td> <td>The EBS volume type of each core storage instance. Valid values are <em>standard</em> and <em>gp2</em>. This cannot be changed once the cluster is launched.</td> </tr> </tbody></table> <p>Click <strong>Next</strong> when you are done. You will arrive at the <strong>Options</strong> screen. You can skip this step if you do not have other options to specify.</p><p>At the <strong>Review</strong> screen, click <strong>Create</strong> to finish.</p><h2 id='using-the
-cluster' class='header-anchors'>Using the Cluster</h2><p>You should see the following when the cluster is being created after the previous step.</p><p><img alt="Stack Creation" src="/images/cloudformation/cf-05-92ee63c2.png"/></p><p>Once the stack creation has finished, you can click on <strong>Events</strong> and select <strong>Outputs</strong> to arrive to the following screen.</p><p><img alt="Completed Stack" src="/images/cloudformation/cf-06-b36528fa.png"/></p><p>Take note of <strong>PIOComputeMasterPublicIp</strong> and <strong>PIOStorageMasterPublicIp</strong>. We will now access the cluster and make sure everything is in place.</p><div class="alert-message warning"><p>Sometimes the stack is created successfully but not all cluster services would launch due to potential network glitches or system issues within a cluster instance. In this case, simply delete and create the stack again.</p></div><h3 id='verify-compute-instances' class='header-anchors'>Verify Compute Instances</
h3><p>SSH to the master compute instance using the <strong>PIOComputeMasterPublicIp</strong>. In this example, let us assume the IP address be 54.175.145.84, and your private key file be <strong>yourkey.pem</strong>.</p><div class="highlight shell"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1</pre></td><td class="code"><pre><span class="gp">$ </span>ssh -i yourkey.pem -A -L 8080:localhost:8080 ubuntu@54.175.145.84
+</pre></td></tr></tbody></table> </div> <p>Once you are in, point your web browser to <a href="http://localhost:8080">http://localhost:8080</a>. You should see something similar to the following.</p><p><img alt="Example Spark UI" src="/images/cloudformation/spark-019c2cf1.png"/></p><div class="alert-message note"><p>In the example above <strong>NumberOfComputeWorkers</strong> is <strong>2</strong>. This is because the example has 1 compute instance and 1 extra compute instance. If you do not have any extra compute instances, you will see only 1 worker on the above page.</p></div><h3 id='verify-storage-instances' class='header-anchors'>Verify Storage Instances</h3><p>SSH to the storage instance using the <strong>PIOStorageMasterPublicIp</strong>. In this example, let us assume the IP address be 54.175.1.36, and your private key file be <strong>yourkey.pem</strong>.</p><div class="highlight shell"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: rig
ht"><pre class="lineno">1</pre></td><td class="code"><pre><span class="gp">$ </span>ssh -i yourkey.pem -A -L 50070:localhost:50070 -L 16010:localhost:16010 -L 16030:localhost:16030 ubuntu@54.175.1.36
+</pre></td></tr></tbody></table> </div> <p>Once you are in, point your web browser to <a href="http://localhost:50070">http://localhost:50070</a> and click on <strong>Datainstances</strong> at the top menu. You should see the following page.</p><p><img alt="Example HDFS UI" src="/images/cloudformation/hdfs-51f0231f.png"/></p><div class="alert-message warning"><p>All <strong>3 storage instances</strong> must be up for proper operation.</p></div><p>If all <strong>3 storage instances</strong> are working properly, you can then verify HBase by pointing your web browser to <a href="http://localhost:16010">http://localhost:16010</a>. You should see something similar to the following.</p><p><img alt="Example HBase UI" src="/images/cloudformation/hbase-32538c47.png"/></p><p>If you do not specify any extra storage instances, you should see 2 region servers. There should also be 1 backup master.</p><h3 id='running-quick-start' class='header-anchors'>Running Quick Start</h3><p>You can now star
t with the fully-distributed PredictionIO cluster. Let's start with the <a href="/templates/recommendation/quickstart/">recommendation quick start</a> with a few twists.</p> <ol> <li><p>Skip the installation steps and run <code>pio status</code>. You should see everything functional.</p></li> <li><p>Run through the section <strong>Create a Sample App</strong> as described. The installation directory of PredictionIO is <code>/opt/PredictionIO</code>.</p></li> <li><p>Run through the section <strong>Collecting Data</strong> as described, except that you will be connecting to the Event Server at the master core storage instance. Assuming the private IP of the master core storage instance is <code>10.0.0.123</code>, add <code>--url http://10.0.0.123:7070</code> to the <code>import_eventserver.py</code> command.</p></li> <li><p>Copy HBase configuration to the engine template directory. The full path of the configuration file is <code>/opt/hbase-0.98.9-hadoop2/conf/hbase-site.xml</code
>. (This step will not be required in future releases.)</p></li> <li><p>Run through the section <strong>Deploy the Engine as a Service</strong> up to the subsection <strong>Training</strong>. Assuming the private DNS name of the master compute instance is <code>ip-10-0-0-234.ec2.internal</code>, add <code>-- --master spark://ip-10-0-0-234.ec2.internal:7077</code> after the <code>pio train</code> command. This will send the training to the compute cluster instead of the local machine. The Spark master URL must match exactly the one shown on its web UI. Repeat the same steps for subsection <strong>Deploying</strong>, which will create an Engine Server backed by the compute cluster.</p></li> </ol> <h2 id='scaling-the-cluster' class='header-anchors'>Scaling the Cluster</h2><p>As your data size and/or audience grow, you can scale your cluster to handle more workload or decrease turnaround time. In this section, we will provide some general guidelines about when and how to scale your clus
ter with CloudFormation.</p><h3 id='scaling-compute-instances' class='header-anchors'>Scaling Compute Instances</h3><p>You can increase compute instances to reduce training time <em>($pio train)</em> and the time to query an engine server. You can also check the [Spark Master Web UI] to see if you need additional compute power.</p><p>Notice that for compute instances, you can increase or decrease the number of extra compute instances <em>(ComputeInstanceExtra)</em> as much as you like. The extra compute instances will join the master and become slave compute instances as Spark workers.</p><p>Let us begin by adding 2 extra compute instances. At the CloudFormation console, right click on the cluster stack and click on <strong>Update Stack</strong>.</p><p><img alt="Updating Stack to Add Extra Compute Instances" src="/images/cloudformation/compute-1-c572ea84.png"/></p><p>At the <strong>Select Template</strong> screen, make sure <strong>Use existing template</strong> is picked, then clic
k <strong>Next</strong>.</p><p>At the <strong>Specify Parameters</strong> screen, increase the value of <strong>ComputeInstanceExtra</strong> to <strong>2</strong>, then click <strong>Next</strong>.</p><p><img alt="Adding 2 Extra Compute Instances" src="/images/cloudformation/compute-2-f7da8e72.png"/></p><p>At the <strong>Options</strong> screen, leave everything unchanged, and click <strong>Next</strong>.</p><p>At the <strong>Review</strong> screen, make sure <strong>ComputeInstanceExtra</strong> is now updated to <strong>2</strong>. Finish by clicking <strong>Update</strong>.</p><p><img alt="Review Changes of Adding Extra Compute Instances" src="/images/cloudformation/compute-3-ee5fc6a8.png"/></p><p>You will be brought back to the CloudFormation console. You should see the stack status changed to <strong>UPDATE_IN_PROGRESS</strong>.</p><p><img alt="Adding Extra Compute Instances In Progress" src="/images/cloudformation/compute-4-67fe0caa.png"/></p><p>Once the status become <strong
>UPDATE_COMPLETED</strong>, you will have 2 extra compute instances. Notice that during the update, your cluster is still functional and any existing work will not be affected. If you are downscaling, existing work might be affected during the update process.</p><h3 id='scaling-storage-instances' class='header-anchors'>Scaling Storage Instances</h3><p>You can scale your storage instances when you are about to run out of space. You can check your storage usage at the [Hadoop NameNode web UI].</p><div class="alert-message warning"><p>For storage instances, you can only increase the number of extra storage instances <em>(StorageInstanceExtra)</em> within the bounds of AWS EC2 limits. Decreasing the instances will risk data corruption.</p></div><p>Let us begin by adding 2 extra storage instances. At the CloudFormation console, right click on the cluster stack and click on <strong>Update Stack</strong>.</p><p><img alt="Updating Stack to Add Extra Storage Instances" src="/images/cloudform
ation/compute-1-c572ea84.png"/></p><p>At the <strong>Select Template</strong> screen, make sure <strong>Use existing template</strong> is picked, then click <strong>Next</strong>.</p><p>At the <strong>Specify Parameters</strong> screen, increase the value of <strong>StorageInstanceExtra</strong> to <strong>2</strong>, and set the value of <strong>StorageInstanceExtraSize</strong> to <strong>100</strong>, then click <strong>Next</strong>. Notice that whenever you add an extra storage instance, you can change its size to a new value. The new size will not affect existing storage instances and your data will be safe.</p><p><img alt="Adding 2 Extra Storage Instances" src="/images/cloudformation/storage-1-ca3ae3a6.png"/></p><p>At the <strong>Options</strong> screen, leave everything unchanged, and click <strong>Next</strong>.</p><p>At the <strong>Review</strong> screen, make sure <strong>StorageInstanceExtra</strong> is now updated to <strong>2</strong>, and <strong>StorageInstanceExtraS
ize</strong> is updated to <strong>100</strong>. Finish by clicking <strong>Update</strong>.</p><p><img alt="Review Changes of Adding Extra Storage Instances" src="/images/cloudformation/storage-2-9395c9f2.png"/></p><p>You will be brought back to the CloudFormation console. You should see the stack status changed to <strong>UPDATE_IN_PROGRESS</strong>.</p><p><img alt="Adding Extra Compute Instances In Progress" src="/images/cloudformation/compute-4-67fe0caa.png"/></p><p>Once the status become <strong>UPDATE_COMPLETED</strong>, you will have 2 extra storage instances. Notice that during the up-scaling update, your cluster is still functional and existing work will not be affected. They may be affected during downscale.</p><h2 id='support-and-pricing' class='header-anchors'>Support and Pricing</h2><p>PredictionIO Cluster comes with Enterprise Support. For pricing and support details, please contact <a href="mailto:support@prediction.io">support@prediction.io</a>.</p></div></div></div>
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<div class="row"><div class="col-md-9 col-sm-11 col-xs-11"><div class="hidden-md hidden-lg" id="mobile-page-heading-wrapper"><p>PredictionIO Docs</p><h4>Architecture Overview</h4></div><h4 class="hidden-sm hidden-xs">PredictionIO Docs</h4></div><div class="col-md-3 col-sm-1 col-xs-1 hidden-md hidden-lg"><img id="left-menu-indicator" src="/images/icons/down-arrow-dfe9f7fe.png"/></div><div class="col-md-3 col-sm-12 col-xs-12 swiftype-wrapper"><div class="swiftype"><form class="search-form"><img class="search-box-toggler hidden-xs hidden-sm" src="/images/icons/search-glass-704bd4ff.png"/><div class="search-box"><img src="/images/icons/search-glass-704bd4ff.png"/><input type="text" id="st-search-input" class="st-search-input" placeholder="Search Doc..."/></div><img class="swiftype-row-hider hidden-md hidden-lg" src="/images/icons/drawer-toggle-active-fcbef12a.png"/></form></div></div><div class="mobile-left-menu-toggler hidden-md hidden-lg"></div></div></div></div><div id="page" class="
container-fluid"><div class="row"><div id="left-menu-wrapper" class="col-md-3"><nav id="nav-main"><ul><li class="level-1"><a class="expandible" href="/"><span>Apache PredictionIO (incubating) Documentation</span></a><ul><li class="level-2"><a class="final" href="/"><span>Welcome to Apache PredictionIO (incubating)</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Getting Started</span></a><ul><li class="level-2"><a class="final" href="/start/"><span>A Quick Intro</span></a></li><li class="level-2"><a class="final" href="/install/"><span>Installing Apache PredictionIO (incubating)</span></a></li><li class="level-2"><a class="final" href="/start/download/"><span>Downloading an Engine Template</span></a></li><li class="level-2"><a class="final" href="/start/deploy/"><span>Deploying Your First Engine</span></a></li><li class="level-2"><a class="final" href="/start/customize/"><span>Customizing the Engine</span></a></li></ul></li><li class="level-1"><a cla
ss="expandible" href="#"><span>Integrating with Your App</span></a><ul><li class="level-2"><a class="final" href="/appintegration/"><span>App Integration Overview</span></a></li><li class="level-2"><a class="expandible" href="/sdk/"><span>List of SDKs</span></a><ul><li class="level-3"><a class="final" href="/sdk/java/"><span>Java & Android SDK</span></a></li><li class="level-3"><a class="final" href="/sdk/php/"><span>PHP SDK</span></a></li><li class="level-3"><a class="final" href="/sdk/python/"><span>Python SDK</span></a></li><li class="level-3"><a class="final" href="/sdk/ruby/"><span>Ruby SDK</span></a></li><li class="level-3"><a class="final" href="/sdk/community/"><span>Community Powered SDKs</span></a></li></ul></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Deploying an Engine</span></a><ul><li class="level-2"><a class="final" href="/deploy/"><span>Deploying as a Web Service</span></a></li><li class="level-2"><a class="final" href="/cli/#engine-command
s"><span>Engine Command-line Interface</span></a></li><li class="level-2"><a class="final" href="/deploy/engineparams/"><span>Setting Engine Parameters</span></a></li><li class="level-2"><a class="final" href="/deploy/enginevariants/"><span>Deploying Multiple Engine Variants</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Customizing an Engine</span></a><ul><li class="level-2"><a class="final" href="/customize/"><span>Learning DASE</span></a></li><li class="level-2"><a class="final" href="/customize/dase/"><span>Implement DASE</span></a></li><li class="level-2"><a class="final" href="/customize/troubleshooting/"><span>Troubleshooting Engine Development</span></a></li><li class="level-2"><a class="final" href="/api/current/#package"><span>Engine Scala APIs</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Collecting and Analyzing Data</span></a><ul><li class="level-2"><a class="final" href="/datacollection/"><span>Even
t Server Overview</span></a></li><li class="level-2"><a class="final" href="/cli/#event-server-commands"><span>Event Server Command-line Interface</span></a></li><li class="level-2"><a class="final" href="/datacollection/eventapi/"><span>Collecting Data with REST/SDKs</span></a></li><li class="level-2"><a class="final" href="/datacollection/eventmodel/"><span>Events Modeling</span></a></li><li class="level-2"><a class="final" href="/datacollection/webhooks/"><span>Unifying Multichannel Data with Webhooks</span></a></li><li class="level-2"><a class="final" href="/datacollection/channel/"><span>Channel</span></a></li><li class="level-2"><a class="final" href="/datacollection/batchimport/"><span>Importing Data in Batch</span></a></li><li class="level-2"><a class="final" href="/datacollection/analytics/"><span>Using Analytics Tools</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Choosing an Algorithm(s)</span></a><ul><li class="level-2"><a class="final"
href="/algorithm/"><span>Built-in Algorithm Libraries</span></a></li><li class="level-2"><a class="final" href="/algorithm/switch/"><span>Switching to Another Algorithm</span></a></li><li class="level-2"><a class="final" href="/algorithm/multiple/"><span>Combining Multiple Algorithms</span></a></li><li class="level-2"><a class="final" href="/algorithm/custom/"><span>Adding Your Own Algorithms</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>ML Tuning and Evaluation</span></a><ul><li class="level-2"><a class="final" href="/evaluation/"><span>Overview</span></a></li><li class="level-2"><a class="final" href="/evaluation/paramtuning/"><span>Hyperparameter Tuning</span></a></li><li class="level-2"><a class="final" href="/evaluation/evaluationdashboard/"><span>Evaluation Dashboard</span></a></li><li class="level-2"><a class="final" href="/evaluation/metricchoose/"><span>Choosing Evaluation Metrics</span></a></li><li class="level-2"><a class="final" href=
"/evaluation/metricbuild/"><span>Building Evaluation Metrics</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>System Architecture</span></a><ul><li class="level-2"><a class="final active" href="/system/"><span>Architecture Overview</span></a></li><li class="level-2"><a class="final" href="/system/anotherdatastore/"><span>Using Another Data Store</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Engine Template Gallery</span></a><ul><li class="level-2"><a class="final" href="http://templates.prediction.io"><span>Browse</span></a></li><li class="level-2"><a class="final" href="/community/submit-template/"><span>Submit your Engine as a Template</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Demo Tutorials</span></a><ul><li class="level-2"><a class="final" href="/demo/tapster/"><span>Comics Recommendation Demo</span></a></li><li class="level-2"><a class="final" href="/demo/community/"><sp
an>Community Contributed Demo</span></a></li><li class="level-2"><a class="final" href="/demo/textclassification/"><span>Text Classification Engine Tutorial</span></a></li></ul></li><li class="level-1"><a class="expandible" href="/community/"><span>Getting Involved</span></a><ul><li class="level-2"><a class="final" href="/community/contribute-code/"><span>Contribute Code</span></a></li><li class="level-2"><a class="final" href="/community/contribute-documentation/"><span>Contribute Documentation</span></a></li><li class="level-2"><a class="final" href="/community/contribute-sdk/"><span>Contribute a SDK</span></a></li><li class="level-2"><a class="final" href="/community/contribute-webhook/"><span>Contribute a Webhook</span></a></li><li class="level-2"><a class="final" href="/community/projects/"><span>Community Projects</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Getting Help</span></a><ul><li class="level-2"><a class="final" href="/resources/fa
q/"><span>FAQs</span></a></li><li class="level-2"><a class="final" href="/support/"><span>Community Support</span></a></li><li class="level-2"><a class="final" href="/support/#enterprise-support"><span>Enterprise Support</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Resources</span></a><ul><li class="level-2"><a class="final" href="/resources/intellij/"><span>Developing Engines with IntelliJ IDEA</span></a></li><li class="level-2"><a class="final" href="/resources/upgrade/"><span>Upgrade Instructions</span></a></li><li class="level-2"><a class="final" href="/resources/glossary/"><span>Glossary</span></a></li></ul></li></ul></nav></div><div class="col-md-9 col-sm-12"><div class="content-header hidden-md hidden-lg"><div id="breadcrumbs" class="hidden-sm hidden xs"><ul><li><a href="#">System Architecture</a><span class="spacer">></span></li><li><span class="last">Architecture Overview</span></li></ul></div><div id="page-title"><h1>System Architect
ure and Dependencies</h1></div></div><div id="table-of-content-wrapper"><a id="edit-page-link" href="https://github.com/apache/incubator-predictionio/tree/livedoc/docs/manual/source/system/index.html.md"><img src="/images/icons/edit-pencil-d6c1bb3d.png"/>Edit this page</a></div><div class="content-header hidden-sm hidden-xs"><div id="breadcrumbs" class="hidden-sm hidden xs"><ul><li><a href="#">System Architecture</a><span class="spacer">></span></li><li><span class="last">Architecture Overview</span></li></ul></div><div id="page-title"><h1>System Architecture and Dependencies</h1></div></div><div class="content"><p>During the <a href="/install">installation</a>, you have installed the following software:</p> <ul> <li>Apache Hadoop 2.4.0 (required only if YARN and HDFS are needed)</li> <li>Apache HBase 0.98.6</li> <li>Apache Spark 1.2.0 for Hadoop 2.4</li> <li>Elasticsearch 1.4.0</li> </ul> <p>This section explains how they are used in PredictionIO.</p><p><img alt="PredictionIO Sy
stems" src="/images/0.8-engine-data-pipeline-49b451b4.png"/></p><p><strong>HBase</strong>: Event Server uses Apache HBase as the data store. It stores imported events. If you are not using the PredictionIO Event Server, you do not need to install HBase.</p><p><strong>Apache Spark</strong>: Spark is a large-scale data processing engine that powers the algorithm, training, and serving processing.</p><p>A spark algorithm is different from conventional single machine algorithm in a way that spark algorithms use the <a href="http://spark.apache.org/docs/1.0.1/programming-guide.html#resilient-distributed-datasets-rdds">RDD</a> abstraction as its primary data type. PredictionIO framework natively support both RDD-based algorithms and traditional single-machine algorithms.</p><p><strong>HDFS</strong>: The output of training has two parts: a model and its meta-data. The model is then stored in HDFS or a local file system.</p><p><strong>Elasticsearch</strong>: It stores metadata such as model
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<div class="row"><div class="col-md-9 col-sm-11 col-xs-11"><div class="hidden-md hidden-lg" id="mobile-page-heading-wrapper"><p>PredictionIO Docs</p><h4></h4></div><h4 class="hidden-sm hidden-xs">PredictionIO Docs</h4></div><div class="col-md-3 col-sm-1 col-xs-1 hidden-md hidden-lg"><img id="left-menu-indicator" src="/images/icons/down-arrow-dfe9f7fe.png"/></div><div class="col-md-3 col-sm-12 col-xs-12 swiftype-wrapper"><div class="swiftype"><form class="search-form"><img class="search-box-toggler hidden-xs hidden-sm" src="/images/icons/search-glass-704bd4ff.png"/><div class="search-box"><img src="/images/icons/search-glass-704bd4ff.png"/><input type="text" id="st-search-input" class="st-search-input" placeholder="Search Doc..."/></div><img class="swiftype-row-hider hidden-md hidden-lg" src="/images/icons/drawer-toggle-active-fcbef12a.png"/></form></div></div><div class="mobile-left-menu-toggler hidden-md hidden-lg"></div></div></div></div><div id="page" class="container-fluid"><div
class="row"><div id="left-menu-wrapper" class="col-md-3"><nav id="nav-main"><ul><li class="level-1"><a class="expandible" href="/"><span>Apache PredictionIO (incubating) Documentation</span></a><ul><li class="level-2"><a class="final" href="/"><span>Welcome to Apache PredictionIO (incubating)</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Getting Started</span></a><ul><li class="level-2"><a class="final" href="/start/"><span>A Quick Intro</span></a></li><li class="level-2"><a class="final" href="/install/"><span>Installing Apache PredictionIO (incubating)</span></a></li><li class="level-2"><a class="final" href="/start/download/"><span>Downloading an Engine Template</span></a></li><li class="level-2"><a class="final" href="/start/deploy/"><span>Deploying Your First Engine</span></a></li><li class="level-2"><a class="final" href="/start/customize/"><span>Customizing the Engine</span></a></li></ul></li><li class="level-1"><a class="expandible" href=
"#"><span>Integrating with Your App</span></a><ul><li class="level-2"><a class="final" href="/appintegration/"><span>App Integration Overview</span></a></li><li class="level-2"><a class="expandible" href="/sdk/"><span>List of SDKs</span></a><ul><li class="level-3"><a class="final" href="/sdk/java/"><span>Java & Android SDK</span></a></li><li class="level-3"><a class="final" href="/sdk/php/"><span>PHP SDK</span></a></li><li class="level-3"><a class="final" href="/sdk/python/"><span>Python SDK</span></a></li><li class="level-3"><a class="final" href="/sdk/ruby/"><span>Ruby SDK</span></a></li><li class="level-3"><a class="final" href="/sdk/community/"><span>Community Powered SDKs</span></a></li></ul></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Deploying an Engine</span></a><ul><li class="level-2"><a class="final" href="/deploy/"><span>Deploying as a Web Service</span></a></li><li class="level-2"><a class="final" href="/cli/#engine-commands"><span>Engine Comma
nd-line Interface</span></a></li><li class="level-2"><a class="final" href="/deploy/engineparams/"><span>Setting Engine Parameters</span></a></li><li class="level-2"><a class="final" href="/deploy/enginevariants/"><span>Deploying Multiple Engine Variants</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Customizing an Engine</span></a><ul><li class="level-2"><a class="final" href="/customize/"><span>Learning DASE</span></a></li><li class="level-2"><a class="final" href="/customize/dase/"><span>Implement DASE</span></a></li><li class="level-2"><a class="final" href="/customize/troubleshooting/"><span>Troubleshooting Engine Development</span></a></li><li class="level-2"><a class="final" href="/api/current/#package"><span>Engine Scala APIs</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Collecting and Analyzing Data</span></a><ul><li class="level-2"><a class="final" href="/datacollection/"><span>Event Server Overview</sp
an></a></li><li class="level-2"><a class="final" href="/cli/#event-server-commands"><span>Event Server Command-line Interface</span></a></li><li class="level-2"><a class="final" href="/datacollection/eventapi/"><span>Collecting Data with REST/SDKs</span></a></li><li class="level-2"><a class="final" href="/datacollection/eventmodel/"><span>Events Modeling</span></a></li><li class="level-2"><a class="final" href="/datacollection/webhooks/"><span>Unifying Multichannel Data with Webhooks</span></a></li><li class="level-2"><a class="final" href="/datacollection/channel/"><span>Channel</span></a></li><li class="level-2"><a class="final" href="/datacollection/batchimport/"><span>Importing Data in Batch</span></a></li><li class="level-2"><a class="final" href="/datacollection/analytics/"><span>Using Analytics Tools</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Choosing an Algorithm(s)</span></a><ul><li class="level-2"><a class="final" href="/algorithm/"><
span>Built-in Algorithm Libraries</span></a></li><li class="level-2"><a class="final" href="/algorithm/switch/"><span>Switching to Another Algorithm</span></a></li><li class="level-2"><a class="final" href="/algorithm/multiple/"><span>Combining Multiple Algorithms</span></a></li><li class="level-2"><a class="final" href="/algorithm/custom/"><span>Adding Your Own Algorithms</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>ML Tuning and Evaluation</span></a><ul><li class="level-2"><a class="final" href="/evaluation/"><span>Overview</span></a></li><li class="level-2"><a class="final" href="/evaluation/paramtuning/"><span>Hyperparameter Tuning</span></a></li><li class="level-2"><a class="final" href="/evaluation/evaluationdashboard/"><span>Evaluation Dashboard</span></a></li><li class="level-2"><a class="final" href="/evaluation/metricchoose/"><span>Choosing Evaluation Metrics</span></a></li><li class="level-2"><a class="final" href="/evaluation/metricbu
ild/"><span>Building Evaluation Metrics</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>System Architecture</span></a><ul><li class="level-2"><a class="final" href="/system/"><span>Architecture Overview</span></a></li><li class="level-2"><a class="final" href="/system/anotherdatastore/"><span>Using Another Data Store</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Engine Template Gallery</span></a><ul><li class="level-2"><a class="final" href="http://templates.prediction.io"><span>Browse</span></a></li><li class="level-2"><a class="final" href="/community/submit-template/"><span>Submit your Engine as a Template</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Demo Tutorials</span></a><ul><li class="level-2"><a class="final" href="/demo/tapster/"><span>Comics Recommendation Demo</span></a></li><li class="level-2"><a class="final" href="/demo/community/"><span>Community Contributed Dem
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<div class="row"><div class="col-md-9 col-sm-11 col-xs-11"><div class="hidden-md hidden-lg" id="mobile-page-heading-wrapper"><p>PredictionIO Docs</p><h4>Using Alternative Algorithm</h4></div><h4 class="hidden-sm hidden-xs">PredictionIO Docs</h4></div><div class="col-md-3 col-sm-1 col-xs-1 hidden-md hidden-lg"><img id="left-menu-indicator" src="/images/icons/down-arrow-dfe9f7fe.png"/></div><div class="col-md-3 col-sm-12 col-xs-12 swiftype-wrapper"><div class="swiftype"><form class="search-form"><img class="search-box-toggler hidden-xs hidden-sm" src="/images/icons/search-glass-704bd4ff.png"/><div class="search-box"><img src="/images/icons/search-glass-704bd4ff.png"/><input type="text" id="st-search-input" class="st-search-input" placeholder="Search Doc..."/></div><img class="swiftype-row-hider hidden-md hidden-lg" src="/images/icons/drawer-toggle-active-fcbef12a.png"/></form></div></div><div class="mobile-left-menu-toggler hidden-md hidden-lg"></div></div></div></div><div id="page" c
lass="container-fluid"><div class="row"><div id="left-menu-wrapper" class="col-md-3"><nav id="nav-main"><ul><li class="level-1"><a class="expandible" href="/"><span>Apache PredictionIO (incubating) Documentation</span></a><ul><li class="level-2"><a class="final" href="/"><span>Welcome to Apache PredictionIO (incubating)</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Getting Started</span></a><ul><li class="level-2"><a class="final" href="/start/"><span>A Quick Intro</span></a></li><li class="level-2"><a class="final" href="/install/"><span>Installing Apache PredictionIO (incubating)</span></a></li><li class="level-2"><a class="final" href="/start/download/"><span>Downloading an Engine Template</span></a></li><li class="level-2"><a class="final" href="/start/deploy/"><span>Deploying Your First Engine</span></a></li><li class="level-2"><a class="final" href="/start/customize/"><span>Customizing the Engine</span></a></li></ul></li><li class="level-1">
<a class="expandible" href="#"><span>Integrating with Your App</span></a><ul><li class="level-2"><a class="final" href="/appintegration/"><span>App Integration Overview</span></a></li><li class="level-2"><a class="expandible" href="/sdk/"><span>List of SDKs</span></a><ul><li class="level-3"><a class="final" href="/sdk/java/"><span>Java & Android SDK</span></a></li><li class="level-3"><a class="final" href="/sdk/php/"><span>PHP SDK</span></a></li><li class="level-3"><a class="final" href="/sdk/python/"><span>Python SDK</span></a></li><li class="level-3"><a class="final" href="/sdk/ruby/"><span>Ruby SDK</span></a></li><li class="level-3"><a class="final" href="/sdk/community/"><span>Community Powered SDKs</span></a></li></ul></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Deploying an Engine</span></a><ul><li class="level-2"><a class="final" href="/deploy/"><span>Deploying as a Web Service</span></a></li><li class="level-2"><a class="final" href="/cli/#engine-c
ommands"><span>Engine Command-line Interface</span></a></li><li class="level-2"><a class="final" href="/deploy/engineparams/"><span>Setting Engine Parameters</span></a></li><li class="level-2"><a class="final" href="/deploy/enginevariants/"><span>Deploying Multiple Engine Variants</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Customizing an Engine</span></a><ul><li class="level-2"><a class="final" href="/customize/"><span>Learning DASE</span></a></li><li class="level-2"><a class="final" href="/customize/dase/"><span>Implement DASE</span></a></li><li class="level-2"><a class="final" href="/customize/troubleshooting/"><span>Troubleshooting Engine Development</span></a></li><li class="level-2"><a class="final" href="/api/current/#package"><span>Engine Scala APIs</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Collecting and Analyzing Data</span></a><ul><li class="level-2"><a class="final" href="/datacollection/"><spa
n>Event Server Overview</span></a></li><li class="level-2"><a class="final" href="/cli/#event-server-commands"><span>Event Server Command-line Interface</span></a></li><li class="level-2"><a class="final" href="/datacollection/eventapi/"><span>Collecting Data with REST/SDKs</span></a></li><li class="level-2"><a class="final" href="/datacollection/eventmodel/"><span>Events Modeling</span></a></li><li class="level-2"><a class="final" href="/datacollection/webhooks/"><span>Unifying Multichannel Data with Webhooks</span></a></li><li class="level-2"><a class="final" href="/datacollection/channel/"><span>Channel</span></a></li><li class="level-2"><a class="final" href="/datacollection/batchimport/"><span>Importing Data in Batch</span></a></li><li class="level-2"><a class="final" href="/datacollection/analytics/"><span>Using Analytics Tools</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Choosing an Algorithm(s)</span></a><ul><li class="level-2"><a class="
final" href="/algorithm/"><span>Built-in Algorithm Libraries</span></a></li><li class="level-2"><a class="final" href="/algorithm/switch/"><span>Switching to Another Algorithm</span></a></li><li class="level-2"><a class="final" href="/algorithm/multiple/"><span>Combining Multiple Algorithms</span></a></li><li class="level-2"><a class="final" href="/algorithm/custom/"><span>Adding Your Own Algorithms</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>ML Tuning and Evaluation</span></a><ul><li class="level-2"><a class="final" href="/evaluation/"><span>Overview</span></a></li><li class="level-2"><a class="final" href="/evaluation/paramtuning/"><span>Hyperparameter Tuning</span></a></li><li class="level-2"><a class="final" href="/evaluation/evaluationdashboard/"><span>Evaluation Dashboard</span></a></li><li class="level-2"><a class="final" href="/evaluation/metricchoose/"><span>Choosing Evaluation Metrics</span></a></li><li class="level-2"><a class="final"
href="/evaluation/metricbuild/"><span>Building Evaluation Metrics</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>System Architecture</span></a><ul><li class="level-2"><a class="final" href="/system/"><span>Architecture Overview</span></a></li><li class="level-2"><a class="final" href="/system/anotherdatastore/"><span>Using Another Data Store</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Engine Template Gallery</span></a><ul><li class="level-2"><a class="final" href="http://templates.prediction.io"><span>Browse</span></a></li><li class="level-2"><a class="final" href="/community/submit-template/"><span>Submit your Engine as a Template</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Demo Tutorials</span></a><ul><li class="level-2"><a class="final" href="/demo/tapster/"><span>Comics Recommendation Demo</span></a></li><li class="level-2"><a class="final" href="/demo/community/"><spa
n>Community Contributed Demo</span></a></li><li class="level-2"><a class="final" href="/demo/textclassification/"><span>Text Classification Engine Tutorial</span></a></li></ul></li><li class="level-1"><a class="expandible" href="/community/"><span>Getting Involved</span></a><ul><li class="level-2"><a class="final" href="/community/contribute-code/"><span>Contribute Code</span></a></li><li class="level-2"><a class="final" href="/community/contribute-documentation/"><span>Contribute Documentation</span></a></li><li class="level-2"><a class="final" href="/community/contribute-sdk/"><span>Contribute a SDK</span></a></li><li class="level-2"><a class="final" href="/community/contribute-webhook/"><span>Contribute a Webhook</span></a></li><li class="level-2"><a class="final" href="/community/projects/"><span>Community Projects</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Getting Help</span></a><ul><li class="level-2"><a class="final" href="/resources/faq
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RandomForestAlgorithm.scala</a> </li> <li> <a href="#define-the-algorithm-class-and-parameters">Define the algorithm class and parameters</a> </li> <li> <a href="#update-engine-scala">Update Engine.scala</a> </li> <li> <a href="#update-engine-json">Update engine.json</a> </li> </ul> </aside><hr/><a id="edit-page-link" href="https://github.com/apache/incubator-predictionio/tree/livedoc/docs/manual/source/templates/classification/add-algorithm.html.md"><img src="/images/icons/edit-pencil-d6c1bb3d.png"/>Edit this page</a></div><div class="content-header hidden-sm hidden-xs"><div id="page-title"><h1>Using Alternative Algorithm</h1></div></div><div class="content"><p>The classification template uses the Naive Bayes algorithm by default. You can easily add and use other MLlib classification algorithms. The following will demonstrate how to add the <a href="https://spark.apache.org/docs/latest/mllib-ensembles.html">MLlib Random Forests algorithm</a> into the engine.</p><h2 id='create-a-ne
w-file-randomforestalgorithm.scala' class='header-anchors'>Create a new file RandomForestAlgorithm.scala</h2><p>Locate <code>src/main/scala/NaiveBayesAlgorithm.scala</code> under your engine directory, which should be /MyClassification if you are following the <a href="/templates/classification/quickstart/">Classification QuickStart</a>. Copy <code>NaiveBayesAlgorithm.scala</code> and create a new file <code>RandomForestAlgorithm.scala</code>. You will modify this file and follow the instructions below to define a new RandomForestAlgorithm class.</p><h2 id='define-the-algorithm-class-and-parameters' class='header-anchors'>Define the algorithm class and parameters</h2><p>In 'RandomForestAlgorithm.scala', import the MLlib Random Forests algorithm by changing the following lines:</p><p>Original</p><div class="highlight scala"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1
+2</pre></td><td class="code"><pre><span class="k">import</span> <span class="nn">org.apache.spark.mllib.classification.NaiveBayes</span>
+<span class="k">import</span> <span class="nn">org.apache.spark.mllib.classification.NaiveBayesModel</span>
+</pre></td></tr></tbody></table> </div> <p>Change to:</p><div class="highlight scala"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1
+2</pre></td><td class="code"><pre><span class="k">import</span> <span class="nn">org.apache.spark.mllib.tree.RandomForest</span> <span class="c1">// CHANGED
+</span><span class="k">import</span> <span class="nn">org.apache.spark.mllib.tree.model.RandomForestModel</span> <span class="c1">// CHANGED
+</span></pre></td></tr></tbody></table> </div> <p>These are the necessary classes in order to use the MLLib's Random Forest algporithm.</p><p>Modify the <code>AlgorithmParams</code> class for the Random Forest algorithm:</p><div class="highlight scala"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1
+2
+3
+4
+5
+6
+7
+8
+9</pre></td><td class="code"><pre><span class="c1">// CHANGED
+</span><span class="k">case</span> <span class="k">class</span> <span class="nc">RandomForestAlgorithmParams</span><span class="o">(</span>
+ <span class="n">numClasses</span><span class="k">:</span> <span class="kt">Int</span><span class="o">,</span>
+ <span class="n">numTrees</span><span class="k">:</span> <span class="kt">Int</span><span class="o">,</span>
+ <span class="n">featureSubsetStrategy</span><span class="k">:</span> <span class="kt">String</span><span class="o">,</span>
+ <span class="n">impurity</span><span class="k">:</span> <span class="kt">String</span><span class="o">,</span>
+ <span class="n">maxDepth</span><span class="k">:</span> <span class="kt">Int</span><span class="o">,</span>
+ <span class="n">maxBins</span><span class="k">:</span> <span class="kt">Int</span>
+<span class="o">)</span> <span class="k">extends</span> <span class="nc">Params</span>
+</pre></td></tr></tbody></table> </div> <p>This class defines the parameters of the Random Forest algorithm (which later you can specify the value in engine.json). Please refer to <a href="https://spark.apache.org/docs/latest/mllib-ensembles.html">MLlib documentation</a> for the description and usage of these parameters.</p><p>Modify the <code>NaiveBayesAlgorithm</code> class to <code>RandomForestAlgorithm</code>. The changes are:</p> <ul> <li>The new <code>RandomForestAlgorithmParams</code> class is used as parameter.</li> <li><code>RandomForestModel</code> is used in type parameter. This is the model returned by the Random Forest algorithm.</li> <li>the <code>train()</code> function is modified and it returns the <code>RandomForestModel</code> instead of <code>NaiveBayesModel</code>.</li> <li>the <code>predict()</code> function takes the <code>RandomForestModel</code> as input.</li> </ul> <div class="highlight scala"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl
" style="text-align: right"><pre class="lineno">1
+2
+3
+4
+5
+6
+7
+8
+9
+10
+11
+12
+13
+14
+15
+16
+17
+18
+19
+20
+21
+22
+23
+24
+25
+26
+27
+28
+29
+30
+31
+32
+33</pre></td><td class="code"><pre><span class="c1">// extends P2LAlgorithm because the MLlib's RandomForestModel doesn't
+// contain RDD.
+</span><span class="k">class</span> <span class="nc">RandomForestAlgorithm</span><span class="o">(</span><span class="k">val</span> <span class="n">ap</span><span class="k">:</span> <span class="kt">RandomForestAlgorithmParams</span><span class="o">)</span> <span class="c1">// CHANGED
+</span> <span class="k">extends</span> <span class="n">P2LAlgorithm</span><span class="o">[</span><span class="kt">PreparedData</span>, <span class="kt">RandomForestModel</span>, <span class="kt">//</span> <span class="kt">CHANGED</span>
+ <span class="kt">Query</span>, <span class="kt">PredictedResult</span><span class="o">]</span> <span class="o">{</span>
+
+ <span class="c1">// CHANGED
+</span> <span class="k">def</span> <span class="n">train</span><span class="o">(</span><span class="n">sc</span><span class="k">:</span> <span class="kt">SparkContext</span><span class="o">,</span> <span class="n">data</span><span class="k">:</span> <span class="kt">PreparedData</span><span class="o">)</span><span class="k">:</span> <span class="kt">RandomForestModel</span> <span class="o">=</span> <span class="o">{</span>
+ <span class="c1">// CHANGED
+</span> <span class="c1">// Empty categoricalFeaturesInfo indicates all features are continuous.
+</span> <span class="k">val</span> <span class="n">categoricalFeaturesInfo</span> <span class="k">=</span> <span class="nc">Map</span><span class="o">[</span><span class="kt">Int</span>, <span class="kt">Int</span><span class="o">]()</span>
+ <span class="nc">RandomForest</span><span class="o">.</span><span class="n">trainClassifier</span><span class="o">(</span>
+ <span class="n">data</span><span class="o">.</span><span class="n">labeledPoints</span><span class="o">,</span>
+ <span class="n">ap</span><span class="o">.</span><span class="n">numClasses</span><span class="o">,</span>
+ <span class="n">categoricalFeaturesInfo</span><span class="o">,</span>
+ <span class="n">ap</span><span class="o">.</span><span class="n">numTrees</span><span class="o">,</span>
+ <span class="n">ap</span><span class="o">.</span><span class="n">featureSubsetStrategy</span><span class="o">,</span>
+ <span class="n">ap</span><span class="o">.</span><span class="n">impurity</span><span class="o">,</span>
+ <span class="n">ap</span><span class="o">.</span><span class="n">maxDepth</span><span class="o">,</span>
+ <span class="n">ap</span><span class="o">.</span><span class="n">maxBins</span><span class="o">)</span>
+ <span class="o">}</span>
+
+ <span class="k">def</span> <span class="n">predict</span><span class="o">(</span>
+ <span class="n">model</span><span class="k">:</span> <span class="kt">RandomForestModel</span><span class="o">,</span> <span class="c1">// CHANGED
+</span> <span class="n">query</span><span class="k">:</span> <span class="kt">Query</span><span class="o">)</span><span class="k">:</span> <span class="kt">PredictedResult</span> <span class="o">=</span> <span class="o">{</span>
+
+ <span class="k">val</span> <span class="n">label</span> <span class="k">=</span> <span class="n">model</span><span class="o">.</span><span class="n">predict</span><span class="o">(</span><span class="nc">Vectors</span><span class="o">.</span><span class="n">dense</span><span class="o">(</span>
+ <span class="n">query</span><span class="o">.</span><span class="n">attr0</span><span class="o">,</span> <span class="n">query</span><span class="o">.</span><span class="n">attr1</span><span class="o">,</span> <span class="n">query</span><span class="o">.</span><span class="n">attr2</span>
+ <span class="o">))</span>
+ <span class="k">new</span> <span class="nc">PredictedResult</span><span class="o">(</span><span class="n">label</span><span class="o">)</span>
+ <span class="o">}</span>
+
+<span class="o">}</span>
+</pre></td></tr></tbody></table> </div> <p>Note that the MLlib Random Forest algorithm takes the same training data as the Navie Bayes algoithm (ie, RDD[LabeledPoint]) so you don't need to modify the <code>DataSource</code>, <code>TrainigData</code> and <code>PreparedData</code> classes. If the new algoritm to be added requires different types of training data, then you need to modify these classes accordingly to accomodate your new algorithm.</p><h2 id='update-engine.scala' class='header-anchors'>Update Engine.scala</h2><p>Modify the EngineFactory to add the new algorithm class <code>RandomForestAlgorithm</code> you just defined and give it a name <code>"randomforest"</code>. The name will be used in <code>engne.json</code> to specify which algorithm to use.</p><div class="highlight scala"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1
+2
+3
+4
+5
+6
+7
+8
+9
+10</pre></td><td class="code"><pre><span class="k">object</span> <span class="nc">ClassificationEngine</span> <span class="k">extends</span> <span class="nc">IEngineFactory</span> <span class="o">{</span>
+ <span class="k">def</span> <span class="n">apply</span><span class="o">()</span> <span class="k">=</span> <span class="o">{</span>
+ <span class="k">new</span> <span class="nc">Engine</span><span class="o">(</span>
+ <span class="n">classOf</span><span class="o">[</span><span class="kt">DataSource</span><span class="o">],</span>
+ <span class="n">classOf</span><span class="o">[</span><span class="kt">Preparator</span><span class="o">],</span>
+ <span class="nc">Map</span><span class="o">(</span><span class="s">"naive"</span> <span class="o">-></span> <span class="n">classOf</span><span class="o">[</span><span class="kt">NaiveBayesAlgorithm</span><span class="o">],</span>
+ <span class="s">"randomforest"</span> <span class="o">-></span> <span class="n">classOf</span><span class="o">[</span><span class="kt">RandomForestAlgorithm</span><span class="o">]),</span> <span class="c1">// ADDED
+</span> <span class="n">classOf</span><span class="o">[</span><span class="kt">Serving</span><span class="o">])</span>
+ <span class="o">}</span>
+<span class="o">}</span>
+</pre></td></tr></tbody></table> </div> <p>This engine factory now returns an engine with two algorithms and they are named as <code>"naive"</code> and <code>"randomforest"</code> respectively.</p><h2 id='update-engine.json' class='header-anchors'>Update engine.json</h2><p>In order to use the new algorithm, you need to modify <code>engine.json</code> to specify the name of the algorithm and the parameters.</p><p>Update the engine.json to use <strong>randomforest</strong>:</p><div class="highlight json"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1
+2
+3
+4
+5
+6
+7
+8
+9
+10
+11
+12
+13
+14
+15</pre></td><td class="code"><pre><span class="err">...</span><span class="w">
+</span><span class="s2">"algorithms"</span><span class="err">:</span><span class="w"> </span><span class="p">[</span><span class="w">
+ </span><span class="p">{</span><span class="w">
+ </span><span class="s2">"name"</span><span class="p">:</span><span class="w"> </span><span class="s2">"randomforest"</span><span class="p">,</span><span class="w">
+ </span><span class="s2">"params"</span><span class="p">:</span><span class="w"> </span><span class="p">{</span><span class="w">
+ </span><span class="s2">"numClasses"</span><span class="p">:</span><span class="w"> </span><span class="mi">3</span><span class="p">,</span><span class="w">
+ </span><span class="s2">"numTrees"</span><span class="p">:</span><span class="w"> </span><span class="mi">5</span><span class="p">,</span><span class="w">
+ </span><span class="s2">"featureSubsetStrategy"</span><span class="p">:</span><span class="w"> </span><span class="s2">"auto"</span><span class="p">,</span><span class="w">
+ </span><span class="s2">"impurity"</span><span class="p">:</span><span class="w"> </span><span class="s2">"gini"</span><span class="p">,</span><span class="w">
+ </span><span class="s2">"maxDepth"</span><span class="p">:</span><span class="w"> </span><span class="mi">4</span><span class="p">,</span><span class="w">
+ </span><span class="s2">"maxBins"</span><span class="p">:</span><span class="w"> </span><span class="mi">100</span><span class="w">
+ </span><span class="p">}</span><span class="w">
+ </span><span class="p">}</span><span class="w">
+</span><span class="p">]</span><span class="w">
+</span><span class="err">...</span><span class="w">
+</span></pre></td></tr></tbody></table> </div> <p>The engine now uses <strong>MLlib Random Forests algorithm</strong> instead of the default Naive Bayes algorithm. You are ready to build, train and deploy the engine as described in <a href="/templates/classification/quickstart/">quickstart</a>.</p><div class="highlight shell"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1
+2
+3</pre></td><td class="code"><pre><span class="gp">$ </span>pio build
+<span class="gp">$ </span>pio train
+<span class="gp">$ </span>pio deploy
+</pre></td></tr></tbody></table> </div> <div class="alert-message info"><p>To switch back using Naive Bayes algorithm, simply modify engine.json.</p></div></div></div></div></div><footer><div class="container"><div class="seperator"></div><div class="row"><div class="col-md-4 col-md-push-8 col-xs-12"><div class="subscription-form-wrapper"><h4>Subscribe to our Newsletter</h4><form class="ajax-form" id="subscribe-form" method="POST" action="https://script.google.com/macros/s/AKfycbwhzeKCQJjQ52eVAqNT_vcklH07OITUO7wzOMDXvK6EGAWgaZgF/exec"><input class="required underlined-input" type="email" placeholder="Your email address" name="subscription_email" id="subscription_email"/><input class="pill-button" value="SUBSCRIBE" type="submit" data-state-normal="SUBSCRIBE" data-state-sucess="SUBSCRIBED!" data-state-loading="SENDING..." onclick="t($('#subscription_email').val());"/><p class="result"></p></form></div></div><div class="col-md-2 col-md-pull-4 col-xs-6 footer-link-column"><div class="fo
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<div class="row"><div class="col-md-9 col-sm-11 col-xs-11"><div class="hidden-md hidden-lg" id="mobile-page-heading-wrapper"><p>PredictionIO Docs</p><h4>DASE Components Explained (Classification)</h4></div><h4 class="hidden-sm hidden-xs">PredictionIO Docs</h4></div><div class="col-md-3 col-sm-1 col-xs-1 hidden-md hidden-lg"><img id="left-menu-indicator" src="/images/icons/down-arrow-dfe9f7fe.png"/></div><div class="col-md-3 col-sm-12 col-xs-12 swiftype-wrapper"><div class="swiftype"><form class="search-form"><img class="search-box-toggler hidden-xs hidden-sm" src="/images/icons/search-glass-704bd4ff.png"/><div class="search-box"><img src="/images/icons/search-glass-704bd4ff.png"/><input type="text" id="st-search-input" class="st-search-input" placeholder="Search Doc..."/></div><img class="swiftype-row-hider hidden-md hidden-lg" src="/images/icons/drawer-toggle-active-fcbef12a.png"/></form></div></div><div class="mobile-left-menu-toggler hidden-md hidden-lg"></div></div></div></div><
div id="page" class="container-fluid"><div class="row"><div id="left-menu-wrapper" class="col-md-3"><nav id="nav-main"><ul><li class="level-1"><a class="expandible" href="/"><span>Apache PredictionIO (incubating) Documentation</span></a><ul><li class="level-2"><a class="final" href="/"><span>Welcome to Apache PredictionIO (incubating)</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Getting Started</span></a><ul><li class="level-2"><a class="final" href="/start/"><span>A Quick Intro</span></a></li><li class="level-2"><a class="final" href="/install/"><span>Installing Apache PredictionIO (incubating)</span></a></li><li class="level-2"><a class="final" href="/start/download/"><span>Downloading an Engine Template</span></a></li><li class="level-2"><a class="final" href="/start/deploy/"><span>Deploying Your First Engine</span></a></li><li class="level-2"><a class="final" href="/start/customize/"><span>Customizing the Engine</span></a></li></ul></li><li c
lass="level-1"><a class="expandible" href="#"><span>Integrating with Your App</span></a><ul><li class="level-2"><a class="final" href="/appintegration/"><span>App Integration Overview</span></a></li><li class="level-2"><a class="expandible" href="/sdk/"><span>List of SDKs</span></a><ul><li class="level-3"><a class="final" href="/sdk/java/"><span>Java & Android SDK</span></a></li><li class="level-3"><a class="final" href="/sdk/php/"><span>PHP SDK</span></a></li><li class="level-3"><a class="final" href="/sdk/python/"><span>Python SDK</span></a></li><li class="level-3"><a class="final" href="/sdk/ruby/"><span>Ruby SDK</span></a></li><li class="level-3"><a class="final" href="/sdk/community/"><span>Community Powered SDKs</span></a></li></ul></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Deploying an Engine</span></a><ul><li class="level-2"><a class="final" href="/deploy/"><span>Deploying as a Web Service</span></a></li><li class="level-2"><a class="final" href=
"/cli/#engine-commands"><span>Engine Command-line Interface</span></a></li><li class="level-2"><a class="final" href="/deploy/engineparams/"><span>Setting Engine Parameters</span></a></li><li class="level-2"><a class="final" href="/deploy/enginevariants/"><span>Deploying Multiple Engine Variants</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Customizing an Engine</span></a><ul><li class="level-2"><a class="final" href="/customize/"><span>Learning DASE</span></a></li><li class="level-2"><a class="final" href="/customize/dase/"><span>Implement DASE</span></a></li><li class="level-2"><a class="final" href="/customize/troubleshooting/"><span>Troubleshooting Engine Development</span></a></li><li class="level-2"><a class="final" href="/api/current/#package"><span>Engine Scala APIs</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Collecting and Analyzing Data</span></a><ul><li class="level-2"><a class="final" href="/dataco
llection/"><span>Event Server Overview</span></a></li><li class="level-2"><a class="final" href="/cli/#event-server-commands"><span>Event Server Command-line Interface</span></a></li><li class="level-2"><a class="final" href="/datacollection/eventapi/"><span>Collecting Data with REST/SDKs</span></a></li><li class="level-2"><a class="final" href="/datacollection/eventmodel/"><span>Events Modeling</span></a></li><li class="level-2"><a class="final" href="/datacollection/webhooks/"><span>Unifying Multichannel Data with Webhooks</span></a></li><li class="level-2"><a class="final" href="/datacollection/channel/"><span>Channel</span></a></li><li class="level-2"><a class="final" href="/datacollection/batchimport/"><span>Importing Data in Batch</span></a></li><li class="level-2"><a class="final" href="/datacollection/analytics/"><span>Using Analytics Tools</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Choosing an Algorithm(s)</span></a><ul><li class="leve
l-2"><a class="final" href="/algorithm/"><span>Built-in Algorithm Libraries</span></a></li><li class="level-2"><a class="final" href="/algorithm/switch/"><span>Switching to Another Algorithm</span></a></li><li class="level-2"><a class="final" href="/algorithm/multiple/"><span>Combining Multiple Algorithms</span></a></li><li class="level-2"><a class="final" href="/algorithm/custom/"><span>Adding Your Own Algorithms</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>ML Tuning and Evaluation</span></a><ul><li class="level-2"><a class="final" href="/evaluation/"><span>Overview</span></a></li><li class="level-2"><a class="final" href="/evaluation/paramtuning/"><span>Hyperparameter Tuning</span></a></li><li class="level-2"><a class="final" href="/evaluation/evaluationdashboard/"><span>Evaluation Dashboard</span></a></li><li class="level-2"><a class="final" href="/evaluation/metricchoose/"><span>Choosing Evaluation Metrics</span></a></li><li class="level-2"><
a class="final" href="/evaluation/metricbuild/"><span>Building Evaluation Metrics</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>System Architecture</span></a><ul><li class="level-2"><a class="final" href="/system/"><span>Architecture Overview</span></a></li><li class="level-2"><a class="final" href="/system/anotherdatastore/"><span>Using Another Data Store</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Engine Template Gallery</span></a><ul><li class="level-2"><a class="final" href="http://templates.prediction.io"><span>Browse</span></a></li><li class="level-2"><a class="final" href="/community/submit-template/"><span>Submit your Engine as a Template</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Demo Tutorials</span></a><ul><li class="level-2"><a class="final" href="/demo/tapster/"><span>Comics Recommendation Demo</span></a></li><li class="level-2"><a class="final" href="/demo/c
ommunity/"><span>Community Contributed Demo</span></a></li><li class="level-2"><a class="final" href="/demo/textclassification/"><span>Text Classification Engine Tutorial</span></a></li></ul></li><li class="level-1"><a class="expandible" href="/community/"><span>Getting Involved</span></a><ul><li class="level-2"><a class="final" href="/community/contribute-code/"><span>Contribute Code</span></a></li><li class="level-2"><a class="final" href="/community/contribute-documentation/"><span>Contribute Documentation</span></a></li><li class="level-2"><a class="final" href="/community/contribute-sdk/"><span>Contribute a SDK</span></a></li><li class="level-2"><a class="final" href="/community/contribute-webhook/"><span>Contribute a Webhook</span></a></li><li class="level-2"><a class="final" href="/community/projects/"><span>Community Projects</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Getting Help</span></a><ul><li class="level-2"><a class="final" href=
"/resources/faq/"><span>FAQs</span></a></li><li class="level-2"><a class="final" href="/support/"><span>Community Support</span></a></li><li class="level-2"><a class="final" href="/support/#enterprise-support"><span>Enterprise Support</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Resources</span></a><ul><li class="level-2"><a class="final" href="/resources/intellij/"><span>Developing Engines with IntelliJ IDEA</span></a></li><li class="level-2"><a class="final" href="/resources/upgrade/"><span>Upgrade Instructions</span></a></li><li class="level-2"><a class="final" href="/resources/glossary/"><span>Glossary</span></a></li></ul></li></ul></nav></div><div class="col-md-9 col-sm-12"><div class="content-header hidden-md hidden-lg"><div id="page-title"><h1>DASE Components Explained (Classification)</h1></div></div><div id="table-of-content-wrapper"><h5>On this page</h5><aside id="table-of-contents"><ul> <li> <a href="#the-engine-design">The Engine Desi
gn</a> </li> <li> <a href="#data">Data</a> </li> <li> <a href="#algorithm">Algorithm</a> </li> <li> <a href="#serving">Serving</a> </li> </ul> </aside><hr/><a id="edit-page-link" href="https://github.com/apache/incubator-predictionio/tree/livedoc/docs/manual/source/templates/classification/dase.html.md.erb"><img src="/images/icons/edit-pencil-d6c1bb3d.png"/>Edit this page</a></div><div class="content-header hidden-sm hidden-xs"><div id="page-title"><h1>DASE Components Explained (Classification)</h1></div></div><div class="content"><p>PredictionIO's DASE architecture brings the separation-of-concerns design principle to predictive engine development. DASE stands for the following components of an engine:</p> <ul> <li><strong>D</strong>ata - includes Data Source and Data Preparator</li> <li><strong>A</strong>lgorithm(s)</li> <li><strong>S</strong>erving</li> <li><strong>E</strong>valuator</li> </ul> <p><p>Let's look at the code and see how you can customize the engine you buil
t from the Classification Engine Template.</p><div class="alert-message note"><p>Evaluator will not be covered in this tutorial. Please visit <a href="/evaluation/paramtuning/">evaluation explained</a> for using evaluation.</p></div></p><h2 id='the-engine-design' class='header-anchors'>The Engine Design</h2><p>As you can see from the Quick Start, <em>MyClassification</em> takes a JSON prediction query, e.g. <code>{ "attr0":4, "attr1":3, "attr2":8 }</code>, and return a JSON predicted result.</p><div class="alert-message warning"><p>for version < v0.3.1, it is array of features values: <code>{ "features": [4, 3, 8] }</code></p></div><p>In MyClassification/src/main/scala/<strong><em>Engine.scala</em></strong>, the <code>Query</code> case class defines the format of <strong>query</strong>, such as <code>{ "attr0":4, "attr1":3, "attr2":8 }</code>:</p><div class="highlight scala"><table style="border-spacing: 0"><tb
ody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1
+2
+3
+4
+5
+6</pre></td><td class="code"><pre><span class="k">class</span> <span class="nc">Query</span><span class="o">(</span>
+ <span class="k">val</span> <span class="n">attr0</span> <span class="k">:</span> <span class="kt">Double</span><span class="o">,</span>
+ <span class="k">val</span> <span class="n">attr1</span> <span class="k">:</span> <span class="kt">Double</span><span class="o">,</span>
+ <span class="k">val</span> <span class="n">attr2</span> <span class="k">:</span> <span class="kt">Double</span>
+<span class="o">)</span> <span class="k">extends</span> <span class="nc">Serializable</span>
+
+</pre></td></tr></tbody></table> </div> <p>The <code>PredictedResult</code> case class defines the format of <strong>predicted result</strong>, such as <code>{"label":2.0}</code>:</p><div class="highlight scala"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1
+2
+3</pre></td><td class="code"><pre><span class="k">class</span> <span class="nc">PredictedResult</span><span class="o">(</span>
+ <span class="k">val</span> <span class="n">label</span><span class="k">:</span> <span class="kt">Double</span>
+<span class="o">)</span> <span class="k">extends</span> <span class="nc">Serializable</span>
+</pre></td></tr></tbody></table> </div> <p>Finally, <code>ClassificationEngine</code> is the Engine Factory that defines the components this engine will use: Data Source, Data Preparator, Algorithm(s) and Serving components.</p><div class="highlight scala"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1
+2
+3
+4
+5
+6
+7
+8
+9</pre></td><td class="code"><pre><span class="k">object</span> <span class="nc">ClassificationEngine</span> <span class="k">extends</span> <span class="nc">IEngineFactory</span> <span class="o">{</span>
+ <span class="k">def</span> <span class="n">apply</span><span class="o">()</span> <span class="k">=</span> <span class="o">{</span>
+ <span class="k">new</span> <span class="nc">Engine</span><span class="o">(</span>
+ <span class="n">classOf</span><span class="o">[</span><span class="kt">DataSource</span><span class="o">],</span>
+ <span class="n">classOf</span><span class="o">[</span><span class="kt">Preparator</span><span class="o">],</span>
+ <span class="nc">Map</span><span class="o">(</span><span class="s">"naive"</span> <span class="o">-></span> <span class="n">classOf</span><span class="o">[</span><span class="kt">NaiveBayesAlgorithm</span><span class="o">]),</span>
+ <span class="n">classOf</span><span class="o">[</span><span class="kt">Serving</span><span class="o">])</span>
+ <span class="o">}</span>
+<span class="o">}</span>
+</pre></td></tr></tbody></table> </div> <h3 id='spark-mllib' class='header-anchors'>Spark MLlib</h3><p>Spark's MLlib NaiveBayes algorithm takes training data of RDD type, i.e. <code>RDD[LabeledPoint]</code> and train a model, which is a <code>NaiveBayesModel</code> object.</p><p>PredictionIO's MLlib Classification engine template, which <em>MyClassification</em> bases on, integrates this algorithm under the DASE architecture. We will take a closer look at the DASE code below.</p> <blockquote> <p><a href="https://spark.apache.org/docs/latest/mllib-naive-bayes.html">Check this out</a> to learn more about MLlib's NaiveBayes algorithm.</p></blockquote> <h2 id='data' class='header-anchors'>Data</h2><p>In the DASE architecture, data is prepared by 2 components sequentially: <em>Data Source</em> and <em>Data Preparator</em>. <em>Data Source</em> and <em>Data Preparator</em> takes data from the data store and prepares <code>RDD[LabeledPoint]</code> for the NaiveBayes algorithm.<
/p><h3 id='data-source' class='header-anchors'>Data Source</h3><p>In MyClassification/src/main/scala/<strong><em>DataSource.scala</em></strong>, the <code>readTraining</code> method of the class <code>DataSource</code> reads, and selects, data from datastore of EventServer and it returns <code>TrainingData</code>.</p><div class="highlight scala"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1
+2
+3
+4
+5
+6
+7
+8
+9
+10
+11
+12
+13
+14
+15
+16
+17
+18
+19
+20
+21
+22
+23
+24
+25
+26
+27
+28
+29
+30
+31
+32
+33
+34
+35
+36
+37
+38</pre></td><td class="code"><pre><span class="k">case</span> <span class="k">class</span> <span class="nc">DataSourceParams</span><span class="o">(</span><span class="n">appName</span><span class="k">:</span> <span class="kt">String</span><span class="o">)</span> <span class="k">extends</span> <span class="nc">Params</span>
+
+<span class="k">class</span> <span class="nc">DataSource</span><span class="o">(</span><span class="k">val</span> <span class="n">dsp</span><span class="k">:</span> <span class="kt">DataSourceParams</span><span class="o">)</span>
+ <span class="k">extends</span> <span class="nc">PDataSource</span><span class="o">[</span><span class="kt">TrainingData</span>, <span class="kt">EmptyEvaluationInfo</span>, <span class="kt">Query</span>, <span class="kt">EmptyActualResult</span><span class="o">]</span> <span class="o">{</span>
+
+ <span class="nd">@transient</span> <span class="k">lazy</span> <span class="k">val</span> <span class="n">logger</span> <span class="k">=</span> <span class="nc">Logger</span><span class="o">[</span><span class="kt">this.</span><span class="k">type</span><span class="o">]</span>
+
+ <span class="k">override</span>
+ <span class="k">def</span> <span class="n">readTraining</span><span class="o">(</span><span class="n">sc</span><span class="k">:</span> <span class="kt">SparkContext</span><span class="o">)</span><span class="k">:</span> <span class="kt">TrainingData</span> <span class="o">=</span> <span class="o">{</span>
+
+ <span class="k">val</span> <span class="n">labeledPoints</span><span class="k">:</span> <span class="kt">RDD</span><span class="o">[</span><span class="kt">LabeledPoint</span><span class="o">]</span> <span class="k">=</span> <span class="nc">PEventStore</span><span class="o">.</span><span class="n">aggregateProperties</span><span class="o">(</span>
+ <span class="n">appName</span> <span class="k">=</span> <span class="n">dsp</span><span class="o">.</span><span class="n">appName</span><span class="o">,</span>
+ <span class="n">entityType</span> <span class="k">=</span> <span class="s">"user"</span><span class="o">,</span>
+ <span class="c1">// only keep entities with these required properties defined
+</span> <span class="n">required</span> <span class="k">=</span> <span class="nc">Some</span><span class="o">(</span><span class="nc">List</span><span class="o">(</span><span class="s">"plan"</span><span class="o">,</span> <span class="s">"attr0"</span><span class="o">,</span> <span class="s">"attr1"</span><span class="o">,</span> <span class="s">"attr2"</span><span class="o">)))(</span><span class="n">sc</span><span class="o">)</span>
+ <span class="c1">// aggregateProperties() returns RDD pair of
+</span> <span class="c1">// entity ID and its aggregated properties
+</span> <span class="o">.</span><span class="n">map</span> <span class="o">{</span> <span class="k">case</span> <span class="o">(</span><span class="n">entityId</span><span class="o">,</span> <span class="n">properties</span><span class="o">)</span> <span class="k">=></span>
+ <span class="k">try</span> <span class="o">{</span>
+ <span class="nc">LabeledPoint</span><span class="o">(</span><span class="n">properties</span><span class="o">.</span><span class="n">get</span><span class="o">[</span><span class="kt">Double</span><span class="o">](</span><span class="s">"plan"</span><span class="o">),</span>
+ <span class="nc">Vectors</span><span class="o">.</span><span class="n">dense</span><span class="o">(</span><span class="nc">Array</span><span class="o">(</span>
+ <span class="n">properties</span><span class="o">.</span><span class="n">get</span><span class="o">[</span><span class="kt">Double</span><span class="o">](</span><span class="s">"attr0"</span><span class="o">),</span>
+ <span class="n">properties</span><span class="o">.</span><span class="n">get</span><span class="o">[</span><span class="kt">Double</span><span class="o">](</span><span class="s">"attr1"</span><span class="o">),</span>
+ <span class="n">properties</span><span class="o">.</span><span class="n">get</span><span class="o">[</span><span class="kt">Double</span><span class="o">](</span><span class="s">"attr2"</span><span class="o">)</span>
+ <span class="o">))</span>
+ <span class="o">)</span>
+ <span class="o">}</span> <span class="k">catch</span> <span class="o">{</span>
+ <span class="k">case</span> <span class="n">e</span><span class="k">:</span> <span class="kt">Exception</span> <span class="o">=></span> <span class="o">{</span>
+ <span class="n">logger</span><span class="o">.</span><span class="n">error</span><span class="o">(</span><span class="n">s</span><span class="s">"Failed to get properties ${properties} of"</span> <span class="o">+</span>
+ <span class="n">s</span><span class="s">" ${entityId}. Exception: ${e}."</span><span class="o">)</span>
+ <span class="k">throw</span> <span class="n">e</span>
+ <span class="o">}</span>
+ <span class="o">}</span>
+ <span class="o">}.</span><span class="n">cache</span><span class="o">()</span>
+
+ <span class="k">new</span> <span class="nc">TrainingData</span><span class="o">(</span><span class="n">labeledPoints</span><span class="o">)</span>
+ <span class="o">}</span>
+<span class="o">}</span>
+</pre></td></tr></tbody></table> </div> <p><code>PEventStore</code> is an object which provides function to access data that is collected through the <em>Event Server</em>, and <code>PEventStore.aggregateProperties</code> aggregates the event records of the 4 properties (attr0, attr1, attr2 and plan) for each user.</p><p>PredictionIO automatically loads the parameters of <em>datasource</em> specified in MyEngine/<strong><em>engine.json</em></strong>, including <em>appName</em>, to <code>dsp</code>.</p><p>In <strong><em>engine.json</em></strong>:</p><div class="highlight shell"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1
+2
+3
+4
+5
+6
+7
+8
+9</pre></td><td class="code"><pre><span class="o">{</span>
+ ...
+ <span class="s2">"datasource"</span>: <span class="o">{</span>
+ <span class="s2">"params"</span>: <span class="o">{</span>
+ <span class="s2">"appName"</span>: <span class="s2">"MyApp1"</span>
+ <span class="o">}</span>
+ <span class="o">}</span>,
+ ...
+<span class="o">}</span>
+</pre></td></tr></tbody></table> </div> <p>In this sample text data file, columns are delimited by comma (,). The first column are labels. The second column are features.</p><p>The class definition of <code>TrainingData</code> is:</p><div class="highlight scala"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1
+2
+3</pre></td><td class="code"><pre><span class="k">class</span> <span class="nc">TrainingData</span><span class="o">(</span>
+ <span class="k">val</span> <span class="n">labeledPoints</span><span class="k">:</span> <span class="kt">RDD</span><span class="o">[</span><span class="kt">LabeledPoint</span><span class="o">]</span>
+<span class="o">)</span> <span class="k">extends</span> <span class="nc">Serializable</span>
+</pre></td></tr></tbody></table> </div> <p>and PredictionIO passes the returned <code>TrainingData</code> object to <em>Data Preparator</em>.</p><h3 id='data-preparator' class='header-anchors'>Data Preparator</h3><p>In MyClassification/src/main/scala/<strong><em>Preparator.scala</em></strong>, the <code>prepare</code> of class <code>Preparator</code> takes <code>TrainingData</code>. It then conducts any necessary feature selection and data processing tasks. At the end, it returns <code>PreparedData</code> which should contain the data <em>Algorithm</em> needs. For MLlib NaiveBayes, it is <code>RDD[LabeledPoint]</code>.</p><p>By default, <code>prepare</code> simply copies the unprocessed <code>TrainingData</code> data to <code>PreparedData</code>:</p><div class="highlight scala"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1
+2
+3
+4
+5
+6
+7
+8
+9
+10
+11</pre></td><td class="code"><pre><span class="k">class</span> <span class="nc">PreparedData</span><span class="o">(</span>
+ <span class="k">val</span> <span class="n">labeledPoints</span><span class="k">:</span> <span class="kt">RDD</span><span class="o">[</span><span class="kt">LabeledPoint</span><span class="o">]</span>
+<span class="o">)</span> <span class="k">extends</span> <span class="nc">Serializable</span>
+
+<span class="k">class</span> <span class="nc">Preparator</span>
+ <span class="k">extends</span> <span class="nc">PPreparator</span><span class="o">[</span><span class="kt">TrainingData</span>, <span class="kt">PreparedData</span><span class="o">]</span> <span class="o">{</span>
+
+ <span class="k">def</span> <span class="n">prepare</span><span class="o">(</span><span class="n">sc</span><span class="k">:</span> <span class="kt">SparkContext</span><span class="o">,</span> <span class="n">trainingData</span><span class="k">:</span> <span class="kt">TrainingData</span><span class="o">)</span><span class="k">:</span> <span class="kt">PreparedData</span> <span class="o">=</span> <span class="o">{</span>
+ <span class="k">new</span> <span class="nc">PreparedData</span><span class="o">(</span><span class="n">trainingData</span><span class="o">.</span><span class="n">labeledPoints</span><span class="o">)</span>
+ <span class="o">}</span>
+<span class="o">}</span>
+</pre></td></tr></tbody></table> </div> <p>PredictionIO passes the returned <code>PreparedData</code> object to Algorithm's <code>train</code> function.</p><h2 id='algorithm' class='header-anchors'>Algorithm</h2><p>In MyClassification/src/main/scala/<strong><em>NaiveBayesAlgorithm.scala</em></strong>, the two methods of the algorithm class are <code>train</code> and <code>predict</code>. <code>train</code> is responsible for training a predictive model. PredictionIO will store this model and <code>predict</code> is responsible for using this model to make prediction.</p><h3 id='train(...)' class='header-anchors'>train(...)</h3><p><code>train</code> is called when you run <strong>pio train</strong>. This is where MLlib NaiveBayes algorithm, i.e. <code>NaiveBayes.train</code>, is used to train a predictive model.</p><div class="highlight scala"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1
+2
+3</pre></td><td class="code"><pre><span class="k">def</span> <span class="n">train</span><span class="o">(</span><span class="n">sc</span><span class="k">:</span> <span class="kt">SparkContext</span><span class="o">,</span> <span class="n">data</span><span class="k">:</span> <span class="kt">PreparedData</span><span class="o">)</span><span class="k">:</span> <span class="kt">NaiveBayesModel</span> <span class="o">=</span> <span class="o">{</span>
+ <span class="nc">NaiveBayes</span><span class="o">.</span><span class="n">train</span><span class="o">(</span><span class="n">data</span><span class="o">.</span><span class="n">labeledPoints</span><span class="o">,</span> <span class="n">ap</span><span class="o">.</span><span class="n">lambda</span><span class="o">)</span>
+<span class="o">}</span>
+</pre></td></tr></tbody></table> </div> <p>In addition to <code>RDD[LabeledPoint]</code> (i.e. <code>data.labeledPoints</code>), <code>NaiveBayes.train</code> takes 1 parameter: <em>lambda</em>.</p><p>The values of this parameter is specified in <em>algorithms</em> of MyClassification/<strong><em>engine.json</em></strong>:</p><div class="highlight shell"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1
+2
+3
+4
+5
+6
+7
+8
+9
+10
+11
+12</pre></td><td class="code"><pre><span class="o">{</span>
+ ...
+ <span class="s2">"algorithms"</span>: <span class="o">[</span>
+ <span class="o">{</span>
+ <span class="s2">"name"</span>: <span class="s2">"naive"</span>,
+ <span class="s2">"params"</span>: <span class="o">{</span>
+ <span class="s2">"lambda"</span>: 1.0
+ <span class="o">}</span>
+ <span class="o">}</span>
+ <span class="o">]</span>
+ ...
+<span class="o">}</span>
+</pre></td></tr></tbody></table> </div> <p>PredictionIO will automatically loads these values into the constructor <code>ap</code>, which has a corresponding case case <code>AlgorithmParams</code>:</p><div class="highlight scala"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1
+2
+3</pre></td><td class="code"><pre><span class="k">case</span> <span class="k">class</span> <span class="nc">AlgorithmParams</span><span class="o">(</span>
+ <span class="n">lambda</span><span class="k">:</span> <span class="kt">Double</span>
+<span class="o">)</span> <span class="k">extends</span> <span class="nc">Params</span>
+</pre></td></tr></tbody></table> </div> <p><code>NaiveBayes.train</code> then returns a <code>NaiveBayesModel</code> model. PredictionIO will automatically store the returned model.</p><h3 id='predict(...)' class='header-anchors'>predict(...)</h3><p>The <code>predict</code> method is called when you send a JSON query to <a href="http://localhost:8000/queries.json">http://localhost:8000/queries.json</a>. PredictionIO converts the query, such as <code>{ "attr0":4, "attr1":3, "attr2":8 }</code> to the <code>Query</code> class you defined previously.</p><p>The predictive model <code>NaiveBayesModel</code> of MLlib NaiveBayes offers a function called <code>predict</code>. <code>predict</code> takes a dense vector of features. It predicts the label of the item represented by this feature vector.</p><div class="highlight scala"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1
+2
+3
+4
+5
+6</pre></td><td class="code"><pre> <span class="k">def</span> <span class="n">predict</span><span class="o">(</span><span class="n">model</span><span class="k">:</span> <span class="kt">NaiveBayesModel</span><span class="o">,</span> <span class="n">query</span><span class="k">:</span> <span class="kt">Query</span><span class="o">)</span><span class="k">:</span> <span class="kt">PredictedResult</span> <span class="o">=</span> <span class="o">{</span>
+ <span class="k">val</span> <span class="n">label</span> <span class="k">=</span> <span class="n">model</span><span class="o">.</span><span class="n">predict</span><span class="o">(</span><span class="nc">Vectors</span><span class="o">.</span><span class="n">dense</span><span class="o">(</span>
+ <span class="n">query</span><span class="o">.</span><span class="n">attr0</span><span class="o">,</span> <span class="n">query</span><span class="o">.</span><span class="n">attr1</span><span class="o">,</span> <span class="n">query</span><span class="o">.</span><span class="n">attr2</span>
+ <span class="o">))</span>
+ <span class="k">new</span> <span class="nc">PredictedResult</span><span class="o">(</span><span class="n">label</span><span class="o">)</span>
+ <span class="o">}</span>
+</pre></td></tr></tbody></table> </div> <blockquote> <p>You have defined the class <code>PredictedResult</code> earlier in this page.</p></blockquote> <p>PredictionIO passes the returned <code>PredictedResult</code> object to <em>Serving</em>.</p><h2 id='serving' class='header-anchors'>Serving</h2><p>The <code>serve</code> method of class <code>Serving</code> processes predicted result. It is also responsible for combining multiple predicted results into one if you have more than one predictive model. <em>Serving</em> then returns the final predicted result. PredictionIO will convert it to a JSON response automatically.</p><p>In MyClassification/src/main/scala/<strong><em>Serving.scala</em></strong>,</p><div class="highlight scala"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1
+2
+3
+4
+5
+6
+7
+8
+9</pre></td><td class="code"><pre><span class="k">class</span> <span class="nc">Serving</span>
+ <span class="k">extends</span> <span class="nc">LServing</span><span class="o">[</span><span class="kt">Query</span>, <span class="kt">PredictedResult</span><span class="o">]</span> <span class="o">{</span>
+
+ <span class="k">override</span>
+ <span class="k">def</span> <span class="n">serve</span><span class="o">(</span><span class="n">query</span><span class="k">:</span> <span class="kt">Query</span><span class="o">,</span>
+ <span class="n">predictedResults</span><span class="k">:</span> <span class="kt">Seq</span><span class="o">[</span><span class="kt">PredictedResult</span><span class="o">])</span><span class="k">:</span> <span class="kt">PredictedResult</span> <span class="o">=</span> <span class="o">{</span>
+ <span class="n">predictedResults</span><span class="o">.</span><span class="n">head</span>
+ <span class="o">}</span>
+<span class="o">}</span>
+</pre></td></tr></tbody></table> </div> <p>When you send a JSON query to <a href="http://localhost:8000/queries.json">http://localhost:8000/queries.json</a>, <code>PredictedResult</code> from all models will be passed to <code>serve</code> as a sequence, i.e. <code>Seq[PredictedResult]</code>.</p> <blockquote> <p>An engine can train multiple models if you specify more than one Algorithm component in <code>object RecommendationEngine</code> inside <strong><em>Engine.scala</em></strong>. Since only one <code>NaiveBayesAlgorithm</code> is implemented by default, this <code>Seq</code> contains one element.</p></blockquote> <p>In this case, <code>serve</code> simply returns the predicted result of the first, and the only, algorithm, i.e. <code>predictedResults.head</code>.</p><p>Congratulations! You have just learned how to customize and build a production-ready engine. Have fun!</p></div></div></div></div><footer><div class="container"><div class="seperator"></div><div class="row"><div
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http://git-wip-us.apache.org/repos/asf/incubator-predictionio-site/blob/92a45fa4/templates/classification/dase/index.html.gz
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site
Posted by do...@apache.org.
http://git-wip-us.apache.org/repos/asf/incubator-predictionio-site/blob/92a45fa4/images/logos/downloads/frog-light-background.eps
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+/xs{exch store}bd
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+/T/true
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+/S/stroke
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+/q/gsave
+/Q/grestore
+counttomark 2 idiv
+{ld}repeat pop
+/SC{
+ /ColorSpace fr scs
+}bd
+/sopr /setoverprint where{pop/setoverprint}{/pop}ifelse ld
+/soprm /setoverprintmode where{pop/setoverprintmode}{/pop}ifelse ld
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+/cm {cmmtx astore CM concat}bd
+/W{clip newpath}bd
+/W*{eoclip newpath}bd
+statusdict begin product end dup (HP) anchorsearch{
+ pop pop pop
+ true
+}{
+ pop
+ (hp) anchorsearch{
+ pop pop true
+ }{
+ pop false
+ }ifelse
+}ifelse
+{
+ {
+ {
+ pop pop
+ (0)dup 0 4 -1 roll put
+ F charpath
+ }cshow
+ }
+}{
+ {F charpath}
+}ifelse
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+gsave
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+CM
+patarray exch get
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+}bd
+/cg_BeginEPSF{
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+ userdict/cg_endepsf/cg_EndEPSF load put
+ count userdict/cg_op_count 3 -1 roll put
+ countdictstack dup array dictstack userdict/cg_dict_array 3 -1 roll put
+ 3 sub{end}repeat
+ /showpage {} def
+ 0 setgray 0 setlinecap 1 setlinewidth 0 setlinejoin
+ 10 setmiterlimit [] 0 setdash newpath
+ false setstrokeadjust false setoverprint
+}bd
+/cg_EndEPSF{
+ countdictstack 3 sub { end } repeat
+ cg_dict_array 3 1 index length 3 sub getinterval
+ {begin}forall
+ count userdict/cg_op_count get sub{pop}repeat
+ userdict/cg_b4_Inc_state get restore
+ F setpacking
+}bd
+/cg_biproc{currentfile/RunLengthDecode filter}bd
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+/ImageDataSource 0 def
+L3?{
+ /cg_mibiproc{pop pop/ImageDataSource{cg_biproc}def}bd
+ /cg_miaiproc{pop pop/ImageDataSource{cg_aiproc}def}bd
+}{
+ /ImageBandMask 0 def
+ /ImageBandData 0 def
+ /cg_mibiproc{
+ string/ImageBandMask xs
+ string/ImageBandData xs
+ /ImageDataSource{[currentfile/RunLengthDecode filter dup ImageBandMask/readstring cvx
+ /pop cvx dup ImageBandData/readstring cvx/pop cvx]cvx bind}bd
+ }bd
+ /cg_miaiproc{
+ string/ImageBandMask xs
+ string/ImageBandData xs
+ /ImageDataSource{[currentfile/ASCII85Decode filter/RunLengthDecode filter
+ dup ImageBandMask/readstring cvx
+ /pop cvx dup ImageBandData/readstring cvx/pop cvx]cvx bind}bd
+ }bd
+}ifelse
+/imsave 0 def
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+dict begin
+{def} repeat
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+currentdict dup/ImageMask known{ImageMask}{F}ifelse exch
+L3?{
+ dup/MaskedImage known
+ {
+ pop
+ <<
+ /ImageType 3
+ /InterleaveType 2
+ /DataDict currentdict
+ /MaskDict
+ << /ImageType 1
+ /Width Width
+ /Height Height
+ /ImageMatrix ImageMatrix
+ /BitsPerComponent 1
+ /Decode [0 1]
+ currentdict/Interpolate known
+ {/Interpolate Interpolate}if
+ >>
+ >>
+ }if
+}if
+exch
+{imagemask}{image}ifelse
+end
+}bd
+/cguidfix{statusdict begin mark version end
+{cvr}stopped{cleartomark 0}{exch pop}ifelse
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+{def} {pop pop} ifelse}forall
+currentdict end definefont pop
+}{pop}ifelse
+}bd
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+ exch t_array t_i get add exch moveto
+ /t_i t_i 1 add store
+}bd
+/y_proc{
+ t_array t_i get add moveto
+ /t_i t_i 1 add store
+}bd
+/xy_proc{
+
+ t_array t_i 2 copy 1 add get 3 1 roll get
+ 4 -1 roll add 3 1 roll add moveto
+ /t_i t_i 2 add store
+}bd
+/sop 0 def
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+{
+ /t_array xs
+ /t_i 0 def
+ {
+ t_c 0 3 -1 roll put
+ currentpoint
+ t_c cply sop
+ cp_proc
+ }forall
+ /t_array 0 def
+}bd
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+{
+ begin
+ /nRange Range length 2 idiv store
+ /mulRange
+
+ [
+ 0 1 nRange 1 sub
+ {
+ 2 mul/nDim2 xd
+ Range nDim2 get
+ Range nDim2 1 add get
+ 1 index sub
+
+ 255 div
+ exch
+ }for
+ ]store
+ end
+}bd
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+{
+ begin
+
+ nRange mul /val xd
+
+ 0 1 nRange 1 sub
+ {
+ dup 2 mul/nDim2 xd
+ val
+ add DataSource exch get
+ mulRange nDim2 get mul
+ mulRange nDim2 1 add get
+ add
+ }for
+ end
+}bd
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+{
+ 2 copy lt
+ {exch pop}{pop}ifelse
+}bd
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+{
+ /Coords load aload pop
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+
+ 3 -1 roll sub
+ 3 1 roll exch
+ sub
+ 2 copy
+ dup mul exch dup mul add sqrt
+ dup
+ scale
+ atan
+
+ rotate
+
+ /Function load setupFunEval
+
+
+ clippath {pathbbox}stopped {0 0 0 0}if newpath
+ /ymax xs
+ /xmax xs
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+ currentdict/Extend known
+ {
+ /Extend load 0 get
+ {
+ 0/Function load FunEval sc
+ xmin ymin xmin abs ymax ymin sub rectfill
+ }if
+ }if
+
+ /Nsteps/Function load/Size get 0 get 1 sub store
+ /dx 1 Nsteps div store
+ gsave
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+ /Function load
+
+ 0 1 Nsteps
+ {
+ 1 index FunEval sc
+ 0 ymin dx di rectfill
+ dx 0 translate
+ }for
+ pop
+ grestore
+ currentdict/Extend known
+ {
+ /Extend load 1 get
+ {
+ Nsteps/Function load FunEval sc
+ 1 ymin xmax 1 sub abs ymax ymin sub rectfill
+ }if
+ }if
+}bd
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+
+ dup 0 gt{
+ 0 exch a1 a0 arc
+ }{
+ pop 0 moveto
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+ dup 0 gt{
+ 0 exch a0 a1 arcn
+ }{
+ pop 0 lineto
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+
+ fill
+
+ dup 0 gt{
+ 0 exch a0 a1 arc
+ }{
+ pop 0 moveto
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+ dup 0 gt{
+ 0 exch a1 a0 arcn
+ }{
+ pop 0 lineto
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+ fill
+}bd
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+
+ xmin dup mul ymin dup mul add sqrt
+ xmax dup mul ymin dup mul add sqrt
+ xmin dup mul ymax dup mul add sqrt
+ xmax dup mul ymax dup mul add sqrt
+ max max max
+}bd
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+ /Coords load aload pop
+ 5 index 5 index translate
+ 3 -1 roll 6 -1 roll sub
+ 3 -1 roll 5 -1 roll sub
+ 2 copy dup mul exch dup mul add sqrt
+ /dx xs
+ 2 copy 0 ne exch 0 ne or
+ {
+
+ exch atan rotate
+ }{
+ pop pop
+ }ifelse
+
+ /r2 xs
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+ /Function load
+ dup/Size get 0 get 1 sub
+ /Nsteps xs
+ setupFunEval
+
+
+
+
+
+ dx r2 add r1 lt{
+
+ 0
+ }{
+ dx r1 add r2 le
+ {
+ 1
+ }{
+ r1 r2 eq
+ {
+ 2
+ }{
+ 3
+ }ifelse
+ }ifelse
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+ /sh3tp xs
+ clippath {pathbbox}stopped {0 0 0 0}if
+ newpath
+ /ymax xs
+ /xmax xs
+ /ymin xs
+ /xmin xs
+
+ dx dup mul r2 r1 sub dup mul sub dup 0 gt
+ {
+ sqrt r2 r1 sub atan
+ /a0 exch 180 exch sub store
+ /a1 a0 neg store
+ }{
+ pop
+ /a0 0 store
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+ }ifelse
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+ {
+ /Extend load 0 get r1 0 gt and
+ {
+ 0/Function load FunEval sc
+
+
+
+
+ {
+ {
+ dx 0 r1 360 0 arcn
+ xmin ymin moveto
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+ xmax ymax lineto
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+
+
+
+
+ 0 r1 xmin abs r1 add neg r1 shp
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+
+ r2 r1 gt{
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+ 0 r1
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+
+
+ 0 r1 calcmaxs
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+
+ r2 add dx mul dx r1 r2 sub sub div
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+ shp
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+ }if
+ }if
+
+ /d0 0 store
+ /r0 r1 store
+ /di dx Nsteps div store
+ /ri r2 r1 sub Nsteps div store
+ /Function load
+ 0 1 Nsteps
+ {
+ 1 index FunEval sc
+ d0 di add r0 ri add d0 r0 shp
+ {
+
+ d0 0 r0 a1 a0 arc
+ d0 di add 0 r0 ri add a0 a1 arcn
+ fill
+
+
+ d0 0 r0 a0 a1 arc
+ d0 di add 0 r0 ri add a1 a0 arcn
+ fill
+ }pop
+
+
+ /d0 d0 di add store
+ /r0 r0 ri add store
+ }for
+ pop
+
+ currentdict/Extend known
+ {
+ /Extend load 1 get r2 0 gt and
+ {
+ Nsteps/Function load FunEval sc
+
+
+
+
+ {
+ {
+ dx 0 r2 0 360 arc fill
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+ {
+ dx 0 r2 360 0 arcn
+ xmin ymin moveto
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+ xmax ymax lineto
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+ eofill
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+
+ xmax abs r1 add r1 dx r1 shp
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+ {
+
+ r2 r1 gt{
+
+
+
+ calcmaxs dup
+
+ r1 add dx mul dx r2 r1 sub sub div
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+ dx r2
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+
+ r1 neg r2 r1 sub div dx mul
+ 0
+ dx
+ r2
+ shp
+ }ifelse
+ }
+ }
+ sh3tp get exec
+ }if
+ }if
+}bd
+/sh
+{
+ begin
+ /ShadingType load dup dup 2 eq exch 3 eq or
+ {
+ gsave
+ newpath
+ /ColorSpace load scs
+ currentdict/BBox known
+ {
+ /BBox load aload pop
+ 2 index sub
+ 3 index
+ 3 -1 roll exch sub
+ exch rectclip
+ }if
+ 2 eq
+ {sh2}{sh3}ifelse
+ grestore
+ }{
+
+ pop
+ (DEBUG: shading type unimplemented\n)print flush
+ }ifelse
+ end
+}bd
+{restore}if not dup{save exch}if
+ L3?{
+ /sh/shfill ld
+ /csq/clipsave ld
+ /csQ/cliprestore ld
+ }if
+{restore}if
+end
+setpacking
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<div class="row"><div class="col-md-9 col-sm-11 col-xs-11"><div class="hidden-md hidden-lg" id="mobile-page-heading-wrapper"><p>PredictionIO Docs</p><h4>Welcome to Apache PredictionIO (incubating)</h4></div><h4 class="hidden-sm hidden-xs">PredictionIO Docs</h4></div><div class="col-md-3 col-sm-1 col-xs-1 hidden-md hidden-lg"><img id="left-menu-indicator" src="/images/icons/down-arrow-dfe9f7fe.png"/></div><div class="col-md-3 col-sm-12 col-xs-12 swiftype-wrapper"><div class="swiftype"><form class="search-form"><img class="search-box-toggler hidden-xs hidden-sm" src="/images/icons/search-glass-704bd4ff.png"/><div class="search-box"><img src="/images/icons/search-glass-704bd4ff.png"/><input type="text" id="st-search-input" class="st-search-input" placeholder="Search Doc..."/></div><img class="swiftype-row-hider hidden-md hidden-lg" src="/images/icons/drawer-toggle-active-fcbef12a.png"/></form></div></div><div class="mobile-left-menu-toggler hidden-md hidden-lg"></div></div></div></div>
<div id="page" class="container-fluid"><div class="row"><div id="left-menu-wrapper" class="col-md-3"><nav id="nav-main"><ul><li class="level-1"><a class="expandible active" href="/"><span>Apache PredictionIO (incubating) Documentation</span></a><ul><li class="level-2"><a class="final active" href="/"><span>Welcome to Apache PredictionIO (incubating)</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Getting Started</span></a><ul><li class="level-2"><a class="final" href="/start/"><span>A Quick Intro</span></a></li><li class="level-2"><a class="final" href="/install/"><span>Installing Apache PredictionIO (incubating)</span></a></li><li class="level-2"><a class="final" href="/start/download/"><span>Downloading an Engine Template</span></a></li><li class="level-2"><a class="final" href="/start/deploy/"><span>Deploying Your First Engine</span></a></li><li class="level-2"><a class="final" href="/start/customize/"><span>Customizing the Engine</span></a></li>
</ul></li><li class="level-1"><a class="expandible" href="#"><span>Integrating with Your App</span></a><ul><li class="level-2"><a class="final" href="/appintegration/"><span>App Integration Overview</span></a></li><li class="level-2"><a class="expandible" href="/sdk/"><span>List of SDKs</span></a><ul><li class="level-3"><a class="final" href="/sdk/java/"><span>Java & Android SDK</span></a></li><li class="level-3"><a class="final" href="/sdk/php/"><span>PHP SDK</span></a></li><li class="level-3"><a class="final" href="/sdk/python/"><span>Python SDK</span></a></li><li class="level-3"><a class="final" href="/sdk/ruby/"><span>Ruby SDK</span></a></li><li class="level-3"><a class="final" href="/sdk/community/"><span>Community Powered SDKs</span></a></li></ul></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Deploying an Engine</span></a><ul><li class="level-2"><a class="final" href="/deploy/"><span>Deploying as a Web Service</span></a></li><li class="level-2"><a clas
s="final" href="/cli/#engine-commands"><span>Engine Command-line Interface</span></a></li><li class="level-2"><a class="final" href="/deploy/engineparams/"><span>Setting Engine Parameters</span></a></li><li class="level-2"><a class="final" href="/deploy/enginevariants/"><span>Deploying Multiple Engine Variants</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Customizing an Engine</span></a><ul><li class="level-2"><a class="final" href="/customize/"><span>Learning DASE</span></a></li><li class="level-2"><a class="final" href="/customize/dase/"><span>Implement DASE</span></a></li><li class="level-2"><a class="final" href="/customize/troubleshooting/"><span>Troubleshooting Engine Development</span></a></li><li class="level-2"><a class="final" href="/api/current/#package"><span>Engine Scala APIs</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Collecting and Analyzing Data</span></a><ul><li class="level-2"><a class="final
" href="/datacollection/"><span>Event Server Overview</span></a></li><li class="level-2"><a class="final" href="/cli/#event-server-commands"><span>Event Server Command-line Interface</span></a></li><li class="level-2"><a class="final" href="/datacollection/eventapi/"><span>Collecting Data with REST/SDKs</span></a></li><li class="level-2"><a class="final" href="/datacollection/eventmodel/"><span>Events Modeling</span></a></li><li class="level-2"><a class="final" href="/datacollection/webhooks/"><span>Unifying Multichannel Data with Webhooks</span></a></li><li class="level-2"><a class="final" href="/datacollection/channel/"><span>Channel</span></a></li><li class="level-2"><a class="final" href="/datacollection/batchimport/"><span>Importing Data in Batch</span></a></li><li class="level-2"><a class="final" href="/datacollection/analytics/"><span>Using Analytics Tools</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Choosing an Algorithm(s)</span></a><ul>
<li class="level-2"><a class="final" href="/algorithm/"><span>Built-in Algorithm Libraries</span></a></li><li class="level-2"><a class="final" href="/algorithm/switch/"><span>Switching to Another Algorithm</span></a></li><li class="level-2"><a class="final" href="/algorithm/multiple/"><span>Combining Multiple Algorithms</span></a></li><li class="level-2"><a class="final" href="/algorithm/custom/"><span>Adding Your Own Algorithms</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>ML Tuning and Evaluation</span></a><ul><li class="level-2"><a class="final" href="/evaluation/"><span>Overview</span></a></li><li class="level-2"><a class="final" href="/evaluation/paramtuning/"><span>Hyperparameter Tuning</span></a></li><li class="level-2"><a class="final" href="/evaluation/evaluationdashboard/"><span>Evaluation Dashboard</span></a></li><li class="level-2"><a class="final" href="/evaluation/metricchoose/"><span>Choosing Evaluation Metrics</span></a></li><li cl
ass="level-2"><a class="final" href="/evaluation/metricbuild/"><span>Building Evaluation Metrics</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>System Architecture</span></a><ul><li class="level-2"><a class="final" href="/system/"><span>Architecture Overview</span></a></li><li class="level-2"><a class="final" href="/system/anotherdatastore/"><span>Using Another Data Store</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Engine Template Gallery</span></a><ul><li class="level-2"><a class="final" href="http://templates.prediction.io"><span>Browse</span></a></li><li class="level-2"><a class="final" href="/community/submit-template/"><span>Submit your Engine as a Template</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Demo Tutorials</span></a><ul><li class="level-2"><a class="final" href="/demo/tapster/"><span>Comics Recommendation Demo</span></a></li><li class="level-2"><a class="final
" href="/demo/community/"><span>Community Contributed Demo</span></a></li><li class="level-2"><a class="final" href="/demo/textclassification/"><span>Text Classification Engine Tutorial</span></a></li></ul></li><li class="level-1"><a class="expandible" href="/community/"><span>Getting Involved</span></a><ul><li class="level-2"><a class="final" href="/community/contribute-code/"><span>Contribute Code</span></a></li><li class="level-2"><a class="final" href="/community/contribute-documentation/"><span>Contribute Documentation</span></a></li><li class="level-2"><a class="final" href="/community/contribute-sdk/"><span>Contribute a SDK</span></a></li><li class="level-2"><a class="final" href="/community/contribute-webhook/"><span>Contribute a Webhook</span></a></li><li class="level-2"><a class="final" href="/community/projects/"><span>Community Projects</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Getting Help</span></a><ul><li class="level-2"><a clas
s="final" href="/resources/faq/"><span>FAQs</span></a></li><li class="level-2"><a class="final" href="/support/"><span>Community Support</span></a></li><li class="level-2"><a class="final" href="/support/#enterprise-support"><span>Enterprise Support</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Resources</span></a><ul><li class="level-2"><a class="final" href="/resources/intellij/"><span>Developing Engines with IntelliJ IDEA</span></a></li><li class="level-2"><a class="final" href="/resources/upgrade/"><span>Upgrade Instructions</span></a></li><li class="level-2"><a class="final" href="/resources/glossary/"><span>Glossary</span></a></li></ul></li></ul></nav></div><div class="col-md-9 col-sm-12"><div class="content-header hidden-md hidden-lg"><div id="breadcrumbs" class="hidden-sm hidden xs"><ul><li><span class="last">Apache PredictionIO (incubating) Documentation</span></li></ul></div><div id="page-title"><h1>Welcome to Apache PredictionIO (incuba
ting)!</h1></div></div><div id="table-of-content-wrapper"><h5>On this page</h5><aside id="table-of-contents"><ul> <li> <a href="#what-is-apache-predictionio-incubating">What is Apache PredictionIO (incubating)?</a> </li> <li> <a href="#release-notes">Release Notes</a> </li> <li> <a href="#licensing">Licensing</a> </li> </ul> </aside><hr/><a id="edit-page-link" href="https://github.com/apache/incubator-predictionio/tree/livedoc/docs/manual/source/index.html.md.erb"><img src="/images/icons/edit-pencil-d6c1bb3d.png"/>Edit this page</a></div><div class="content-header hidden-sm hidden-xs"><div id="breadcrumbs" class="hidden-sm hidden xs"><ul><li><span class="last">Apache PredictionIO (incubating) Documentation</span></li></ul></div><div id="page-title"><h1>Welcome to Apache PredictionIO (incubating)!</h1></div></div><div class="content"><h2 id='what-is-apache-predictionio-(incubating)?' class='header-anchors'>What is Apache PredictionIO (incubating)?</h2><p>Apache PredictionIO (incubati
ng) is an <strong>open source Machine Learning Server</strong> built on top of state-of-the-art open source stack for developers and data scientists create predictive engines for any machine learning task. It lets you:</p> <ul> <li>quickly build and deploy an engine as a web service on production with <a href="http://templates.prediction.io">customizable templates</a>;</li> <li>respond to dynamic queries in <strong>real-time</strong> once deployed as a web service;</li> <li>evaluate and tune multiple engine variants systematically;</li> <li>unify data from multiple platforms in batch or in real-time for comprehensive predictive analytics;</li> <li>speed up machine learning modeling with systematic processes and pre-built evaluation measures;</li> <li>support machine learning and data processing libraries such as Spark MLLib and OpenNLP;</li> <li>implement your own machine learning models and seamlessly incorporate them into your engine;</li> <li>simplify data infrastructure manageme
nt.</li> </ul> <p>Apache PredictionIO (incubating) can be <a href="/install/">installed</a> as a full machine learning stack, bundled with <strong>Apache Spark</strong>, <strong>MLlib</strong>, <strong>HBase</strong>, <strong>Spray</strong> and <strong>Elasticsearch</strong>, which simplifies and accelerates scalable machine learning infrastructure management.</p> <table><thead> <tr> <th>Getting Started</th> <th>Developer Guides</th> <th>ML Education and Usage</th> <th>PredictionIO SDKs</th> </tr> </thead><tbody> <tr> <td><a href="/start/">Quick Intro</a></td> <td><a href="/system/">System Architecture</a></td> <td><a href="/demo/tapster/">Comics Recommendation</a></td> <td><a href="/sdk/java/">Java</a></td> </tr> <tr> <td><a href="/install/">Installation Guide</a></td> <td><a href="/datacollection/">Event Server Overview</a></td> <td><a href="/demo/textclassification/">Text Classification</a></td> <td><a href="/sdk/php/">PHP</a></td> </tr> <tr> <td><a href="/start/download/">Downlo
ading Template</a></td> <td><a href="/datacollection/eventapi/">Collecting Data</a></td> <td><a href="/demo/community/">Community Contributed Demo</a></td> <td><a href="/sdk/python/">Python</a></td> </tr> <tr> <td><a href="/start/deploy/">Deploying an Engine</a></td> <td><a href="/customize/">Learning DASE</a></td> <td><a href="/machinelearning/dimensionalityreduction/">Dimensionality Reduction</a></td> <td><a href="/sdk/ruby/">Ruby</a></td> </tr> <tr> <td><a href="/start/customize/">Customizing an Engine</a></td> <td><a href="/customize/dase/">Implementing DASE</a></td> <td></td> <td><a href="/sdk/community/">Community Contributed</a></td> </tr> <tr> <td><a href="/appintegration/">App Integration Overview</a></td> <td><a href="/evaluation/">Evaluation Overview</a></td> <td></td> <td></td> </tr> <tr> <td></td> <td><a href="/resources/intellij/">Intellij IDEA Guide</a></td> <td></td> <td></td> </tr> <tr> <td></td> <td><a href="/api/current/#package">Scala API</a></td> <td></td> <td><
/td> </tr> </tbody></table> <h2 id='release-notes' class='header-anchors'>Release Notes</h2><p>A summary of the changes in each release before migrating to Apache Software Foundation are on GitHub <a href="https://github.com/PredictionIO/PredictionIO/blob/master/RELEASE.md">here</a>.</p><h2 id='licensing' class='header-anchors'>Licensing</h2><p>Apache PredictionIO (incubating) is licensed under the Apache License, Version 2.0. See <a href="https://github.com/apache/incubator-predictionio/blob/master/LICENSE.txt">LICENSE</a> for the full license text.</p></div></div></div></div><footer><div class="container"><div class="seperator"></div><div class="row"><div class="col-md-4 col-md-push-8 col-xs-12"><div class="subscription-form-wrapper"><h4>Subscribe to our Newsletter</h4><form class="ajax-form" id="subscribe-form" method="POST" action="https://script.google.com/macros/s/AKfycbwhzeKCQJjQ52eVAqNT_vcklH07OITUO7wzOMDXvK6EGAWgaZgF/exec"><input class="required underlined-input" type="emai
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<div class="row"><div class="col-md-9 col-sm-11 col-xs-11"><div class="hidden-md hidden-lg" id="mobile-page-heading-wrapper"><p>PredictionIO Docs</p><h4>Changing Data Store</h4></div><h4 class="hidden-sm hidden-xs">PredictionIO Docs</h4></div><div class="col-md-3 col-sm-1 col-xs-1 hidden-md hidden-lg"><img id="left-menu-indicator" src="/images/icons/down-arrow-dfe9f7fe.png"/></div><div class="col-md-3 col-sm-12 col-xs-12 swiftype-wrapper"><div class="swiftype"><form class="search-form"><img class="search-box-toggler hidden-xs hidden-sm" src="/images/icons/search-glass-704bd4ff.png"/><div class="search-box"><img src="/images/icons/search-glass-704bd4ff.png"/><input type="text" id="st-search-input" class="st-search-input" placeholder="Search Doc..."/></div><img class="swiftype-row-hider hidden-md hidden-lg" src="/images/icons/drawer-toggle-active-fcbef12a.png"/></form></div></div><div class="mobile-left-menu-toggler hidden-md hidden-lg"></div></div></div></div><div id="page" class="co
ntainer-fluid"><div class="row"><div id="left-menu-wrapper" class="col-md-3"><nav id="nav-main"><ul><li class="level-1"><a class="expandible" href="/"><span>Apache PredictionIO (incubating) Documentation</span></a><ul><li class="level-2"><a class="final" href="/"><span>Welcome to Apache PredictionIO (incubating)</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Getting Started</span></a><ul><li class="level-2"><a class="final" href="/start/"><span>A Quick Intro</span></a></li><li class="level-2"><a class="final" href="/install/"><span>Installing Apache PredictionIO (incubating)</span></a></li><li class="level-2"><a class="final" href="/start/download/"><span>Downloading an Engine Template</span></a></li><li class="level-2"><a class="final" href="/start/deploy/"><span>Deploying Your First Engine</span></a></li><li class="level-2"><a class="final" href="/start/customize/"><span>Customizing the Engine</span></a></li></ul></li><li class="level-1"><a class
="expandible" href="#"><span>Integrating with Your App</span></a><ul><li class="level-2"><a class="final" href="/appintegration/"><span>App Integration Overview</span></a></li><li class="level-2"><a class="expandible" href="/sdk/"><span>List of SDKs</span></a><ul><li class="level-3"><a class="final" href="/sdk/java/"><span>Java & Android SDK</span></a></li><li class="level-3"><a class="final" href="/sdk/php/"><span>PHP SDK</span></a></li><li class="level-3"><a class="final" href="/sdk/python/"><span>Python SDK</span></a></li><li class="level-3"><a class="final" href="/sdk/ruby/"><span>Ruby SDK</span></a></li><li class="level-3"><a class="final" href="/sdk/community/"><span>Community Powered SDKs</span></a></li></ul></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Deploying an Engine</span></a><ul><li class="level-2"><a class="final" href="/deploy/"><span>Deploying as a Web Service</span></a></li><li class="level-2"><a class="final" href="/cli/#engine-commands"
><span>Engine Command-line Interface</span></a></li><li class="level-2"><a class="final" href="/deploy/engineparams/"><span>Setting Engine Parameters</span></a></li><li class="level-2"><a class="final" href="/deploy/enginevariants/"><span>Deploying Multiple Engine Variants</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Customizing an Engine</span></a><ul><li class="level-2"><a class="final" href="/customize/"><span>Learning DASE</span></a></li><li class="level-2"><a class="final" href="/customize/dase/"><span>Implement DASE</span></a></li><li class="level-2"><a class="final" href="/customize/troubleshooting/"><span>Troubleshooting Engine Development</span></a></li><li class="level-2"><a class="final" href="/api/current/#package"><span>Engine Scala APIs</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Collecting and Analyzing Data</span></a><ul><li class="level-2"><a class="final" href="/datacollection/"><span>Event
Server Overview</span></a></li><li class="level-2"><a class="final" href="/cli/#event-server-commands"><span>Event Server Command-line Interface</span></a></li><li class="level-2"><a class="final" href="/datacollection/eventapi/"><span>Collecting Data with REST/SDKs</span></a></li><li class="level-2"><a class="final" href="/datacollection/eventmodel/"><span>Events Modeling</span></a></li><li class="level-2"><a class="final" href="/datacollection/webhooks/"><span>Unifying Multichannel Data with Webhooks</span></a></li><li class="level-2"><a class="final" href="/datacollection/channel/"><span>Channel</span></a></li><li class="level-2"><a class="final" href="/datacollection/batchimport/"><span>Importing Data in Batch</span></a></li><li class="level-2"><a class="final" href="/datacollection/analytics/"><span>Using Analytics Tools</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Choosing an Algorithm(s)</span></a><ul><li class="level-2"><a class="final" h
ref="/algorithm/"><span>Built-in Algorithm Libraries</span></a></li><li class="level-2"><a class="final" href="/algorithm/switch/"><span>Switching to Another Algorithm</span></a></li><li class="level-2"><a class="final" href="/algorithm/multiple/"><span>Combining Multiple Algorithms</span></a></li><li class="level-2"><a class="final" href="/algorithm/custom/"><span>Adding Your Own Algorithms</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>ML Tuning and Evaluation</span></a><ul><li class="level-2"><a class="final" href="/evaluation/"><span>Overview</span></a></li><li class="level-2"><a class="final" href="/evaluation/paramtuning/"><span>Hyperparameter Tuning</span></a></li><li class="level-2"><a class="final" href="/evaluation/evaluationdashboard/"><span>Evaluation Dashboard</span></a></li><li class="level-2"><a class="final" href="/evaluation/metricchoose/"><span>Choosing Evaluation Metrics</span></a></li><li class="level-2"><a class="final" href="/
evaluation/metricbuild/"><span>Building Evaluation Metrics</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>System Architecture</span></a><ul><li class="level-2"><a class="final" href="/system/"><span>Architecture Overview</span></a></li><li class="level-2"><a class="final" href="/system/anotherdatastore/"><span>Using Another Data Store</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Engine Template Gallery</span></a><ul><li class="level-2"><a class="final" href="http://templates.prediction.io"><span>Browse</span></a></li><li class="level-2"><a class="final" href="/community/submit-template/"><span>Submit your Engine as a Template</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Demo Tutorials</span></a><ul><li class="level-2"><a class="final" href="/demo/tapster/"><span>Comics Recommendation Demo</span></a></li><li class="level-2"><a class="final" href="/demo/community/"><span>Commun
ity Contributed Demo</span></a></li><li class="level-2"><a class="final" href="/demo/textclassification/"><span>Text Classification Engine Tutorial</span></a></li></ul></li><li class="level-1"><a class="expandible" href="/community/"><span>Getting Involved</span></a><ul><li class="level-2"><a class="final" href="/community/contribute-code/"><span>Contribute Code</span></a></li><li class="level-2"><a class="final" href="/community/contribute-documentation/"><span>Contribute Documentation</span></a></li><li class="level-2"><a class="final" href="/community/contribute-sdk/"><span>Contribute a SDK</span></a></li><li class="level-2"><a class="final" href="/community/contribute-webhook/"><span>Contribute a Webhook</span></a></li><li class="level-2"><a class="final" href="/community/projects/"><span>Community Projects</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Getting Help</span></a><ul><li class="level-2"><a class="final" href="/resources/faq/"><span
>FAQs</span></a></li><li class="level-2"><a class="final" href="/support/"><span>Community Support</span></a></li><li class="level-2"><a class="final" href="/support/#enterprise-support"><span>Enterprise Support</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Resources</span></a><ul><li class="level-2"><a class="final" href="/resources/intellij/"><span>Developing Engines with IntelliJ IDEA</span></a></li><li class="level-2"><a class="final" href="/resources/upgrade/"><span>Upgrade Instructions</span></a></li><li class="level-2"><a class="final" href="/resources/glossary/"><span>Glossary</span></a></li></ul></li></ul></nav></div><div class="col-md-9 col-sm-12"><div class="content-header hidden-md hidden-lg"><div id="page-title"><h1>Changing Data Store</h1></div></div><div id="table-of-content-wrapper"><h5>On this page</h5><aside id="table-of-contents"><ul> <li> <a href="#changing-storage-setup">Changing Storage Setup</a> </li> </ul> </aside><hr/><a i
d="edit-page-link" href="https://github.com/apache/incubator-predictionio/tree/livedoc/docs/manual/source/install/config-datastore.html.md"><img src="/images/icons/edit-pencil-d6c1bb3d.png"/>Edit this page</a></div><div class="content-header hidden-sm hidden-xs"><div id="page-title"><h1>Changing Data Store</h1></div></div><div class="content"><h1 id='changing-storage-setup' class='header-anchors'>Changing Storage Setup</h1><p>PredictionIO relies on a data store to store its metadata. At the moment, PredictionIO's storage layer supports <a href="http://www.elasticsearch.org/">Elasticsearch</a>. Make sure you have it running and functioning properly on your computer.</p> <ol> <li><p>If you are using Elasticsearch at the localhost and its default settings, you may stop here.</p></li> <li><p>Otherwise, change the following in <code>conf/pio-env.sh</code> to fit your setup.</p></li> </ol> <div class="highlight shell"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" s
tyle="text-align: right"><pre class="lineno">1
+2
+3</pre></td><td class="code"><pre> <span class="nv">PIO_STORAGE_SOURCES_ELASTICSEARCH_TYPE</span><span class="o">=</span>elasticsearch
+ <span class="nv">PIO_STORAGE_SOURCES_ELASTICSEARCH_HOSTS</span><span class="o">=</span>localhost
+ <span class="nv">PIO_STORAGE_SOURCES_ELASTICSEARCH_PORTS</span><span class="o">=</span>9300
+</pre></td></tr></tbody></table> </div> <p>Save <code>conf/pio-env.sh</code> and you are done!</p></div></div></div></div><footer><div class="container"><div class="seperator"></div><div class="row"><div class="col-md-4 col-md-push-8 col-xs-12"><div class="subscription-form-wrapper"><h4>Subscribe to our Newsletter</h4><form class="ajax-form" id="subscribe-form" method="POST" action="https://script.google.com/macros/s/AKfycbwhzeKCQJjQ52eVAqNT_vcklH07OITUO7wzOMDXvK6EGAWgaZgF/exec"><input class="required underlined-input" type="email" placeholder="Your email address" name="subscription_email" id="subscription_email"/><input class="pill-button" value="SUBSCRIBE" type="submit" data-state-normal="SUBSCRIBE" data-state-sucess="SUBSCRIBED!" data-state-loading="SENDING..." onclick="t($('#subscription_email').val());"/><p class="result"></p></form></div></div><div class="col-md-2 col-md-pull-4 col-xs-6 footer-link-column"><div class="footer-link-column-row"><h4>Community</h4><ul><li><a href="
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<div class="row"><div class="col-md-9 col-sm-11 col-xs-11"><div class="hidden-md hidden-lg" id="mobile-page-heading-wrapper"><p>PredictionIO Docs</p><h4>Level 4</h4></div><h4 class="hidden-sm hidden-xs">PredictionIO Docs</h4></div><div class="col-md-3 col-sm-1 col-xs-1 hidden-md hidden-lg"><img id="left-menu-indicator" src="/images/icons/down-arrow-dfe9f7fe.png"/></div><div class="col-md-3 col-sm-12 col-xs-12 swiftype-wrapper"><div class="swiftype"><form class="search-form"><img class="search-box-toggler hidden-xs hidden-sm" src="/images/icons/search-glass-704bd4ff.png"/><div class="search-box"><img src="/images/icons/search-glass-704bd4ff.png"/><input type="text" id="st-search-input" class="st-search-input" placeholder="Search Doc..."/></div><img class="swiftype-row-hider hidden-md hidden-lg" src="/images/icons/drawer-toggle-active-fcbef12a.png"/></form></div></div><div class="mobile-left-menu-toggler hidden-md hidden-lg"></div></div></div></div><div id="page" class="container-flui
d"><div class="row"><div id="left-menu-wrapper" class="col-md-3"><nav id="nav-main"><ul><li class="level-1"><a class="expandible" href="/"><span>Apache PredictionIO (incubating) Documentation</span></a><ul><li class="level-2"><a class="final" href="/"><span>Welcome to Apache PredictionIO (incubating)</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Getting Started</span></a><ul><li class="level-2"><a class="final" href="/start/"><span>A Quick Intro</span></a></li><li class="level-2"><a class="final" href="/install/"><span>Installing Apache PredictionIO (incubating)</span></a></li><li class="level-2"><a class="final" href="/start/download/"><span>Downloading an Engine Template</span></a></li><li class="level-2"><a class="final" href="/start/deploy/"><span>Deploying Your First Engine</span></a></li><li class="level-2"><a class="final" href="/start/customize/"><span>Customizing the Engine</span></a></li></ul></li><li class="level-1"><a class="expandible
" href="#"><span>Integrating with Your App</span></a><ul><li class="level-2"><a class="final" href="/appintegration/"><span>App Integration Overview</span></a></li><li class="level-2"><a class="expandible" href="/sdk/"><span>List of SDKs</span></a><ul><li class="level-3"><a class="final" href="/sdk/java/"><span>Java & Android SDK</span></a></li><li class="level-3"><a class="final" href="/sdk/php/"><span>PHP SDK</span></a></li><li class="level-3"><a class="final" href="/sdk/python/"><span>Python SDK</span></a></li><li class="level-3"><a class="final" href="/sdk/ruby/"><span>Ruby SDK</span></a></li><li class="level-3"><a class="final" href="/sdk/community/"><span>Community Powered SDKs</span></a></li></ul></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Deploying an Engine</span></a><ul><li class="level-2"><a class="final" href="/deploy/"><span>Deploying as a Web Service</span></a></li><li class="level-2"><a class="final" href="/cli/#engine-commands"><span>Engin
e Command-line Interface</span></a></li><li class="level-2"><a class="final" href="/deploy/engineparams/"><span>Setting Engine Parameters</span></a></li><li class="level-2"><a class="final" href="/deploy/enginevariants/"><span>Deploying Multiple Engine Variants</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Customizing an Engine</span></a><ul><li class="level-2"><a class="final" href="/customize/"><span>Learning DASE</span></a></li><li class="level-2"><a class="final" href="/customize/dase/"><span>Implement DASE</span></a></li><li class="level-2"><a class="final" href="/customize/troubleshooting/"><span>Troubleshooting Engine Development</span></a></li><li class="level-2"><a class="final" href="/api/current/#package"><span>Engine Scala APIs</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Collecting and Analyzing Data</span></a><ul><li class="level-2"><a class="final" href="/datacollection/"><span>Event Server Overv
iew</span></a></li><li class="level-2"><a class="final" href="/cli/#event-server-commands"><span>Event Server Command-line Interface</span></a></li><li class="level-2"><a class="final" href="/datacollection/eventapi/"><span>Collecting Data with REST/SDKs</span></a></li><li class="level-2"><a class="final" href="/datacollection/eventmodel/"><span>Events Modeling</span></a></li><li class="level-2"><a class="final" href="/datacollection/webhooks/"><span>Unifying Multichannel Data with Webhooks</span></a></li><li class="level-2"><a class="final" href="/datacollection/channel/"><span>Channel</span></a></li><li class="level-2"><a class="final" href="/datacollection/batchimport/"><span>Importing Data in Batch</span></a></li><li class="level-2"><a class="final" href="/datacollection/analytics/"><span>Using Analytics Tools</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Choosing an Algorithm(s)</span></a><ul><li class="level-2"><a class="final" href="/algori
thm/"><span>Built-in Algorithm Libraries</span></a></li><li class="level-2"><a class="final" href="/algorithm/switch/"><span>Switching to Another Algorithm</span></a></li><li class="level-2"><a class="final" href="/algorithm/multiple/"><span>Combining Multiple Algorithms</span></a></li><li class="level-2"><a class="final" href="/algorithm/custom/"><span>Adding Your Own Algorithms</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>ML Tuning and Evaluation</span></a><ul><li class="level-2"><a class="final" href="/evaluation/"><span>Overview</span></a></li><li class="level-2"><a class="final" href="/evaluation/paramtuning/"><span>Hyperparameter Tuning</span></a></li><li class="level-2"><a class="final" href="/evaluation/evaluationdashboard/"><span>Evaluation Dashboard</span></a></li><li class="level-2"><a class="final" href="/evaluation/metricchoose/"><span>Choosing Evaluation Metrics</span></a></li><li class="level-2"><a class="final" href="/evaluation/m
etricbuild/"><span>Building Evaluation Metrics</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>System Architecture</span></a><ul><li class="level-2"><a class="final" href="/system/"><span>Architecture Overview</span></a></li><li class="level-2"><a class="final" href="/system/anotherdatastore/"><span>Using Another Data Store</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Engine Template Gallery</span></a><ul><li class="level-2"><a class="final" href="http://templates.prediction.io"><span>Browse</span></a></li><li class="level-2"><a class="final" href="/community/submit-template/"><span>Submit your Engine as a Template</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Demo Tutorials</span></a><ul><li class="level-2"><a class="final" href="/demo/tapster/"><span>Comics Recommendation Demo</span></a></li><li class="level-2"><a class="final" href="/demo/community/"><span>Community Contribu
ted Demo</span></a></li><li class="level-2"><a class="final" href="/demo/textclassification/"><span>Text Classification Engine Tutorial</span></a></li></ul></li><li class="level-1"><a class="expandible" href="/community/"><span>Getting Involved</span></a><ul><li class="level-2"><a class="final" href="/community/contribute-code/"><span>Contribute Code</span></a></li><li class="level-2"><a class="final" href="/community/contribute-documentation/"><span>Contribute Documentation</span></a></li><li class="level-2"><a class="final" href="/community/contribute-sdk/"><span>Contribute a SDK</span></a></li><li class="level-2"><a class="final" href="/community/contribute-webhook/"><span>Contribute a Webhook</span></a></li><li class="level-2"><a class="final" href="/community/projects/"><span>Community Projects</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Getting Help</span></a><ul><li class="level-2"><a class="final" href="/resources/faq/"><span>FAQs</span>
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d hidden-lg"></div></div></div></div><div id="page" class="container-fluid"><div class="row"><div id="left-menu-wrapper" class="col-md-3"><nav id="nav-main"><ul><li class="level-1"><a class="expandible" href="/"><span>Apache PredictionIO (incubating) Documentation</span></a><ul><li class="level-2"><a class="final" href="/"><span>Welcome to Apache PredictionIO (incubating)</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Getting Started</span></a><ul><li class="level-2"><a class="final" href="/start/"><span>A Quick Intro</span></a></li><li class="level-2"><a class="final" href="/install/"><span>Installing Apache PredictionIO (incubating)</span></a></li><li class="level-2"><a class="final" href="/start/download/"><span>Downloading an Engine Template</span></a></li><li class="level-2"><a class="final" href="/start/deploy/"><span>Deploying Your First Engine</span></a></li><li class="level-2"><a class="final" href="/start/customize/"><span>Customizing the
Engine</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Integrating with Your App</span></a><ul><li class="level-2"><a class="final" href="/appintegration/"><span>App Integration Overview</span></a></li><li class="level-2"><a class="expandible" href="/sdk/"><span>List of SDKs</span></a><ul><li class="level-3"><a class="final" href="/sdk/java/"><span>Java & Android SDK</span></a></li><li class="level-3"><a class="final" href="/sdk/php/"><span>PHP SDK</span></a></li><li class="level-3"><a class="final" href="/sdk/python/"><span>Python SDK</span></a></li><li class="level-3"><a class="final" href="/sdk/ruby/"><span>Ruby SDK</span></a></li><li class="level-3"><a class="final" href="/sdk/community/"><span>Community Powered SDKs</span></a></li></ul></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Deploying an Engine</span></a><ul><li class="level-2"><a class="final" href="/deploy/"><span>Deploying as a Web Service</span></a></li><li
class="level-2"><a class="final" href="/cli/#engine-commands"><span>Engine Command-line Interface</span></a></li><li class="level-2"><a class="final" href="/deploy/engineparams/"><span>Setting Engine Parameters</span></a></li><li class="level-2"><a class="final" href="/deploy/enginevariants/"><span>Deploying Multiple Engine Variants</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Customizing an Engine</span></a><ul><li class="level-2"><a class="final" href="/customize/"><span>Learning DASE</span></a></li><li class="level-2"><a class="final" href="/customize/dase/"><span>Implement DASE</span></a></li><li class="level-2"><a class="final" href="/customize/troubleshooting/"><span>Troubleshooting Engine Development</span></a></li><li class="level-2"><a class="final" href="/api/current/#package"><span>Engine Scala APIs</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Collecting and Analyzing Data</span></a><ul><li class="l
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rithm(s)</span></a><ul><li class="level-2"><a class="final" href="/algorithm/"><span>Built-in Algorithm Libraries</span></a></li><li class="level-2"><a class="final" href="/algorithm/switch/"><span>Switching to Another Algorithm</span></a></li><li class="level-2"><a class="final" href="/algorithm/multiple/"><span>Combining Multiple Algorithms</span></a></li><li class="level-2"><a class="final" href="/algorithm/custom/"><span>Adding Your Own Algorithms</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>ML Tuning and Evaluation</span></a><ul><li class="level-2"><a class="final" href="/evaluation/"><span>Overview</span></a></li><li class="level-2"><a class="final" href="/evaluation/paramtuning/"><span>Hyperparameter Tuning</span></a></li><li class="level-2"><a class="final" href="/evaluation/evaluationdashboard/"><span>Evaluation Dashboard</span></a></li><li class="level-2"><a class="final" href="/evaluation/metricchoose/"><span>Choosing Evaluation Metric
s</span></a></li><li class="level-2"><a class="final" href="/evaluation/metricbuild/"><span>Building Evaluation Metrics</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>System Architecture</span></a><ul><li class="level-2"><a class="final" href="/system/"><span>Architecture Overview</span></a></li><li class="level-2"><a class="final" href="/system/anotherdatastore/"><span>Using Another Data Store</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Engine Template Gallery</span></a><ul><li class="level-2"><a class="final" href="http://templates.prediction.io"><span>Browse</span></a></li><li class="level-2"><a class="final" href="/community/submit-template/"><span>Submit your Engine as a Template</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Demo Tutorials</span></a><ul><li class="level-2"><a class="final" href="/demo/tapster/"><span>Comics Recommendation Demo</span></a></li><li class="l
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class="level-2"><a class="final" href="/resources/faq/"><span>FAQs</span></a></li><li class="level-2"><a class="final" href="/support/"><span>Community Support</span></a></li><li class="level-2"><a class="final" href="/support/#enterprise-support"><span>Enterprise Support</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Resources</span></a><ul><li class="level-2"><a class="final" href="/resources/intellij/"><span>Developing Engines with IntelliJ IDEA</span></a></li><li class="level-2"><a class="final" href="/resources/upgrade/"><span>Upgrade Instructions</span></a></li><li class="level-2"><a class="final" href="/resources/glossary/"><span>Glossary</span></a></li></ul></li></ul></nav></div><div class="col-md-9 col-sm-12"><div class="content-header hidden-md hidden-lg"><div id="page-title"><h1>Sizing Samples with an Extra Long Title to ThisIsAVeryVeryLongWord Show Wrapping</h1></div></div><div id="table-of-content-wrapper"><h5>On this page</h5><aside i
d="table-of-contents"><ul> <li> <a href="#long-text">Long Text</a> </li> </ul> </aside><hr/><a id="edit-page-link" href="https://github.com/apache/incubator-predictionio/tree/livedoc/docs/manual/source/samples/sizing.html.md"><img src="/images/icons/edit-pencil-d6c1bb3d.png"/>Edit this page</a></div><div class="content-header hidden-sm hidden-xs"><div id="page-title"><h1>Sizing Samples with an Extra Long Title to ThisIsAVeryVeryLongWord Show Wrapping</h1></div></div><div class="content"><h2 id='long-text' class='header-anchors'>Long Text</h2><p>This is a paragraph of text that spans multiple lines. This is a paragraph of text that spans multiple lines. This is a paragraph of text that spans multiple lines. This is a paragraph of text that spans multiple lines. This is a paragraph of text that spans multiple lines. This is a paragraph of text that spans multiple lines.</p><div class="highlight shell"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align:
right"><pre class="lineno">1
+2
+3</pre></td><td class="code"><pre>This is a code block with lines longer than 80 characters. This is a code block with lines longer than 80 characters. This is a code block with lines longer than 80 characters.
+
+This is a code block with lines longer than 80 characters. This is a code block with lines longer than 80 characters. This is a code block with lines longer than 80 characters.
+</pre></td></tr></tbody></table> </div> <p>This paragraph contains a single word 80 characters long. 12345678901234567890123456789012345678901234567890123456789012345678901234567890</p></div></div></div></div><footer><div class="container"><div class="seperator"></div><div class="row"><div class="col-md-4 col-md-push-8 col-xs-12"><div class="subscription-form-wrapper"><h4>Subscribe to our Newsletter</h4><form class="ajax-form" id="subscribe-form" method="POST" action="https://script.google.com/macros/s/AKfycbwhzeKCQJjQ52eVAqNT_vcklH07OITUO7wzOMDXvK6EGAWgaZgF/exec"><input class="required underlined-input" type="email" placeholder="Your email address" name="subscription_email" id="subscription_email"/><input class="pill-button" value="SUBSCRIBE" type="submit" data-state-normal="SUBSCRIBE" data-state-sucess="SUBSCRIBED!" data-state-loading="SENDING..." onclick="t($('#subscription_email').val());"/><p class="result"></p></form></div></div><div class="col-md-2 col-md-pull-4 col-xs-6 foot
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<div class="row"><div class="col-md-9 col-sm-11 col-xs-11"><div class="hidden-md hidden-lg" id="mobile-page-heading-wrapper"><p>PredictionIO Docs</p><h4>Troubleshooting Engine Development</h4></div><h4 class="hidden-sm hidden-xs">PredictionIO Docs</h4></div><div class="col-md-3 col-sm-1 col-xs-1 hidden-md hidden-lg"><img id="left-menu-indicator" src="/images/icons/down-arrow-dfe9f7fe.png"/></div><div class="col-md-3 col-sm-12 col-xs-12 swiftype-wrapper"><div class="swiftype"><form class="search-form"><img class="search-box-toggler hidden-xs hidden-sm" src="/images/icons/search-glass-704bd4ff.png"/><div class="search-box"><img src="/images/icons/search-glass-704bd4ff.png"/><input type="text" id="st-search-input" class="st-search-input" placeholder="Search Doc..."/></div><img class="swiftype-row-hider hidden-md hidden-lg" src="/images/icons/drawer-toggle-active-fcbef12a.png"/></form></div></div><div class="mobile-left-menu-toggler hidden-md hidden-lg"></div></div></div></div><div id="
page" class="container-fluid"><div class="row"><div id="left-menu-wrapper" class="col-md-3"><nav id="nav-main"><ul><li class="level-1"><a class="expandible" href="/"><span>Apache PredictionIO (incubating) Documentation</span></a><ul><li class="level-2"><a class="final" href="/"><span>Welcome to Apache PredictionIO (incubating)</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Getting Started</span></a><ul><li class="level-2"><a class="final" href="/start/"><span>A Quick Intro</span></a></li><li class="level-2"><a class="final" href="/install/"><span>Installing Apache PredictionIO (incubating)</span></a></li><li class="level-2"><a class="final" href="/start/download/"><span>Downloading an Engine Template</span></a></li><li class="level-2"><a class="final" href="/start/deploy/"><span>Deploying Your First Engine</span></a></li><li class="level-2"><a class="final" href="/start/customize/"><span>Customizing the Engine</span></a></li></ul></li><li class="le
vel-1"><a class="expandible" href="#"><span>Integrating with Your App</span></a><ul><li class="level-2"><a class="final" href="/appintegration/"><span>App Integration Overview</span></a></li><li class="level-2"><a class="expandible" href="/sdk/"><span>List of SDKs</span></a><ul><li class="level-3"><a class="final" href="/sdk/java/"><span>Java & Android SDK</span></a></li><li class="level-3"><a class="final" href="/sdk/php/"><span>PHP SDK</span></a></li><li class="level-3"><a class="final" href="/sdk/python/"><span>Python SDK</span></a></li><li class="level-3"><a class="final" href="/sdk/ruby/"><span>Ruby SDK</span></a></li><li class="level-3"><a class="final" href="/sdk/community/"><span>Community Powered SDKs</span></a></li></ul></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Deploying an Engine</span></a><ul><li class="level-2"><a class="final" href="/deploy/"><span>Deploying as a Web Service</span></a></li><li class="level-2"><a class="final" href="/cli/#e
ngine-commands"><span>Engine Command-line Interface</span></a></li><li class="level-2"><a class="final" href="/deploy/engineparams/"><span>Setting Engine Parameters</span></a></li><li class="level-2"><a class="final" href="/deploy/enginevariants/"><span>Deploying Multiple Engine Variants</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Customizing an Engine</span></a><ul><li class="level-2"><a class="final" href="/customize/"><span>Learning DASE</span></a></li><li class="level-2"><a class="final" href="/customize/dase/"><span>Implement DASE</span></a></li><li class="level-2"><a class="final active" href="/customize/troubleshooting/"><span>Troubleshooting Engine Development</span></a></li><li class="level-2"><a class="final" href="/api/current/#package"><span>Engine Scala APIs</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Collecting and Analyzing Data</span></a><ul><li class="level-2"><a class="final" href="/datacol
lection/"><span>Event Server Overview</span></a></li><li class="level-2"><a class="final" href="/cli/#event-server-commands"><span>Event Server Command-line Interface</span></a></li><li class="level-2"><a class="final" href="/datacollection/eventapi/"><span>Collecting Data with REST/SDKs</span></a></li><li class="level-2"><a class="final" href="/datacollection/eventmodel/"><span>Events Modeling</span></a></li><li class="level-2"><a class="final" href="/datacollection/webhooks/"><span>Unifying Multichannel Data with Webhooks</span></a></li><li class="level-2"><a class="final" href="/datacollection/channel/"><span>Channel</span></a></li><li class="level-2"><a class="final" href="/datacollection/batchimport/"><span>Importing Data in Batch</span></a></li><li class="level-2"><a class="final" href="/datacollection/analytics/"><span>Using Analytics Tools</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Choosing an Algorithm(s)</span></a><ul><li class="level
-2"><a class="final" href="/algorithm/"><span>Built-in Algorithm Libraries</span></a></li><li class="level-2"><a class="final" href="/algorithm/switch/"><span>Switching to Another Algorithm</span></a></li><li class="level-2"><a class="final" href="/algorithm/multiple/"><span>Combining Multiple Algorithms</span></a></li><li class="level-2"><a class="final" href="/algorithm/custom/"><span>Adding Your Own Algorithms</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>ML Tuning and Evaluation</span></a><ul><li class="level-2"><a class="final" href="/evaluation/"><span>Overview</span></a></li><li class="level-2"><a class="final" href="/evaluation/paramtuning/"><span>Hyperparameter Tuning</span></a></li><li class="level-2"><a class="final" href="/evaluation/evaluationdashboard/"><span>Evaluation Dashboard</span></a></li><li class="level-2"><a class="final" href="/evaluation/metricchoose/"><span>Choosing Evaluation Metrics</span></a></li><li class="level-2"><a
class="final" href="/evaluation/metricbuild/"><span>Building Evaluation Metrics</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>System Architecture</span></a><ul><li class="level-2"><a class="final" href="/system/"><span>Architecture Overview</span></a></li><li class="level-2"><a class="final" href="/system/anotherdatastore/"><span>Using Another Data Store</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Engine Template Gallery</span></a><ul><li class="level-2"><a class="final" href="http://templates.prediction.io"><span>Browse</span></a></li><li class="level-2"><a class="final" href="/community/submit-template/"><span>Submit your Engine as a Template</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Demo Tutorials</span></a><ul><li class="level-2"><a class="final" href="/demo/tapster/"><span>Comics Recommendation Demo</span></a></li><li class="level-2"><a class="final" href="/demo/co
mmunity/"><span>Community Contributed Demo</span></a></li><li class="level-2"><a class="final" href="/demo/textclassification/"><span>Text Classification Engine Tutorial</span></a></li></ul></li><li class="level-1"><a class="expandible" href="/community/"><span>Getting Involved</span></a><ul><li class="level-2"><a class="final" href="/community/contribute-code/"><span>Contribute Code</span></a></li><li class="level-2"><a class="final" href="/community/contribute-documentation/"><span>Contribute Documentation</span></a></li><li class="level-2"><a class="final" href="/community/contribute-sdk/"><span>Contribute a SDK</span></a></li><li class="level-2"><a class="final" href="/community/contribute-webhook/"><span>Contribute a Webhook</span></a></li><li class="level-2"><a class="final" href="/community/projects/"><span>Community Projects</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Getting Help</span></a><ul><li class="level-2"><a class="final" href="
/resources/faq/"><span>FAQs</span></a></li><li class="level-2"><a class="final" href="/support/"><span>Community Support</span></a></li><li class="level-2"><a class="final" href="/support/#enterprise-support"><span>Enterprise Support</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Resources</span></a><ul><li class="level-2"><a class="final" href="/resources/intellij/"><span>Developing Engines with IntelliJ IDEA</span></a></li><li class="level-2"><a class="final" href="/resources/upgrade/"><span>Upgrade Instructions</span></a></li><li class="level-2"><a class="final" href="/resources/glossary/"><span>Glossary</span></a></li></ul></li></ul></nav></div><div class="col-md-9 col-sm-12"><div class="content-header hidden-md hidden-lg"><div id="breadcrumbs" class="hidden-sm hidden xs"><ul><li><a href="#">Customizing an Engine</a><span class="spacer">></span></li><li><span class="last">Troubleshooting Engine Development</span></li></ul></div><div id="page
-title"><h1>Engine Development - Troubleshoot</h1></div></div><div id="table-of-content-wrapper"><h5>On this page</h5><aside id="table-of-contents"><ul> <li> <a href="#stop-training-between-stages">Stop Training between Stages</a> </li> <li> <a href="#sanity-check">Sanity Check</a> </li> <li> <a href="#engine-status-page">Engine Status Page</a> </li> <li> <a href="#pio-shell">pio-shell</a> </li> </ul> </aside><hr/><a id="edit-page-link" href="https://github.com/apache/incubator-predictionio/tree/livedoc/docs/manual/source/customize/troubleshooting.html.md"><img src="/images/icons/edit-pencil-d6c1bb3d.png"/>Edit this page</a></div><div class="content-header hidden-sm hidden-xs"><div id="breadcrumbs" class="hidden-sm hidden xs"><ul><li><a href="#">Customizing an Engine</a><span class="spacer">></span></li><li><span class="last">Troubleshooting Engine Development</span></li></ul></div><div id="page-title"><h1>Engine Development - Troubleshoot</h1></div></div><div class="content"><p>
Apache PredictionIO (incubating) provides the following features to help you debug engines during development cycle.</p><h2 id='stop-training-between-stages' class='header-anchors'>Stop Training between Stages</h2><p>By default <code>pio train</code> runs through the whole training process including <a href="/templates/recommendation/dase/">DataSource, Preparator and Algorithm</a>. To speed up the development and debug cycle, you can stop the process after each stage to verify it has completed correctly.</p><p>If you have modified DataSource and want to confirm the TrainingData is generated as expected, you can run <code>pio train</code> with <code>--stop-after-read</code> option:</p><div class="highlight shell"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1</pre></td><td class="code"><pre>pio train --stop-after-read
+</pre></td></tr></tbody></table> </div> <p>This would stop the training process after the TrainingData is generated.</p><p>For example, if you are running <a href="/templates/recommendation/quickstart/">Recommendation Template</a>, you should see the the training process stops after the TrainingData is printed.</p><div class="highlight shell"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1
+2
+3
+4</pre></td><td class="code"><pre><span class="o">[</span>INFO] <span class="o">[</span>CoreWorkflow<span class="nv">$]</span> TrainingData:
+<span class="o">[</span>INFO] <span class="o">[</span>CoreWorkflow<span class="nv">$]</span> ratings: <span class="o">[</span>1501] <span class="o">(</span>List<span class="o">(</span>Rating<span class="o">(</span>3,0,4.0<span class="o">)</span>, Rating<span class="o">(</span>3,1,4.0<span class="o">))</span>...<span class="o">)</span>
+...
+<span class="o">[</span>INFO] <span class="o">[</span>CoreWorkflow<span class="nv">$]</span> Training interrupted by io.prediction.workflow.StopAfterReadInterruption.
+</pre></td></tr></tbody></table> </div> <p>Similarly, you can stop the training after the Preparator phase by using --stop-after-prepare option and it would stop after PreparedData is generated:</p><div class="highlight shell"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1</pre></td><td class="code"><pre>pio train --stop-after-prepare
+</pre></td></tr></tbody></table> </div> <h2 id='sanity-check' class='header-anchors'>Sanity Check</h2><p>You can extend a trait <code>SanityCheck</code> and implement the method <code>sanityCheck()</code> with your error checking code. The <code>sanityCheck()</code> is called when the data is generated. This can be applied to <code>TrainingData</code>, <code>PreparedData</code> and the <code>Model</code> classes, which are outputs of DataSource's <code>readTraining()</code>, Preparator's <code>prepare()</code> and Algorithm's <code>train()</code> methods, respectively.</p><p>For example, one frequent error with the Recommendation Template is that the TrainingData is empty because the DataSource is not reading data correctly. You can add the check of empty data inside the <code>sanityCheck()</code> function. You can easily add other checking logic into the <code>sanityCheck()</code> function based on your own needs. Also, If you implement <code>toString()</code> method in
your TrainingData. You can call <code>toString()</code> inside <code>sanityCheck()</code> to print out some data for visual checking.</p><p>For example, to print TrainingData to console and check if the <code>ratings</code> is empty, you can do the following:</p><div class="highlight scala"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1
+2
+3
+4
+5
+6
+7
+8
+9
+10
+11
+12
+13
+14
+15
+16</pre></td><td class="code"><pre><span class="k">import</span> <span class="nn">io.prediction.controller.SanityCheck</span> <span class="c1">// ADDED
+</span>
+<span class="k">class</span> <span class="nc">TrainingData</span><span class="o">(</span>
+ <span class="k">val</span> <span class="n">ratings</span><span class="k">:</span> <span class="kt">RDD</span><span class="o">[</span><span class="kt">Rating</span><span class="o">]</span>
+<span class="o">)</span> <span class="k">extends</span> <span class="nc">Serializable</span> <span class="k">with</span> <span class="nc">SanityCheck</span> <span class="o">{</span> <span class="c1">// EXTEND SanityCheck
+</span> <span class="k">override</span> <span class="k">def</span> <span class="n">toString</span> <span class="k">=</span> <span class="o">{</span>
+ <span class="n">s</span><span class="s">"ratings: [${ratings.count()}] (${ratings.take(2).toList}...)"</span>
+ <span class="o">}</span>
+
+ <span class="c1">// IMPLEMENT sanityCheck()
+</span> <span class="k">override</span> <span class="k">def</span> <span class="n">sanityCheck</span><span class="o">()</span><span class="k">:</span> <span class="kt">Unit</span> <span class="o">=</span> <span class="o">{</span>
+ <span class="n">println</span><span class="o">(</span><span class="n">toString</span><span class="o">())</span>
+ <span class="c1">// add your other checking here
+</span> <span class="n">require</span><span class="o">(!</span><span class="n">ratings</span><span class="o">.</span><span class="n">take</span><span class="o">(</span><span class="mi">1</span><span class="o">).</span><span class="n">isEmpty</span><span class="o">,</span> <span class="n">s</span><span class="s">"ratings cannot be empty!"</span><span class="o">)</span>
+ <span class="o">}</span>
+<span class="o">}</span>
+</pre></td></tr></tbody></table> </div> <p>You may also use together with --stop-after-read flag to debug the DataSource:</p><div class="highlight shell"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1
+2</pre></td><td class="code"><pre>pio build
+pio train --stop-after-read
+</pre></td></tr></tbody></table> </div> <p>If your data is empty, you should see the following error thrown by the <code>sanityCheck()</code> function:</p><div class="highlight shell"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1
+2
+3
+4
+5
+6
+7
+8
+9</pre></td><td class="code"><pre><span class="o">[</span>INFO] <span class="o">[</span>CoreWorkflow<span class="nv">$]</span> Performing data sanity check on training data.
+<span class="o">[</span>INFO] <span class="o">[</span>CoreWorkflow<span class="nv">$]</span> org.template.recommendation.TrainingData supports data sanity check. Performing check.
+Exception <span class="k">in </span>thread <span class="s2">"main"</span> java.lang.IllegalArgumentException: requirement failed: ratings cannot be empty!
+ at scala.Predef<span class="nv">$.</span>require<span class="o">(</span>Predef.scala:233<span class="o">)</span>
+ at org.template.recommendation.TrainingData.sanityCheck<span class="o">(</span>DataSource.scala:73<span class="o">)</span>
+ at io.prediction.workflow.CoreWorkflow<span class="nv">$$</span>anonfun<span class="nv">$runTypelessContext$7</span>.apply<span class="o">(</span>Workflow.scala:474<span class="o">)</span>
+ at io.prediction.workflow.CoreWorkflow<span class="nv">$$</span>anonfun<span class="nv">$runTypelessContext$7</span>.apply<span class="o">(</span>Workflow.scala:465<span class="o">)</span>
+ at scala.collection.immutable.Map<span class="nv">$Map1</span>.foreach<span class="o">(</span>Map.scala:109<span class="o">)</span>
+ ...
+</pre></td></tr></tbody></table> </div> <p>You can specify the <code>--skip-sanity-check</code> option to turn off sanityCheck:</p><div class="highlight shell"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1</pre></td><td class="code"><pre>pio train --stop-after-read --skip-sanity-check
+</pre></td></tr></tbody></table> </div> <p>You should see the checking is skipped such as the following output:</p><div class="highlight shell"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1
+2
+3
+4</pre></td><td class="code"><pre><span class="o">[</span>INFO] <span class="o">[</span>CoreWorkflow<span class="nv">$]</span> Data sanity checking is off.
+<span class="o">[</span>INFO] <span class="o">[</span>CoreWorkflow<span class="nv">$]</span> Data Source
+...
+<span class="o">[</span>INFO] <span class="o">[</span>CoreWorkflow<span class="nv">$]</span> Training interrupted by io.prediction.workflow.StopAfterReadInterruption.
+</pre></td></tr></tbody></table> </div> <h2 id='engine-status-page' class='header-anchors'>Engine Status Page</h2><p>After run <code>pio deploy</code>, you can access the engine status page by go to same URL and port of the deployed engine with your browser, which is "<a href="http://localhost:8000">http://localhost:8000</a>" by default. In the engine status page, you can find the Engine information, and parameters of each DASE components. In particular, you can also see the "Model" trained by the algorithm based on how <code>toString()</code> method is implemented in the Algorithm's Model class.</p><h2 id='pio-shell' class='header-anchors'>pio-shell</h2><p>Apache PredictionIO (incubating) also provides <code>pio-shell</code> in which you can easily access Apache PredictionIO (incubating) API, Spark context and Spark API for quickly testing code or debugging purposes.</p><p>To bring up the shell, simply run:</p><div class="highlight shell"><table style="borde
r-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1</pre></td><td class="code"><pre><span class="gp">$ </span>pio-shell --with-spark
+</pre></td></tr></tbody></table> </div> <p>(<code>pio-shell</code> is available inside <code>bin/</code> directory of installed Apache PredictionIO (incubating) directory, you should be able to access it if you have added PredictionIO/bin into your environment variable <code>PATH</code>)</p><p>Note that the Spark context is available as variable <code>sc</code> inside the shell.</p><p>For example, to get the events of <code>MyApp1</code> using PEventStore API inside the pio-shell and collect them into an array <code>c</code>. run the following in the shell:</p><div class="highlight shell"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1
+2
+3</pre></td><td class="code"><pre><span class="gp">> </span>import io.prediction.data.store.PEventStore
+<span class="gp">> </span>val eventsRDD <span class="o">=</span> PEventStore.find<span class="o">(</span><span class="nv">appName</span><span class="o">=</span><span class="s2">"MyApp1"</span><span class="o">)(</span>sc<span class="o">)</span>
+<span class="gp">> </span>val c <span class="o">=</span> eventsRDD.collect<span class="o">()</span>
+</pre></td></tr></tbody></table> </div> <p>Then you should see following returned in the shell:</p><div class="highlight shell"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1
+2
+3</pre></td><td class="code"><pre>...
+15/05/18 14:24:42 INFO DAGScheduler: Job 0 finished: collect at <console>:24, took 1.850779 s
+c: Array[io.prediction.data.storage.Event] <span class="o">=</span> Array<span class="o">(</span>Event<span class="o">(</span><span class="nv">id</span><span class="o">=</span>Some<span class="o">(</span>AaQUUBsFZxteRpDV_7fDGQAAAU1ZfRW1tX9LSWdZSb0<span class="o">)</span>,event<span class="o">=</span><span class="nv">$set</span>,eType<span class="o">=</span>item,eId<span class="o">=</span>i42,tType<span class="o">=</span>None,tId<span class="o">=</span>None,p<span class="o">=</span>DataMap<span class="o">(</span>Map<span class="o">(</span>categories -> JArray<span class="o">(</span>List<span class="o">(</span>JString<span class="o">(</span>c2<span class="o">)</span>, JString<span class="o">(</span>c1<span class="o">)</span>, JString<span class="o">(</span>c6<span class="o">)</span>, JString<span class="o">(</span>c3<span class="o">)))))</span>,t<span class="o">=</span>2015-05-15T21:31:19.349Z,tags<span class="o">=</span>List<span class="o">()</span>,pKey<span class="o">=</span>Non
e,ct<span class="o">=</span>2015-05-15T21:31:19.354Z<span class="o">)</span>, Event<span class="o">(</span><span class="nv">id</span><span class="o">=</span>Some<span class="o">(</span>DjvP3Dnci9F4CWmiqoLabQAAAU1ZfROaqdRYO-pZ_no<span class="o">)</span>,event<span class="o">=</span><span class="nv">$set</span>,eType<span class="o">=</span>user,eId<span class="o">=</span>u9,tType<span class="o">=</span>None,tId<span class="o">=</span>None,p<span class="o">=</span>DataMap<span class="o">(</span>Map<span class="o">())</span>,t<span class="o">=</span>2015-05-15T21:31:18.810Z,tags<span class="o">=</span>List<span class="o">()</span>,pKey<span class="o">=</span>None,ct<span class="o">=</span>2015-05-15T21:31:18.817Z<span class="o">)</span>, Event<span class="o">(</span><span class="nv">id</span><span class="o">=</span>Some<span class="o">(</span>DjvP3Dnci9F4CWmiqoLabQAAAU1ZfRq7tsanlemwmZQ<span class="o">)</span>,event<span class="o">=</span>view,eType<span class="o">=</span>user,eId<span c
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+</pre></td></tr></tbody></table> </div> </div></div></div></div><footer><div class="container"><div class="seperator"></div><div class="row"><div class="col-md-4 col-md-push-8 col-xs-12"><div class="subscription-form-wrapper"><h4>Subscribe to our Newsletter</h4><form class="ajax-form" id="subscribe-form" method="POST" action="https://script.google.com/macros/s/AKfycbwhzeKCQJjQ52eVAqNT_vcklH07OITUO7wzOMDXvK6EGAWgaZgF/exec"><input class="required underlined-input" type="email" placeholder="Your email address" name="subscription_email" id="subscription_email"/><input class="pill-button" value="SUBSCRIBE" type="submit" data-state-normal="SUBSCRIBE" data-state-sucess="SUBSCRIBED!" data-state-loading="SENDING..." onclick="t($('#subscription_email').val());"/><p class="result"></p></form></div></div><div class="col-md-2 col-md-pull-4 col-xs-6 footer-link-column"><div class="footer-link-column-row"><h4>Community</h4><ul><li><a href="//docs.prediction.io/install/" target="blank">Download</a>
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/div><div id="page" class="container-fluid"><div class="row"><div id="left-menu-wrapper" class="col-md-3"><nav id="nav-main"><ul><li class="level-1"><a class="expandible" href="/"><span>Apache PredictionIO (incubating) Documentation</span></a><ul><li class="level-2"><a class="final" href="/"><span>Welcome to Apache PredictionIO (incubating)</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Getting Started</span></a><ul><li class="level-2"><a class="final" href="/start/"><span>A Quick Intro</span></a></li><li class="level-2"><a class="final" href="/install/"><span>Installing Apache PredictionIO (incubating)</span></a></li><li class="level-2"><a class="final" href="/start/download/"><span>Downloading an Engine Template</span></a></li><li class="level-2"><a class="final" href="/start/deploy/"><span>Deploying Your First Engine</span></a></li><li class="level-2"><a class="final" href="/start/customize/"><span>Customizing the Engine</span></a></li></ul></li
><li class="level-1"><a class="expandible" href="#"><span>Integrating with Your App</span></a><ul><li class="level-2"><a class="final" href="/appintegration/"><span>App Integration Overview</span></a></li><li class="level-2"><a class="expandible" href="/sdk/"><span>List of SDKs</span></a><ul><li class="level-3"><a class="final" href="/sdk/java/"><span>Java & Android SDK</span></a></li><li class="level-3"><a class="final" href="/sdk/php/"><span>PHP SDK</span></a></li><li class="level-3"><a class="final" href="/sdk/python/"><span>Python SDK</span></a></li><li class="level-3"><a class="final" href="/sdk/ruby/"><span>Ruby SDK</span></a></li><li class="level-3"><a class="final" href="/sdk/community/"><span>Community Powered SDKs</span></a></li></ul></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Deploying an Engine</span></a><ul><li class="level-2"><a class="final" href="/deploy/"><span>Deploying as a Web Service</span></a></li><li class="level-2"><a class="final"
href="/cli/#engine-commands"><span>Engine Command-line Interface</span></a></li><li class="level-2"><a class="final" href="/deploy/engineparams/"><span>Setting Engine Parameters</span></a></li><li class="level-2"><a class="final" href="/deploy/enginevariants/"><span>Deploying Multiple Engine Variants</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Customizing an Engine</span></a><ul><li class="level-2"><a class="final" href="/customize/"><span>Learning DASE</span></a></li><li class="level-2"><a class="final" href="/customize/dase/"><span>Implement DASE</span></a></li><li class="level-2"><a class="final" href="/customize/troubleshooting/"><span>Troubleshooting Engine Development</span></a></li><li class="level-2"><a class="final" href="/api/current/#package"><span>Engine Scala APIs</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Collecting and Analyzing Data</span></a><ul><li class="level-2"><a class="final" href="/
datacollection/"><span>Event Server Overview</span></a></li><li class="level-2"><a class="final" href="/cli/#event-server-commands"><span>Event Server Command-line Interface</span></a></li><li class="level-2"><a class="final" href="/datacollection/eventapi/"><span>Collecting Data with REST/SDKs</span></a></li><li class="level-2"><a class="final" href="/datacollection/eventmodel/"><span>Events Modeling</span></a></li><li class="level-2"><a class="final" href="/datacollection/webhooks/"><span>Unifying Multichannel Data with Webhooks</span></a></li><li class="level-2"><a class="final" href="/datacollection/channel/"><span>Channel</span></a></li><li class="level-2"><a class="final" href="/datacollection/batchimport/"><span>Importing Data in Batch</span></a></li><li class="level-2"><a class="final" href="/datacollection/analytics/"><span>Using Analytics Tools</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Choosing an Algorithm(s)</span></a><ul><li class
="level-2"><a class="final" href="/algorithm/"><span>Built-in Algorithm Libraries</span></a></li><li class="level-2"><a class="final" href="/algorithm/switch/"><span>Switching to Another Algorithm</span></a></li><li class="level-2"><a class="final" href="/algorithm/multiple/"><span>Combining Multiple Algorithms</span></a></li><li class="level-2"><a class="final" href="/algorithm/custom/"><span>Adding Your Own Algorithms</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>ML Tuning and Evaluation</span></a><ul><li class="level-2"><a class="final" href="/evaluation/"><span>Overview</span></a></li><li class="level-2"><a class="final" href="/evaluation/paramtuning/"><span>Hyperparameter Tuning</span></a></li><li class="level-2"><a class="final" href="/evaluation/evaluationdashboard/"><span>Evaluation Dashboard</span></a></li><li class="level-2"><a class="final" href="/evaluation/metricchoose/"><span>Choosing Evaluation Metrics</span></a></li><li class="leve
l-2"><a class="final" href="/evaluation/metricbuild/"><span>Building Evaluation Metrics</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>System Architecture</span></a><ul><li class="level-2"><a class="final" href="/system/"><span>Architecture Overview</span></a></li><li class="level-2"><a class="final" href="/system/anotherdatastore/"><span>Using Another Data Store</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Engine Template Gallery</span></a><ul><li class="level-2"><a class="final" href="http://templates.prediction.io"><span>Browse</span></a></li><li class="level-2"><a class="final" href="/community/submit-template/"><span>Submit your Engine as a Template</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Demo Tutorials</span></a><ul><li class="level-2"><a class="final" href="/demo/tapster/"><span>Comics Recommendation Demo</span></a></li><li class="level-2"><a class="final" href="/
demo/community/"><span>Community Contributed Demo</span></a></li><li class="level-2"><a class="final" href="/demo/textclassification/"><span>Text Classification Engine Tutorial</span></a></li></ul></li><li class="level-1"><a class="expandible" href="/community/"><span>Getting Involved</span></a><ul><li class="level-2"><a class="final" href="/community/contribute-code/"><span>Contribute Code</span></a></li><li class="level-2"><a class="final" href="/community/contribute-documentation/"><span>Contribute Documentation</span></a></li><li class="level-2"><a class="final" href="/community/contribute-sdk/"><span>Contribute a SDK</span></a></li><li class="level-2"><a class="final" href="/community/contribute-webhook/"><span>Contribute a Webhook</span></a></li><li class="level-2"><a class="final" href="/community/projects/"><span>Community Projects</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Getting Help</span></a><ul><li class="level-2"><a class="final"
href="/resources/faq/"><span>FAQs</span></a></li><li class="level-2"><a class="final" href="/support/"><span>Community Support</span></a></li><li class="level-2"><a class="final" href="/support/#enterprise-support"><span>Enterprise Support</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Resources</span></a><ul><li class="level-2"><a class="final" href="/resources/intellij/"><span>Developing Engines with IntelliJ IDEA</span></a></li><li class="level-2"><a class="final" href="/resources/upgrade/"><span>Upgrade Instructions</span></a></li><li class="level-2"><a class="final" href="/resources/glossary/"><span>Glossary</span></a></li></ul></li></ul></nav></div><div class="col-md-9 col-sm-12"><div class="content-header hidden-md hidden-lg"><div id="page-title"><h1>Machine Learning Analytics with IPython Notebook</h1></div></div><div id="table-of-content-wrapper"><h5>On this page</h5><aside id="table-of-contents"><ul> <li> <a href="#prerequisites">Prerequ
isites</a> </li> <li> <a href="#preparing-ipython-notebook">Preparing IPython Notebook</a> </li> <li> <a href="#performing-analysis-with-spark-sql">Performing Analysis with Spark SQL</a> </li> </ul> </aside><hr/><a id="edit-page-link" href="https://github.com/apache/incubator-predictionio/tree/livedoc/docs/manual/source/datacollection/analytics-ipynb.html.md.erb"><img src="/images/icons/edit-pencil-d6c1bb3d.png"/>Edit this page</a></div><div class="content-header hidden-sm hidden-xs"><div id="page-title"><h1>Machine Learning Analytics with IPython Notebook</h1></div></div><div class="content"><p><a href="http://ipython.org/notebook.html">IPython Notebook</a> is a very powerful interactive computational environment, and with <a href="http://predictionio.incubator.apache.org">Apache PredictionIO (incubating)</a>, <a href="http://spark.apache.org/docs/latest/api/python/">PySpark</a> and <a href="https://spark.apache.org/sql/">Spark SQL</a>, you can easily analyze your collected events
when you are developing or tuning your engine.</p><h2 id='prerequisites' class='header-anchors'>Prerequisites</h2><p>Before you begin, please make sure you have the latest stable IPython installed, and that the command <code>ipython</code> can be accessed from your shell's search path.</p><p><h2 id='export-events-to-apache-parquet' class='header-anchors'>Export Events to Apache Parquet</h2><p>PredictionIO supports exporting your events to <a href="http://parquet.incubator.apache.org/">Apache Parquet</a>, a columnar storage format that allows you to query quickly.</p><p>Let's export the data we imported in <a href="/templates/recommendation/quickstart/#import-sample-data">Recommendation Engine Template Quick Start</a>, and assume the App ID is 1.</p><div class="highlight shell"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1</pre></td><td class="code"><pre><span class="gp">$ </span><span class="nv">$PIO_HOME</s
pan>/bin/pio <span class="nb">export</span> --appid 1 --output /tmp/movies --format parquet
+</pre></td></tr></tbody></table> </div> <p>After the command has finished successfully, you should see something similar to the following.</p><div class="highlight shell"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1
+2
+3
+4
+5
+6
+7
+8
+9
+10
+11</pre></td><td class="code"><pre>root
+ |-- creationTime: string <span class="o">(</span>nullable <span class="o">=</span> <span class="nb">true</span><span class="o">)</span>
+ |-- entityId: string <span class="o">(</span>nullable <span class="o">=</span> <span class="nb">true</span><span class="o">)</span>
+ |-- entityType: string <span class="o">(</span>nullable <span class="o">=</span> <span class="nb">true</span><span class="o">)</span>
+ |-- event: string <span class="o">(</span>nullable <span class="o">=</span> <span class="nb">true</span><span class="o">)</span>
+ |-- eventId: string <span class="o">(</span>nullable <span class="o">=</span> <span class="nb">true</span><span class="o">)</span>
+ |-- eventTime: string <span class="o">(</span>nullable <span class="o">=</span> <span class="nb">true</span><span class="o">)</span>
+ |-- properties: struct <span class="o">(</span>nullable <span class="o">=</span> <span class="nb">true</span><span class="o">)</span>
+ | |-- rating: double <span class="o">(</span>nullable <span class="o">=</span> <span class="nb">true</span><span class="o">)</span>
+ |-- targetEntityId: string <span class="o">(</span>nullable <span class="o">=</span> <span class="nb">true</span><span class="o">)</span>
+ |-- targetEntityType: string <span class="o">(</span>nullable <span class="o">=</span> <span class="nb">true</span><span class="o">)</span>
+</pre></td></tr></tbody></table> </div></p><h2 id='preparing-ipython-notebook' class='header-anchors'>Preparing IPython Notebook</h2><p>Launch IPython Notebook with PySpark using the following command, with <code>$SPARK_HOME</code> replaced by the location of Apache Spark.</p><div class="highlight shell"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1</pre></td><td class="code"><pre><span class="gp">$ </span><span class="nv">PYSPARK_DRIVER_PYTHON</span><span class="o">=</span>ipython <span class="nv">PYSPARK_DRIVER_PYTHON_OPTS</span><span class="o">=</span><span class="s2">"notebook --pylab inline"</span> <span class="nv">$SPARK_HOME</span>/bin/pyspark
+</pre></td></tr></tbody></table> </div> <p>By default, you should be able to access your IPython Notebook via web browser at <a href="http://localhost:8888">http://localhost:8888</a>.</p><p>Let's initialize our notebook for the following code in the first cell.</p><div class="highlight python"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1
+2
+3
+4
+5
+6
+7</pre></td><td class="code"><pre><span class="kn">import</span> <span class="nn">pandas</span> <span class="kn">as</span> <span class="nn">pd</span>
+<span class="k">def</span> <span class="nf">rows_to_df</span><span class="p">(</span><span class="n">rows</span><span class="p">):</span>
+ <span class="k">return</span> <span class="n">pd</span><span class="o">.</span><span class="n">DataFrame</span><span class="p">(</span><span class="nb">map</span><span class="p">(</span><span class="k">lambda</span> <span class="n">e</span><span class="p">:</span> <span class="n">e</span><span class="o">.</span><span class="n">asDict</span><span class="p">(),</span> <span class="n">rows</span><span class="p">))</span>
+<span class="kn">from</span> <span class="nn">pyspark.sql</span> <span class="kn">import</span> <span class="n">SQLContext</span>
+<span class="n">sqlc</span> <span class="o">=</span> <span class="n">SQLContext</span><span class="p">(</span><span class="n">sc</span><span class="p">)</span>
+<span class="n">rdd</span> <span class="o">=</span> <span class="n">sqlc</span><span class="o">.</span><span class="n">parquetFile</span><span class="p">(</span><span class="s">"/tmp/movies"</span><span class="p">)</span>
+<span class="n">rdd</span><span class="o">.</span><span class="n">registerTempTable</span><span class="p">(</span><span class="s">"events"</span><span class="p">)</span>
+</pre></td></tr></tbody></table> </div> <p><img alt="Initialization for IPython Notebook" src="/images/datacollection/ipynb-01-004d791e.png"/></p><p><code>rows_to_df(rows)</code> will come in handy when we want to dump the results from Spark SQL using IPython Notebook's native table rendering.</p><h2 id='performing-analysis-with-spark-sql' class='header-anchors'>Performing Analysis with Spark SQL</h2><p>If all steps above ran successfully, you should have a ready-to-use analytics environment by now. Let's try a few examples to see if everything is functional.</p><p>In the second cell, put in this piece of code and run it.</p><div class="highlight python"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1
+2
+3
+4
+5</pre></td><td class="code"><pre><span class="n">summary</span> <span class="o">=</span> <span class="n">sqlc</span><span class="o">.</span><span class="n">sql</span><span class="p">(</span><span class="s">"SELECT "</span>
+ <span class="s">"entityType, event, targetEntityType, COUNT(*) AS c "</span>
+ <span class="s">"FROM events "</span>
+ <span class="s">"GROUP BY entityType, event, targetEntityType"</span><span class="p">)</span><span class="o">.</span><span class="n">collect</span><span class="p">()</span>
+<span class="n">rows_to_df</span><span class="p">(</span><span class="n">summary</span><span class="p">)</span>
+</pre></td></tr></tbody></table> </div> <p>You should see the following screen.</p><p><img alt="Summary of Events" src="/images/datacollection/ipynb-02-cd8b12e4.png"/></p><p>We can also plot our data, in the next two cells.</p><div class="highlight python"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1
+2
+3
+4
+5
+6
+7</pre></td><td class="code"><pre><span class="kn">import</span> <span class="nn">matplotlib.pyplot</span> <span class="kn">as</span> <span class="nn">plt</span>
+<span class="n">count</span> <span class="o">=</span> <span class="nb">map</span><span class="p">(</span><span class="k">lambda</span> <span class="n">e</span><span class="p">:</span> <span class="n">e</span><span class="o">.</span><span class="n">c</span><span class="p">,</span> <span class="n">summary</span><span class="p">)</span>
+<span class="n">event</span> <span class="o">=</span> <span class="nb">map</span><span class="p">(</span><span class="k">lambda</span> <span class="n">e</span><span class="p">:</span> <span class="s">"</span><span class="si">%</span><span class="s">s (</span><span class="si">%</span><span class="s">d)"</span> <span class="o">%</span> <span class="p">(</span><span class="n">e</span><span class="o">.</span><span class="n">event</span><span class="p">,</span> <span class="n">e</span><span class="o">.</span><span class="n">c</span><span class="p">),</span> <span class="n">summary</span><span class="p">)</span>
+<span class="n">colors</span> <span class="o">=</span> <span class="p">[</span><span class="s">'gold'</span><span class="p">,</span> <span class="s">'lightskyblue'</span><span class="p">]</span>
+<span class="n">plt</span><span class="o">.</span><span class="n">pie</span><span class="p">(</span><span class="n">count</span><span class="p">,</span> <span class="n">labels</span><span class="o">=</span><span class="n">event</span><span class="p">,</span> <span class="n">colors</span><span class="o">=</span><span class="n">colors</span><span class="p">,</span> <span class="n">startangle</span><span class="o">=</span><span class="mi">90</span><span class="p">,</span> <span class="n">autopct</span><span class="o">=</span><span class="s">"</span><span class="si">%1.1</span><span class="s">f</span><span class="si">%%</span><span class="s">"</span><span class="p">)</span>
+<span class="n">plt</span><span class="o">.</span><span class="n">axis</span><span class="p">(</span><span class="s">'equal'</span><span class="p">)</span>
+<span class="n">plt</span><span class="o">.</span><span class="n">show</span><span class="p">()</span>
+</pre></td></tr></tbody></table> </div> <p><img alt="Summary in Pie Chart" src="/images/datacollection/ipynb-03-28f3aa3d.png"/></p><div class="highlight python"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1
+2
+3
+4
+5
+6
+7
+8
+9
+10
+11
+12</pre></td><td class="code"><pre><span class="n">ratings</span> <span class="o">=</span> <span class="n">sqlc</span><span class="o">.</span><span class="n">sql</span><span class="p">(</span><span class="s">"SELECT properties.rating AS r, COUNT(*) AS c "</span>
+ <span class="s">"FROM events "</span>
+ <span class="s">"WHERE properties.rating IS NOT NULL "</span>
+ <span class="s">"GROUP BY properties.rating "</span>
+ <span class="s">"ORDER BY r"</span><span class="p">)</span><span class="o">.</span><span class="n">collect</span><span class="p">()</span>
+<span class="n">count</span> <span class="o">=</span> <span class="nb">map</span><span class="p">(</span><span class="k">lambda</span> <span class="n">e</span><span class="p">:</span> <span class="n">e</span><span class="o">.</span><span class="n">c</span><span class="p">,</span> <span class="n">ratings</span><span class="p">)</span>
+<span class="n">rating</span> <span class="o">=</span> <span class="nb">map</span><span class="p">(</span><span class="k">lambda</span> <span class="n">e</span><span class="p">:</span> <span class="s">"</span><span class="si">%</span><span class="s">s (</span><span class="si">%</span><span class="s">d)"</span> <span class="o">%</span> <span class="p">(</span><span class="n">e</span><span class="o">.</span><span class="n">r</span><span class="p">,</span> <span class="n">e</span><span class="o">.</span><span class="n">c</span><span class="p">),</span> <span class="n">ratings</span><span class="p">)</span>
+<span class="n">colors</span> <span class="o">=</span> <span class="p">[</span><span class="s">'yellowgreen'</span><span class="p">,</span> <span class="s">'plum'</span><span class="p">,</span> <span class="s">'gold'</span><span class="p">,</span> <span class="s">'lightskyblue'</span><span class="p">,</span> <span class="s">'lightcoral'</span><span class="p">]</span>
+<span class="n">plt</span><span class="o">.</span><span class="n">pie</span><span class="p">(</span><span class="n">count</span><span class="p">,</span> <span class="n">labels</span><span class="o">=</span><span class="n">rating</span><span class="p">,</span> <span class="n">colors</span><span class="o">=</span><span class="n">colors</span><span class="p">,</span> <span class="n">startangle</span><span class="o">=</span><span class="mi">90</span><span class="p">,</span>
+ <span class="n">autopct</span><span class="o">=</span><span class="s">"</span><span class="si">%1.1</span><span class="s">f</span><span class="si">%%</span><span class="s">"</span><span class="p">)</span>
+<span class="n">plt</span><span class="o">.</span><span class="n">axis</span><span class="p">(</span><span class="s">'equal'</span><span class="p">)</span>
+<span class="n">plt</span><span class="o">.</span><span class="n">show</span><span class="p">()</span>
+</pre></td></tr></tbody></table> </div> <p><img alt="Breakdown of Ratings" src="/images/datacollection/ipynb-04-797d73f1.png"/></p><p>Happy analyzing!</p></div></div></div></div><footer><div class="container"><div class="seperator"></div><div class="row"><div class="col-md-4 col-md-push-8 col-xs-12"><div class="subscription-form-wrapper"><h4>Subscribe to our Newsletter</h4><form class="ajax-form" id="subscribe-form" method="POST" action="https://script.google.com/macros/s/AKfycbwhzeKCQJjQ52eVAqNT_vcklH07OITUO7wzOMDXvK6EGAWgaZgF/exec"><input class="required underlined-input" type="email" placeholder="Your email address" name="subscription_email" id="subscription_email"/><input class="pill-button" value="SUBSCRIBE" type="submit" data-state-normal="SUBSCRIBE" data-state-sucess="SUBSCRIBED!" data-state-loading="SENDING..." onclick="t($('#subscription_email').val());"/><p class="result"></p></form></div></div><div class="col-md-2 col-md-pull-4 col-xs-6 footer-link-column"><div class="foo
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<div class="row"><div class="col-md-9 col-sm-11 col-xs-11"><div class="hidden-md hidden-lg" id="mobile-page-heading-wrapper"><p>PredictionIO Docs</p><h4>Upgrade Instructions</h4></div><h4 class="hidden-sm hidden-xs">PredictionIO Docs</h4></div><div class="col-md-3 col-sm-1 col-xs-1 hidden-md hidden-lg"><img id="left-menu-indicator" src="/images/icons/down-arrow-dfe9f7fe.png"/></div><div class="col-md-3 col-sm-12 col-xs-12 swiftype-wrapper"><div class="swiftype"><form class="search-form"><img class="search-box-toggler hidden-xs hidden-sm" src="/images/icons/search-glass-704bd4ff.png"/><div class="search-box"><img src="/images/icons/search-glass-704bd4ff.png"/><input type="text" id="st-search-input" class="st-search-input" placeholder="Search Doc..."/></div><img class="swiftype-row-hider hidden-md hidden-lg" src="/images/icons/drawer-toggle-active-fcbef12a.png"/></form></div></div><div class="mobile-left-menu-toggler hidden-md hidden-lg"></div></div></div></div><div id="page" class="c
ontainer-fluid"><div class="row"><div id="left-menu-wrapper" class="col-md-3"><nav id="nav-main"><ul><li class="level-1"><a class="expandible" href="/"><span>Apache PredictionIO (incubating) Documentation</span></a><ul><li class="level-2"><a class="final" href="/"><span>Welcome to Apache PredictionIO (incubating)</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Getting Started</span></a><ul><li class="level-2"><a class="final" href="/start/"><span>A Quick Intro</span></a></li><li class="level-2"><a class="final" href="/install/"><span>Installing Apache PredictionIO (incubating)</span></a></li><li class="level-2"><a class="final" href="/start/download/"><span>Downloading an Engine Template</span></a></li><li class="level-2"><a class="final" href="/start/deploy/"><span>Deploying Your First Engine</span></a></li><li class="level-2"><a class="final" href="/start/customize/"><span>Customizing the Engine</span></a></li></ul></li><li class="level-1"><a clas
s="expandible" href="#"><span>Integrating with Your App</span></a><ul><li class="level-2"><a class="final" href="/appintegration/"><span>App Integration Overview</span></a></li><li class="level-2"><a class="expandible" href="/sdk/"><span>List of SDKs</span></a><ul><li class="level-3"><a class="final" href="/sdk/java/"><span>Java & Android SDK</span></a></li><li class="level-3"><a class="final" href="/sdk/php/"><span>PHP SDK</span></a></li><li class="level-3"><a class="final" href="/sdk/python/"><span>Python SDK</span></a></li><li class="level-3"><a class="final" href="/sdk/ruby/"><span>Ruby SDK</span></a></li><li class="level-3"><a class="final" href="/sdk/community/"><span>Community Powered SDKs</span></a></li></ul></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Deploying an Engine</span></a><ul><li class="level-2"><a class="final" href="/deploy/"><span>Deploying as a Web Service</span></a></li><li class="level-2"><a class="final" href="/cli/#engine-commands
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Server Overview</span></a></li><li class="level-2"><a class="final" href="/cli/#event-server-commands"><span>Event Server Command-line Interface</span></a></li><li class="level-2"><a class="final" href="/datacollection/eventapi/"><span>Collecting Data with REST/SDKs</span></a></li><li class="level-2"><a class="final" href="/datacollection/eventmodel/"><span>Events Modeling</span></a></li><li class="level-2"><a class="final" href="/datacollection/webhooks/"><span>Unifying Multichannel Data with Webhooks</span></a></li><li class="level-2"><a class="final" href="/datacollection/channel/"><span>Channel</span></a></li><li class="level-2"><a class="final" href="/datacollection/batchimport/"><span>Importing Data in Batch</span></a></li><li class="level-2"><a class="final" href="/datacollection/analytics/"><span>Using Analytics Tools</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Choosing an Algorithm(s)</span></a><ul><li class="level-2"><a class="final"
href="/algorithm/"><span>Built-in Algorithm Libraries</span></a></li><li class="level-2"><a class="final" href="/algorithm/switch/"><span>Switching to Another Algorithm</span></a></li><li class="level-2"><a class="final" href="/algorithm/multiple/"><span>Combining Multiple Algorithms</span></a></li><li class="level-2"><a class="final" href="/algorithm/custom/"><span>Adding Your Own Algorithms</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>ML Tuning and Evaluation</span></a><ul><li class="level-2"><a class="final" href="/evaluation/"><span>Overview</span></a></li><li class="level-2"><a class="final" href="/evaluation/paramtuning/"><span>Hyperparameter Tuning</span></a></li><li class="level-2"><a class="final" href="/evaluation/evaluationdashboard/"><span>Evaluation Dashboard</span></a></li><li class="level-2"><a class="final" href="/evaluation/metricchoose/"><span>Choosing Evaluation Metrics</span></a></li><li class="level-2"><a class="final" href="
/evaluation/metricbuild/"><span>Building Evaluation Metrics</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>System Architecture</span></a><ul><li class="level-2"><a class="final" href="/system/"><span>Architecture Overview</span></a></li><li class="level-2"><a class="final" href="/system/anotherdatastore/"><span>Using Another Data Store</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Engine Template Gallery</span></a><ul><li class="level-2"><a class="final" href="http://templates.prediction.io"><span>Browse</span></a></li><li class="level-2"><a class="final" href="/community/submit-template/"><span>Submit your Engine as a Template</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Demo Tutorials</span></a><ul><li class="level-2"><a class="final" href="/demo/tapster/"><span>Comics Recommendation Demo</span></a></li><li class="level-2"><a class="final" href="/demo/community/"><span>Commu
nity Contributed Demo</span></a></li><li class="level-2"><a class="final" href="/demo/textclassification/"><span>Text Classification Engine Tutorial</span></a></li></ul></li><li class="level-1"><a class="expandible" href="/community/"><span>Getting Involved</span></a><ul><li class="level-2"><a class="final" href="/community/contribute-code/"><span>Contribute Code</span></a></li><li class="level-2"><a class="final" href="/community/contribute-documentation/"><span>Contribute Documentation</span></a></li><li class="level-2"><a class="final" href="/community/contribute-sdk/"><span>Contribute a SDK</span></a></li><li class="level-2"><a class="final" href="/community/contribute-webhook/"><span>Contribute a Webhook</span></a></li><li class="level-2"><a class="final" href="/community/projects/"><span>Community Projects</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Getting Help</span></a><ul><li class="level-2"><a class="final" href="/resources/faq/"><spa
n>FAQs</span></a></li><li class="level-2"><a class="final" href="/support/"><span>Community Support</span></a></li><li class="level-2"><a class="final" href="/support/#enterprise-support"><span>Enterprise Support</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Resources</span></a><ul><li class="level-2"><a class="final" href="/resources/intellij/"><span>Developing Engines with IntelliJ IDEA</span></a></li><li class="level-2"><a class="final active" href="/resources/upgrade/"><span>Upgrade Instructions</span></a></li><li class="level-2"><a class="final" href="/resources/glossary/"><span>Glossary</span></a></li></ul></li></ul></nav></div><div class="col-md-9 col-sm-12"><div class="content-header hidden-md hidden-lg"><div id="breadcrumbs" class="hidden-sm hidden xs"><ul><li><a href="#">Resources</a><span class="spacer">></span></li><li><span class="last">Upgrade Instructions</span></li></ul></div><div id="page-title"><h1>Upgrade Instructions</h1></d
iv></div><div id="table-of-content-wrapper"><h5>On this page</h5><aside id="table-of-contents"><ul> <li> <a href="#how-to-upgrade">How to upgrade</a> </li> <li> <a href="#additional-notes-for-specific-versions-upgrade">Additional Notes for Specific Versions Upgrade</a> <ul> <li> <a href="#upgrade-to-0-9-2">Upgrade to 0.9.2</a> </li> <li> <a href="#upgrade-to-0-9-0">Upgrade to 0.9.0</a> </li> <li> <a href="#upgrade-to-0-8-4">Upgrade to 0.8.4</a> </li> <li> <a href="#upgrade-from-0-8-2-to-0-8-3">Upgrade from 0.8.2 to 0.8.3</a> </li> <li> <a href="#schema-changes-in-0-8-2">Schema Changes in 0.8.2</a> </li> <li> <a href="#experimental-upgrade-tool-upgrade-hbase-schema-from-0-8-0-0-8-1-to-0-8-2">Experimental upgrade tool (Upgrade HBase schema from 0.8.0/0.8.1 to 0.8.2)</a> </li> </ul> </li> </ul> </aside><hr/><a id="edit-page-link" href="https://github.com/apache/incubator-predictionio/tree/livedoc/docs/manual/source/resources/upgrade.html.md"><img src="/images/icons/edit-pencil-d6c1bb3d
.png"/>Edit this page</a></div><div class="content-header hidden-sm hidden-xs"><div id="breadcrumbs" class="hidden-sm hidden xs"><ul><li><a href="#">Resources</a><span class="spacer">></span></li><li><span class="last">Upgrade Instructions</span></li></ul></div><div id="page-title"><h1>Upgrade Instructions</h1></div></div><div class="content"><p>This page highlights major changes in each version and upgrade tools.</p><h1 id='how-to-upgrade' class='header-anchors'>How to upgrade</h1><p>To upgrade and use new version of PredictionIO, do the following:</p> <ul> <li>Download and unzip the new PredictionIO binary (the download path can be found in the <a href="/install/install-linux/#method-2:-manual-install">Download PredictionIO section</a>)</li> <li>Retain the setting from current PredictionIO/conf/pio-env.sh to the new PredictionIO/conf/pio-env.sh.</li> <li>If you have added PredictionIO/bin to your <code>PATH</code> environment variable before, change it to the new PredictionIO/b
in as well.</li> </ul> <h1 id='additional-notes-for-specific-versions-upgrade' class='header-anchors'>Additional Notes for Specific Versions Upgrade</h1><p>In addition, please take notes of the following for specific version upgrade.</p><h2 id='upgrade-to-0.9.2' class='header-anchors'>Upgrade to 0.9.2</h2><p>The Spark dependency has been upgraded to version 1.3.0. All engines must be rebuilt against it in order to work.</p><p>Open and edit <code>build.sbt</code> of your engine, and look for these two lines:</p><div class="highlight scala"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1
+2
+3</pre></td><td class="code"><pre><span class="s">"org.apache.spark"</span> <span class="o">%%</span> <span class="s">"spark-core"</span> <span class="o">%</span> <span class="s">"1.2.0"</span> <span class="o">%</span> <span class="s">"provided"</span>
+
+<span class="s">"org.apache.spark"</span> <span class="o">%%</span> <span class="s">"spark-mllib"</span> <span class="o">%</span> <span class="s">"1.2.0"</span> <span class="o">%</span> <span class="s">"provided"</span>
+</pre></td></tr></tbody></table> </div> <p>Change <code>1.2.0</code> to <code>1.3.0</code>, and do a clean rebuild by <code>pio build --clean</code>. Your engine should now work with the latest Apache Spark.</p><h3 id='new-peventstore-and-leventstore-api' class='header-anchors'>New PEventStore and LEventStore API</h3><p>In addition, new PEventStore and LEventStore API are introduced so that appName can be used as parameters in engine.json to access Event Store.</p><div class="alert-message note"><p>The following changes are not required for using 0.9.2 but it's recommended to upgrade your engine code as described below because the old API will be deprecated.</p></div><h4 id='1.-in-<strong>datasource.scala</strong>:' class='header-anchors' >1. In <strong>DataSource.scala</strong>:</h4> <ul> <li><p>remove this line of code:</p><div class="highlight scala"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1</pre></td><td
class="code"><pre><span class="k">import</span> <span class="nn">io.prediction.data.storage.Storage</span>
+</pre></td></tr></tbody></table> </div> <p>and replace it by</p><div class="highlight scala"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1</pre></td><td class="code"><pre><span class="k">import</span> <span class="nn">io.prediction.data.store.PEventStore</span>
+</pre></td></tr></tbody></table> </div></li> <li><p>Change <code>appId: Int</code> to <code>appName: String</code> in DataSourceParams</p><p>For example,</p><div class="highlight scala"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1</pre></td><td class="code"><pre><span class="k">case</span> <span class="k">class</span> <span class="nc">DataSourceParams</span><span class="o">(</span><span class="n">appName</span><span class="k">:</span> <span class="kt">String</span><span class="o">)</span> <span class="k">extends</span> <span class="nc">Params</span>
+</pre></td></tr></tbody></table> </div></li> <li><p>remove this line of code: <code>val eventsDb = Storage.getPEvents()</code></p></li> <li><p>locate where <code>eventsDb.aggregateProperties()</code> is used, change it to <code>PEventStore.aggregateProperties()</code>:</p><p>For example,</p><div class="highlight scala"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1
+2
+3
+4
+5
+6</pre></td><td class="code"><pre>
+ <span class="k">val</span> <span class="n">usersRDD</span><span class="k">:</span> <span class="kt">RDD</span><span class="o">[(</span><span class="kt">String</span>, <span class="kt">User</span><span class="o">)]</span> <span class="k">=</span> <span class="nc">PEventStore</span><span class="o">.</span><span class="n">aggregateProperties</span><span class="o">(</span> <span class="c1">// CHANGED
+</span> <span class="n">appName</span> <span class="k">=</span> <span class="n">dsp</span><span class="o">.</span><span class="n">appName</span><span class="o">,</span> <span class="c1">// CHANGED: use appName
+</span> <span class="n">entityType</span> <span class="k">=</span> <span class="s">"user"</span>
+ <span class="o">)(</span><span class="n">sc</span><span class="o">).</span><span class="n">map</span> <span class="o">{</span> <span class="o">...</span> <span class="o">}</span>
+
+</pre></td></tr></tbody></table> </div></li> <li><p>locate where <code>eventsDb.find()</code>is used, change it to <code>PEventStore.find()</code></p><p>For example,</p><div class="highlight scala"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1
+2
+3
+4
+5
+6</pre></td><td class="code"><pre>
+ <span class="k">val</span> <span class="n">viewEventsRDD</span><span class="k">:</span> <span class="kt">RDD</span><span class="o">[</span><span class="kt">ViewEvent</span><span class="o">]</span> <span class="k">=</span> <span class="nc">PEventStore</span><span class="o">.</span><span class="n">find</span><span class="o">(</span> <span class="c1">// CHANGED
+</span> <span class="n">appName</span> <span class="k">=</span> <span class="n">dsp</span><span class="o">.</span><span class="n">appName</span><span class="o">,</span> <span class="c1">// CHANGED: use appName
+</span> <span class="n">entityType</span> <span class="k">=</span> <span class="nc">Some</span><span class="o">(</span><span class="s">"user"</span><span class="o">),</span>
+ <span class="o">...</span>
+
+</pre></td></tr></tbody></table> </div></li> </ul> <h4 id='2.-in-<strong>xxxalgorithm.scala</strong>:' class='header-anchors' >2. In <strong>XXXAlgorithm.scala</strong>:</h4><p>If Storage.getLEvents() is also used in Algorithm (such as ALSAlgorithm of E-Commerce Recommendation template), you also need to do following:</p><div class="alert-message note"><p>If <code>io.prediction.data.storage.Storage</code> is not used at all (such as Recommendation, Similar Product, Classification, Lead Scoring, Product Ranking template), there is no need to change Algorithm and can go to the later <strong>engine.json</strong> section.</p></div> <ul> <li>remove <code>import io.prediction.data.storage.Storage</code> and replace it by <code>import io.prediction.data.store.LEventStore</code></li> <li>change <code>appId</code> to <code>appName</code> in the XXXAlgorithmParams class.</li> <li>remove this line of code: <code>@transient lazy val lEventsDb = Storage.getLEvents()</code></li> <li><p>locate whe
re <code>LEventStore.findByEntity()</code> is used, change it to <code>LEventStore.findByEntity()</code>:</p><p>For example, change following code</p><div class="highlight scala"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1
+2
+3
+4
+5
+6
+7
+8
+9
+10
+11
+12
+13
+14
+15
+16</pre></td><td class="code"><pre> <span class="o">...</span>
+ <span class="k">val</span> <span class="n">seenEvents</span><span class="k">:</span> <span class="kt">Iterator</span><span class="o">[</span><span class="kt">Event</span><span class="o">]</span> <span class="k">=</span> <span class="n">lEventsDb</span><span class="o">.</span><span class="n">findSingleEntity</span><span class="o">(</span>
+ <span class="n">appId</span> <span class="k">=</span> <span class="n">ap</span><span class="o">.</span><span class="n">appId</span><span class="o">,</span>
+ <span class="n">entityType</span> <span class="k">=</span> <span class="s">"user"</span><span class="o">,</span>
+ <span class="n">entityId</span> <span class="k">=</span> <span class="n">query</span><span class="o">.</span><span class="n">user</span><span class="o">,</span>
+ <span class="n">eventNames</span> <span class="k">=</span> <span class="nc">Some</span><span class="o">(</span><span class="n">ap</span><span class="o">.</span><span class="n">seenEvents</span><span class="o">),</span>
+ <span class="n">targetEntityType</span> <span class="k">=</span> <span class="nc">Some</span><span class="o">(</span><span class="nc">Some</span><span class="o">(</span><span class="s">"item"</span><span class="o">)),</span>
+ <span class="c1">// set time limit to avoid super long DB access
+</span> <span class="n">timeout</span> <span class="k">=</span> <span class="nc">Duration</span><span class="o">(</span><span class="mi">200</span><span class="o">,</span> <span class="s">"millis"</span><span class="o">)</span>
+ <span class="o">)</span> <span class="k">match</span> <span class="o">{</span>
+ <span class="k">case</span> <span class="nc">Right</span><span class="o">(</span><span class="n">x</span><span class="o">)</span> <span class="k">=></span> <span class="n">x</span>
+ <span class="k">case</span> <span class="nc">Left</span><span class="o">(</span><span class="n">e</span><span class="o">)</span> <span class="k">=></span> <span class="o">{</span>
+ <span class="n">logger</span><span class="o">.</span><span class="n">error</span><span class="o">(</span><span class="n">s</span><span class="s">"Error when read seen events: ${e}"</span><span class="o">)</span>
+ <span class="nc">Iterator</span><span class="o">[</span><span class="kt">Event</span><span class="o">]()</span>
+ <span class="o">}</span>
+ <span class="o">}</span>
+</pre></td></tr></tbody></table> </div> <p>to</p><div class="highlight scala"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1
+2
+3
+4
+5
+6
+7
+8
+9
+10
+11
+12
+13
+14
+15
+16
+17
+18
+19</pre></td><td class="code"><pre> <span class="k">val</span> <span class="n">seenEvents</span><span class="k">:</span> <span class="kt">Iterator</span><span class="o">[</span><span class="kt">Event</span><span class="o">]</span> <span class="k">=</span> <span class="k">try</span> <span class="o">{</span> <span class="c1">// CHANGED: try catch block is used
+</span> <span class="nc">LEventStore</span><span class="o">.</span><span class="n">findByEntity</span><span class="o">(</span> <span class="c1">// CHANGED: new API
+</span> <span class="n">appName</span> <span class="k">=</span> <span class="n">ap</span><span class="o">.</span><span class="n">appName</span><span class="o">,</span> <span class="c1">// CHANGED: use appName
+</span> <span class="n">entityType</span> <span class="k">=</span> <span class="s">"user"</span><span class="o">,</span>
+ <span class="n">entityId</span> <span class="k">=</span> <span class="n">query</span><span class="o">.</span><span class="n">user</span><span class="o">,</span>
+ <span class="n">eventNames</span> <span class="k">=</span> <span class="nc">Some</span><span class="o">(</span><span class="n">ap</span><span class="o">.</span><span class="n">seenEvents</span><span class="o">),</span>
+ <span class="n">targetEntityType</span> <span class="k">=</span> <span class="nc">Some</span><span class="o">(</span><span class="nc">Some</span><span class="o">(</span><span class="s">"item"</span><span class="o">)),</span>
+ <span class="c1">// set time limit to avoid super long DB access
+</span> <span class="n">timeout</span> <span class="k">=</span> <span class="nc">Duration</span><span class="o">(</span><span class="mi">200</span><span class="o">,</span> <span class="s">"millis"</span><span class="o">)</span>
+ <span class="o">)</span>
+ <span class="o">}</span> <span class="k">catch</span> <span class="o">{</span> <span class="c1">// CHANGED: try catch block is used
+</span> <span class="k">case</span> <span class="n">e</span><span class="k">:</span> <span class="kt">scala.concurrent.TimeoutException</span> <span class="o">=></span>
+ <span class="n">logger</span><span class="o">.</span><span class="n">error</span><span class="o">(</span><span class="n">s</span><span class="s">"Timeout when read seen events."</span> <span class="o">+</span>
+ <span class="n">s</span><span class="s">" Empty list is used. ${e}"</span><span class="o">)</span>
+ <span class="nc">Iterator</span><span class="o">[</span><span class="kt">Event</span><span class="o">]()</span>
+ <span class="k">case</span> <span class="n">e</span><span class="k">:</span> <span class="kt">Exception</span> <span class="o">=></span>
+ <span class="n">logger</span><span class="o">.</span><span class="n">error</span><span class="o">(</span><span class="n">s</span><span class="s">"Error when read seen events: ${e}"</span><span class="o">)</span>
+ <span class="k">throw</span> <span class="n">e</span>
+ <span class="o">}</span>
+</pre></td></tr></tbody></table> </div> <p>If you are using E-Commerce Recommendation template, please refer to the latest version for other updates related to <code>LEventStore.findByEntity()</code></p></li> </ul> <h4 id='3.-in-<strong>engine.json</strong>:' class='header-anchors' >3. In <strong>engine.json</strong>:</h4><p>locate where <code>appId</code> is used, change it to <code>appName</code> and specify the name of the app instead.</p><p>For example:</p><div class="highlight json"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1
+2
+3
+4
+5
+6
+7
+8</pre></td><td class="code"><pre><span class="w"> </span><span class="err">...</span><span class="w">
+
+ </span><span class="s2">"datasource"</span><span class="err">:</span><span class="w"> </span><span class="p">{</span><span class="w">
+ </span><span class="s2">"params"</span><span class="w"> </span><span class="p">:</span><span class="w"> </span><span class="p">{</span><span class="w">
+ </span><span class="s2">"appName"</span><span class="p">:</span><span class="w"> </span><span class="s2">"MyAppName"</span><span class="w">
+ </span><span class="p">}</span><span class="w">
+ </span><span class="p">}</span><span class="err">,</span><span class="w">
+
+</span></pre></td></tr></tbody></table> </div> <p>Note that other components such as <code>algorithms</code> may also have <code>appId</code> param (e.g. E-Commerce Recommendation template). Remember to change it to <code>appName</code> as well.</p><p>That's it! You can re-biuld your engine to try it out!</p><h2 id='upgrade-to-0.9.0' class='header-anchors'>Upgrade to 0.9.0</h2><p>0.9.0 has the following new changes:</p> <ul> <li><p>The signature of <code>P2LAlgorithm</code> and <code>PAlgorithm</code>'s <code>train()</code> method is changed from</p><div class="highlight scala"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1</pre></td><td class="code"><pre> <span class="k">def</span> <span class="n">train</span><span class="o">(</span><span class="n">pd</span><span class="k">:</span> <span class="kt">PD</span><span class="o">)</span><span class="k">:</span> <span class="kt">M</span>
+</pre></td></tr></tbody></table> </div> <p>to</p><div class="highlight scala"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1</pre></td><td class="code"><pre> <span class="k">def</span> <span class="n">train</span><span class="o">(</span><span class="n">sc</span><span class="k">:</span> <span class="kt">SparkContext</span><span class="o">,</span> <span class="n">pd</span><span class="k">:</span> <span class="kt">PD</span><span class="o">)</span><span class="k">:</span> <span class="kt">M</span>
+</pre></td></tr></tbody></table> </div> <p>which allows you to access SparkContext inside <code>train()</code> with this new parameter <code>sc</code>.</p></li> <li><p>A new SBT build plugin (<code>pio-build</code>) is added for engine template</p></li> </ul> <div class="alert-message warning"><p>If you have existing engine templates running with previous version of PredictionIO, you need to either download the latest templates which are compatible with 0.9.0, or follow the instructions below to modify them.</p></div><p>Follow instructions below to modify existing engine templates to be compatible with PredictionIO 0.9.0:</p> <ol> <li><p>Add a new parameter <code>sc: SparkContext</code> in the signature of <code>train()</code> method of algorithm in the templates.</p><p>For example, in Recommendation engine template, you will find the following <code>train()</code> function in <code>ALSAlgorithm.scala</code></p><div class="highlight scala"><table style="border-spacing: 0"><tbody><tr
><td class="gutter gl" style="text-align: right"><pre class="lineno">1
+2
+3
+4
+5
+6
+7
+8
+9</pre></td><td class="code"><pre><span class="k">class</span> <span class="nc">ALSAlgorithm</span><span class="o">(</span><span class="k">val</span> <span class="n">ap</span><span class="k">:</span> <span class="kt">ALSAlgorithmParams</span><span class="o">)</span>
+ <span class="k">extends</span> <span class="n">P2LAlgorithm</span><span class="o">[</span><span class="kt">PreparedData</span>, <span class="kt">ALSModel</span>, <span class="kt">Query</span>, <span class="kt">PredictedResult</span><span class="o">]</span> <span class="o">{</span>
+
+ <span class="o">...</span>
+
+ <span class="k">def</span> <span class="n">train</span><span class="o">(</span><span class="n">data</span><span class="k">:</span> <span class="kt">PreparedData</span><span class="o">)</span><span class="k">:</span> <span class="kt">ALSModel</span> <span class="o">=</span> <span class="o">...</span>
+
+ <span class="o">...</span>
+<span class="o">}</span>
+</pre></td></tr></tbody></table> </div> <p>Simply add the new parameter <code>sc: SparkContext,</code> to <code>train()</code> function signature:</p><div class="highlight scala"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1
+2
+3
+4
+5
+6
+7
+8
+9</pre></td><td class="code"><pre><span class="k">class</span> <span class="nc">ALSAlgorithm</span><span class="o">(</span><span class="k">val</span> <span class="n">ap</span><span class="k">:</span> <span class="kt">ALSAlgorithmParams</span><span class="o">)</span>
+ <span class="k">extends</span> <span class="n">P2LAlgorithm</span><span class="o">[</span><span class="kt">PreparedData</span>, <span class="kt">ALSModel</span>, <span class="kt">Query</span>, <span class="kt">PredictedResult</span><span class="o">]</span> <span class="o">{</span>
+
+ <span class="o">...</span>
+
+ <span class="k">def</span> <span class="n">train</span><span class="o">(</span><span class="n">sc</span><span class="k">:</span> <span class="kt">SparkContext</span><span class="o">,</span> <span class="n">data</span><span class="k">:</span> <span class="kt">PreparedData</span><span class="o">)</span><span class="k">:</span> <span class="kt">ALSModel</span> <span class="o">=</span> <span class="o">...</span>
+
+ <span class="o">...</span>
+<span class="o">}</span>
+</pre></td></tr></tbody></table> </div> <p>You need to add the following import for your algorithm as well if it is not there:</p><div class="highlight scala"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1</pre></td><td class="code"><pre><span class="k">import</span> <span class="nn">org.apache.spark.SparkContext</span>
+</pre></td></tr></tbody></table> </div></li> <li><p>Modify the file <code>build.sbt</code> in your template directory to use <code>pioVersion.value</code> as the version of io.prediction.core dependency:</p><p>Under your template's root directory, you should see a file <code>build.sbt</code> which has the following content:</p><div class="highlight shell"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1
+2
+3
+4</pre></td><td class="code"><pre>libraryDependencies ++<span class="o">=</span> Seq<span class="o">(</span>
+ <span class="s2">"io.prediction"</span> %% <span class="s2">"core"</span> % <span class="s2">"0.8.6"</span> % <span class="s2">"provided"</span>,
+ <span class="s2">"org.apache.spark"</span> %% <span class="s2">"spark-core"</span> % <span class="s2">"1.2.0"</span> % <span class="s2">"provided"</span>,
+ <span class="s2">"org.apache.spark"</span> %% <span class="s2">"spark-mllib"</span> % <span class="s2">"1.2.0"</span> % <span class="s2">"provided"</span><span class="o">)</span>
+</pre></td></tr></tbody></table> </div> <p>Change the version of <code>"io.prediction" && "core"</code> to <code>pioVersion.value</code>:</p><div class="highlight shell"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1
+2
+3
+4</pre></td><td class="code"><pre>libraryDependencies ++<span class="o">=</span> Seq<span class="o">(</span>
+ <span class="s2">"io.prediction"</span> %% <span class="s2">"core"</span> % pioVersion.value % <span class="s2">"provided"</span>,
+ <span class="s2">"org.apache.spark"</span> %% <span class="s2">"spark-core"</span> % <span class="s2">"1.2.0"</span> % <span class="s2">"provided"</span>,
+ <span class="s2">"org.apache.spark"</span> %% <span class="s2">"spark-mllib"</span> % <span class="s2">"1.2.0"</span> % <span class="s2">"provided"</span><span class="o">)</span>
+</pre></td></tr></tbody></table> </div></li> <li><p>Create a new file <code>pio-build.sbt</code> in template's <strong>project/</strong> directory with the following content:</p><div class="highlight shell"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1</pre></td><td class="code"><pre>addSbtPlugin<span class="o">(</span><span class="s2">"io.prediction"</span> % <span class="s2">"pio-build"</span> % <span class="s2">"0.9.0"</span><span class="o">)</span>
+</pre></td></tr></tbody></table> </div> <p>Then, you should see the following two files in the <strong>project/</strong> directory:</p><div class="highlight shell"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1
+2</pre></td><td class="code"><pre><span class="gp">your_template_directory$ </span>ls project/
+assembly.sbt pio-build.sbt
+</pre></td></tr></tbody></table> </div></li> <li><p>Create a new file <code>template.json</code> file in the engine template's root directory with the following content:</p><div class="highlight shell"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1</pre></td><td class="code"><pre><span class="o">{</span><span class="s2">"pio"</span>: <span class="o">{</span><span class="s2">"version"</span>: <span class="o">{</span> <span class="s2">"min"</span>: <span class="s2">"0.9.0"</span> <span class="o">}}}</span>
+</pre></td></tr></tbody></table> </div> <p>This is to specify the minium PredictionIO version which the engine can run with.</p></li> <li><p>Lastly, you can add <code>/pio.sbt</code> into your engine template's <code>.gitignore</code>. <code>pio.sbt</code> is automatically generated by <code>pio build</code>.</p></li> </ol> <p>That's it! Now you can run <code>pio build</code>, <code>pio train</code> and <code>pio deploy</code> with PredictionIO 0.9.0 in the same way as before!</p><h2 id='upgrade-to-0.8.4' class='header-anchors'>Upgrade to 0.8.4</h2><p><strong>engine.json</strong> has slightly changed its format in 0.8.4 in order to make engine more flexible. If you are upgrading to 0.8.4, engine.json needs to have the <code>params</code> field for <em>datasource</em>, <em>preparator</em>, and <em>serving</em>. Here is the sample engine.json from templates/scala-parallel-recommendation-custom-preparator that demonstrate the change for <em>datasource</em> (line 7).</p><div cla
ss="highlight shell"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1
+2
+3
+4
+5
+6
+7
+8
+9
+10
+11
+12
+13
+14
+15
+16
+17
+18
+19</pre></td><td class="code"><pre>In 0.8.3
+<span class="o">{</span>
+ <span class="s2">"id"</span>: <span class="s2">"default"</span>,
+ <span class="s2">"description"</span>: <span class="s2">"Default settings"</span>,
+ <span class="s2">"engineFactory"</span>: <span class="s2">"org.template.recommendation.RecommendationEngine"</span>,
+ <span class="s2">"datasource"</span>: <span class="o">{</span>
+ <span class="s2">"appId"</span>: 1
+ <span class="o">}</span>,
+ <span class="s2">"algorithms"</span>: <span class="o">[</span>
+ <span class="o">{</span>
+ <span class="s2">"name"</span>: <span class="s2">"als"</span>,
+ <span class="s2">"params"</span>: <span class="o">{</span>
+ <span class="s2">"rank"</span>: 10,
+ <span class="s2">"numIterations"</span>: 20,
+ <span class="s2">"lambda"</span>: 0.01
+ <span class="o">}</span>
+ <span class="o">}</span>
+ <span class="o">]</span>
+<span class="o">}</span>
+</pre></td></tr></tbody></table> </div> <div class="highlight shell"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1
+2
+3
+4
+5
+6
+7
+8
+9
+10
+11
+12
+13
+14
+15
+16
+17
+18
+19
+20</pre></td><td class="code"><pre>In 0.8.4
+<span class="o">{</span>
+ <span class="s2">"id"</span>: <span class="s2">"default"</span>,
+ <span class="s2">"description"</span>: <span class="s2">"Default settings"</span>,
+ <span class="s2">"engineFactory"</span>: <span class="s2">"org.template.recommendation.RecommendationEngine"</span>,
+ <span class="s2">"datasource"</span>: <span class="o">{</span>
+ <span class="s2">"params"</span> : <span class="o">{</span>
+ <span class="s2">"appId"</span>: 1
+ <span class="o">}</span>
+ <span class="o">}</span>,
+ <span class="s2">"algorithms"</span>: <span class="o">[</span>
+ <span class="o">{</span>
+ <span class="s2">"name"</span>: <span class="s2">"als"</span>,
+ <span class="s2">"params"</span>: <span class="o">{</span>
+ <span class="s2">"rank"</span>: 10,
+ <span class="s2">"numIterations"</span>: 20,
+ <span class="s2">"lambda"</span>: 0.01
+ <span class="o">}</span>
+ <span class="o">}</span>
+ <span class="o">]</span>
+</pre></td></tr></tbody></table> </div> <h2 id='upgrade-from-0.8.2-to-0.8.3' class='header-anchors'>Upgrade from 0.8.2 to 0.8.3</h2><p>0.8.3 disallows entity types <strong>pio_user</strong> and <strong>pio_item</strong>. These types are used by default for most SDKs. They are deprecated in 0.8.3, and SDKs helper functions have been updated to use <strong>user</strong> and <strong>item</strong> instead.</p><p>If you are upgrading to 0.8.3, you can follow these steps to migrate your data.</p><h5 id='1.-create-a-new-app' class='header-anchors'>1. Create a new app</h5><div class="highlight shell"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1</pre></td><td class="code"><pre><span class="gp">$ </span>pio app new <my app name>
+</pre></td></tr></tbody></table> </div> <p>Please take note of the <new app id> generated for the new app.</p><h5 id='2.-run-the-upgrade-command' class='header-anchors'>2. Run the upgrade command</h5><div class="highlight shell"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1</pre></td><td class="code"><pre><span class="gp">$ </span>pio upgrade 0.8.2 0.8.3 <old app id> <new app id>
+</pre></td></tr></tbody></table> </div> <p>It will run a script that creates a new app with the new app id and migreate the data to the new app.</p><h5 id='3.-update-<strong>engine.json</strong>-to-use-the-new-app-id.-<strong>engine.json</strong>-is-located-under-your-engine-project-directory.' class='header-anchors' >3. Update <strong>engine.json</strong> to use the new app id. <strong>Engine.json</strong> is located under your engine project directory.</h5><div class="highlight shell"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1
+2
+3</pre></td><td class="code"><pre> <span class="s2">"datasource"</span>: <span class="o">{</span>
+ <span class="s2">"appId"</span>: <new app id>
+ <span class="o">}</span>,
+</pre></td></tr></tbody></table> </div> <h2 id='schema-changes-in-0.8.2' class='header-anchors'>Schema Changes in 0.8.2</h2><p>0.8.2 contains HBase and Elasticsearch schema changes from previous versions. If you are upgrading from a pre-0.8.2 version, you need to first clear HBase and ElasticSearch. These will clear out all data in Elasticsearch and HBase. Please be extra cautious.</p><div class="alert-message danger"><p><strong>ALL EXISTING DATA WILL BE LOST!</strong></p></div><h3 id='clearing-elasticsearch' class='header-anchors'>Clearing Elasticsearch</h3><p>With Elasticsearch running, do</p><div class="highlight shell"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1</pre></td><td class="code"><pre><span class="gp">$ </span>curl -X DELETE http://localhost:9200/_all
+</pre></td></tr></tbody></table> </div> <p>For details see <a href="http://www.elasticsearch.org/guide/en/elasticsearch/reference/current/indices-delete-index.html">http://www.elasticsearch.org/guide/en/elasticsearch/reference/current/indices-delete-index.html</a>.</p><h3 id='clearing-hbase' class='header-anchors'>Clearing HBase</h3><div class="highlight shell"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1
+2
+3
+4
+5
+6</pre></td><td class="code"><pre><span class="gp">$ </span><span class="nv">$HBASE_HOME</span>/bin/hbase shell
+...
+<span class="gp">> </span>disable_all <span class="s1">'predictionio.*'</span>
+...
+<span class="gp">> </span>drop_all <span class="s1">'predictionio.*'</span>
+...
+</pre></td></tr></tbody></table> </div> <p>For details see <a href="http://wiki.apache.org/hadoop/Hbase/Shell">http://wiki.apache.org/hadoop/Hbase/Shell</a>.</p><h2 id='experimental-upgrade-tool-(upgrade-hbase-schema-from-0.8.0/0.8.1-to-0.8.2)' class='header-anchors'>Experimental upgrade tool (Upgrade HBase schema from 0.8.0/0.8.1 to 0.8.2)</h2><p>Create an app to store the data</p><div class="highlight shell"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1</pre></td><td class="code"><pre><span class="gp">$ </span>bin/pio app new <my app>
+</pre></td></tr></tbody></table> </div> <p>Replace by the returned app ID: ( is the original app ID used in 0.8.0/0.8.2.)</p><div class="highlight shell"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1
+2
+3
+4</pre></td><td class="code"><pre><span class="gp">$ </span><span class="nb">set</span> -a
+<span class="gp">$ </span><span class="nb">source </span>conf/pio-env.sh
+<span class="gp">$ </span><span class="nb">set</span> +a
+<span class="gp">$ </span>sbt/sbt <span class="s2">"data/run-main io.prediction.data.storage.hbase.upgrade.Upgrade <from app ID>"</span> <span class="s2">"<to app ID>"</span>
+</pre></td></tr></tbody></table> </div> </div></div></div></div><footer><div class="container"><div class="seperator"></div><div class="row"><div class="col-md-4 col-md-push-8 col-xs-12"><div class="subscription-form-wrapper"><h4>Subscribe to our Newsletter</h4><form class="ajax-form" id="subscribe-form" method="POST" action="https://script.google.com/macros/s/AKfycbwhzeKCQJjQ52eVAqNT_vcklH07OITUO7wzOMDXvK6EGAWgaZgF/exec"><input class="required underlined-input" type="email" placeholder="Your email address" name="subscription_email" id="subscription_email"/><input class="pill-button" value="SUBSCRIBE" type="submit" data-state-normal="SUBSCRIBE" data-state-sucess="SUBSCRIBED!" data-state-loading="SENDING..." onclick="t($('#subscription_email').val());"/><p class="result"></p></form></div></div><div class="col-md-2 col-md-pull-4 col-xs-6 footer-link-column"><div class="footer-link-column-row"><h4>Community</h4><ul><li><a href="//docs.prediction.io/install/" target="blank">Download</a>
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ainer-fluid"><div class="row"><div id="left-menu-wrapper" class="col-md-3"><nav id="nav-main"><ul><li class="level-1"><a class="expandible" href="/"><span>Apache PredictionIO (incubating) Documentation</span></a><ul><li class="level-2"><a class="final" href="/"><span>Welcome to Apache PredictionIO (incubating)</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Getting Started</span></a><ul><li class="level-2"><a class="final" href="/start/"><span>A Quick Intro</span></a></li><li class="level-2"><a class="final" href="/install/"><span>Installing Apache PredictionIO (incubating)</span></a></li><li class="level-2"><a class="final" href="/start/download/"><span>Downloading an Engine Template</span></a></li><li class="level-2"><a class="final" href="/start/deploy/"><span>Deploying Your First Engine</span></a></li><li class="level-2"><a class="final" href="/start/customize/"><span>Customizing the Engine</span></a></li></ul></li><li class="level-1"><a class="
expandible" href="#"><span>Integrating with Your App</span></a><ul><li class="level-2"><a class="final" href="/appintegration/"><span>App Integration Overview</span></a></li><li class="level-2"><a class="expandible" href="/sdk/"><span>List of SDKs</span></a><ul><li class="level-3"><a class="final" href="/sdk/java/"><span>Java & Android SDK</span></a></li><li class="level-3"><a class="final" href="/sdk/php/"><span>PHP SDK</span></a></li><li class="level-3"><a class="final" href="/sdk/python/"><span>Python SDK</span></a></li><li class="level-3"><a class="final" href="/sdk/ruby/"><span>Ruby SDK</span></a></li><li class="level-3"><a class="final" href="/sdk/community/"><span>Community Powered SDKs</span></a></li></ul></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Deploying an Engine</span></a><ul><li class="level-2"><a class="final" href="/deploy/"><span>Deploying as a Web Service</span></a></li><li class="level-2"><a class="final" href="/cli/#engine-commands"><
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rver Overview</span></a></li><li class="level-2"><a class="final" href="/cli/#event-server-commands"><span>Event Server Command-line Interface</span></a></li><li class="level-2"><a class="final" href="/datacollection/eventapi/"><span>Collecting Data with REST/SDKs</span></a></li><li class="level-2"><a class="final" href="/datacollection/eventmodel/"><span>Events Modeling</span></a></li><li class="level-2"><a class="final" href="/datacollection/webhooks/"><span>Unifying Multichannel Data with Webhooks</span></a></li><li class="level-2"><a class="final" href="/datacollection/channel/"><span>Channel</span></a></li><li class="level-2"><a class="final" href="/datacollection/batchimport/"><span>Importing Data in Batch</span></a></li><li class="level-2"><a class="final" href="/datacollection/analytics/"><span>Using Analytics Tools</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Choosing an Algorithm(s)</span></a><ul><li class="level-2"><a class="final" hre
f="/algorithm/"><span>Built-in Algorithm Libraries</span></a></li><li class="level-2"><a class="final" href="/algorithm/switch/"><span>Switching to Another Algorithm</span></a></li><li class="level-2"><a class="final" href="/algorithm/multiple/"><span>Combining Multiple Algorithms</span></a></li><li class="level-2"><a class="final" href="/algorithm/custom/"><span>Adding Your Own Algorithms</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>ML Tuning and Evaluation</span></a><ul><li class="level-2"><a class="final" href="/evaluation/"><span>Overview</span></a></li><li class="level-2"><a class="final" href="/evaluation/paramtuning/"><span>Hyperparameter Tuning</span></a></li><li class="level-2"><a class="final" href="/evaluation/evaluationdashboard/"><span>Evaluation Dashboard</span></a></li><li class="level-2"><a class="final" href="/evaluation/metricchoose/"><span>Choosing Evaluation Metrics</span></a></li><li class="level-2"><a class="final" href="/ev
aluation/metricbuild/"><span>Building Evaluation Metrics</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>System Architecture</span></a><ul><li class="level-2"><a class="final" href="/system/"><span>Architecture Overview</span></a></li><li class="level-2"><a class="final" href="/system/anotherdatastore/"><span>Using Another Data Store</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Engine Template Gallery</span></a><ul><li class="level-2"><a class="final" href="http://templates.prediction.io"><span>Browse</span></a></li><li class="level-2"><a class="final" href="/community/submit-template/"><span>Submit your Engine as a Template</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Demo Tutorials</span></a><ul><li class="level-2"><a class="final" href="/demo/tapster/"><span>Comics Recommendation Demo</span></a></li><li class="level-2"><a class="final" href="/demo/community/"><span>Communit
y Contributed Demo</span></a></li><li class="level-2"><a class="final" href="/demo/textclassification/"><span>Text Classification Engine Tutorial</span></a></li></ul></li><li class="level-1"><a class="expandible" href="/community/"><span>Getting Involved</span></a><ul><li class="level-2"><a class="final" href="/community/contribute-code/"><span>Contribute Code</span></a></li><li class="level-2"><a class="final" href="/community/contribute-documentation/"><span>Contribute Documentation</span></a></li><li class="level-2"><a class="final" href="/community/contribute-sdk/"><span>Contribute a SDK</span></a></li><li class="level-2"><a class="final" href="/community/contribute-webhook/"><span>Contribute a Webhook</span></a></li><li class="level-2"><a class="final" href="/community/projects/"><span>Community Projects</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Getting Help</span></a><ul><li class="level-2"><a class="final" href="/resources/faq/"><span>F
AQs</span></a></li><li class="level-2"><a class="final" href="/support/"><span>Community Support</span></a></li><li class="level-2"><a class="final" href="/support/#enterprise-support"><span>Enterprise Support</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Resources</span></a><ul><li class="level-2"><a class="final" href="/resources/intellij/"><span>Developing Engines with IntelliJ IDEA</span></a></li><li class="level-2"><a class="final" href="/resources/upgrade/"><span>Upgrade Instructions</span></a></li><li class="level-2"><a class="final" href="/resources/glossary/"><span>Glossary</span></a></li></ul></li></ul></nav></div><div class="col-md-9 col-sm-12"><div class="content-header hidden-md hidden-lg"><div id="page-title"><h1>Sample Style Page</h1></div></div><div id="table-of-content-wrapper"><h5>On this page</h5><aside id="table-of-contents"><ul> <li> <a href="#alerts">Alerts</a> </li> <li> <a href="#text">Text</a> </li> <li> <a href="#lists">L
ists</a> </li> <li> <a href="#code">Code</a> </li> <li> <a href="#image">Image</a> </li> <li> <a href="#quotes">Quotes</a> </li> <li> <a href="#tables">Tables</a> </li> <li> <a href="#other">Other</a> </li> </ul> </li> <li> <a href="#heading-1">Heading 1</a> <ul> <li> <a href="#heading-2">Heading 2</a> </li> </ul> </aside><hr/><a id="edit-page-link" href="https://github.com/apache/incubator-predictionio/tree/livedoc/docs/manual/source/samples/index.html.md"><img src="/images/icons/edit-pencil-d6c1bb3d.png"/>Edit this page</a></div><div class="content-header hidden-sm hidden-xs"><div id="page-title"><h1>Sample Style Page</h1></div></div><div class="content"><h2 id='alerts' class='header-anchors'>Alerts</h2><h3 id='info' class='header-anchors'>Info</h3><p>Markdown: <code>INFO: This is a info message!</code> will display this:</p><div class="alert-message info"><p>This is a info message!</p></div><h3 id='success' class='header-anchors'>Success</h3><p>Markdown: <code>SUCCESS: This is a
success message!</code> will display this:</p><div class="alert-message success"><p>This is a success message!</p></div><h3 id='warning' class='header-anchors'>Warning</h3><p>Markdown: <code>WARNING: This is a warning message!</code> will display this:</p><div class="alert-message warning"><p>This is a warning message!</p></div><h3 id='danger' class='header-anchors'>Danger</h3><p>Markdown: <code>DANGER: This is a danger message!</code> will display this:</p><div class="alert-message danger"><p>This is a danger message!</p></div><h3 id='note' class='header-anchors'>Note</h3><p>Markdown: <code>NOTE: This is a note message!</code> will display this:</p><div class="alert-message note"><p>This is a note message!</p></div><h3 id='todo' class='header-anchors'>TODO</h3><p>Markdown: <code>TODO: This is a TODO message!</code> will display this:</p><div class="alert-message todo"><p>This is a TODO message! This message is longer to demonstrate what a multi line message would look like. This me
ssage is longer to demonstrate what a multi line message would look like. This message is longer to demonstrate what a multi line message would look like. Yes <strong>bold</strong> and other styling still work inside alerts!</p></div><h2 id='text' class='header-anchors'>Text</h2><p>This is the normal paragraph font. This is a <a href="/samples/tabs">internal link</a>. This is an <a href="http://google.com/">external link</a> This is a <a href="https://google.com/">secure external link</a> This is <strong>bold</strong>. This is <em>italic</em>. This is <u>underlined</u>. This is <mark>highlighted</mark>. This is <del>strikethough</del>. This is <sup>superscript</sup>.</p><p>This is another paragraph.</p><p>View <a href="/samples/sizing">additional sizing</a> samples.</p><h2 id='lists' class='header-anchors'>Lists</h2> <ul> <li>Bullet 1</li> <li>Bullet 2 <ul> <li>Bullet 2.1</li> <li>Bullet 2.2</li> </ul></li> <li>Bullet 3</li> </ul> <ol> <li>First item</li> <li>Second item</li> <li>Th
ird item</li> </ol> <h2 id='code' class='header-anchors'>Code</h2><h3 id='block' class='header-anchors'>Block</h3><p>This is a Scala code block:</p><div class="highlight scala"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1
+2
+3
+4
+5</pre></td><td class="code"><pre><span class="k">case</span> <span class="k">class</span> <span class="nc">Query</span><span class="o">(</span>
+ <span class="n">user</span><span class="k">:</span> <span class="kt">Int</span><span class="o">,</span>
+ <span class="n">num</span><span class="k">:</span> <span class="kt">Int</span>
+<span class="o">)</span> <span class="k">extends</span> <span class="nc">Serializable</span>
+
+</pre></td></tr></tbody></table> </div> <p>See a full list of <a href="/samples/languages">supported languages</a>.</p><h3 id='inline' class='header-anchors'>Inline</h3><p>This <code>code is inline</code>.</p><h2 id='image' class='header-anchors'>Image</h2><p><img alt="Sample Image" src="/images/tutorials/rails/localhost-8000-e55d5dd2.png"/></p><h2 id='quotes' class='header-anchors'>Quotes</h2> <blockquote> <p>This is a blockquote. Don't use these for anything other actual quotes! Use <a href="#alerts">alerts</a> instead.</p></blockquote> <h2 id='tables' class='header-anchors'>Tables</h2> <table><thead> <tr> <th>First Header</th> <th>Second Header</th> </tr> </thead><tbody> <tr> <td>Content Cell</td> <td>Content Cell</td> </tr> <tr> <td>Content Cell</td> <td>Content Cell</td> </tr> </tbody></table> <h2 id='other' class='header-anchors'>Other</h2><p>This is a horizontal rule:</p> <hr> <p>This is a en dash – and an em dash — using HTML entities.</p><div>This is inside
a div tag.</div> <h1 id='heading-1' class='header-anchors'>Heading 1</h1><p>This is the normal paragraph font.</p><h2 id='heading-2' class='header-anchors'>Heading 2</h2><p>This is the normal paragraph font.</p><h3 id='heading-3' class='header-anchors'>Heading 3</h3><p>This is the normal paragraph font.</p><h4 id='heading-4' class='header-anchors'>Heading 4</h4><p>This is the normal paragraph font.</p><h5 id='heading-5' class='header-anchors'>Heading 5</h5><p>This is the normal paragraph font.</p><h6 id='heading-6' class='header-anchors'>Heading 6</h6><p>This is the normal paragraph font.</p></div></div></div></div><footer><div class="container"><div class="seperator"></div><div class="row"><div class="col-md-4 col-md-push-8 col-xs-12"><div class="subscription-form-wrapper"><h4>Subscribe to our Newsletter</h4><form class="ajax-form" id="subscribe-form" method="POST" action="https://script.google.com/macros/s/AKfycbwhzeKCQJjQ52eVAqNT_vcklH07OITUO7wzOMDXvK6EGAWgaZgF/exec"><input class
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site
Posted by do...@apache.org.
http://git-wip-us.apache.org/repos/asf/incubator-predictionio-site/blob/92a45fa4/templates/complementarypurchase/dase/index.html
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@@ -0,0 +1,465 @@
+<!DOCTYPE html><html><head><title>DASE Components Explained (Complementary Purchase)</title><meta charset="utf-8"/><meta content="IE=edge,chrome=1" http-equiv="X-UA-Compatible"/><meta name="viewport" content="width=device-width, initial-scale=1.0"/><meta class="swiftype" name="title" data-type="string" content="DASE Components Explained (Complementary Purchase)"/><link rel="canonical" href="https://docs.prediction.io/templates/complementarypurchase/dase/"/><link href="/images/favicon/normal-b330020a.png" rel="shortcut icon"/><link href="/images/favicon/apple-c0febcf2.png" rel="apple-touch-icon"/><link href="//fonts.googleapis.com/css?family=Open+Sans:300italic,400italic,600italic,700italic,800italic,400,300,600,700,800" rel="stylesheet"/><link href="//maxcdn.bootstrapcdn.com/font-awesome/4.2.0/css/font-awesome.min.css" rel="stylesheet"/><link href="/stylesheets/application-3598c7d7.css" rel="stylesheet" type="text/css"/><!--[if lt IE 9]><script src="//cdnjs.cloudflare.com/ajax/libs/
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+(i[r].q=i[r].q||[]).push(arguments)},i[r].l=1*new Date();a=s.createElement(o),
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+})(window,document,'script','//www.google-analytics.com/analytics.js','ga');
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+fbq('track', "PageView");</script><script src="//use.typekit.net/mut4mjx.js"></script><script>try{Typekit.load();}catch(e){}</script></head><body><div id="global"><header><div class="container" id="header-wrapper"><div class="row"><div class="col-sm-12"><div id="logo-wrapper"><span id="drawer-toggle"></span><a href="#"></a><a href="http://prediction.io/"><img alt="PredictionIO" id="logo" src="/images/logos/logo-ee2b9bb3.png"/></a></div><div id="menu-wrapper"><div id="header-nav-options-wrapper"><ul><li><a href="/">Install & Doc</a></li> <li><a href="/support">Support</a></li> </ul></div><div id="pill-wrapper"><a class="pill left" href="//templates.prediction.io/">TEMPLATES</a> <a class="pill right" href="//github.com/PredictionIO/PredictionIO/">OPEN SOURCE</a></div></div><img class="mobile-search-bar-toggler hidden-md hidden-lg" src="/images/icons/search-glass-704bd4ff.png"/></div></div></div></header><div id="search-bar-row-wrapper"><div class="container-fluid" id="search-bar-row">
<div class="row"><div class="col-md-9 col-sm-11 col-xs-11"><div class="hidden-md hidden-lg" id="mobile-page-heading-wrapper"><p>PredictionIO Docs</p><h4>DASE Components Explained (Complementary Purchase)</h4></div><h4 class="hidden-sm hidden-xs">PredictionIO Docs</h4></div><div class="col-md-3 col-sm-1 col-xs-1 hidden-md hidden-lg"><img id="left-menu-indicator" src="/images/icons/down-arrow-dfe9f7fe.png"/></div><div class="col-md-3 col-sm-12 col-xs-12 swiftype-wrapper"><div class="swiftype"><form class="search-form"><img class="search-box-toggler hidden-xs hidden-sm" src="/images/icons/search-glass-704bd4ff.png"/><div class="search-box"><img src="/images/icons/search-glass-704bd4ff.png"/><input type="text" id="st-search-input" class="st-search-input" placeholder="Search Doc..."/></div><img class="swiftype-row-hider hidden-md hidden-lg" src="/images/icons/drawer-toggle-active-fcbef12a.png"/></form></div></div><div class="mobile-left-menu-toggler hidden-md hidden-lg"></div></div></div
></div><div id="page" class="container-fluid"><div class="row"><div id="left-menu-wrapper" class="col-md-3"><nav id="nav-main"><ul><li class="level-1"><a class="expandible" href="/"><span>Apache PredictionIO (incubating) Documentation</span></a><ul><li class="level-2"><a class="final" href="/"><span>Welcome to Apache PredictionIO (incubating)</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Getting Started</span></a><ul><li class="level-2"><a class="final" href="/start/"><span>A Quick Intro</span></a></li><li class="level-2"><a class="final" href="/install/"><span>Installing Apache PredictionIO (incubating)</span></a></li><li class="level-2"><a class="final" href="/start/download/"><span>Downloading an Engine Template</span></a></li><li class="level-2"><a class="final" href="/start/deploy/"><span>Deploying Your First Engine</span></a></li><li class="level-2"><a class="final" href="/start/customize/"><span>Customizing the Engine</span></a></li></ul></
li><li class="level-1"><a class="expandible" href="#"><span>Integrating with Your App</span></a><ul><li class="level-2"><a class="final" href="/appintegration/"><span>App Integration Overview</span></a></li><li class="level-2"><a class="expandible" href="/sdk/"><span>List of SDKs</span></a><ul><li class="level-3"><a class="final" href="/sdk/java/"><span>Java & Android SDK</span></a></li><li class="level-3"><a class="final" href="/sdk/php/"><span>PHP SDK</span></a></li><li class="level-3"><a class="final" href="/sdk/python/"><span>Python SDK</span></a></li><li class="level-3"><a class="final" href="/sdk/ruby/"><span>Ruby SDK</span></a></li><li class="level-3"><a class="final" href="/sdk/community/"><span>Community Powered SDKs</span></a></li></ul></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Deploying an Engine</span></a><ul><li class="level-2"><a class="final" href="/deploy/"><span>Deploying as a Web Service</span></a></li><li class="level-2"><a class="fina
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vel-2"><a class="final" href="/evaluation/metricbuild/"><span>Building Evaluation Metrics</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>System Architecture</span></a><ul><li class="level-2"><a class="final" href="/system/"><span>Architecture Overview</span></a></li><li class="level-2"><a class="final" href="/system/anotherdatastore/"><span>Using Another Data Store</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Engine Template Gallery</span></a><ul><li class="level-2"><a class="final" href="http://templates.prediction.io"><span>Browse</span></a></li><li class="level-2"><a class="final" href="/community/submit-template/"><span>Submit your Engine as a Template</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Demo Tutorials</span></a><ul><li class="level-2"><a class="final" href="/demo/tapster/"><span>Comics Recommendation Demo</span></a></li><li class="level-2"><a class="final" href=
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l" href="/resources/faq/"><span>FAQs</span></a></li><li class="level-2"><a class="final" href="/support/"><span>Community Support</span></a></li><li class="level-2"><a class="final" href="/support/#enterprise-support"><span>Enterprise Support</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Resources</span></a><ul><li class="level-2"><a class="final" href="/resources/intellij/"><span>Developing Engines with IntelliJ IDEA</span></a></li><li class="level-2"><a class="final" href="/resources/upgrade/"><span>Upgrade Instructions</span></a></li><li class="level-2"><a class="final" href="/resources/glossary/"><span>Glossary</span></a></li></ul></li></ul></nav></div><div class="col-md-9 col-sm-12"><div class="content-header hidden-md hidden-lg"><div id="page-title"><h1>DASE Components Explained (Complementary Purchase)</h1></div></div><div id="table-of-content-wrapper"><h5>On this page</h5><aside id="table-of-contents"><ul> <li> <a href="#the-engine-design"
>The Engine Design</a> </li> <li> <a href="#data">Data</a> </li> <li> <a href="#algorithm">Algorithm</a> </li> <li> <a href="#serving">Serving</a> </li> </ul> </aside><hr/><a id="edit-page-link" href="https://github.com/apache/incubator-predictionio/tree/livedoc/docs/manual/source/templates/complementarypurchase/dase.html.md.erb"><img src="/images/icons/edit-pencil-d6c1bb3d.png"/>Edit this page</a></div><div class="content-header hidden-sm hidden-xs"><div id="page-title"><h1>DASE Components Explained (Complementary Purchase)</h1></div></div><div class="content"><p>PredictionIO's DASE architecture brings the separation-of-concerns design principle to predictive engine development. DASE stands for the following components of an engine:</p> <ul> <li><strong>D</strong>ata - includes Data Source and Data Preparator</li> <li><strong>A</strong>lgorithm(s)</li> <li><strong>S</strong>erving</li> <li><strong>E</strong>valuator</li> </ul> <p><p>Let's look at the code and see how you ca
n customize the engine you built from the Complementary Purchase Engine Template.</p><div class="alert-message note"><p>Evaluator will not be covered in this tutorial.</p></div></p><h2 id='the-engine-design' class='header-anchors'>The Engine Design</h2><p>As you can see from the Quick Start, <em>MyComplementaryPurchase</em> takes a JSON prediction query, e.g. <code>{ "items" : ["s2i1"], "num" : 3 }</code>, and return a JSON predicted result. In MyComplementaryPurchase/src/main/scala/<strong><em>Engine.scala</em></strong>, the <code>Query</code> case class defines the format of such <strong>query</strong>:</p><div class="highlight scala"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1
+2</pre></td><td class="code"><pre><span class="k">case</span> <span class="k">class</span> <span class="nc">Query</span><span class="o">(</span><span class="n">items</span><span class="k">:</span> <span class="kt">Set</span><span class="o">[</span><span class="kt">String</span><span class="o">],</span> <span class="n">num</span><span class="k">:</span> <span class="kt">Int</span><span class="o">)</span>
+ <span class="k">extends</span> <span class="nc">Serializable</span>
+</pre></td></tr></tbody></table> </div> <p>The <code>PredictedResult</code> case class defines the format of <strong>predicted result</strong>, such as</p><div class="highlight json"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1
+2
+3
+4
+5
+6
+7
+8
+9
+10
+11
+12
+13
+14
+15
+16
+17
+18
+19
+20
+21</pre></td><td class="code"><pre><span class="p">{</span><span class="w">
+ </span><span class="s2">"rules"</span><span class="p">:[</span><span class="w">
+ </span><span class="p">{</span><span class="w">
+ </span><span class="s2">"cond"</span><span class="p">:[</span><span class="s2">"s2i1"</span><span class="p">],</span><span class="w">
+ </span><span class="s2">"itemScores"</span><span class="p">:[</span><span class="w">
+ </span><span class="p">{</span><span class="w">
+ </span><span class="s2">"item"</span><span class="p">:</span><span class="s2">"s2i2"</span><span class="p">,</span><span class="w">
+ </span><span class="s2">"support"</span><span class="p">:</span><span class="mf">0.2</span><span class="p">,</span><span class="w">
+ </span><span class="s2">"confidence"</span><span class="p">:</span><span class="mf">0.9090909090909091</span><span class="p">,</span><span class="w">
+ </span><span class="s2">"lift"</span><span class="p">:</span><span class="mf">3.787878787878788</span><span class="w">
+ </span><span class="p">},</span><span class="w">
+ </span><span class="p">{</span><span class="w">
+ </span><span class="s2">"item"</span><span class="p">:</span><span class="s2">"s2i3"</span><span class="p">,</span><span class="w">
+ </span><span class="s2">"support"</span><span class="p">:</span><span class="mf">0.14</span><span class="p">,</span><span class="w">
+ </span><span class="s2">"confidence"</span><span class="p">:</span><span class="mf">0.6363636363636364</span><span class="p">,</span><span class="w">
+ </span><span class="s2">"lift"</span><span class="p">:</span><span class="mf">3.535353535353535</span><span class="w">
+ </span><span class="p">}</span><span class="w">
+ </span><span class="p">]</span><span class="w">
+ </span><span class="p">}</span><span class="w">
+ </span><span class="p">]</span><span class="w">
+</span><span class="p">}</span><span class="w">
+</span></pre></td></tr></tbody></table> </div> <p>with:</p><div class="highlight scala"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1
+2
+3
+4
+5
+6
+7
+8
+9</pre></td><td class="code"><pre><span class="k">case</span> <span class="k">class</span> <span class="nc">PredictedResult</span><span class="o">(</span><span class="n">rules</span><span class="k">:</span> <span class="kt">Array</span><span class="o">[</span><span class="kt">Rule</span><span class="o">])</span>
+ <span class="k">extends</span> <span class="nc">Serializable</span>
+
+<span class="k">case</span> <span class="k">class</span> <span class="nc">Rule</span><span class="o">(</span><span class="n">cond</span><span class="k">:</span> <span class="kt">Set</span><span class="o">[</span><span class="kt">String</span><span class="o">],</span> <span class="n">itemScores</span><span class="k">:</span> <span class="kt">Array</span><span class="o">[</span><span class="kt">ItemScore</span><span class="o">])</span>
+ <span class="k">extends</span> <span class="nc">Serializable</span>
+
+<span class="k">case</span> <span class="k">class</span> <span class="nc">ItemScore</span><span class="o">(</span>
+ <span class="n">item</span><span class="k">:</span> <span class="kt">String</span><span class="o">,</span> <span class="n">support</span><span class="k">:</span> <span class="kt">Double</span><span class="o">,</span> <span class="n">confidence</span><span class="k">:</span> <span class="kt">Double</span><span class="o">,</span> <span class="n">lift</span><span class="k">:</span> <span class="kt">Double</span>
+<span class="o">)</span> <span class="k">extends</span> <span class="nc">Serializable</span>
+</pre></td></tr></tbody></table> </div> <p>Finally, <code>ComplementaryPurchaseEngine</code> is the <em>Engine Factory</em> that defines the components this engine will use: Data Source, Data Preparator, Algorithm(s) and Serving components.</p><div class="highlight scala"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1
+2
+3
+4
+5
+6
+7
+8
+9</pre></td><td class="code"><pre><span class="k">object</span> <span class="nc">ComplementaryPurchaseEngine</span> <span class="k">extends</span> <span class="nc">IEngineFactory</span> <span class="o">{</span>
+ <span class="k">def</span> <span class="n">apply</span><span class="o">()</span> <span class="k">=</span> <span class="o">{</span>
+ <span class="k">new</span> <span class="nc">Engine</span><span class="o">(</span>
+ <span class="n">classOf</span><span class="o">[</span><span class="kt">DataSource</span><span class="o">],</span>
+ <span class="n">classOf</span><span class="o">[</span><span class="kt">Preparator</span><span class="o">],</span>
+ <span class="nc">Map</span><span class="o">(</span><span class="s">"algo"</span> <span class="o">-></span> <span class="n">classOf</span><span class="o">[</span><span class="kt">Algorithm</span><span class="o">]),</span>
+ <span class="n">classOf</span><span class="o">[</span><span class="kt">Serving</span><span class="o">])</span>
+ <span class="o">}</span>
+<span class="o">}</span>
+</pre></td></tr></tbody></table> </div> <p>Each DASE component of the <code>ComplementaryPurchaseEngine</code> will be explained below.</p><h2 id='data' class='header-anchors'>Data</h2><p>In the DASE architecture, data is prepared by 2 components sequentially: <em>DataSource</em> and <em>DataPreparator</em>. They take data from the data store and prepare them for Algorithm.</p><h3 id='data-source' class='header-anchors'>Data Source</h3><p>In MyComplementaryPurchase/src/main/scala/<strong><em>DataSource.scala</em></strong>, the <code>readTraining</code> method of class <code>DataSource</code> reads and selects data from the <em>Event Store</em> (data store of the <em>Event Server</em>). It returns <code>TrainingData</code>.</p><div class="highlight scala"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1
+2
+3
+4
+5
+6
+7
+8
+9
+10
+11
+12
+13
+14
+15
+16
+17
+18
+19
+20
+21
+22
+23
+24
+25
+26
+27
+28
+29
+30
+31
+32
+33
+34
+35</pre></td><td class="code"><pre><span class="k">case</span> <span class="k">class</span> <span class="nc">DataSourceParams</span><span class="o">(</span><span class="n">appName</span><span class="k">:</span> <span class="kt">String</span><span class="o">)</span> <span class="k">extends</span> <span class="nc">Params</span>
+
+<span class="k">class</span> <span class="nc">DataSource</span><span class="o">(</span><span class="k">val</span> <span class="n">dsp</span><span class="k">:</span> <span class="kt">DataSourceParams</span><span class="o">)</span>
+ <span class="k">extends</span> <span class="nc">PDataSource</span><span class="o">[</span><span class="kt">TrainingData</span>,
+ <span class="kt">EmptyEvaluationInfo</span>, <span class="kt">Query</span>, <span class="kt">EmptyActualResult</span><span class="o">]</span> <span class="o">{</span>
+
+ <span class="nd">@transient</span> <span class="k">lazy</span> <span class="k">val</span> <span class="n">logger</span> <span class="k">=</span> <span class="nc">Logger</span><span class="o">[</span><span class="kt">this.</span><span class="k">type</span><span class="o">]</span>
+
+ <span class="k">override</span>
+ <span class="k">def</span> <span class="n">readTraining</span><span class="o">(</span><span class="n">sc</span><span class="k">:</span> <span class="kt">SparkContext</span><span class="o">)</span><span class="k">:</span> <span class="kt">TrainingData</span> <span class="o">=</span> <span class="o">{</span>
+
+ <span class="c1">// get all "user" "buy" "item" events
+</span> <span class="k">val</span> <span class="n">buyEvents</span><span class="k">:</span> <span class="kt">RDD</span><span class="o">[</span><span class="kt">BuyEvent</span><span class="o">]</span> <span class="k">=</span> <span class="nc">PEventStore</span><span class="o">.</span><span class="n">find</span><span class="o">(</span>
+ <span class="n">appName</span> <span class="k">=</span> <span class="n">dsp</span><span class="o">.</span><span class="n">appName</span><span class="o">,</span>
+ <span class="n">entityType</span> <span class="k">=</span> <span class="nc">Some</span><span class="o">(</span><span class="s">"user"</span><span class="o">),</span>
+ <span class="n">eventNames</span> <span class="k">=</span> <span class="nc">Some</span><span class="o">(</span><span class="nc">List</span><span class="o">(</span><span class="s">"buy"</span><span class="o">)),</span>
+ <span class="n">targetEntityType</span> <span class="k">=</span> <span class="nc">Some</span><span class="o">(</span><span class="nc">Some</span><span class="o">(</span><span class="s">"item"</span><span class="o">)))(</span><span class="n">sc</span><span class="o">)</span>
+ <span class="o">.</span><span class="n">map</span> <span class="o">{</span> <span class="n">event</span> <span class="k">=></span>
+ <span class="k">try</span> <span class="o">{</span>
+ <span class="k">new</span> <span class="nc">BuyEvent</span><span class="o">(</span>
+ <span class="n">user</span> <span class="k">=</span> <span class="n">event</span><span class="o">.</span><span class="n">entityId</span><span class="o">,</span>
+ <span class="n">item</span> <span class="k">=</span> <span class="n">event</span><span class="o">.</span><span class="n">targetEntityId</span><span class="o">.</span><span class="n">get</span><span class="o">,</span>
+ <span class="n">t</span> <span class="k">=</span> <span class="n">event</span><span class="o">.</span><span class="n">eventTime</span><span class="o">.</span><span class="n">getMillis</span>
+ <span class="o">)</span>
+ <span class="o">}</span> <span class="k">catch</span> <span class="o">{</span>
+ <span class="k">case</span> <span class="n">e</span><span class="k">:</span> <span class="kt">Exception</span> <span class="o">=></span> <span class="o">{</span>
+ <span class="n">logger</span><span class="o">.</span><span class="n">error</span><span class="o">(</span><span class="n">s</span><span class="s">"Cannot convert ${event} to BuyEvent. ${e}"</span><span class="o">)</span>
+ <span class="k">throw</span> <span class="n">e</span>
+ <span class="o">}</span>
+ <span class="o">}</span>
+ <span class="o">}.</span><span class="n">cache</span><span class="o">()</span>
+
+ <span class="k">new</span> <span class="nc">TrainingData</span><span class="o">(</span><span class="n">buyEvents</span><span class="o">)</span>
+ <span class="o">}</span>
+<span class="o">}</span>
+</pre></td></tr></tbody></table> </div> <p>PredictionIO automatically loads the parameters of <em>datasource</em> specified in MyComplementaryPurchase/<strong><em>engine.json</em></strong>, including <em>appName</em>, to <code>dsp</code>.</p><p>In <strong><em>engine.json</em></strong>:</p><div class="highlight shell"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1
+2
+3
+4
+5
+6
+7
+8
+9</pre></td><td class="code"><pre><span class="o">{</span>
+ ...
+ <span class="s2">"datasource"</span>: <span class="o">{</span>
+ <span class="s2">"params"</span> : <span class="o">{</span>
+ <span class="s2">"appName"</span>: <span class="s2">"MyApp1"</span>
+ <span class="o">}</span>
+ <span class="o">}</span>,
+ ...
+<span class="o">}</span>
+</pre></td></tr></tbody></table> </div> <p>In <code>readTraining()</code>, <code>PEventStore</code> is an object which provides function to access data that is collected by PredictionIO Event Server.</p><p>This Complementary Purchase Engine Template requires "buy" events.</p><p><code>PEventStore.find(...)</code> specifies the events that you want to read. In this case, "user buy item" events are read and then each is mapped to a <code>BuyEvent</code> object.</p><p><code>BuyEvent</code> case class is defined as:</p><div class="highlight scala"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1</pre></td><td class="code"><pre><span class="k">case</span> <span class="k">class</span> <span class="nc">BuyEvent</span><span class="o">(</span><span class="n">user</span><span class="k">:</span> <span class="kt">String</span><span class="o">,</span> <span class="n">item</span><span class="k">:</span> <span clas
s="kt">String</span><span class="o">,</span> <span class="n">t</span><span class="k">:</span> <span class="kt">Long</span><span class="o">)</span>
+</pre></td></tr></tbody></table> </div> <p><code>TrainingData</code> contains an RDD of <code>BuyEvent</code> objects. The class definition of <code>TrainingData</code> is:</p><div class="highlight scala"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1
+2
+3</pre></td><td class="code"><pre><span class="k">class</span> <span class="nc">TrainingData</span><span class="o">(</span>
+ <span class="k">val</span> <span class="n">buyEvents</span><span class="k">:</span> <span class="kt">RDD</span><span class="o">[</span><span class="kt">BuyEvent</span><span class="o">]</span>
+<span class="o">)</span> <span class="k">extends</span> <span class="nc">Serializable</span> <span class="o">{</span> <span class="o">...</span> <span class="o">}</span>
+</pre></td></tr></tbody></table> </div> <p>PredictionIO then passes the returned <code>TrainingData</code> object to <em>Data Preparator</em>.</p><div class="alert-message note"><p>You could modify the DataSource to read other event other than the default <strong>buy</strong>.</p></div><h3 id='data-preparator' class='header-anchors'>Data Preparator</h3><p>In MyComplementaryPurchase/src/main/scala/<strong><em>Preparator.scala</em></strong>, the <code>prepare</code> method of class <code>Preparator</code> takes <code>TrainingData</code> as its input and performs any necessary feature selection and data processing tasks. At the end, it returns <code>PreparedData</code> which should contain the data <em>Algorithm</em> needs.</p><p>By default, <code>prepare</code> simply copies the unprocessed <code>TrainingData</code> data to <code>PreparedData</code>:</p><div class="highlight scala"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="
lineno">1
+2
+3
+4
+5
+6
+7
+8
+9
+10
+11
+12
+13</pre></td><td class="code"><pre><span class="k">class</span> <span class="nc">Preparator</span>
+ <span class="k">extends</span> <span class="nc">PPreparator</span><span class="o">[</span><span class="kt">TrainingData</span>, <span class="kt">PreparedData</span><span class="o">]</span> <span class="o">{</span>
+
+ <span class="nd">@transient</span> <span class="k">lazy</span> <span class="k">val</span> <span class="n">logger</span> <span class="k">=</span> <span class="nc">Logger</span><span class="o">[</span><span class="kt">this.</span><span class="k">type</span><span class="o">]</span>
+
+ <span class="k">def</span> <span class="n">prepare</span><span class="o">(</span><span class="n">sc</span><span class="k">:</span> <span class="kt">SparkContext</span><span class="o">,</span> <span class="n">td</span><span class="k">:</span> <span class="kt">TrainingData</span><span class="o">)</span><span class="k">:</span> <span class="kt">PreparedData</span> <span class="o">=</span> <span class="o">{</span>
+ <span class="k">new</span> <span class="nc">PreparedData</span><span class="o">(</span><span class="n">buyEvents</span> <span class="k">=</span> <span class="n">td</span><span class="o">.</span><span class="n">buyEvents</span><span class="o">)</span>
+ <span class="o">}</span>
+<span class="o">}</span>
+
+<span class="k">class</span> <span class="nc">PreparedData</span><span class="o">(</span>
+ <span class="k">val</span> <span class="n">buyEvents</span><span class="k">:</span> <span class="kt">RDD</span><span class="o">[</span><span class="kt">BuyEvent</span><span class="o">]</span>
+<span class="o">)</span> <span class="k">extends</span> <span class="nc">Serializable</span>
+</pre></td></tr></tbody></table> </div> <p>PredictionIO passes the returned <code>PreparedData</code> object to Algorithm's <code>train</code> function.</p><h2 id='algorithm' class='header-anchors'>Algorithm</h2><p>In MyComplementaryPurchase/src/main/scala/<strong><em>ALSAlgorithm.scala</em></strong>, the two methods of the algorithm class are <code>train</code> and <code>predict</code>. <code>train</code> is responsible for training the predictive model; <code>predict</code> is responsible for using this model to make prediction.</p><p>The default algorithm is based on concept of <a href="http://en.wikipedia.org/wiki/Association_rule_learning">Association Rule Learning</a> to find interesting association rules (A implies B) that indicates additional item (B) may be bought together given a list of items (A). A is the <em>condition</em> and B is the <em>consequence</em>.</p><h3 id='algorithm-parameters' class='header-anchors'>Algorithm parameters</h3><p>The Algorithm takes the fo
llowing parameters, as defined by the <code>AlgorithmParams</code> case class:</p><div class="highlight scala"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1
+2
+3
+4
+5
+6
+7
+8
+9
+10</pre></td><td class="code"><pre><span class="k">case</span> <span class="k">class</span> <span class="nc">AlgorithmParams</span><span class="o">(</span>
+ <span class="n">basketWindow</span><span class="k">:</span> <span class="kt">Int</span><span class="o">,</span> <span class="c1">// in seconds
+</span> <span class="n">maxRuleLength</span><span class="k">:</span> <span class="kt">Int</span><span class="o">,</span>
+ <span class="n">minSupport</span><span class="k">:</span> <span class="kt">Double</span><span class="o">,</span>
+ <span class="n">minConfidence</span><span class="k">:</span> <span class="kt">Double</span><span class="o">,</span>
+ <span class="n">minLift</span><span class="k">:</span> <span class="kt">Double</span><span class="o">,</span>
+ <span class="n">minBasketSize</span><span class="k">:</span> <span class="kt">Int</span><span class="o">,</span>
+ <span class="n">maxNumRulesPerCond</span><span class="k">:</span> <span class="kt">Int</span> <span class="c1">// max number of rules per condition
+</span> <span class="o">)</span> <span class="k">extends</span> <span class="nc">Params</span>
+
+</pre></td></tr></tbody></table> </div> <p>Parameter description:</p> <ul> <li><strong>basketWindow</strong>: The buy event is considered as the same basket as previous one if the time difference is within this window (in unit of seconds). For example, if it's set to 120, it means that if the user buys item B within 2 minutes of previous purchase (item A), then the item set [A, B] is considered as the same basket. The purchase of this <em>basket</em> is referred as one <em>transaction</em>.</li> <li><strong>maxRuleLength</strong>: The maximum length of the association rule length. Must be at least 2. For example, rule of "A implies B" has length of 2 while rule "A, B implies C" has a length of 3. Increasing this number will incrase the training time significantly because more combinations are considered.</li> <li><strong>minSupport</strong>: The minimum required <em>support</em> for the item set to be considered as rule (valid range is 0 to 1). It's the p
ercentage of the item set appearing among all transcations. This is used to filter out infrequent item set. For example, setting to 0.1 means that the item set must appear in 10 % of all transactions.</li> <li><strong>minConfidence</strong>: The minimum <em>confidence</em> required for the rules (valid range is 0 to 1). The confidence indicates the probability of the condition and conseuquence appear in the same transaction. For example, if A appears in 30 transactions and the item set [A, B] appears in 20 transactions, then the rule "A implies B" has confidence of 0.66.</li> <li><strong>minLift</strong>: The minimum <em>lift</em> required for the rule. It should be set to 1 to find high quality rule. It's the confidence of the rule divided by the support of the consequence. It is used to filter out rules that the consequence is very frequent anyway regardless of the condition.</li> <li><strong>minBasketSize</strong>: The minimum number of items in basket to be conside
red by algorithm. This value must be at least 2.</li> <li><strong>maxNumRulesPerCond</strong>: Maximum number of rules generated per condition and stored in the model. By default, the top rules are sorted by <em>lift</em> score.</li> </ul> <div class="alert-message info"><p>If you import your own data and the engine doesn't return any results, it could be caused by the following reasons: (1) the algorithm parameter constraint is too high and the algo couldn't find rules that satisfy the condition. you could try setting the following param to 0: <strong>minSupport</strong>, <strong>minConfidence</strong>, <strong>minLift</strong> and then see if anything returned (regardless of recommendation quality), and then adjust the parameter accordingly. (2) the complementary purchase engine requires buy event with correct eventTime. If you import data without specifying eventTime, the SDK will use current time because it assumes the event happens in real time (which is not the case if
you import as batch offline), resulting in that all buy events are treated as one big transcation while they should be treated as multiple transcations.</p></div><p>The values of these parameters can be specified in <em>algorithms</em> of MyComplementaryPurchase/<strong><em>engine.json</em></strong>:</p><div class="highlight shell"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1
+2
+3
+4
+5
+6
+7
+8
+9
+10
+11
+12
+13
+14
+15
+16
+17
+18</pre></td><td class="code"><pre><span class="o">{</span>
+ ...
+ <span class="s2">"algorithms"</span>: <span class="o">[</span>
+ <span class="o">{</span>
+ <span class="s2">"name"</span>: <span class="s2">"algo"</span>,
+ <span class="s2">"params"</span>: <span class="o">{</span>
+ <span class="s2">"basketWindow"</span> : 120,
+ <span class="s2">"maxRuleLength"</span> : 2,
+ <span class="s2">"minSupport"</span>: 0.1,
+ <span class="s2">"minConfidence"</span>: 0.6,
+ <span class="s2">"minLift"</span> : 1.0,
+ <span class="s2">"minBasketSize"</span> : 2,
+ <span class="s2">"maxNumRulesPerCond"</span>: 5
+ <span class="o">}</span>
+ <span class="o">}</span>
+ <span class="o">]</span>
+ ...
+<span class="o">}</span>
+</pre></td></tr></tbody></table> </div> <p>PredictionIO will automatically loads these values into the constructor of the <code>Algorithm</code> class.</p><div class="highlight scala"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1
+2
+3
+4</pre></td><td class="code"><pre><span class="k">class</span> <span class="nc">Algorithm</span><span class="o">(</span><span class="k">val</span> <span class="n">ap</span><span class="k">:</span> <span class="kt">AlgorithmParams</span><span class="o">)</span>
+ <span class="k">extends</span> <span class="n">P2LAlgorithm</span><span class="o">[</span><span class="kt">PreparedData</span>, <span class="kt">Model</span>, <span class="kt">Query</span>, <span class="kt">PredictedResult</span><span class="o">]</span> <span class="o">{</span>
+ <span class="o">...</span>
+<span class="o">}</span>
+</pre></td></tr></tbody></table> </div> <h3 id='train(...)' class='header-anchors'>train(...)</h3><p><code>train</code> is called when you run <strong>pio train</strong> to train a predictive model. The algorithm first find all basket transcations, generates and filters the association rules based on the algorithm parameters:</p><div class="highlight scala"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1
+2
+3
+4
+5
+6
+7
+8
+9
+10
+11
+12
+13
+14
+15
+16
+17
+18
+19
+20
+21
+22
+23
+24
+25
+26
+27
+28
+29
+30
+31
+32
+33
+34
+35
+36
+37
+38</pre></td><td class="code"><pre>
+ <span class="k">def</span> <span class="n">train</span><span class="o">(</span><span class="n">sc</span><span class="k">:</span> <span class="kt">SparkContext</span><span class="o">,</span> <span class="n">pd</span><span class="k">:</span> <span class="kt">PreparedData</span><span class="o">)</span><span class="k">:</span> <span class="kt">Model</span> <span class="o">=</span> <span class="o">{</span>
+ <span class="k">val</span> <span class="n">windowMillis</span> <span class="k">=</span> <span class="n">ap</span><span class="o">.</span><span class="n">basketWindow</span> <span class="o">*</span> <span class="mi">1000</span>
+
+ <span class="o">...</span>
+
+ <span class="k">val</span> <span class="n">transactions</span><span class="k">:</span> <span class="kt">RDD</span><span class="o">[</span><span class="kt">Set</span><span class="o">[</span><span class="kt">String</span><span class="o">]]</span> <span class="k">=</span> <span class="o">...</span>
+
+ <span class="k">val</span> <span class="n">totalTransaction</span> <span class="k">=</span> <span class="n">transactions</span><span class="o">.</span><span class="n">count</span><span class="o">()</span>
+ <span class="k">val</span> <span class="n">minSupportCount</span> <span class="k">=</span> <span class="n">ap</span><span class="o">.</span><span class="n">minSupport</span> <span class="o">*</span> <span class="n">totalTransaction</span>
+
+ <span class="o">...</span>
+
+ <span class="c1">// generate item sets
+</span> <span class="k">val</span> <span class="n">itemSets</span><span class="k">:</span> <span class="kt">RDD</span><span class="o">[</span><span class="kt">Set</span><span class="o">[</span><span class="kt">String</span><span class="o">]]</span> <span class="k">=</span> <span class="n">transactions</span>
+ <span class="o">.</span><span class="n">flatMap</span> <span class="o">{</span> <span class="n">tran</span> <span class="k">=></span>
+ <span class="o">(</span><span class="mi">1</span> <span class="n">to</span> <span class="n">ap</span><span class="o">.</span><span class="n">maxRuleLength</span><span class="o">).</span><span class="n">flatMap</span><span class="o">(</span><span class="n">n</span> <span class="k">=></span> <span class="n">tran</span><span class="o">.</span><span class="n">subsets</span><span class="o">(</span><span class="n">n</span><span class="o">))</span>
+ <span class="o">}</span>
+
+ <span class="o">...</span>
+
+ <span class="k">val</span> <span class="n">itemSetCount</span><span class="k">:</span> <span class="kt">RDD</span><span class="o">[(</span><span class="kt">Set</span><span class="o">[</span><span class="kt">String</span><span class="o">]</span>, <span class="kt">Int</span><span class="o">)]</span> <span class="k">=</span> <span class="o">...</span>
+
+ <span class="o">...</span>
+
+ <span class="k">val</span> <span class="n">rules</span><span class="k">:</span> <span class="kt">RDD</span><span class="o">[(</span><span class="kt">Set</span><span class="o">[</span><span class="kt">String</span><span class="o">]</span>, <span class="kt">RuleScore</span><span class="o">)]</span> <span class="k">=</span> <span class="o">...</span>
+
+ <span class="k">val</span> <span class="n">sortedRules</span> <span class="k">=</span> <span class="n">rules</span><span class="o">.</span><span class="n">groupByKey</span>
+ <span class="o">.</span><span class="n">mapValues</span><span class="o">(</span><span class="n">iter</span> <span class="k">=></span>
+ <span class="n">iter</span><span class="o">.</span><span class="n">toVector</span>
+ <span class="o">.</span><span class="n">sortBy</span><span class="o">(</span><span class="k">_</span><span class="o">.</span><span class="n">lift</span><span class="o">)(</span><span class="nc">Ordering</span><span class="o">.</span><span class="nc">Double</span><span class="o">.</span><span class="n">reverse</span><span class="o">)</span>
+ <span class="o">.</span><span class="n">take</span><span class="o">(</span><span class="n">ap</span><span class="o">.</span><span class="n">maxNumRulesPerCond</span><span class="o">)</span>
+ <span class="o">)</span>
+ <span class="o">.</span><span class="n">collectAsMap</span><span class="o">.</span><span class="n">toMap</span>
+
+ <span class="k">new</span> <span class="nc">Model</span><span class="o">(</span><span class="n">sortedRules</span><span class="o">)</span>
+ <span class="o">}</span>
+
+</pre></td></tr></tbody></table> </div> <p>PredictionIO will automatically store the returned model after training, i.e. the <code>Model</code> object.</p><p>The <code>Model</code> stores the top rules for each condition:</p><div class="highlight scala"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1
+2
+3
+4
+5</pre></td><td class="code"><pre><span class="k">class</span> <span class="nc">Model</span><span class="o">(</span>
+ <span class="k">val</span> <span class="n">rules</span><span class="k">:</span> <span class="kt">Map</span><span class="o">[</span><span class="kt">Set</span><span class="o">[</span><span class="kt">String</span><span class="o">]</span>, <span class="kt">Vector</span><span class="o">[</span><span class="kt">RuleScore</span><span class="o">]]</span>
+<span class="o">)</span> <span class="k">extends</span> <span class="nc">Serializable</span> <span class="o">{</span>
+ <span class="o">...</span>
+<span class="o">}</span>
+</pre></td></tr></tbody></table> </div> <h3 id='predict(...)' class='header-anchors'>predict(...)</h3><p><code>predict</code> is called when you send a JSON query to <a href="http://localhost:8000/queries.json">http://localhost:8000/queries.json</a>. PredictionIO converts the query, such as <code>{ "items" : ["s2i1"], "num" : 3 }</code> to the <code>Query</code> class you defined previously in <code>Engine.scala</code>.</p><p>The <code>predict()</code> function does the following:</p> <ol> <li>find all possible subset of the items in query</li> <li>use the subsets as condition to look up the model and return the rules for each condition.</li> </ol> <div class="highlight scala"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1
+2
+3
+4
+5
+6
+7
+8
+9
+10
+11
+12
+13
+14
+15
+16
+17
+18
+19
+20
+21
+22
+23
+24
+25</pre></td><td class="code"><pre>
+ <span class="o">...</span>
+
+ <span class="k">def</span> <span class="n">predict</span><span class="o">(</span><span class="n">model</span><span class="k">:</span> <span class="kt">Model</span><span class="o">,</span> <span class="n">query</span><span class="k">:</span> <span class="kt">Query</span><span class="o">)</span><span class="k">:</span> <span class="kt">PredictedResult</span> <span class="o">=</span> <span class="o">{</span>
+ <span class="k">val</span> <span class="n">conds</span> <span class="k">=</span> <span class="o">(</span><span class="mi">1</span> <span class="n">to</span> <span class="n">maxCondLength</span><span class="o">).</span><span class="n">flatMap</span><span class="o">(</span><span class="n">n</span> <span class="k">=></span> <span class="n">query</span><span class="o">.</span><span class="n">items</span><span class="o">.</span><span class="n">subsets</span><span class="o">(</span><span class="n">n</span><span class="o">))</span>
+
+ <span class="k">val</span> <span class="n">rules</span> <span class="k">=</span> <span class="n">conds</span><span class="o">.</span><span class="n">map</span> <span class="o">{</span> <span class="n">cond</span> <span class="k">=></span>
+ <span class="n">model</span><span class="o">.</span><span class="n">rules</span><span class="o">.</span><span class="n">get</span><span class="o">(</span><span class="n">cond</span><span class="o">).</span><span class="n">map</span><span class="o">{</span> <span class="n">vec</span> <span class="k">=></span>
+ <span class="k">val</span> <span class="n">itemScores</span> <span class="k">=</span> <span class="n">vec</span><span class="o">.</span><span class="n">take</span><span class="o">(</span><span class="n">query</span><span class="o">.</span><span class="n">num</span><span class="o">).</span><span class="n">map</span> <span class="o">{</span> <span class="n">rs</span> <span class="k">=></span>
+ <span class="k">new</span> <span class="nc">ItemScore</span><span class="o">(</span>
+ <span class="n">item</span> <span class="k">=</span> <span class="n">rs</span><span class="o">.</span><span class="n">conseq</span><span class="o">,</span>
+ <span class="n">support</span> <span class="k">=</span> <span class="n">rs</span><span class="o">.</span><span class="n">support</span><span class="o">,</span>
+ <span class="n">confidence</span> <span class="k">=</span> <span class="n">rs</span><span class="o">.</span><span class="n">confidence</span><span class="o">,</span>
+ <span class="n">lift</span> <span class="k">=</span> <span class="n">rs</span><span class="o">.</span><span class="n">lift</span>
+ <span class="o">)</span>
+ <span class="o">}.</span><span class="n">toArray</span>
+ <span class="nc">Rule</span><span class="o">(</span><span class="n">cond</span> <span class="k">=</span> <span class="n">cond</span><span class="o">,</span> <span class="n">itemScores</span> <span class="k">=</span> <span class="n">itemScores</span><span class="o">)</span>
+ <span class="o">}</span>
+ <span class="o">}.</span><span class="n">flatten</span><span class="o">.</span><span class="n">toArray</span>
+
+ <span class="k">new</span> <span class="nc">PredictedResult</span><span class="o">(</span><span class="n">rules</span><span class="o">)</span>
+ <span class="o">}</span>
+
+ <span class="o">...</span>
+
+</pre></td></tr></tbody></table> </div> <p>PredictionIO passes the returned <code>PredictedResult</code> object to <em>Serving</em>.</p><h2 id='serving' class='header-anchors'>Serving</h2><p>The <code>serve</code> method of class <code>Serving</code> processes predicted result. It is also responsible for combining multiple predicted results into one if you have more than one predictive model. <em>Serving</em> then returns the final predicted result. PredictionIO will convert it to a JSON response automatically.</p><p>In MyComplementaryPurchase/src/main/scala/<strong><em>Serving.scala</em></strong>,</p><div class="highlight scala"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1
+2
+3
+4
+5
+6
+7
+8
+9
+10
+11</pre></td><td class="code"><pre><span class="k">class</span> <span class="nc">Serving</span>
+ <span class="k">extends</span> <span class="nc">LServing</span><span class="o">[</span><span class="kt">Query</span>, <span class="kt">PredictedResult</span><span class="o">]</span> <span class="o">{</span>
+
+ <span class="nd">@transient</span> <span class="k">lazy</span> <span class="k">val</span> <span class="n">logger</span> <span class="k">=</span> <span class="nc">Logger</span><span class="o">[</span><span class="kt">this.</span><span class="k">type</span><span class="o">]</span>
+
+ <span class="k">override</span>
+ <span class="k">def</span> <span class="n">serve</span><span class="o">(</span><span class="n">query</span><span class="k">:</span> <span class="kt">Query</span><span class="o">,</span>
+ <span class="n">predictedResults</span><span class="k">:</span> <span class="kt">Seq</span><span class="o">[</span><span class="kt">PredictedResult</span><span class="o">])</span><span class="k">:</span> <span class="kt">PredictedResult</span> <span class="o">=</span> <span class="o">{</span>
+ <span class="n">predictedResults</span><span class="o">.</span><span class="n">head</span>
+ <span class="o">}</span>
+<span class="o">}</span>
+</pre></td></tr></tbody></table> </div> <p>When you send a JSON query to <a href="http://localhost:8000/queries.json">http://localhost:8000/queries.json</a>, <code>PredictedResult</code> from all models will be passed to <code>serve</code> as a sequence, i.e. <code>Seq[PredictedResult]</code>.</p><div class="alert-message note"><p>An engine can train multiple models if you specify more than one Algorithm component in <code>object ComplementaryPurchaseEngine</code> inside <strong><em>Engine.scala</em></strong> and the corresponding parameters in <strong><em>engine.json</em></strong>. Since only one <code>Algorithm</code> is implemented by default, this <code>Seq</code> contains one element.</p></div></div></div></div></div><footer><div class="container"><div class="seperator"></div><div class="row"><div class="col-md-4 col-md-push-8 col-xs-12"><div class="subscription-form-wrapper"><h4>Subscribe to our Newsletter</h4><form class="ajax-form" id="subscribe-form" method="POST" action="h
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<div class="row"><div class="col-md-9 col-sm-11 col-xs-11"><div class="hidden-md hidden-lg" id="mobile-page-heading-wrapper"><p>PredictionIO Docs</p><h4>Unifying Multichannel Data with Webhooks</h4></div><h4 class="hidden-sm hidden-xs">PredictionIO Docs</h4></div><div class="col-md-3 col-sm-1 col-xs-1 hidden-md hidden-lg"><img id="left-menu-indicator" src="/images/icons/down-arrow-dfe9f7fe.png"/></div><div class="col-md-3 col-sm-12 col-xs-12 swiftype-wrapper"><div class="swiftype"><form class="search-form"><img class="search-box-toggler hidden-xs hidden-sm" src="/images/icons/search-glass-704bd4ff.png"/><div class="search-box"><img src="/images/icons/search-glass-704bd4ff.png"/><input type="text" id="st-search-input" class="st-search-input" placeholder="Search Doc..."/></div><img class="swiftype-row-hider hidden-md hidden-lg" src="/images/icons/drawer-toggle-active-fcbef12a.png"/></form></div></div><div class="mobile-left-menu-toggler hidden-md hidden-lg"></div></div></div></div><di
v id="page" class="container-fluid"><div class="row"><div id="left-menu-wrapper" class="col-md-3"><nav id="nav-main"><ul><li class="level-1"><a class="expandible" href="/"><span>Apache PredictionIO (incubating) Documentation</span></a><ul><li class="level-2"><a class="final" href="/"><span>Welcome to Apache PredictionIO (incubating)</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Getting Started</span></a><ul><li class="level-2"><a class="final" href="/start/"><span>A Quick Intro</span></a></li><li class="level-2"><a class="final" href="/install/"><span>Installing Apache PredictionIO (incubating)</span></a></li><li class="level-2"><a class="final" href="/start/download/"><span>Downloading an Engine Template</span></a></li><li class="level-2"><a class="final" href="/start/deploy/"><span>Deploying Your First Engine</span></a></li><li class="level-2"><a class="final" href="/start/customize/"><span>Customizing the Engine</span></a></li></ul></li><li cla
ss="level-1"><a class="expandible" href="#"><span>Integrating with Your App</span></a><ul><li class="level-2"><a class="final" href="/appintegration/"><span>App Integration Overview</span></a></li><li class="level-2"><a class="expandible" href="/sdk/"><span>List of SDKs</span></a><ul><li class="level-3"><a class="final" href="/sdk/java/"><span>Java & Android SDK</span></a></li><li class="level-3"><a class="final" href="/sdk/php/"><span>PHP SDK</span></a></li><li class="level-3"><a class="final" href="/sdk/python/"><span>Python SDK</span></a></li><li class="level-3"><a class="final" href="/sdk/ruby/"><span>Ruby SDK</span></a></li><li class="level-3"><a class="final" href="/sdk/community/"><span>Community Powered SDKs</span></a></li></ul></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Deploying an Engine</span></a><ul><li class="level-2"><a class="final" href="/deploy/"><span>Deploying as a Web Service</span></a></li><li class="level-2"><a class="final" href="/
cli/#engine-commands"><span>Engine Command-line Interface</span></a></li><li class="level-2"><a class="final" href="/deploy/engineparams/"><span>Setting Engine Parameters</span></a></li><li class="level-2"><a class="final" href="/deploy/enginevariants/"><span>Deploying Multiple Engine Variants</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Customizing an Engine</span></a><ul><li class="level-2"><a class="final" href="/customize/"><span>Learning DASE</span></a></li><li class="level-2"><a class="final" href="/customize/dase/"><span>Implement DASE</span></a></li><li class="level-2"><a class="final" href="/customize/troubleshooting/"><span>Troubleshooting Engine Development</span></a></li><li class="level-2"><a class="final" href="/api/current/#package"><span>Engine Scala APIs</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Collecting and Analyzing Data</span></a><ul><li class="level-2"><a class="final" href="/datacoll
ection/"><span>Event Server Overview</span></a></li><li class="level-2"><a class="final" href="/cli/#event-server-commands"><span>Event Server Command-line Interface</span></a></li><li class="level-2"><a class="final" href="/datacollection/eventapi/"><span>Collecting Data with REST/SDKs</span></a></li><li class="level-2"><a class="final" href="/datacollection/eventmodel/"><span>Events Modeling</span></a></li><li class="level-2"><a class="final active" href="/datacollection/webhooks/"><span>Unifying Multichannel Data with Webhooks</span></a></li><li class="level-2"><a class="final" href="/datacollection/channel/"><span>Channel</span></a></li><li class="level-2"><a class="final" href="/datacollection/batchimport/"><span>Importing Data in Batch</span></a></li><li class="level-2"><a class="final" href="/datacollection/analytics/"><span>Using Analytics Tools</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Choosing an Algorithm(s)</span></a><ul><li class=
"level-2"><a class="final" href="/algorithm/"><span>Built-in Algorithm Libraries</span></a></li><li class="level-2"><a class="final" href="/algorithm/switch/"><span>Switching to Another Algorithm</span></a></li><li class="level-2"><a class="final" href="/algorithm/multiple/"><span>Combining Multiple Algorithms</span></a></li><li class="level-2"><a class="final" href="/algorithm/custom/"><span>Adding Your Own Algorithms</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>ML Tuning and Evaluation</span></a><ul><li class="level-2"><a class="final" href="/evaluation/"><span>Overview</span></a></li><li class="level-2"><a class="final" href="/evaluation/paramtuning/"><span>Hyperparameter Tuning</span></a></li><li class="level-2"><a class="final" href="/evaluation/evaluationdashboard/"><span>Evaluation Dashboard</span></a></li><li class="level-2"><a class="final" href="/evaluation/metricchoose/"><span>Choosing Evaluation Metrics</span></a></li><li class="level
-2"><a class="final" href="/evaluation/metricbuild/"><span>Building Evaluation Metrics</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>System Architecture</span></a><ul><li class="level-2"><a class="final" href="/system/"><span>Architecture Overview</span></a></li><li class="level-2"><a class="final" href="/system/anotherdatastore/"><span>Using Another Data Store</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Engine Template Gallery</span></a><ul><li class="level-2"><a class="final" href="http://templates.prediction.io"><span>Browse</span></a></li><li class="level-2"><a class="final" href="/community/submit-template/"><span>Submit your Engine as a Template</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Demo Tutorials</span></a><ul><li class="level-2"><a class="final" href="/demo/tapster/"><span>Comics Recommendation Demo</span></a></li><li class="level-2"><a class="final" href="/d
emo/community/"><span>Community Contributed Demo</span></a></li><li class="level-2"><a class="final" href="/demo/textclassification/"><span>Text Classification Engine Tutorial</span></a></li></ul></li><li class="level-1"><a class="expandible" href="/community/"><span>Getting Involved</span></a><ul><li class="level-2"><a class="final" href="/community/contribute-code/"><span>Contribute Code</span></a></li><li class="level-2"><a class="final" href="/community/contribute-documentation/"><span>Contribute Documentation</span></a></li><li class="level-2"><a class="final" href="/community/contribute-sdk/"><span>Contribute a SDK</span></a></li><li class="level-2"><a class="final" href="/community/contribute-webhook/"><span>Contribute a Webhook</span></a></li><li class="level-2"><a class="final" href="/community/projects/"><span>Community Projects</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Getting Help</span></a><ul><li class="level-2"><a class="final"
href="/resources/faq/"><span>FAQs</span></a></li><li class="level-2"><a class="final" href="/support/"><span>Community Support</span></a></li><li class="level-2"><a class="final" href="/support/#enterprise-support"><span>Enterprise Support</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Resources</span></a><ul><li class="level-2"><a class="final" href="/resources/intellij/"><span>Developing Engines with IntelliJ IDEA</span></a></li><li class="level-2"><a class="final" href="/resources/upgrade/"><span>Upgrade Instructions</span></a></li><li class="level-2"><a class="final" href="/resources/glossary/"><span>Glossary</span></a></li></ul></li></ul></nav></div><div class="col-md-9 col-sm-12"><div class="content-header hidden-md hidden-lg"><div id="breadcrumbs" class="hidden-sm hidden xs"><ul><li><a href="#">Collecting and Analyzing Data</a><span class="spacer">></span></li><li><span class="last">Unifying Multichannel Data with Webhooks</span></li></ul
></div><div id="page-title"><h1>Unifying Multichannel Data with Webhooks</h1></div></div><div id="table-of-content-wrapper"><a id="edit-page-link" href="https://github.com/apache/incubator-predictionio/tree/livedoc/docs/manual/source/datacollection/webhooks.html.md.erb"><img src="/images/icons/edit-pencil-d6c1bb3d.png"/>Edit this page</a></div><div class="content-header hidden-sm hidden-xs"><div id="breadcrumbs" class="hidden-sm hidden xs"><ul><li><a href="#">Collecting and Analyzing Data</a><span class="spacer">></span></li><li><span class="last">Unifying Multichannel Data with Webhooks</span></li></ul></div><div id="page-title"><h1>Unifying Multichannel Data with Webhooks</h1></div></div><div class="content"><p>Webhooks are used to collects data for your application from multiple channels automatically.</p><p>Apache PredictionIO (incubating) offers webhooks for Segment.io and MailChimp (backend only). Several users also have expressed interest in Magento, Shopify and KeenIO so
we'd be happy to help if anyone wishes to implement these.</p></div></div></div></div><footer><div class="container"><div class="seperator"></div><div class="row"><div class="col-md-4 col-md-push-8 col-xs-12"><div class="subscription-form-wrapper"><h4>Subscribe to our Newsletter</h4><form class="ajax-form" id="subscribe-form" method="POST" action="https://script.google.com/macros/s/AKfycbwhzeKCQJjQ52eVAqNT_vcklH07OITUO7wzOMDXvK6EGAWgaZgF/exec"><input class="required underlined-input" type="email" placeholder="Your email address" name="subscription_email" id="subscription_email"/><input class="pill-button" value="SUBSCRIBE" type="submit" data-state-normal="SUBSCRIBE" data-state-sucess="SUBSCRIBED!" data-state-loading="SENDING..." onclick="t($('#subscription_email').val());"/><p class="result"></p></form></div></div><div class="col-md-2 col-md-pull-4 col-xs-6 footer-link-column"><div class="footer-link-column-row"><h4>Community</h4><ul><li><a href="//docs.prediction.io/install/" t
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ass="container-fluid"><div class="row"><div id="left-menu-wrapper" class="col-md-3"><nav id="nav-main"><ul><li class="level-1"><a class="expandible" href="/"><span>Apache PredictionIO (incubating) Documentation</span></a><ul><li class="level-2"><a class="final" href="/"><span>Welcome to Apache PredictionIO (incubating)</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Getting Started</span></a><ul><li class="level-2"><a class="final" href="/start/"><span>A Quick Intro</span></a></li><li class="level-2"><a class="final" href="/install/"><span>Installing Apache PredictionIO (incubating)</span></a></li><li class="level-2"><a class="final" href="/start/download/"><span>Downloading an Engine Template</span></a></li><li class="level-2"><a class="final" href="/start/deploy/"><span>Deploying Your First Engine</span></a></li><li class="level-2"><a class="final" href="/start/customize/"><span>Customizing the Engine</span></a></li></ul></li><li class="level-1"><
a class="expandible" href="#"><span>Integrating with Your App</span></a><ul><li class="level-2"><a class="final" href="/appintegration/"><span>App Integration Overview</span></a></li><li class="level-2"><a class="expandible" href="/sdk/"><span>List of SDKs</span></a><ul><li class="level-3"><a class="final" href="/sdk/java/"><span>Java & Android SDK</span></a></li><li class="level-3"><a class="final" href="/sdk/php/"><span>PHP SDK</span></a></li><li class="level-3"><a class="final" href="/sdk/python/"><span>Python SDK</span></a></li><li class="level-3"><a class="final" href="/sdk/ruby/"><span>Ruby SDK</span></a></li><li class="level-3"><a class="final" href="/sdk/community/"><span>Community Powered SDKs</span></a></li></ul></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Deploying an Engine</span></a><ul><li class="level-2"><a class="final" href="/deploy/"><span>Deploying as a Web Service</span></a></li><li class="level-2"><a class="final" href="/cli/#engine-co
mmands"><span>Engine Command-line Interface</span></a></li><li class="level-2"><a class="final" href="/deploy/engineparams/"><span>Setting Engine Parameters</span></a></li><li class="level-2"><a class="final" href="/deploy/enginevariants/"><span>Deploying Multiple Engine Variants</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Customizing an Engine</span></a><ul><li class="level-2"><a class="final" href="/customize/"><span>Learning DASE</span></a></li><li class="level-2"><a class="final" href="/customize/dase/"><span>Implement DASE</span></a></li><li class="level-2"><a class="final" href="/customize/troubleshooting/"><span>Troubleshooting Engine Development</span></a></li><li class="level-2"><a class="final" href="/api/current/#package"><span>Engine Scala APIs</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Collecting and Analyzing Data</span></a><ul><li class="level-2"><a class="final" href="/datacollection/"><span
>Event Server Overview</span></a></li><li class="level-2"><a class="final" href="/cli/#event-server-commands"><span>Event Server Command-line Interface</span></a></li><li class="level-2"><a class="final" href="/datacollection/eventapi/"><span>Collecting Data with REST/SDKs</span></a></li><li class="level-2"><a class="final" href="/datacollection/eventmodel/"><span>Events Modeling</span></a></li><li class="level-2"><a class="final" href="/datacollection/webhooks/"><span>Unifying Multichannel Data with Webhooks</span></a></li><li class="level-2"><a class="final" href="/datacollection/channel/"><span>Channel</span></a></li><li class="level-2"><a class="final" href="/datacollection/batchimport/"><span>Importing Data in Batch</span></a></li><li class="level-2"><a class="final" href="/datacollection/analytics/"><span>Using Analytics Tools</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Choosing an Algorithm(s)</span></a><ul><li class="level-2"><a class="f
inal" href="/algorithm/"><span>Built-in Algorithm Libraries</span></a></li><li class="level-2"><a class="final" href="/algorithm/switch/"><span>Switching to Another Algorithm</span></a></li><li class="level-2"><a class="final" href="/algorithm/multiple/"><span>Combining Multiple Algorithms</span></a></li><li class="level-2"><a class="final" href="/algorithm/custom/"><span>Adding Your Own Algorithms</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>ML Tuning and Evaluation</span></a><ul><li class="level-2"><a class="final" href="/evaluation/"><span>Overview</span></a></li><li class="level-2"><a class="final" href="/evaluation/paramtuning/"><span>Hyperparameter Tuning</span></a></li><li class="level-2"><a class="final" href="/evaluation/evaluationdashboard/"><span>Evaluation Dashboard</span></a></li><li class="level-2"><a class="final" href="/evaluation/metricchoose/"><span>Choosing Evaluation Metrics</span></a></li><li class="level-2"><a class="final"
href="/evaluation/metricbuild/"><span>Building Evaluation Metrics</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>System Architecture</span></a><ul><li class="level-2"><a class="final" href="/system/"><span>Architecture Overview</span></a></li><li class="level-2"><a class="final" href="/system/anotherdatastore/"><span>Using Another Data Store</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Engine Template Gallery</span></a><ul><li class="level-2"><a class="final" href="http://templates.prediction.io"><span>Browse</span></a></li><li class="level-2"><a class="final" href="/community/submit-template/"><span>Submit your Engine as a Template</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Demo Tutorials</span></a><ul><li class="level-2"><a class="final" href="/demo/tapster/"><span>Comics Recommendation Demo</span></a></li><li class="level-2"><a class="final active" href="/demo/community/
"><span>Community Contributed Demo</span></a></li><li class="level-2"><a class="final" href="/demo/textclassification/"><span>Text Classification Engine Tutorial</span></a></li></ul></li><li class="level-1"><a class="expandible" href="/community/"><span>Getting Involved</span></a><ul><li class="level-2"><a class="final" href="/community/contribute-code/"><span>Contribute Code</span></a></li><li class="level-2"><a class="final" href="/community/contribute-documentation/"><span>Contribute Documentation</span></a></li><li class="level-2"><a class="final" href="/community/contribute-sdk/"><span>Contribute a SDK</span></a></li><li class="level-2"><a class="final" href="/community/contribute-webhook/"><span>Contribute a Webhook</span></a></li><li class="level-2"><a class="final" href="/community/projects/"><span>Community Projects</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Getting Help</span></a><ul><li class="level-2"><a class="final" href="/resourc
es/faq/"><span>FAQs</span></a></li><li class="level-2"><a class="final" href="/support/"><span>Community Support</span></a></li><li class="level-2"><a class="final" href="/support/#enterprise-support"><span>Enterprise Support</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Resources</span></a><ul><li class="level-2"><a class="final" href="/resources/intellij/"><span>Developing Engines with IntelliJ IDEA</span></a></li><li class="level-2"><a class="final" href="/resources/upgrade/"><span>Upgrade Instructions</span></a></li><li class="level-2"><a class="final" href="/resources/glossary/"><span>Glossary</span></a></li></ul></li></ul></nav></div><div class="col-md-9 col-sm-12"><div class="content-header hidden-md hidden-lg"><div id="breadcrumbs" class="hidden-sm hidden xs"><ul><li><a href="#">Demo Tutorials</a><span class="spacer">></span></li><li><span class="last">Community Contributed Demo</span></li></ul></div><div id="page-title"><h1>Demo Tutori
als with Apache PredictionIO (incubating)</h1></div></div><div id="table-of-content-wrapper"><h5>On this page</h5><aside id="table-of-contents"><ul> <li> <a href="#tapster-ios-demo">Tapster iOS Demo</a> </li> <li> <a href="#nogoodgamez">NoGoodGamez</a> </li> <li> <a href="#ontapp">OnTapp</a> </li> <li> <a href="#yelpio">Yelpio</a> </li> </ul> </aside><hr/><a id="edit-page-link" href="https://github.com/apache/incubator-predictionio/tree/livedoc/docs/manual/source/demo/community.html.md"><img src="/images/icons/edit-pencil-d6c1bb3d.png"/>Edit this page</a></div><div class="content-header hidden-sm hidden-xs"><div id="breadcrumbs" class="hidden-sm hidden xs"><ul><li><a href="#">Demo Tutorials</a><span class="spacer">></span></li><li><span class="last">Community Contributed Demo</span></li></ul></div><div id="page-title"><h1>Demo Tutorials with Apache PredictionIO (incubating)</h1></div></div><div class="content"><p>Here is a list of demo tutorials for Apache PredictionIO (incubatin
g).</p><div class="alert-message info"><p>If you want to showcase your demo app here, simply edit <a href="https://github.com/apache/incubator-predictionio/blob/livedoc/docs/manual/source/community/showcase.html.md">this page</a> and submit a pull request.</p></div><h2 id='tapster-ios-demo' class='header-anchors'>Tapster iOS Demo</h2><p>Similar product recommendation in an iOS Swift app built by <a href="https://github.com/minhtule">Minh-Tu Le</a></p><p>URL: <a href="https://github.com/minhtule/Tapster-iOS-Demo">https://github.com/minhtule/Tapster-iOS-Demo</a></p><p>Tutorial: <a href="https://github.com/minhtule/Tapster-iOS-Demo/blob/master/TUTORIAL.md">https://github.com/minhtule/Tapster-iOS-Demo/blob/master/TUTORIAL.md</a></p><h2 id='nogoodgamez' class='header-anchors'>NoGoodGamez</h2><p><img src="/images/showcase/nogoodgamez-158x70-40bb6146.png" alt="NoGoodGamez" class="static"/></p><p>PS3/PS4 game Recommendation built by <a href="https://github.com/pashadude/">pashadude</a></p><
p>URL: <a href="http://nogoodgamez.com">http://nogoodgamez.com</a></p><h2 id='ontapp' class='header-anchors'>OnTapp</h2><p><img src="/images/showcase/on-tapp-70x70-424ec75e.png" alt="OnTapp" class="static"/></p><p>Beer recommendation app built by <a href="https://twitter.com/victorleungtw">Victor Leung</a>.</p><p>URL: <a href="http://ontappapp.com/">http://ontappapp.com/</a></p><p>Writeup: <a href="http://victorleungtw.com/prediction-io/">http://victorleungtw.com/prediction-io/</a></p><h2 id='yelpio' class='header-anchors'>Yelpio</h2><p><img src="/images/showcase/yelpio-70x70-70b520c6.png" alt="OnTapp" class="static"/></p><p>Business Recommendation built by <a href="https://twitter.com/k09ht">TRAN QUOC HOAN</a>, <a href="https://github.com/ihlee01">Inhwan Lee</a>, and \u5c71\u672c\u76f4\u4eba.</p><p>URL: <a href="http://yelpio.hongo.wide.ad.jp/">http://yelpio.hongo.wide.ad.jp/</a></p></div></div></div></div><footer><div class="container"><div class="seperator"></div><div class="row"><div class=
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<div class="row"><div class="col-md-9 col-sm-11 col-xs-11"><div class="hidden-md hidden-lg" id="mobile-page-heading-wrapper"><p>PredictionIO Docs</p><h4>Demos</h4></div><h4 class="hidden-sm hidden-xs">PredictionIO Docs</h4></div><div class="col-md-3 col-sm-1 col-xs-1 hidden-md hidden-lg"><img id="left-menu-indicator" src="/images/icons/down-arrow-dfe9f7fe.png"/></div><div class="col-md-3 col-sm-12 col-xs-12 swiftype-wrapper"><div class="swiftype"><form class="search-form"><img class="search-box-toggler hidden-xs hidden-sm" src="/images/icons/search-glass-704bd4ff.png"/><div class="search-box"><img src="/images/icons/search-glass-704bd4ff.png"/><input type="text" id="st-search-input" class="st-search-input" placeholder="Search Doc..."/></div><img class="swiftype-row-hider hidden-md hidden-lg" src="/images/icons/drawer-toggle-active-fcbef12a.png"/></form></div></div><div class="mobile-left-menu-toggler hidden-md hidden-lg"></div></div></div></div><div id="page" class="container-fluid"
><div class="row"><div id="left-menu-wrapper" class="col-md-3"><nav id="nav-main"><ul><li class="level-1"><a class="expandible" href="/"><span>Apache PredictionIO (incubating) Documentation</span></a><ul><li class="level-2"><a class="final" href="/"><span>Welcome to Apache PredictionIO (incubating)</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Getting Started</span></a><ul><li class="level-2"><a class="final" href="/start/"><span>A Quick Intro</span></a></li><li class="level-2"><a class="final" href="/install/"><span>Installing Apache PredictionIO (incubating)</span></a></li><li class="level-2"><a class="final" href="/start/download/"><span>Downloading an Engine Template</span></a></li><li class="level-2"><a class="final" href="/start/deploy/"><span>Deploying Your First Engine</span></a></li><li class="level-2"><a class="final" href="/start/customize/"><span>Customizing the Engine</span></a></li></ul></li><li class="level-1"><a class="expandible"
href="#"><span>Integrating with Your App</span></a><ul><li class="level-2"><a class="final" href="/appintegration/"><span>App Integration Overview</span></a></li><li class="level-2"><a class="expandible" href="/sdk/"><span>List of SDKs</span></a><ul><li class="level-3"><a class="final" href="/sdk/java/"><span>Java & Android SDK</span></a></li><li class="level-3"><a class="final" href="/sdk/php/"><span>PHP SDK</span></a></li><li class="level-3"><a class="final" href="/sdk/python/"><span>Python SDK</span></a></li><li class="level-3"><a class="final" href="/sdk/ruby/"><span>Ruby SDK</span></a></li><li class="level-3"><a class="final" href="/sdk/community/"><span>Community Powered SDKs</span></a></li></ul></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Deploying an Engine</span></a><ul><li class="level-2"><a class="final" href="/deploy/"><span>Deploying as a Web Service</span></a></li><li class="level-2"><a class="final" href="/cli/#engine-commands"><span>Engine
Command-line Interface</span></a></li><li class="level-2"><a class="final" href="/deploy/engineparams/"><span>Setting Engine Parameters</span></a></li><li class="level-2"><a class="final" href="/deploy/enginevariants/"><span>Deploying Multiple Engine Variants</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Customizing an Engine</span></a><ul><li class="level-2"><a class="final" href="/customize/"><span>Learning DASE</span></a></li><li class="level-2"><a class="final" href="/customize/dase/"><span>Implement DASE</span></a></li><li class="level-2"><a class="final" href="/customize/troubleshooting/"><span>Troubleshooting Engine Development</span></a></li><li class="level-2"><a class="final" href="/api/current/#package"><span>Engine Scala APIs</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Collecting and Analyzing Data</span></a><ul><li class="level-2"><a class="final" href="/datacollection/"><span>Event Server Overvie
w</span></a></li><li class="level-2"><a class="final" href="/cli/#event-server-commands"><span>Event Server Command-line Interface</span></a></li><li class="level-2"><a class="final" href="/datacollection/eventapi/"><span>Collecting Data with REST/SDKs</span></a></li><li class="level-2"><a class="final" href="/datacollection/eventmodel/"><span>Events Modeling</span></a></li><li class="level-2"><a class="final" href="/datacollection/webhooks/"><span>Unifying Multichannel Data with Webhooks</span></a></li><li class="level-2"><a class="final" href="/datacollection/channel/"><span>Channel</span></a></li><li class="level-2"><a class="final" href="/datacollection/batchimport/"><span>Importing Data in Batch</span></a></li><li class="level-2"><a class="final" href="/datacollection/analytics/"><span>Using Analytics Tools</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Choosing an Algorithm(s)</span></a><ul><li class="level-2"><a class="final" href="/algorith
m/"><span>Built-in Algorithm Libraries</span></a></li><li class="level-2"><a class="final" href="/algorithm/switch/"><span>Switching to Another Algorithm</span></a></li><li class="level-2"><a class="final" href="/algorithm/multiple/"><span>Combining Multiple Algorithms</span></a></li><li class="level-2"><a class="final" href="/algorithm/custom/"><span>Adding Your Own Algorithms</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>ML Tuning and Evaluation</span></a><ul><li class="level-2"><a class="final" href="/evaluation/"><span>Overview</span></a></li><li class="level-2"><a class="final" href="/evaluation/paramtuning/"><span>Hyperparameter Tuning</span></a></li><li class="level-2"><a class="final" href="/evaluation/evaluationdashboard/"><span>Evaluation Dashboard</span></a></li><li class="level-2"><a class="final" href="/evaluation/metricchoose/"><span>Choosing Evaluation Metrics</span></a></li><li class="level-2"><a class="final" href="/evaluation/met
ricbuild/"><span>Building Evaluation Metrics</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>System Architecture</span></a><ul><li class="level-2"><a class="final" href="/system/"><span>Architecture Overview</span></a></li><li class="level-2"><a class="final" href="/system/anotherdatastore/"><span>Using Another Data Store</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Engine Template Gallery</span></a><ul><li class="level-2"><a class="final" href="http://templates.prediction.io"><span>Browse</span></a></li><li class="level-2"><a class="final" href="/community/submit-template/"><span>Submit your Engine as a Template</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Demo Tutorials</span></a><ul><li class="level-2"><a class="final" href="/demo/tapster/"><span>Comics Recommendation Demo</span></a></li><li class="level-2"><a class="final" href="/demo/community/"><span>Community Contribute
d Demo</span></a></li><li class="level-2"><a class="final" href="/demo/textclassification/"><span>Text Classification Engine Tutorial</span></a></li></ul></li><li class="level-1"><a class="expandible" href="/community/"><span>Getting Involved</span></a><ul><li class="level-2"><a class="final" href="/community/contribute-code/"><span>Contribute Code</span></a></li><li class="level-2"><a class="final" href="/community/contribute-documentation/"><span>Contribute Documentation</span></a></li><li class="level-2"><a class="final" href="/community/contribute-sdk/"><span>Contribute a SDK</span></a></li><li class="level-2"><a class="final" href="/community/contribute-webhook/"><span>Contribute a Webhook</span></a></li><li class="level-2"><a class="final" href="/community/projects/"><span>Community Projects</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Getting Help</span></a><ul><li class="level-2"><a class="final" href="/resources/faq/"><span>FAQs</span></
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+fbq('track', "PageView");</script><script src="//use.typekit.net/mut4mjx.js"></script><script>try{Typekit.load();}catch(e){}</script></head><body><div id="global"><header><div class="container" id="header-wrapper"><div class="row"><div class="col-sm-12"><div id="logo-wrapper"><span id="drawer-toggle"></span><a href="#"></a><a href="http://prediction.io/"><img alt="PredictionIO" id="logo" src="/images/logos/logo-ee2b9bb3.png"/></a></div><div id="menu-wrapper"><div id="header-nav-options-wrapper"><ul><li><a href="/">Install & Doc</a></li> <li><a href="/support">Support</a></li> </ul></div><div id="pill-wrapper"><a class="pill left" href="//templates.prediction.io/">TEMPLATES</a> <a class="pill right" href="//github.com/PredictionIO/PredictionIO/">OPEN SOURCE</a></div></div><img class="mobile-search-bar-toggler hidden-md hidden-lg" src="/images/icons/search-glass-704bd4ff.png"/></div></div></div></header><div id="search-bar-row-wrapper"><div class="container-fluid" id="search-bar-row">
<div class="row"><div class="col-md-9 col-sm-11 col-xs-11"><div class="hidden-md hidden-lg" id="mobile-page-heading-wrapper"><p>PredictionIO Docs</p><h4>Implement DASE</h4></div><h4 class="hidden-sm hidden-xs">PredictionIO Docs</h4></div><div class="col-md-3 col-sm-1 col-xs-1 hidden-md hidden-lg"><img id="left-menu-indicator" src="/images/icons/down-arrow-dfe9f7fe.png"/></div><div class="col-md-3 col-sm-12 col-xs-12 swiftype-wrapper"><div class="swiftype"><form class="search-form"><img class="search-box-toggler hidden-xs hidden-sm" src="/images/icons/search-glass-704bd4ff.png"/><div class="search-box"><img src="/images/icons/search-glass-704bd4ff.png"/><input type="text" id="st-search-input" class="st-search-input" placeholder="Search Doc..."/></div><img class="swiftype-row-hider hidden-md hidden-lg" src="/images/icons/drawer-toggle-active-fcbef12a.png"/></form></div></div><div class="mobile-left-menu-toggler hidden-md hidden-lg"></div></div></div></div><div id="page" class="contain
er-fluid"><div class="row"><div id="left-menu-wrapper" class="col-md-3"><nav id="nav-main"><ul><li class="level-1"><a class="expandible" href="/"><span>Apache PredictionIO (incubating) Documentation</span></a><ul><li class="level-2"><a class="final" href="/"><span>Welcome to Apache PredictionIO (incubating)</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Getting Started</span></a><ul><li class="level-2"><a class="final" href="/start/"><span>A Quick Intro</span></a></li><li class="level-2"><a class="final" href="/install/"><span>Installing Apache PredictionIO (incubating)</span></a></li><li class="level-2"><a class="final" href="/start/download/"><span>Downloading an Engine Template</span></a></li><li class="level-2"><a class="final" href="/start/deploy/"><span>Deploying Your First Engine</span></a></li><li class="level-2"><a class="final" href="/start/customize/"><span>Customizing the Engine</span></a></li></ul></li><li class="level-1"><a class="exp
andible" href="#"><span>Integrating with Your App</span></a><ul><li class="level-2"><a class="final" href="/appintegration/"><span>App Integration Overview</span></a></li><li class="level-2"><a class="expandible" href="/sdk/"><span>List of SDKs</span></a><ul><li class="level-3"><a class="final" href="/sdk/java/"><span>Java & Android SDK</span></a></li><li class="level-3"><a class="final" href="/sdk/php/"><span>PHP SDK</span></a></li><li class="level-3"><a class="final" href="/sdk/python/"><span>Python SDK</span></a></li><li class="level-3"><a class="final" href="/sdk/ruby/"><span>Ruby SDK</span></a></li><li class="level-3"><a class="final" href="/sdk/community/"><span>Community Powered SDKs</span></a></li></ul></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Deploying an Engine</span></a><ul><li class="level-2"><a class="final" href="/deploy/"><span>Deploying as a Web Service</span></a></li><li class="level-2"><a class="final" href="/cli/#engine-commands"><spa
n>Engine Command-line Interface</span></a></li><li class="level-2"><a class="final" href="/deploy/engineparams/"><span>Setting Engine Parameters</span></a></li><li class="level-2"><a class="final" href="/deploy/enginevariants/"><span>Deploying Multiple Engine Variants</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Customizing an Engine</span></a><ul><li class="level-2"><a class="final" href="/customize/"><span>Learning DASE</span></a></li><li class="level-2"><a class="final active" href="/customize/dase/"><span>Implement DASE</span></a></li><li class="level-2"><a class="final" href="/customize/troubleshooting/"><span>Troubleshooting Engine Development</span></a></li><li class="level-2"><a class="final" href="/api/current/#package"><span>Engine Scala APIs</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Collecting and Analyzing Data</span></a><ul><li class="level-2"><a class="final" href="/datacollection/"><span>Even
t Server Overview</span></a></li><li class="level-2"><a class="final" href="/cli/#event-server-commands"><span>Event Server Command-line Interface</span></a></li><li class="level-2"><a class="final" href="/datacollection/eventapi/"><span>Collecting Data with REST/SDKs</span></a></li><li class="level-2"><a class="final" href="/datacollection/eventmodel/"><span>Events Modeling</span></a></li><li class="level-2"><a class="final" href="/datacollection/webhooks/"><span>Unifying Multichannel Data with Webhooks</span></a></li><li class="level-2"><a class="final" href="/datacollection/channel/"><span>Channel</span></a></li><li class="level-2"><a class="final" href="/datacollection/batchimport/"><span>Importing Data in Batch</span></a></li><li class="level-2"><a class="final" href="/datacollection/analytics/"><span>Using Analytics Tools</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Choosing an Algorithm(s)</span></a><ul><li class="level-2"><a class="final"
href="/algorithm/"><span>Built-in Algorithm Libraries</span></a></li><li class="level-2"><a class="final" href="/algorithm/switch/"><span>Switching to Another Algorithm</span></a></li><li class="level-2"><a class="final" href="/algorithm/multiple/"><span>Combining Multiple Algorithms</span></a></li><li class="level-2"><a class="final" href="/algorithm/custom/"><span>Adding Your Own Algorithms</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>ML Tuning and Evaluation</span></a><ul><li class="level-2"><a class="final" href="/evaluation/"><span>Overview</span></a></li><li class="level-2"><a class="final" href="/evaluation/paramtuning/"><span>Hyperparameter Tuning</span></a></li><li class="level-2"><a class="final" href="/evaluation/evaluationdashboard/"><span>Evaluation Dashboard</span></a></li><li class="level-2"><a class="final" href="/evaluation/metricchoose/"><span>Choosing Evaluation Metrics</span></a></li><li class="level-2"><a class="final" href=
"/evaluation/metricbuild/"><span>Building Evaluation Metrics</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>System Architecture</span></a><ul><li class="level-2"><a class="final" href="/system/"><span>Architecture Overview</span></a></li><li class="level-2"><a class="final" href="/system/anotherdatastore/"><span>Using Another Data Store</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Engine Template Gallery</span></a><ul><li class="level-2"><a class="final" href="http://templates.prediction.io"><span>Browse</span></a></li><li class="level-2"><a class="final" href="/community/submit-template/"><span>Submit your Engine as a Template</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Demo Tutorials</span></a><ul><li class="level-2"><a class="final" href="/demo/tapster/"><span>Comics Recommendation Demo</span></a></li><li class="level-2"><a class="final" href="/demo/community/"><span>Comm
unity Contributed Demo</span></a></li><li class="level-2"><a class="final" href="/demo/textclassification/"><span>Text Classification Engine Tutorial</span></a></li></ul></li><li class="level-1"><a class="expandible" href="/community/"><span>Getting Involved</span></a><ul><li class="level-2"><a class="final" href="/community/contribute-code/"><span>Contribute Code</span></a></li><li class="level-2"><a class="final" href="/community/contribute-documentation/"><span>Contribute Documentation</span></a></li><li class="level-2"><a class="final" href="/community/contribute-sdk/"><span>Contribute a SDK</span></a></li><li class="level-2"><a class="final" href="/community/contribute-webhook/"><span>Contribute a Webhook</span></a></li><li class="level-2"><a class="final" href="/community/projects/"><span>Community Projects</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Getting Help</span></a><ul><li class="level-2"><a class="final" href="/resources/faq/"><sp
an>FAQs</span></a></li><li class="level-2"><a class="final" href="/support/"><span>Community Support</span></a></li><li class="level-2"><a class="final" href="/support/#enterprise-support"><span>Enterprise Support</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Resources</span></a><ul><li class="level-2"><a class="final" href="/resources/intellij/"><span>Developing Engines with IntelliJ IDEA</span></a></li><li class="level-2"><a class="final" href="/resources/upgrade/"><span>Upgrade Instructions</span></a></li><li class="level-2"><a class="final" href="/resources/glossary/"><span>Glossary</span></a></li></ul></li></ul></nav></div><div class="col-md-9 col-sm-12"><div class="content-header hidden-md hidden-lg"><div id="breadcrumbs" class="hidden-sm hidden xs"><ul><li><a href="#">Customizing an Engine</a><span class="spacer">></span></li><li><span class="last">Implement DASE</span></li></ul></div><div id="page-title"><h1>Implementing DASE</h1></div>
</div><div id="table-of-content-wrapper"><h5>On this page</h5><aside id="table-of-contents"><ul> <li> <a href="#datasource">DataSource</a> <ul> <li> <a href="#readtraining">readTraining()</a> </li> <li> <a href="#using-peventstore-engine-api">Using PEventStore Engine API</a> </li> </ul> </li> <li> <a href="#preparator">Preparator</a> <ul> <li> <a href="#prepare">prepare()</a> </li> </ul> </li> <li> <a href="#algorithm">Algorithm</a> <ul> <li> <a href="#train">train()</a> </li> <li> <a href="#predict">predict()</a> </li> <li> <a href="#p2lalgorithm">P2LAlgorithm</a> </li> <li> <a href="#palgorithm">PAlgorithm</a> </li> <li> <a href="#using-leventstore-engine-api-in-predict">using LEventStore Engine API in predict()</a> </li> </ul> </li> <li> <a href="#serving">Serving</a> <ul> <li> <a href="#serve">serve()</a> </li> </ul> </li> </ul> </aside><hr/><a id="edit-page-link" href="https://github.com/apache/incubator-predictionio/tree/livedoc/docs/manual/source/customize/dase.html.md.erb"><
img src="/images/icons/edit-pencil-d6c1bb3d.png"/>Edit this page</a></div><div class="content-header hidden-sm hidden-xs"><div id="breadcrumbs" class="hidden-sm hidden xs"><ul><li><a href="#">Customizing an Engine</a><span class="spacer">></span></li><li><span class="last">Implement DASE</span></li></ul></div><div id="page-title"><h1>Implementing DASE</h1></div></div><div class="content"><p>This section gives you an overview of DASE components and how to implement them. You will find links to some engine templates for more concrete examples.</p><h1 id='datasource' class='header-anchors'>DataSource</h1><p>DataSource reads and selects useful data from the Event Store (data store of the Event Server) and returns TrainingData.</p><h2 id='readtraining()' class='header-anchors'>readTraining()</h2><p>You need to implment readTraining() of <a href="https://docs.prediction.io/api/current/#io.prediction.controller.PDataSource">PDataSource</a>, where you can use the <a href="https://docs.pr
ediction.io/api/current/#io.prediction.data.store.PEventStore$">PEventStore Engine API</a> to read the events and create the TrainingData based on the events.</p><p>The following code example reads user "view" and "buy" item events, filters specific type of events for future processing and returns TrainingData accordingly.</p><div class="highlight scala"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1
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+ <span class="k">extends</span> <span class="nc">PDataSource</span><span class="o">[</span><span class="kt">TrainingData</span>,
+ <span class="kt">EmptyEvaluationInfo</span>, <span class="kt">Query</span>, <span class="kt">EmptyActualResult</span><span class="o">]</span> <span class="o">{</span>
+
+ <span class="nd">@transient</span> <span class="k">lazy</span> <span class="k">val</span> <span class="n">logger</span> <span class="k">=</span> <span class="nc">Logger</span><span class="o">[</span><span class="kt">this.</span><span class="k">type</span><span class="o">]</span>
+
+ <span class="k">override</span>
+ <span class="k">def</span> <span class="n">readTraining</span><span class="o">(</span><span class="n">sc</span><span class="k">:</span> <span class="kt">SparkContext</span><span class="o">)</span><span class="k">:</span> <span class="kt">TrainingData</span> <span class="o">=</span> <span class="o">{</span>
+
+ <span class="k">val</span> <span class="n">eventsRDD</span><span class="k">:</span> <span class="kt">RDD</span><span class="o">[</span><span class="kt">Event</span><span class="o">]</span> <span class="k">=</span> <span class="nc">PEventStore</span><span class="o">.</span><span class="n">find</span><span class="o">(</span>
+ <span class="n">appName</span> <span class="k">=</span> <span class="n">dsp</span><span class="o">.</span><span class="n">appName</span><span class="o">,</span>
+ <span class="n">entityType</span> <span class="k">=</span> <span class="nc">Some</span><span class="o">(</span><span class="s">"user"</span><span class="o">),</span>
+ <span class="n">eventNames</span> <span class="k">=</span> <span class="nc">Some</span><span class="o">(</span><span class="nc">List</span><span class="o">(</span><span class="s">"view"</span><span class="o">,</span> <span class="s">"buy"</span><span class="o">)),</span>
+ <span class="c1">// targetEntityType is optional field of an event.
+</span> <span class="n">targetEntityType</span> <span class="k">=</span> <span class="nc">Some</span><span class="o">(</span><span class="nc">Some</span><span class="o">(</span><span class="s">"item"</span><span class="o">)))(</span><span class="n">sc</span><span class="o">)</span>
+ <span class="o">.</span><span class="n">cache</span><span class="o">()</span>
+
+ <span class="k">val</span> <span class="n">viewEventsRDD</span><span class="k">:</span> <span class="kt">RDD</span><span class="o">[</span><span class="kt">ViewEvent</span><span class="o">]</span> <span class="k">=</span> <span class="n">eventsRDD</span>
+ <span class="o">.</span><span class="n">filter</span> <span class="o">{</span> <span class="n">event</span> <span class="k">=></span> <span class="n">event</span><span class="o">.</span><span class="n">event</span> <span class="o">==</span> <span class="s">"view"</span> <span class="o">}</span>
+ <span class="o">.</span><span class="n">map</span> <span class="o">{</span> <span class="o">...</span> <span class="o">}</span>
+
+ <span class="o">...</span>
+
+ <span class="k">new</span> <span class="nc">TrainingData</span><span class="o">(...)</span>
+ <span class="o">}</span>
+
+<span class="o">}</span>
+</pre></td></tr></tbody></table> </div> <h2 id='using-peventstore-engine-api' class='header-anchors'>Using PEventStore Engine API</h2><p>Please see <a href="https://docs.prediction.io/datacollection/">Event Server Overview</a> to understand <a href="https://docs.prediction.io/datacollection/eventapi/">EventAPI</a> and <a href="https://docs.prediction.io/datacollection/eventmodel/">event modeling</a>.</p><p>With <a href="https://docs.prediction.io/api/current/#io.prediction.data.store.PEventStore$">PEventStore Engine API</a>, you can easily read different events in DataSource and get the information you need.</p><p>For example, let's say you have events like the following:</p><div class="highlight json"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1
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+ </span><span class="s2">"event"</span><span class="p">:</span><span class="w"> </span><span class="s2">"myEvent"</span><span class="p">,</span><span class="w">
+ </span><span class="s2">"entityType"</span><span class="p">:</span><span class="w"> </span><span class="s2">"user"</span><span class="p">,</span><span class="w">
+ </span><span class="s2">"entityId"</span><span class="p">:</span><span class="w"> </span><span class="s2">"u0"</span><span class="p">,</span><span class="w">
+ </span><span class="s2">"targetEntityType"</span><span class="p">:</span><span class="w"> </span><span class="s2">"item"</span><span class="p">,</span><span class="w">
+ </span><span class="s2">"targetEntityId"</span><span class="p">:</span><span class="w"> </span><span class="s2">"i0"</span><span class="p">,</span><span class="w">
+ </span><span class="s2">"properties"</span><span class="w"> </span><span class="p">:</span><span class="w"> </span><span class="p">{</span><span class="w">
+ </span><span class="s2">"a"</span><span class="w"> </span><span class="p">:</span><span class="w"> </span><span class="mi">3</span><span class="p">,</span><span class="w">
+ </span><span class="s2">"b"</span><span class="w"> </span><span class="p">:</span><span class="w"> </span><span class="s2">"some_string"</span><span class="p">,</span><span class="w">
+ </span><span class="s2">"c"</span><span class="w"> </span><span class="p">:</span><span class="w"> </span><span class="p">[</span><span class="s2">"a"</span><span class="p">,</span><span class="w"> </span><span class="s2">"b"</span><span class="p">,</span><span class="w"> </span><span class="s2">"c"</span><span class="p">],</span><span class="w">
+ </span><span class="s2">"d"</span><span class="w"> </span><span class="p">:</span><span class="w"> </span><span class="p">[</span><span class="mf">1.2</span><span class="p">,</span><span class="w"> </span><span class="mf">3.4</span><span class="p">,</span><span class="w"> </span><span class="mf">5.6</span><span class="p">],</span><span class="w">
+ </span><span class="s2">"e"</span><span class="w"> </span><span class="p">:</span><span class="w"> </span><span class="mi">6</span><span class="w">
+ </span><span class="p">}</span><span class="w">
+</span><span class="p">}</span><span class="w">
+</span></pre></td></tr></tbody></table> </div> <p>Then following code could read these events and extract the properties field of the event and convert it to a <code>MyEvent</code> object.</p><div class="highlight scala"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1
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+ <span class="n">appName</span> <span class="k">=</span> <span class="n">dsp</span><span class="o">.</span><span class="n">appName</span><span class="o">,</span>
+ <span class="n">entityType</span> <span class="k">=</span> <span class="nc">Some</span><span class="o">(</span><span class="s">"user"</span><span class="o">),</span>
+ <span class="n">eventNames</span> <span class="k">=</span> <span class="nc">Some</span><span class="o">(</span><span class="nc">List</span><span class="o">(</span><span class="s">"myEvent"</span><span class="o">)),</span>
+ <span class="c1">// targetEntityType is optional field of an event.
+</span> <span class="n">targetEntityType</span> <span class="k">=</span> <span class="nc">Some</span><span class="o">(</span><span class="nc">Some</span><span class="o">(</span><span class="s">"item"</span><span class="o">)))(</span><span class="n">sc</span><span class="o">)</span>
+ <span class="o">.</span><span class="n">map</span> <span class="o">{</span> <span class="n">event</span> <span class="k">=></span>
+ <span class="k">try</span> <span class="o">{</span>
+ <span class="nc">MyEvent</span><span class="o">(</span>
+ <span class="n">entityId</span> <span class="k">=</span> <span class="n">event</span><span class="o">.</span><span class="n">entityId</span><span class="o">,</span>
+ <span class="n">targetEntityId</span> <span class="k">=</span> <span class="n">event</span><span class="o">.</span><span class="n">targetEntityId</span><span class="o">.</span><span class="n">get</span><span class="o">,</span>
+ <span class="n">a</span> <span class="k">=</span> <span class="n">event</span><span class="o">.</span><span class="n">properties</span><span class="o">.</span><span class="n">get</span><span class="o">[</span><span class="kt">Int</span><span class="o">](</span><span class="s">"a"</span><span class="o">),</span>
+ <span class="n">b</span> <span class="k">=</span> <span class="n">event</span><span class="o">.</span><span class="n">properties</span><span class="o">.</span><span class="n">get</span><span class="o">[</span><span class="kt">String</span><span class="o">](</span><span class="s">"b"</span><span class="o">),</span>
+ <span class="n">c</span> <span class="k">=</span> <span class="n">event</span><span class="o">.</span><span class="n">properties</span><span class="o">.</span><span class="n">get</span><span class="o">[</span><span class="kt">List</span><span class="o">[</span><span class="kt">String</span><span class="o">]](</span><span class="s">"c"</span><span class="o">),</span>
+ <span class="n">d</span> <span class="k">=</span> <span class="n">event</span><span class="o">.</span><span class="n">properties</span><span class="o">.</span><span class="n">get</span><span class="o">[</span><span class="kt">List</span><span class="o">[</span><span class="kt">Double</span><span class="o">]](</span><span class="s">"d"</span><span class="o">),</span>
+ <span class="n">e</span> <span class="k">=</span> <span class="n">event</span><span class="o">.</span><span class="n">properties</span><span class="o">.</span><span class="n">getOpt</span><span class="o">[</span><span class="kt">Int</span><span class="o">](</span><span class="s">"e"</span><span class="o">)</span> <span class="c1">// use getOpt for optional data
+</span> <span class="o">)</span>
+ <span class="o">}</span> <span class="k">catch</span> <span class="o">{</span>
+ <span class="k">case</span> <span class="n">e</span><span class="k">:</span> <span class="kt">Exception</span> <span class="o">=></span>
+ <span class="n">logger</span><span class="o">.</span><span class="n">error</span><span class="o">(</span><span class="n">s</span><span class="s">"Cannot convert ${event}. Exception: ${e}."</span><span class="o">)</span>
+ <span class="k">throw</span> <span class="n">e</span>
+ <span class="o">}</span>
+ <span class="o">}</span>
+</pre></td></tr></tbody></table> </div> <p>If you have used special events <code>$set/$unset/$delete</code> setting entity's properties, you can retrieve it with <code>PEventStore.aggregateProperties()</code>.</p><p>Please see <a href="https://docs.prediction.io/datacollection/eventmodel/">event modeling</a> to understand usage of special <code>$set/$unset/$delete</code> events.</p><p>For example, the following code show how you could retrieve properties of the "item" entities:</p><div class="highlight scala"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1
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+</span> <span class="k">val</span> <span class="n">itemsRDD</span><span class="k">:</span> <span class="kt">RDD</span><span class="o">[(</span><span class="kt">String</span>, <span class="kt">Item</span><span class="o">)]</span> <span class="k">=</span> <span class="nc">PEventStore</span><span class="o">.</span><span class="n">aggregateProperties</span><span class="o">(</span>
+ <span class="n">appName</span> <span class="k">=</span> <span class="n">dsp</span><span class="o">.</span><span class="n">appName</span><span class="o">,</span>
+ <span class="n">entityType</span> <span class="k">=</span> <span class="s">"item"</span>
+ <span class="o">)(</span><span class="n">sc</span><span class="o">).</span><span class="n">map</span> <span class="o">{</span> <span class="k">case</span> <span class="o">(</span><span class="n">entityId</span><span class="o">,</span> <span class="n">properties</span><span class="o">)</span> <span class="k">=></span>
+
+ <span class="k">try</span> <span class="o">{</span>
+ <span class="k">val</span> <span class="n">item</span> <span class="k">=</span> <span class="nc">Item</span><span class="o">(</span>
+ <span class="n">a</span> <span class="k">=</span> <span class="n">preopties</span><span class="o">.</span><span class="n">get</span><span class="o">[</span><span class="kt">Int</span><span class="o">](</span><span class="s">"a"</span><span class="o">),</span>
+ <span class="n">b</span> <span class="k">=</span> <span class="n">properties</span><span class="o">.</span><span class="n">get</span><span class="o">[</span><span class="kt">String</span><span class="o">](</span><span class="s">"b"</span><span class="o">),</span>
+ <span class="n">c</span> <span class="k">=</span> <span class="n">properties</span><span class="o">.</span><span class="n">get</span><span class="o">[</span><span class="kt">List</span><span class="o">[</span><span class="kt">String</span><span class="o">]](</span><span class="s">"c"</span><span class="o">),</span>
+ <span class="n">d</span> <span class="k">=</span> <span class="n">properties</span><span class="o">.</span><span class="n">get</span><span class="o">[</span><span class="kt">List</span><span class="o">[</span><span class="kt">Double</span><span class="o">]](</span><span class="s">"d"</span><span class="o">),</span>
+ <span class="n">e</span> <span class="k">=</span> <span class="n">properties</span><span class="o">.</span><span class="n">getOpt</span><span class="o">[</span><span class="kt">Int</span><span class="o">](</span><span class="s">"e"</span><span class="o">)</span> <span class="c1">// use getOpt for optional data
+</span> <span class="o">)</span>
+
+ <span class="o">(</span><span class="n">entityId</span><span class="o">,</span> <span class="n">item</span><span class="o">)</span>
+ <span class="o">}</span> <span class="k">catch</span> <span class="o">{</span>
+ <span class="k">case</span> <span class="n">e</span><span class="k">:</span> <span class="kt">Exception</span> <span class="o">=></span>
+ <span class="n">logger</span><span class="o">.</span><span class="n">error</span><span class="o">(</span><span class="n">s</span><span class="s">"Failed to get properties ${properties} of ${entityId}. Exception: ${e}."</span><span class="o">)</span>
+ <span class="k">throw</span> <span class="n">e</span>
+ <span class="o">}</span>
+
+ <span class="o">}</span>
+</pre></td></tr></tbody></table> </div> <p>Example:</p> <ul> <li><a href="/templates/similarproduct/dase/#data">DataSource of Similar Product Template</a></li> </ul> <h1 id='preparator' class='header-anchors'>Preparator</h1><p>Preparator is responsible for pre-processing <code>TrainingData</code> for any necessary feature selection and data processing tasks and generate <code>PreparedData</code> which contains the data the Algorithm needs.</p><p>A few example usages of Preparator:</p> <ul> <li>Feature extraction</li> <li>Common pre-processing logic if you have multiple algorithms</li> <li>For simple cases, the Preparator may simply pass the same <code>TrainingData</code> as <code>PreparedData</code> for Algorithm.</li> </ul> <h2 id='prepare()' class='header-anchors'>prepare()</h2><p>You need to implement the <code>prepare()</code> method of <a href="https://docs.prediction.io/api/current/#io.prediction.controller.PPreparator">PPrepartor</a> to perform such tasks.</p><p>Example:</p>
<ul> <li><a href="/templates/leadscoring/dase/#data">Preparator of Leading Scoring Template</a>: it pre-processes the TrainingData and generate the feature vectors needed for the algorithm.</li> <li><a href="/templates/similarproduct/dase/#data">Preparator of Similar Product Template</a>: it simply passes the TrainingData as PreparedData for the algorithm.</li> </ul> <h1 id='algorithm' class='header-anchors'>Algorithm</h1><p>The two methods of the Algorithm class are train() and predict():</p><h2 id='train()' class='header-anchors'>train()</h2><p>train() is responsible for training a predictive model. It is called when you run <code>pio train</code>. Apache PredictionIO (incubating) will store this model.</p><h2 id='predict()' class='header-anchors'>predict()</h2><p>predict() is responsible for using this model to make prediction. It is called when you send a JSON query to the engine. Note that predict() is called in real time.</p><p>Apache PredictionIO (incubating) supports two typ
es of algorithms:</p> <ul> <li><strong><a href="https://docs.prediction.io/api/current/#io.prediction.controller.P2LAlgorithm">P2LAlgorithm</a></strong>: trains a Model which does not contain RDD</li> <li><strong><a href="https://docs.prediction.io/api/current/#io.prediction.controller.PAlgorithm">PAlgorithm</a></strong>: trains a Model which contains RDD</li> </ul> <h2 id='p2lalgorithm' class='header-anchors'>P2LAlgorithm</h2><p>For <code>P2LAlgorithm</code>, the Model is automatically serialized and persisted by Apache PredictionIO (incubating) after training.</p><p>Implementing <code>IPersistentModel</code> and <code>IPersistentModelLoader</code> is optional for P2LAlgorithm.</p><p>Example:</p> <ul> <li><a href="/templates/similarproduct/dase/#algorithm">Algorithm of Similar Product Template</a></li> </ul> <h2 id='palgorithm' class='header-anchors'>PAlgorithm</h2><p><code>PAlgorithm</code> should be used when your Model contains RDD. The model produced by <code>PAlgorithm</code>
is not persisted by default. To persist the model, you need to do the following:</p> <ul> <li>The Model class should extend the <code>IPersistentModel</code> trait and implement the <code>save()</code> method for saving the model. The trait <code>IPersistentModel</code> requires a type parameter which is the class type of algorithm parameter.</li> <li>Implement a Model factory object which extends the <code>IPersistentModelLoader</code> trait and implement the <code>apply()</code> for loading the model. The trait <code>IPersistentModelLoader</code> requires two type parameters which are the types of algorithm parameter and the model produced by the algorithm.</li> </ul> <p>Example:</p> <ul> <li><a href="/templates/recommendation/dase/#algorithm">Algorithm of Recommendation Template</a>: it implements PAlgorithm and the IPersistentModel and IPersistentModelLoader.</li> <li><a href="/templates/vanilla/dase">Algorithm of Vanilla Template</a>: it walks through example of P2LAlgorithm an
d PAlgorithm.</li> </ul> <h2 id='using-leventstore-engine-api-in-predict()' class='header-anchors'>using LEventStore Engine API in predict()</h2><p>You may use <a href="https://docs.prediction.io/api/current/#io.prediction.data.store.LEventStore$">LEventStore.findByEntity()</a> to retrieve events of a specific entity. For example, retrieve recent events of the user specified in the query) and use these recent events to make prediction in real time.</p><p>For example, the following code reads the recent 10 view events of <code>query.user</code>:</p><div class="highlight scala"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1
+2
+3
+4
+5
+6
+7
+8
+9
+10
+11
+12
+13
+14
+15
+16
+17
+18
+19
+20
+21
+22</pre></td><td class="code"><pre> <span class="k">val</span> <span class="n">recentEvents</span> <span class="k">=</span> <span class="k">try</span> <span class="o">{</span>
+ <span class="nc">LEventStore</span><span class="o">.</span><span class="n">findByEntity</span><span class="o">(</span>
+ <span class="n">appName</span> <span class="k">=</span> <span class="n">ap</span><span class="o">.</span><span class="n">appName</span><span class="o">,</span>
+ <span class="c1">// entityType and entityId is specified for fast lookup
+</span> <span class="n">entityType</span> <span class="k">=</span> <span class="s">"user"</span><span class="o">,</span>
+ <span class="n">entityId</span> <span class="k">=</span> <span class="n">query</span><span class="o">.</span><span class="n">user</span><span class="o">,</span>
+ <span class="n">eventNames</span> <span class="k">=</span> <span class="nc">Some</span><span class="o">(</span><span class="nc">List</span><span class="o">(</span><span class="s">"view"</span><span class="o">)),</span>
+ <span class="n">targetEntityType</span> <span class="k">=</span> <span class="nc">Some</span><span class="o">(</span><span class="nc">Some</span><span class="o">(</span><span class="s">"item"</span><span class="o">)),</span>
+ <span class="n">limit</span> <span class="k">=</span> <span class="nc">Some</span><span class="o">(</span><span class="mi">10</span><span class="o">),</span>
+ <span class="n">latest</span> <span class="k">=</span> <span class="kc">true</span><span class="o">,</span>
+ <span class="c1">// set time limit to avoid super long DB access
+</span> <span class="n">timeout</span> <span class="k">=</span> <span class="nc">Duration</span><span class="o">(</span><span class="mi">200</span><span class="o">,</span> <span class="s">"millis"</span><span class="o">)</span>
+ <span class="o">)</span>
+ <span class="o">}</span> <span class="k">catch</span> <span class="o">{</span>
+ <span class="k">case</span> <span class="n">e</span><span class="k">:</span> <span class="kt">scala.concurrent.TimeoutException</span> <span class="o">=></span>
+ <span class="n">logger</span><span class="o">.</span><span class="n">error</span><span class="o">(</span><span class="n">s</span><span class="s">"Timeout when read recent events."</span> <span class="o">+</span>
+ <span class="n">s</span><span class="s">" Empty list is used. ${e}"</span><span class="o">)</span>
+ <span class="nc">Iterator</span><span class="o">[</span><span class="kt">Event</span><span class="o">]()</span>
+ <span class="k">case</span> <span class="n">e</span><span class="k">:</span> <span class="kt">Exception</span> <span class="o">=></span>
+ <span class="n">logger</span><span class="o">.</span><span class="n">error</span><span class="o">(</span><span class="n">s</span><span class="s">"Error when read recent events: ${e}"</span><span class="o">)</span>
+ <span class="k">throw</span> <span class="n">e</span>
+ <span class="o">}</span>
+</pre></td></tr></tbody></table> </div> <p>Example:</p> <ul> <li><a href="/templates/ecommercerecommendation/dase#algorithm">Algorithm of E-Commerce Recommendation template</a>: LEventStore.findByEntity() is used to retrieve all items seen by the user and filter them from recommendation in predict().</li> </ul> <h1 id='serving' class='header-anchors'>Serving</h1><h2 id='serve()' class='header-anchors'>serve()</h2><p>You need to implement the serve() method of the class <a href="https://docs.prediction.io/api/current/#io.prediction.controller.LServing">LServing</a>. The serve() method processes predicted result. It is also responsible for combining multiple predicted results into one if you have more than one predictive model.</p><p>Example:</p> <ul> <li><a href="/templates/similarproduct/dase/#serving">Serving of Similar Product Template</a>: It simply returns the predicted result</li> <li><a href="/templates/similarproduct/multi-events-multi-algos/">Serving of multi-algorithm examp
les of Similar Product Template</a>: It combines the result of multiple algorithms and return</li> </ul> </div></div></div></div><footer><div class="container"><div class="seperator"></div><div class="row"><div class="col-md-4 col-md-push-8 col-xs-12"><div class="subscription-form-wrapper"><h4>Subscribe to our Newsletter</h4><form class="ajax-form" id="subscribe-form" method="POST" action="https://script.google.com/macros/s/AKfycbwhzeKCQJjQ52eVAqNT_vcklH07OITUO7wzOMDXvK6EGAWgaZgF/exec"><input class="required underlined-input" type="email" placeholder="Your email address" name="subscription_email" id="subscription_email"/><input class="pill-button" value="SUBSCRIBE" type="submit" data-state-normal="SUBSCRIBE" data-state-sucess="SUBSCRIBED!" data-state-loading="SENDING..." onclick="t($('#subscription_email').val());"/><p class="result"></p></form></div></div><div class="col-md-2 col-md-pull-4 col-xs-6 footer-link-column"><div class="footer-link-column-row"><h4>Community</h4><ul><li><a
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<div class="row"><div class="col-md-9 col-sm-11 col-xs-11"><div class="hidden-md hidden-lg" id="mobile-page-heading-wrapper"><p>PredictionIO Docs</p><h4>Learning DASE</h4></div><h4 class="hidden-sm hidden-xs">PredictionIO Docs</h4></div><div class="col-md-3 col-sm-1 col-xs-1 hidden-md hidden-lg"><img id="left-menu-indicator" src="/images/icons/down-arrow-dfe9f7fe.png"/></div><div class="col-md-3 col-sm-12 col-xs-12 swiftype-wrapper"><div class="swiftype"><form class="search-form"><img class="search-box-toggler hidden-xs hidden-sm" src="/images/icons/search-glass-704bd4ff.png"/><div class="search-box"><img src="/images/icons/search-glass-704bd4ff.png"/><input type="text" id="st-search-input" class="st-search-input" placeholder="Search Doc..."/></div><img class="swiftype-row-hider hidden-md hidden-lg" src="/images/icons/drawer-toggle-active-fcbef12a.png"/></form></div></div><div class="mobile-left-menu-toggler hidden-md hidden-lg"></div></div></div></div><div id="page" class="containe
r-fluid"><div class="row"><div id="left-menu-wrapper" class="col-md-3"><nav id="nav-main"><ul><li class="level-1"><a class="expandible" href="/"><span>Apache PredictionIO (incubating) Documentation</span></a><ul><li class="level-2"><a class="final" href="/"><span>Welcome to Apache PredictionIO (incubating)</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Getting Started</span></a><ul><li class="level-2"><a class="final" href="/start/"><span>A Quick Intro</span></a></li><li class="level-2"><a class="final" href="/install/"><span>Installing Apache PredictionIO (incubating)</span></a></li><li class="level-2"><a class="final" href="/start/download/"><span>Downloading an Engine Template</span></a></li><li class="level-2"><a class="final" href="/start/deploy/"><span>Deploying Your First Engine</span></a></li><li class="level-2"><a class="final" href="/start/customize/"><span>Customizing the Engine</span></a></li></ul></li><li class="level-1"><a class="expa
ndible" href="#"><span>Integrating with Your App</span></a><ul><li class="level-2"><a class="final" href="/appintegration/"><span>App Integration Overview</span></a></li><li class="level-2"><a class="expandible" href="/sdk/"><span>List of SDKs</span></a><ul><li class="level-3"><a class="final" href="/sdk/java/"><span>Java & Android SDK</span></a></li><li class="level-3"><a class="final" href="/sdk/php/"><span>PHP SDK</span></a></li><li class="level-3"><a class="final" href="/sdk/python/"><span>Python SDK</span></a></li><li class="level-3"><a class="final" href="/sdk/ruby/"><span>Ruby SDK</span></a></li><li class="level-3"><a class="final" href="/sdk/community/"><span>Community Powered SDKs</span></a></li></ul></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Deploying an Engine</span></a><ul><li class="level-2"><a class="final" href="/deploy/"><span>Deploying as a Web Service</span></a></li><li class="level-2"><a class="final" href="/cli/#engine-commands"><span
>Engine Command-line Interface</span></a></li><li class="level-2"><a class="final" href="/deploy/engineparams/"><span>Setting Engine Parameters</span></a></li><li class="level-2"><a class="final" href="/deploy/enginevariants/"><span>Deploying Multiple Engine Variants</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Customizing an Engine</span></a><ul><li class="level-2"><a class="final active" href="/customize/"><span>Learning DASE</span></a></li><li class="level-2"><a class="final" href="/customize/dase/"><span>Implement DASE</span></a></li><li class="level-2"><a class="final" href="/customize/troubleshooting/"><span>Troubleshooting Engine Development</span></a></li><li class="level-2"><a class="final" href="/api/current/#package"><span>Engine Scala APIs</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Collecting and Analyzing Data</span></a><ul><li class="level-2"><a class="final" href="/datacollection/"><span>Event
Server Overview</span></a></li><li class="level-2"><a class="final" href="/cli/#event-server-commands"><span>Event Server Command-line Interface</span></a></li><li class="level-2"><a class="final" href="/datacollection/eventapi/"><span>Collecting Data with REST/SDKs</span></a></li><li class="level-2"><a class="final" href="/datacollection/eventmodel/"><span>Events Modeling</span></a></li><li class="level-2"><a class="final" href="/datacollection/webhooks/"><span>Unifying Multichannel Data with Webhooks</span></a></li><li class="level-2"><a class="final" href="/datacollection/channel/"><span>Channel</span></a></li><li class="level-2"><a class="final" href="/datacollection/batchimport/"><span>Importing Data in Batch</span></a></li><li class="level-2"><a class="final" href="/datacollection/analytics/"><span>Using Analytics Tools</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Choosing an Algorithm(s)</span></a><ul><li class="level-2"><a class="final"
href="/algorithm/"><span>Built-in Algorithm Libraries</span></a></li><li class="level-2"><a class="final" href="/algorithm/switch/"><span>Switching to Another Algorithm</span></a></li><li class="level-2"><a class="final" href="/algorithm/multiple/"><span>Combining Multiple Algorithms</span></a></li><li class="level-2"><a class="final" href="/algorithm/custom/"><span>Adding Your Own Algorithms</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>ML Tuning and Evaluation</span></a><ul><li class="level-2"><a class="final" href="/evaluation/"><span>Overview</span></a></li><li class="level-2"><a class="final" href="/evaluation/paramtuning/"><span>Hyperparameter Tuning</span></a></li><li class="level-2"><a class="final" href="/evaluation/evaluationdashboard/"><span>Evaluation Dashboard</span></a></li><li class="level-2"><a class="final" href="/evaluation/metricchoose/"><span>Choosing Evaluation Metrics</span></a></li><li class="level-2"><a class="final" href="
/evaluation/metricbuild/"><span>Building Evaluation Metrics</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>System Architecture</span></a><ul><li class="level-2"><a class="final" href="/system/"><span>Architecture Overview</span></a></li><li class="level-2"><a class="final" href="/system/anotherdatastore/"><span>Using Another Data Store</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Engine Template Gallery</span></a><ul><li class="level-2"><a class="final" href="http://templates.prediction.io"><span>Browse</span></a></li><li class="level-2"><a class="final" href="/community/submit-template/"><span>Submit your Engine as a Template</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Demo Tutorials</span></a><ul><li class="level-2"><a class="final" href="/demo/tapster/"><span>Comics Recommendation Demo</span></a></li><li class="level-2"><a class="final" href="/demo/community/"><span>Commu
nity Contributed Demo</span></a></li><li class="level-2"><a class="final" href="/demo/textclassification/"><span>Text Classification Engine Tutorial</span></a></li></ul></li><li class="level-1"><a class="expandible" href="/community/"><span>Getting Involved</span></a><ul><li class="level-2"><a class="final" href="/community/contribute-code/"><span>Contribute Code</span></a></li><li class="level-2"><a class="final" href="/community/contribute-documentation/"><span>Contribute Documentation</span></a></li><li class="level-2"><a class="final" href="/community/contribute-sdk/"><span>Contribute a SDK</span></a></li><li class="level-2"><a class="final" href="/community/contribute-webhook/"><span>Contribute a Webhook</span></a></li><li class="level-2"><a class="final" href="/community/projects/"><span>Community Projects</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Getting Help</span></a><ul><li class="level-2"><a class="final" href="/resources/faq/"><spa
n>FAQs</span></a></li><li class="level-2"><a class="final" href="/support/"><span>Community Support</span></a></li><li class="level-2"><a class="final" href="/support/#enterprise-support"><span>Enterprise Support</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Resources</span></a><ul><li class="level-2"><a class="final" href="/resources/intellij/"><span>Developing Engines with IntelliJ IDEA</span></a></li><li class="level-2"><a class="final" href="/resources/upgrade/"><span>Upgrade Instructions</span></a></li><li class="level-2"><a class="final" href="/resources/glossary/"><span>Glossary</span></a></li></ul></li></ul></nav></div><div class="col-md-9 col-sm-12"><div class="content-header hidden-md hidden-lg"><div id="breadcrumbs" class="hidden-sm hidden xs"><ul><li><a href="#">Customizing an Engine</a><span class="spacer">></span></li><li><span class="last">Learning DASE</span></li></ul></div><div id="page-title"><h1>Learning DASE</h1></div></div>
<div id="table-of-content-wrapper"><h5>On this page</h5><aside id="table-of-contents"><ul> <li> <a href="#the-roles-of-an-engine">The Roles of an Engine</a> </li> <li> <a href="#examples-of-dase">Examples of DASE</a> </li> </ul> </aside><hr/><a id="edit-page-link" href="https://github.com/apache/incubator-predictionio/tree/livedoc/docs/manual/source/customize/index.html.md"><img src="/images/icons/edit-pencil-d6c1bb3d.png"/>Edit this page</a></div><div class="content-header hidden-sm hidden-xs"><div id="breadcrumbs" class="hidden-sm hidden xs"><ul><li><a href="#">Customizing an Engine</a><span class="spacer">></span></li><li><span class="last">Learning DASE</span></li></ul></div><div id="page-title"><h1>Learning DASE</h1></div></div><div class="content"><p>The code of an engine consists of D-A-S-E components:</p><h3 id='[d]-data-source-and-data-preparator' class='header-anchors'>[D] Data Source and Data Preparator</h3><p>Data Source reads data from an input source and transforms
it into a desired format. Data Preparator preprocesses the data and forwards it to the algorithm for model training.</p><h3 id='[a]-algorithm' class='header-anchors'>[A] Algorithm</h3><p>The Algorithm component includes the Machine Learning algorithm, and the settings of its parameters, determines how a predictive model is constructed.</p><h3 id='[s]-serving' class='header-anchors'>[S] Serving</h3><p>The Serving component takes prediction <em>queries</em> and returns prediction results. If the engine has multiple algorithms, Serving will combine the results into one. Additionally, business-specific logic can be added in Serving to further customize the final returned results.</p><h3 id='[e]-evaluation-metrics' class='header-anchors'>[E] Evaluation Metrics</h3><p>An Evaluation Metric quantifies prediction accuracy with a numerical score. It can be used for comparing algorithms or algorithm parameter settings.</p> <blockquote> <p>Apache PredictionIO (incubating) helps you modularize t
hese components so you can build, for example, several Serving components for an Engine. You will be able to choose which one to be deployed when you create an Engine.</p></blockquote> <p><img alt="Engine Overview" src="/images/engineinstance-overview-c6668657.png"/></p><h2 id='the-roles-of-an-engine' class='header-anchors'>The Roles of an Engine</h2><p>The main functions of an engine are:</p> <ul> <li>Train a model using the training data and be deployed as a web service</li> <li>Respond to prediction query in real-time</li> </ul> <p>An engine puts all DASE components into a deployable state by specifying:</p> <ul> <li><p>One Data Source</p></li> <li><p>One Data Preparator</p></li> <li><p>One or more Algorithm(s)</p></li> <li><p>One Serving</p></li> </ul> <div class="alert-message info"><p>If more than one algorithm is specified, each of their model prediction results will be passed to Serving for ensembling.</p></div><p>Each Engine processes data and constructs predictive models i
ndependently. Therefore, every engine serves its own set of prediction results. For example, you may deploy two engines for your mobile application: one for recommending news to users and another one for suggesting new friends to users.</p><h3 id='training-a-model---the-dase-view' class='header-anchors'>Training a Model - The DASE View</h3><p>The following graph shows the workflow of DASE components when <code>pio train</code> is run.</p><p><img alt="Engine Overview" src="/images/engine-training-93bc1b69.png"/></p><h3 id='respond-to-prediction-query---the-dase-view' class='header-anchors'>Respond to Prediction Query - The DASE View</h3><p>The following graph shows the workflow of DASE components when a REST query is received by a deployed engine.</p><p><img alt="Engine Overview" src="/images/engine-query-8d7311ff.png"/></p><p>Please see <a href="/customize/dase">Implement DASE</a> for DASE implementation details.</p><p>Please refer to following templates and their how-to guides for
concrete examples.</p><h2 id='examples-of-dase' class='header-anchors'>Examples of DASE</h2> <ul> <li><a href="/templates/recommendation/dase/">DASE of Recommendation Template</a></li> <li><a href="/templates/similarproduct/dase/">DASE of Similar Product Template</a></li> <li><a href="/templates/classification/dase/">DASE of Classification Template</a></li> <li><a href="/templates/leadscoring/dase/">DASE of Lead Scoring Template</a></li> </ul> </div></div></div></div><footer><div class="container"><div class="seperator"></div><div class="row"><div class="col-md-4 col-md-push-8 col-xs-12"><div class="subscription-form-wrapper"><h4>Subscribe to our Newsletter</h4><form class="ajax-form" id="subscribe-form" method="POST" action="https://script.google.com/macros/s/AKfycbwhzeKCQJjQ52eVAqNT_vcklH07OITUO7wzOMDXvK6EGAWgaZgF/exec"><input class="required underlined-input" type="email" placeholder="Your email address" name="subscription_email" id="subscription_email"/><input class="pill-button
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tainer-fluid"><div class="row"><div id="left-menu-wrapper" class="col-md-3"><nav id="nav-main"><ul><li class="level-1"><a class="expandible" href="/"><span>Apache PredictionIO (incubating) Documentation</span></a><ul><li class="level-2"><a class="final" href="/"><span>Welcome to Apache PredictionIO (incubating)</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Getting Started</span></a><ul><li class="level-2"><a class="final" href="/start/"><span>A Quick Intro</span></a></li><li class="level-2"><a class="final" href="/install/"><span>Installing Apache PredictionIO (incubating)</span></a></li><li class="level-2"><a class="final" href="/start/download/"><span>Downloading an Engine Template</span></a></li><li class="level-2"><a class="final" href="/start/deploy/"><span>Deploying Your First Engine</span></a></li><li class="level-2"><a class="final" href="/start/customize/"><span>Customizing the Engine</span></a></li></ul></li><li class="level-1"><a class=
"expandible" href="#"><span>Integrating with Your App</span></a><ul><li class="level-2"><a class="final" href="/appintegration/"><span>App Integration Overview</span></a></li><li class="level-2"><a class="expandible" href="/sdk/"><span>List of SDKs</span></a><ul><li class="level-3"><a class="final" href="/sdk/java/"><span>Java & Android SDK</span></a></li><li class="level-3"><a class="final" href="/sdk/php/"><span>PHP SDK</span></a></li><li class="level-3"><a class="final" href="/sdk/python/"><span>Python SDK</span></a></li><li class="level-3"><a class="final" href="/sdk/ruby/"><span>Ruby SDK</span></a></li><li class="level-3"><a class="final" href="/sdk/community/"><span>Community Powered SDKs</span></a></li></ul></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Deploying an Engine</span></a><ul><li class="level-2"><a class="final" href="/deploy/"><span>Deploying as a Web Service</span></a></li><li class="level-2"><a class="final" href="/cli/#engine-commands">
<span>Engine Command-line Interface</span></a></li><li class="level-2"><a class="final" href="/deploy/engineparams/"><span>Setting Engine Parameters</span></a></li><li class="level-2"><a class="final" href="/deploy/enginevariants/"><span>Deploying Multiple Engine Variants</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Customizing an Engine</span></a><ul><li class="level-2"><a class="final" href="/customize/"><span>Learning DASE</span></a></li><li class="level-2"><a class="final" href="/customize/dase/"><span>Implement DASE</span></a></li><li class="level-2"><a class="final" href="/customize/troubleshooting/"><span>Troubleshooting Engine Development</span></a></li><li class="level-2"><a class="final" href="/api/current/#package"><span>Engine Scala APIs</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Collecting and Analyzing Data</span></a><ul><li class="level-2"><a class="final" href="/datacollection/"><span>Event S
erver Overview</span></a></li><li class="level-2"><a class="final" href="/cli/#event-server-commands"><span>Event Server Command-line Interface</span></a></li><li class="level-2"><a class="final" href="/datacollection/eventapi/"><span>Collecting Data with REST/SDKs</span></a></li><li class="level-2"><a class="final" href="/datacollection/eventmodel/"><span>Events Modeling</span></a></li><li class="level-2"><a class="final" href="/datacollection/webhooks/"><span>Unifying Multichannel Data with Webhooks</span></a></li><li class="level-2"><a class="final" href="/datacollection/channel/"><span>Channel</span></a></li><li class="level-2"><a class="final" href="/datacollection/batchimport/"><span>Importing Data in Batch</span></a></li><li class="level-2"><a class="final" href="/datacollection/analytics/"><span>Using Analytics Tools</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Choosing an Algorithm(s)</span></a><ul><li class="level-2"><a class="final" hr
ef="/algorithm/"><span>Built-in Algorithm Libraries</span></a></li><li class="level-2"><a class="final" href="/algorithm/switch/"><span>Switching to Another Algorithm</span></a></li><li class="level-2"><a class="final" href="/algorithm/multiple/"><span>Combining Multiple Algorithms</span></a></li><li class="level-2"><a class="final" href="/algorithm/custom/"><span>Adding Your Own Algorithms</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>ML Tuning and Evaluation</span></a><ul><li class="level-2"><a class="final" href="/evaluation/"><span>Overview</span></a></li><li class="level-2"><a class="final" href="/evaluation/paramtuning/"><span>Hyperparameter Tuning</span></a></li><li class="level-2"><a class="final" href="/evaluation/evaluationdashboard/"><span>Evaluation Dashboard</span></a></li><li class="level-2"><a class="final" href="/evaluation/metricchoose/"><span>Choosing Evaluation Metrics</span></a></li><li class="level-2"><a class="final" href="/e
valuation/metricbuild/"><span>Building Evaluation Metrics</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>System Architecture</span></a><ul><li class="level-2"><a class="final" href="/system/"><span>Architecture Overview</span></a></li><li class="level-2"><a class="final" href="/system/anotherdatastore/"><span>Using Another Data Store</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Engine Template Gallery</span></a><ul><li class="level-2"><a class="final" href="http://templates.prediction.io"><span>Browse</span></a></li><li class="level-2"><a class="final" href="/community/submit-template/"><span>Submit your Engine as a Template</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Demo Tutorials</span></a><ul><li class="level-2"><a class="final" href="/demo/tapster/"><span>Comics Recommendation Demo</span></a></li><li class="level-2"><a class="final" href="/demo/community/"><span>Communi
ty Contributed Demo</span></a></li><li class="level-2"><a class="final" href="/demo/textclassification/"><span>Text Classification Engine Tutorial</span></a></li></ul></li><li class="level-1"><a class="expandible" href="/community/"><span>Getting Involved</span></a><ul><li class="level-2"><a class="final" href="/community/contribute-code/"><span>Contribute Code</span></a></li><li class="level-2"><a class="final" href="/community/contribute-documentation/"><span>Contribute Documentation</span></a></li><li class="level-2"><a class="final" href="/community/contribute-sdk/"><span>Contribute a SDK</span></a></li><li class="level-2"><a class="final" href="/community/contribute-webhook/"><span>Contribute a Webhook</span></a></li><li class="level-2"><a class="final active" href="/community/projects/"><span>Community Projects</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Getting Help</span></a><ul><li class="level-2"><a class="final" href="/resources/faq/"
><span>FAQs</span></a></li><li class="level-2"><a class="final" href="/support/"><span>Community Support</span></a></li><li class="level-2"><a class="final" href="/support/#enterprise-support"><span>Enterprise Support</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Resources</span></a><ul><li class="level-2"><a class="final" href="/resources/intellij/"><span>Developing Engines with IntelliJ IDEA</span></a></li><li class="level-2"><a class="final" href="/resources/upgrade/"><span>Upgrade Instructions</span></a></li><li class="level-2"><a class="final" href="/resources/glossary/"><span>Glossary</span></a></li></ul></li></ul></nav></div><div class="col-md-9 col-sm-12"><div class="content-header hidden-md hidden-lg"><div id="breadcrumbs" class="hidden-sm hidden xs"><ul><li><a href="/community/">Getting Involved</a><span class="spacer">></span></li><li><span class="last">Community Projects</span></li></ul></div><div id="page-title"><h1>Community Power
ed Projects</h1></div></div><div id="table-of-content-wrapper"><h5>On this page</h5><aside id="table-of-contents"><ul> <li> <a href="#sdks">SDKs</a> </li> <li> <a href="#magento-2-personalised-products-module">Magento 2 Personalised Products Module</a> </li> <li> <a href="#vagrant-installation-for-predictionio">Vagrant Installation for PredictionIO</a> </li> <li> <a href="#docker-installation-for-predictionio">Docker Installation for PredictionIO</a> </li> <li> <a href="#another-docker-installation-for-predictionio">Another Docker Installation for PredictionIO</a> </li> <li> <a href="#graphx-parallel-simrank-algorithm">GraphX Parallel SimRank Algorithm</a> </li> <li> <a href="#magento-similar-products-extension">Magento Similar Products Extension</a> </li> </ul> </aside><hr/><a id="edit-page-link" href="https://github.com/apache/incubator-predictionio/tree/livedoc/docs/manual/source/community/projects.html.md"><img src="/images/icons/edit-pencil-d6c1bb3d.png"/>Edit this page</a></di
v><div class="content-header hidden-sm hidden-xs"><div id="breadcrumbs" class="hidden-sm hidden xs"><ul><li><a href="/community/">Getting Involved</a><span class="spacer">></span></li><li><span class="last">Community Projects</span></li></ul></div><div id="page-title"><h1>Community Powered Projects</h1></div></div><div class="content"><p>Here you will find great projects contributed by the Apache PredictionIO (incubating) community. Stay tuned.</p><div class="alert-message info"><p>If you have built a Apache PredictionIO (incubating)-related project, we would love to showcase it to the community! Simply edit <a href="https://github.com/apache/incubator-predictionio/blob/livedoc/docs/manual/source/community/projects.html.md">this page</a> and submit a pull request.</p></div><h2 id='sdks' class='header-anchors'>SDKs</h2><p>Community-powered SDKs are <a href="/sdk/">separately listed</a>.</p><h2 id='magento-2-personalised-products-module' class='header-anchors'>Magento 2 Personalise
d Products Module</h2><p>URL: <a href="https://github.com/richdynamix/personalised-products">https://github.com/richdynamix/personalised-products</a></p><p>Personalised Products is a Magento 2 module that will serve realtime predicted suggestions for product upsells on the product page and complimentary suggestions for cross sells on the basket page. All powered by PredictionIO using the <a title="Similar Product" href="https://templates.prediction.io/PredictionIO/template-scala-parallel-similarproduct">Similar Product</a> engine and the <a title="Complementary Purchase" href="https://templates.prediction.io/PredictionIO/template-scala-parallel-complementarypurchase">Complementary Purchase</a> engine.</p> <ul> <li><p>Core Author: Steven Richardson</p></li> <li><p>Status: It works with PredictionIO v0.9.5 - Under active development</p></li> </ul> <h2 id='vagrant-installation-for-predictionio' class='header-anchors'>Vagrant Installation for PredictionIO</h2><p>URL: <a href="https://gi
thub.com/PredictionIO/PredictionIO-Vagrant">https://github.com/PredictionIO/PredictionIO-Vagrant</a></p><p>Bring Up PredictionIO 0.9.x VM with Vagrant.</p> <ul> <li><p>Core Author: Raphael M�der</p></li> <li><p>Status: It works with PredictionIO v0.8 - Under active development</p></li> </ul> <h2 id='docker-installation-for-predictionio' class='header-anchors'>Docker Installation for PredictionIO</h2><p>URL: <a href="https://github.com/mingfang/docker-predictionio">https://github.com/mingfang/docker-predictionio</a></p><p>Run PredictionIO inside Docker.</p> <ul> <li><p>Core Author: Ming Fang</p></li> <li><p>Status: It works with PredictionIO v0.8 - Under active development</p></li> </ul> <h2 id='another-docker-installation-for-predictionio' class='header-anchors'>Another Docker Installation for PredictionIO</h2><p>URL: <a href="https://github.com/sphereio/docker-predictionio">https://github.com/sphereio/docker-predictionio</a></p><p>Docker container for PredictionIO-based machine le
arning services.</p> <ul> <li><p>Core Author: Fabian M. Borschel</p></li> <li><p>Status: Runs latest PredictionIO v0.9.3 - Under active development</p></li> </ul> <h2 id='graphx-parallel-simrank-algorithm' class='header-anchors'>GraphX Parallel SimRank Algorithm</h2><p>URL: <a href="https://github.com/ZhouYii/PIO-Parallel-Simrank-Engine">https://github.com/ZhouYii/PIO-Parallel-Simrank-Engine</a></p><p>Implementation of Delta-Simrank algorithm using Spark's GraphX framework.</p> <ul> <li><p>Core Author: Joey Zhou</p></li> <li><p>Status: It works with PredictionIO v0.8 - Under active development</p></li> </ul> <h2 id='magento-similar-products-extension' class='header-anchors'>Magento Similar Products Extension</h2><p>URL: <a href="https://github.com/magento-hackathon/Predictionio">https://github.com/magento-hackathon/Predictionio</a></p><p>Similar Products is a Magento extension that utilizes PredictionIO to create a more personalized suggestion of up-sell products on the Magento
product page.</p> <ul> <li><p>Core Author: Steven Richardson, Raphael M�der & Damian Luszczymak</p></li> <li><p>Status: It works with PredictionIO v0.8 - Under active development</p></li> </ul> </div></div></div></div><footer><div class="container"><div class="seperator"></div><div class="row"><div class="col-md-4 col-md-push-8 col-xs-12"><div class="subscription-form-wrapper"><h4>Subscribe to our Newsletter</h4><form class="ajax-form" id="subscribe-form" method="POST" action="https://script.google.com/macros/s/AKfycbwhzeKCQJjQ52eVAqNT_vcklH07OITUO7wzOMDXvK6EGAWgaZgF/exec"><input class="required underlined-input" type="email" placeholder="Your email address" name="subscription_email" id="subscription_email"/><input class="pill-button" value="SUBSCRIBE" type="submit" data-state-normal="SUBSCRIBE" data-state-sucess="SUBSCRIBED!" data-state-loading="SENDING..." onclick="t($('#subscription_email').val());"/><p class="result"></p></form></div></div><div class="col-md-2 col-md-pull-4
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<div class="row"><div class="col-md-9 col-sm-11 col-xs-11"><div class="hidden-md hidden-lg" id="mobile-page-heading-wrapper"><p>PredictionIO Docs</p><h4>Submit your Engine as a Template</h4></div><h4 class="hidden-sm hidden-xs">PredictionIO Docs</h4></div><div class="col-md-3 col-sm-1 col-xs-1 hidden-md hidden-lg"><img id="left-menu-indicator" src="/images/icons/down-arrow-dfe9f7fe.png"/></div><div class="col-md-3 col-sm-12 col-xs-12 swiftype-wrapper"><div class="swiftype"><form class="search-form"><img class="search-box-toggler hidden-xs hidden-sm" src="/images/icons/search-glass-704bd4ff.png"/><div class="search-box"><img src="/images/icons/search-glass-704bd4ff.png"/><input type="text" id="st-search-input" class="st-search-input" placeholder="Search Doc..."/></div><img class="swiftype-row-hider hidden-md hidden-lg" src="/images/icons/drawer-toggle-active-fcbef12a.png"/></form></div></div><div class="mobile-left-menu-toggler hidden-md hidden-lg"></div></div></div></div><div id="pa
ge" class="container-fluid"><div class="row"><div id="left-menu-wrapper" class="col-md-3"><nav id="nav-main"><ul><li class="level-1"><a class="expandible" href="/"><span>Apache PredictionIO (incubating) Documentation</span></a><ul><li class="level-2"><a class="final" href="/"><span>Welcome to Apache PredictionIO (incubating)</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Getting Started</span></a><ul><li class="level-2"><a class="final" href="/start/"><span>A Quick Intro</span></a></li><li class="level-2"><a class="final" href="/install/"><span>Installing Apache PredictionIO (incubating)</span></a></li><li class="level-2"><a class="final" href="/start/download/"><span>Downloading an Engine Template</span></a></li><li class="level-2"><a class="final" href="/start/deploy/"><span>Deploying Your First Engine</span></a></li><li class="level-2"><a class="final" href="/start/customize/"><span>Customizing the Engine</span></a></li></ul></li><li class="leve
l-1"><a class="expandible" href="#"><span>Integrating with Your App</span></a><ul><li class="level-2"><a class="final" href="/appintegration/"><span>App Integration Overview</span></a></li><li class="level-2"><a class="expandible" href="/sdk/"><span>List of SDKs</span></a><ul><li class="level-3"><a class="final" href="/sdk/java/"><span>Java & Android SDK</span></a></li><li class="level-3"><a class="final" href="/sdk/php/"><span>PHP SDK</span></a></li><li class="level-3"><a class="final" href="/sdk/python/"><span>Python SDK</span></a></li><li class="level-3"><a class="final" href="/sdk/ruby/"><span>Ruby SDK</span></a></li><li class="level-3"><a class="final" href="/sdk/community/"><span>Community Powered SDKs</span></a></li></ul></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Deploying an Engine</span></a><ul><li class="level-2"><a class="final" href="/deploy/"><span>Deploying as a Web Service</span></a></li><li class="level-2"><a class="final" href="/cli/#eng
ine-commands"><span>Engine Command-line Interface</span></a></li><li class="level-2"><a class="final" href="/deploy/engineparams/"><span>Setting Engine Parameters</span></a></li><li class="level-2"><a class="final" href="/deploy/enginevariants/"><span>Deploying Multiple Engine Variants</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Customizing an Engine</span></a><ul><li class="level-2"><a class="final" href="/customize/"><span>Learning DASE</span></a></li><li class="level-2"><a class="final" href="/customize/dase/"><span>Implement DASE</span></a></li><li class="level-2"><a class="final" href="/customize/troubleshooting/"><span>Troubleshooting Engine Development</span></a></li><li class="level-2"><a class="final" href="/api/current/#package"><span>Engine Scala APIs</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Collecting and Analyzing Data</span></a><ul><li class="level-2"><a class="final" href="/datacollection/"
><span>Event Server Overview</span></a></li><li class="level-2"><a class="final" href="/cli/#event-server-commands"><span>Event Server Command-line Interface</span></a></li><li class="level-2"><a class="final" href="/datacollection/eventapi/"><span>Collecting Data with REST/SDKs</span></a></li><li class="level-2"><a class="final" href="/datacollection/eventmodel/"><span>Events Modeling</span></a></li><li class="level-2"><a class="final" href="/datacollection/webhooks/"><span>Unifying Multichannel Data with Webhooks</span></a></li><li class="level-2"><a class="final" href="/datacollection/channel/"><span>Channel</span></a></li><li class="level-2"><a class="final" href="/datacollection/batchimport/"><span>Importing Data in Batch</span></a></li><li class="level-2"><a class="final" href="/datacollection/analytics/"><span>Using Analytics Tools</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Choosing an Algorithm(s)</span></a><ul><li class="level-2"><a cl
ass="final" href="/algorithm/"><span>Built-in Algorithm Libraries</span></a></li><li class="level-2"><a class="final" href="/algorithm/switch/"><span>Switching to Another Algorithm</span></a></li><li class="level-2"><a class="final" href="/algorithm/multiple/"><span>Combining Multiple Algorithms</span></a></li><li class="level-2"><a class="final" href="/algorithm/custom/"><span>Adding Your Own Algorithms</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>ML Tuning and Evaluation</span></a><ul><li class="level-2"><a class="final" href="/evaluation/"><span>Overview</span></a></li><li class="level-2"><a class="final" href="/evaluation/paramtuning/"><span>Hyperparameter Tuning</span></a></li><li class="level-2"><a class="final" href="/evaluation/evaluationdashboard/"><span>Evaluation Dashboard</span></a></li><li class="level-2"><a class="final" href="/evaluation/metricchoose/"><span>Choosing Evaluation Metrics</span></a></li><li class="level-2"><a class="f
inal" href="/evaluation/metricbuild/"><span>Building Evaluation Metrics</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>System Architecture</span></a><ul><li class="level-2"><a class="final" href="/system/"><span>Architecture Overview</span></a></li><li class="level-2"><a class="final" href="/system/anotherdatastore/"><span>Using Another Data Store</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Engine Template Gallery</span></a><ul><li class="level-2"><a class="final" href="http://templates.prediction.io"><span>Browse</span></a></li><li class="level-2"><a class="final active" href="/community/submit-template/"><span>Submit your Engine as a Template</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Demo Tutorials</span></a><ul><li class="level-2"><a class="final" href="/demo/tapster/"><span>Comics Recommendation Demo</span></a></li><li class="level-2"><a class="final" href="/demo/comm
unity/"><span>Community Contributed Demo</span></a></li><li class="level-2"><a class="final" href="/demo/textclassification/"><span>Text Classification Engine Tutorial</span></a></li></ul></li><li class="level-1"><a class="expandible" href="/community/"><span>Getting Involved</span></a><ul><li class="level-2"><a class="final" href="/community/contribute-code/"><span>Contribute Code</span></a></li><li class="level-2"><a class="final" href="/community/contribute-documentation/"><span>Contribute Documentation</span></a></li><li class="level-2"><a class="final" href="/community/contribute-sdk/"><span>Contribute a SDK</span></a></li><li class="level-2"><a class="final" href="/community/contribute-webhook/"><span>Contribute a Webhook</span></a></li><li class="level-2"><a class="final" href="/community/projects/"><span>Community Projects</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Getting Help</span></a><ul><li class="level-2"><a class="final" href="/r
esources/faq/"><span>FAQs</span></a></li><li class="level-2"><a class="final" href="/support/"><span>Community Support</span></a></li><li class="level-2"><a class="final" href="/support/#enterprise-support"><span>Enterprise Support</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Resources</span></a><ul><li class="level-2"><a class="final" href="/resources/intellij/"><span>Developing Engines with IntelliJ IDEA</span></a></li><li class="level-2"><a class="final" href="/resources/upgrade/"><span>Upgrade Instructions</span></a></li><li class="level-2"><a class="final" href="/resources/glossary/"><span>Glossary</span></a></li></ul></li></ul></nav></div><div class="col-md-9 col-sm-12"><div class="content-header hidden-md hidden-lg"><div id="breadcrumbs" class="hidden-sm hidden xs"><ul><li><a href="#">Engine Template Gallery</a><span class="spacer">></span></li><li><span class="last">Submit your Engine as a Template</span></li></ul></div><div id="page-t
itle"><h1>Submitting a Template to Template Gallery</h1></div></div><div id="table-of-content-wrapper"><h5>On this page</h5><aside id="table-of-contents"><ul> <li> <a href="#template-guidelines">Template Guidelines</a> </li> <li> <a href="#how-to-submit">How to submit</a> </li> </ul> </aside><hr/><a id="edit-page-link" href="https://github.com/apache/incubator-predictionio/tree/livedoc/docs/manual/source/community/submit-template.html.md"><img src="/images/icons/edit-pencil-d6c1bb3d.png"/>Edit this page</a></div><div class="content-header hidden-sm hidden-xs"><div id="breadcrumbs" class="hidden-sm hidden xs"><ul><li><a href="#">Engine Template Gallery</a><span class="spacer">></span></li><li><span class="last">Submit your Engine as a Template</span></li></ul></div><div id="page-title"><h1>Submitting a Template to Template Gallery</h1></div></div><div class="content"><h2 id='template-guidelines' class='header-anchors'>Template Guidelines</h2> <ul> <li><p>Please give your template
and GitHub repo a meaningful name (for example, My-MLlibKMeansClustering-Template).</p></li> <li><p>Please tag your repo for each released version. This is required by Template Gallery.</p><p>For example, tag the release with v0.1.0:</p><div class="highlight shell"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1</pre></td><td class="code"><pre><span class="gp">$ </span>git tag -a v0.1.0 -m <span class="s1">'version 0.1.0'</span>
+</pre></td></tr></tbody></table> </div></li> <li><p>For clarity, the engine template directory structure should be:</p><div class="highlight shell"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1
+2
+3
+4
+5
+6
+7
+8</pre></td><td class="code"><pre>data/ <span class="c"># contains sample data or related files</span>
+project/ <span class="c"># contains the necessary sbt files for build (e.g assembly.sbt)</span>
+src/ <span class="c"># template source code</span>
+.gitignore
+README.md
+build.sbt
+engine.json <span class="c"># one or more engine.json</span>
+template.json
+</pre></td></tr></tbody></table> </div></li> <li><p>Try to keep the root directory clean. If you have additional script files or other files, please create new folders for them and provide description.</p></li> <li><p>Include a QuickStart of how to use the engine, including:</p> <ol> <li>Overview description of the template</li> <li>Events and Data required by the template</li> <li>Description of Query and PredictedResult</li> <li>Steps to import sample data</li> <li>Description of the sample data</li> <li>Steps to build, train and deploy the engine</li> <li>Steps to send sample query and expected output</li> </ol></li> <li><p>If you have additional sample data, please also provide description and how to import them in README</p></li> <li><p>If you have multiple engine.json files, please provide description of them in README</p></li> <li><p>It's recommended to follow <a href="http://docs.scala-lang.org/style/">Scala Style Guide</a></p></li> </ul> <h2 id='how-to-submit' class='he
ader-anchors'>How to submit</h2><p>Go to <a href="http://templates.prediction.io/repositories/new">http://templates.prediction.io/repositories/new</a> and follow instructions.</p></div></div></div></div><footer><div class="container"><div class="seperator"></div><div class="row"><div class="col-md-4 col-md-push-8 col-xs-12"><div class="subscription-form-wrapper"><h4>Subscribe to our Newsletter</h4><form class="ajax-form" id="subscribe-form" method="POST" action="https://script.google.com/macros/s/AKfycbwhzeKCQJjQ52eVAqNT_vcklH07OITUO7wzOMDXvK6EGAWgaZgF/exec"><input class="required underlined-input" type="email" placeholder="Your email address" name="subscription_email" id="subscription_email"/><input class="pill-button" value="SUBSCRIBE" type="submit" data-state-normal="SUBSCRIBE" data-state-sucess="SUBSCRIBED!" data-state-loading="SENDING..." onclick="t($('#subscription_email').val());"/><p class="result"></p></form></div></div><div class="col-md-2 col-md-pull-4 col-xs-6 footer-lin
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site
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+ * Bootstrap v3.3.5 (http://getbootstrap.com)
+ * Copyright 2011-2015 Twitter, Inc.
+ * Licensed under MIT (https://github.com/twbs/bootstrap/blob/master/LICENSE)
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<div class="row"><div class="col-md-9 col-sm-11 col-xs-11"><div class="hidden-md hidden-lg" id="mobile-page-heading-wrapper"><p>PredictionIO Docs</p><h4>Setting Engine Parameters</h4></div><h4 class="hidden-sm hidden-xs">PredictionIO Docs</h4></div><div class="col-md-3 col-sm-1 col-xs-1 hidden-md hidden-lg"><img id="left-menu-indicator" src="/images/icons/down-arrow-dfe9f7fe.png"/></div><div class="col-md-3 col-sm-12 col-xs-12 swiftype-wrapper"><div class="swiftype"><form class="search-form"><img class="search-box-toggler hidden-xs hidden-sm" src="/images/icons/search-glass-704bd4ff.png"/><div class="search-box"><img src="/images/icons/search-glass-704bd4ff.png"/><input type="text" id="st-search-input" class="st-search-input" placeholder="Search Doc..."/></div><img class="swiftype-row-hider hidden-md hidden-lg" src="/images/icons/drawer-toggle-active-fcbef12a.png"/></form></div></div><div class="mobile-left-menu-toggler hidden-md hidden-lg"></div></div></div></div><div id="page" cla
ss="container-fluid"><div class="row"><div id="left-menu-wrapper" class="col-md-3"><nav id="nav-main"><ul><li class="level-1"><a class="expandible" href="/"><span>Apache PredictionIO (incubating) Documentation</span></a><ul><li class="level-2"><a class="final" href="/"><span>Welcome to Apache PredictionIO (incubating)</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Getting Started</span></a><ul><li class="level-2"><a class="final" href="/start/"><span>A Quick Intro</span></a></li><li class="level-2"><a class="final" href="/install/"><span>Installing Apache PredictionIO (incubating)</span></a></li><li class="level-2"><a class="final" href="/start/download/"><span>Downloading an Engine Template</span></a></li><li class="level-2"><a class="final" href="/start/deploy/"><span>Deploying Your First Engine</span></a></li><li class="level-2"><a class="final" href="/start/customize/"><span>Customizing the Engine</span></a></li></ul></li><li class="level-1"><a
class="expandible" href="#"><span>Integrating with Your App</span></a><ul><li class="level-2"><a class="final" href="/appintegration/"><span>App Integration Overview</span></a></li><li class="level-2"><a class="expandible" href="/sdk/"><span>List of SDKs</span></a><ul><li class="level-3"><a class="final" href="/sdk/java/"><span>Java & Android SDK</span></a></li><li class="level-3"><a class="final" href="/sdk/php/"><span>PHP SDK</span></a></li><li class="level-3"><a class="final" href="/sdk/python/"><span>Python SDK</span></a></li><li class="level-3"><a class="final" href="/sdk/ruby/"><span>Ruby SDK</span></a></li><li class="level-3"><a class="final" href="/sdk/community/"><span>Community Powered SDKs</span></a></li></ul></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Deploying an Engine</span></a><ul><li class="level-2"><a class="final" href="/deploy/"><span>Deploying as a Web Service</span></a></li><li class="level-2"><a class="final" href="/cli/#engine-com
mands"><span>Engine Command-line Interface</span></a></li><li class="level-2"><a class="final active" href="/deploy/engineparams/"><span>Setting Engine Parameters</span></a></li><li class="level-2"><a class="final" href="/deploy/enginevariants/"><span>Deploying Multiple Engine Variants</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Customizing an Engine</span></a><ul><li class="level-2"><a class="final" href="/customize/"><span>Learning DASE</span></a></li><li class="level-2"><a class="final" href="/customize/dase/"><span>Implement DASE</span></a></li><li class="level-2"><a class="final" href="/customize/troubleshooting/"><span>Troubleshooting Engine Development</span></a></li><li class="level-2"><a class="final" href="/api/current/#package"><span>Engine Scala APIs</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Collecting and Analyzing Data</span></a><ul><li class="level-2"><a class="final" href="/datacollection/"
><span>Event Server Overview</span></a></li><li class="level-2"><a class="final" href="/cli/#event-server-commands"><span>Event Server Command-line Interface</span></a></li><li class="level-2"><a class="final" href="/datacollection/eventapi/"><span>Collecting Data with REST/SDKs</span></a></li><li class="level-2"><a class="final" href="/datacollection/eventmodel/"><span>Events Modeling</span></a></li><li class="level-2"><a class="final" href="/datacollection/webhooks/"><span>Unifying Multichannel Data with Webhooks</span></a></li><li class="level-2"><a class="final" href="/datacollection/channel/"><span>Channel</span></a></li><li class="level-2"><a class="final" href="/datacollection/batchimport/"><span>Importing Data in Batch</span></a></li><li class="level-2"><a class="final" href="/datacollection/analytics/"><span>Using Analytics Tools</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Choosing an Algorithm(s)</span></a><ul><li class="level-2"><a cl
ass="final" href="/algorithm/"><span>Built-in Algorithm Libraries</span></a></li><li class="level-2"><a class="final" href="/algorithm/switch/"><span>Switching to Another Algorithm</span></a></li><li class="level-2"><a class="final" href="/algorithm/multiple/"><span>Combining Multiple Algorithms</span></a></li><li class="level-2"><a class="final" href="/algorithm/custom/"><span>Adding Your Own Algorithms</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>ML Tuning and Evaluation</span></a><ul><li class="level-2"><a class="final" href="/evaluation/"><span>Overview</span></a></li><li class="level-2"><a class="final" href="/evaluation/paramtuning/"><span>Hyperparameter Tuning</span></a></li><li class="level-2"><a class="final" href="/evaluation/evaluationdashboard/"><span>Evaluation Dashboard</span></a></li><li class="level-2"><a class="final" href="/evaluation/metricchoose/"><span>Choosing Evaluation Metrics</span></a></li><li class="level-2"><a class="f
inal" href="/evaluation/metricbuild/"><span>Building Evaluation Metrics</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>System Architecture</span></a><ul><li class="level-2"><a class="final" href="/system/"><span>Architecture Overview</span></a></li><li class="level-2"><a class="final" href="/system/anotherdatastore/"><span>Using Another Data Store</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Engine Template Gallery</span></a><ul><li class="level-2"><a class="final" href="http://templates.prediction.io"><span>Browse</span></a></li><li class="level-2"><a class="final" href="/community/submit-template/"><span>Submit your Engine as a Template</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Demo Tutorials</span></a><ul><li class="level-2"><a class="final" href="/demo/tapster/"><span>Comics Recommendation Demo</span></a></li><li class="level-2"><a class="final" href="/demo/community/"
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<div class="row"><div class="col-md-9 col-sm-11 col-xs-11"><div class="hidden-md hidden-lg" id="mobile-page-heading-wrapper"><p>PredictionIO Docs</p><h4>Deploying Multiple Engine Variants</h4></div><h4 class="hidden-sm hidden-xs">PredictionIO Docs</h4></div><div class="col-md-3 col-sm-1 col-xs-1 hidden-md hidden-lg"><img id="left-menu-indicator" src="/images/icons/down-arrow-dfe9f7fe.png"/></div><div class="col-md-3 col-sm-12 col-xs-12 swiftype-wrapper"><div class="swiftype"><form class="search-form"><img class="search-box-toggler hidden-xs hidden-sm" src="/images/icons/search-glass-704bd4ff.png"/><div class="search-box"><img src="/images/icons/search-glass-704bd4ff.png"/><input type="text" id="st-search-input" class="st-search-input" placeholder="Search Doc..."/></div><img class="swiftype-row-hider hidden-md hidden-lg" src="/images/icons/drawer-toggle-active-fcbef12a.png"/></form></div></div><div class="mobile-left-menu-toggler hidden-md hidden-lg"></div></div></div></div><div id="
page" class="container-fluid"><div class="row"><div id="left-menu-wrapper" class="col-md-3"><nav id="nav-main"><ul><li class="level-1"><a class="expandible" href="/"><span>Apache PredictionIO (incubating) Documentation</span></a><ul><li class="level-2"><a class="final" href="/"><span>Welcome to Apache PredictionIO (incubating)</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Getting Started</span></a><ul><li class="level-2"><a class="final" href="/start/"><span>A Quick Intro</span></a></li><li class="level-2"><a class="final" href="/install/"><span>Installing Apache PredictionIO (incubating)</span></a></li><li class="level-2"><a class="final" href="/start/download/"><span>Downloading an Engine Template</span></a></li><li class="level-2"><a class="final" href="/start/deploy/"><span>Deploying Your First Engine</span></a></li><li class="level-2"><a class="final" href="/start/customize/"><span>Customizing the Engine</span></a></li></ul></li><li class="le
vel-1"><a class="expandible" href="#"><span>Integrating with Your App</span></a><ul><li class="level-2"><a class="final" href="/appintegration/"><span>App Integration Overview</span></a></li><li class="level-2"><a class="expandible" href="/sdk/"><span>List of SDKs</span></a><ul><li class="level-3"><a class="final" href="/sdk/java/"><span>Java & Android SDK</span></a></li><li class="level-3"><a class="final" href="/sdk/php/"><span>PHP SDK</span></a></li><li class="level-3"><a class="final" href="/sdk/python/"><span>Python SDK</span></a></li><li class="level-3"><a class="final" href="/sdk/ruby/"><span>Ruby SDK</span></a></li><li class="level-3"><a class="final" href="/sdk/community/"><span>Community Powered SDKs</span></a></li></ul></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Deploying an Engine</span></a><ul><li class="level-2"><a class="final" href="/deploy/"><span>Deploying as a Web Service</span></a></li><li class="level-2"><a class="final" href="/cli/#e
ngine-commands"><span>Engine Command-line Interface</span></a></li><li class="level-2"><a class="final" href="/deploy/engineparams/"><span>Setting Engine Parameters</span></a></li><li class="level-2"><a class="final active" href="/deploy/enginevariants/"><span>Deploying Multiple Engine Variants</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Customizing an Engine</span></a><ul><li class="level-2"><a class="final" href="/customize/"><span>Learning DASE</span></a></li><li class="level-2"><a class="final" href="/customize/dase/"><span>Implement DASE</span></a></li><li class="level-2"><a class="final" href="/customize/troubleshooting/"><span>Troubleshooting Engine Development</span></a></li><li class="level-2"><a class="final" href="/api/current/#package"><span>Engine Scala APIs</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Collecting and Analyzing Data</span></a><ul><li class="level-2"><a class="final" href="/datacol
lection/"><span>Event Server Overview</span></a></li><li class="level-2"><a class="final" href="/cli/#event-server-commands"><span>Event Server Command-line Interface</span></a></li><li class="level-2"><a class="final" href="/datacollection/eventapi/"><span>Collecting Data with REST/SDKs</span></a></li><li class="level-2"><a class="final" href="/datacollection/eventmodel/"><span>Events Modeling</span></a></li><li class="level-2"><a class="final" href="/datacollection/webhooks/"><span>Unifying Multichannel Data with Webhooks</span></a></li><li class="level-2"><a class="final" href="/datacollection/channel/"><span>Channel</span></a></li><li class="level-2"><a class="final" href="/datacollection/batchimport/"><span>Importing Data in Batch</span></a></li><li class="level-2"><a class="final" href="/datacollection/analytics/"><span>Using Analytics Tools</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Choosing an Algorithm(s)</span></a><ul><li class="level
-2"><a class="final" href="/algorithm/"><span>Built-in Algorithm Libraries</span></a></li><li class="level-2"><a class="final" href="/algorithm/switch/"><span>Switching to Another Algorithm</span></a></li><li class="level-2"><a class="final" href="/algorithm/multiple/"><span>Combining Multiple Algorithms</span></a></li><li class="level-2"><a class="final" href="/algorithm/custom/"><span>Adding Your Own Algorithms</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>ML Tuning and Evaluation</span></a><ul><li class="level-2"><a class="final" href="/evaluation/"><span>Overview</span></a></li><li class="level-2"><a class="final" href="/evaluation/paramtuning/"><span>Hyperparameter Tuning</span></a></li><li class="level-2"><a class="final" href="/evaluation/evaluationdashboard/"><span>Evaluation Dashboard</span></a></li><li class="level-2"><a class="final" href="/evaluation/metricchoose/"><span>Choosing Evaluation Metrics</span></a></li><li class="level-2"><a
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<div class="row"><div class="col-md-9 col-sm-11 col-xs-11"><div class="hidden-md hidden-lg" id="mobile-page-heading-wrapper"><p>PredictionIO Docs</p><h4>Deploying as a Web Service</h4></div><h4 class="hidden-sm hidden-xs">PredictionIO Docs</h4></div><div class="col-md-3 col-sm-1 col-xs-1 hidden-md hidden-lg"><img id="left-menu-indicator" src="/images/icons/down-arrow-dfe9f7fe.png"/></div><div class="col-md-3 col-sm-12 col-xs-12 swiftype-wrapper"><div class="swiftype"><form class="search-form"><img class="search-box-toggler hidden-xs hidden-sm" src="/images/icons/search-glass-704bd4ff.png"/><div class="search-box"><img src="/images/icons/search-glass-704bd4ff.png"/><input type="text" id="st-search-input" class="st-search-input" placeholder="Search Doc..."/></div><img class="swiftype-row-hider hidden-md hidden-lg" src="/images/icons/drawer-toggle-active-fcbef12a.png"/></form></div></div><div class="mobile-left-menu-toggler hidden-md hidden-lg"></div></div></div></div><div id="page" cl
ass="container-fluid"><div class="row"><div id="left-menu-wrapper" class="col-md-3"><nav id="nav-main"><ul><li class="level-1"><a class="expandible" href="/"><span>Apache PredictionIO (incubating) Documentation</span></a><ul><li class="level-2"><a class="final" href="/"><span>Welcome to Apache PredictionIO (incubating)</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Getting Started</span></a><ul><li class="level-2"><a class="final" href="/start/"><span>A Quick Intro</span></a></li><li class="level-2"><a class="final" href="/install/"><span>Installing Apache PredictionIO (incubating)</span></a></li><li class="level-2"><a class="final" href="/start/download/"><span>Downloading an Engine Template</span></a></li><li class="level-2"><a class="final" href="/start/deploy/"><span>Deploying Your First Engine</span></a></li><li class="level-2"><a class="final" href="/start/customize/"><span>Customizing the Engine</span></a></li></ul></li><li class="level-1"><
a class="expandible" href="#"><span>Integrating with Your App</span></a><ul><li class="level-2"><a class="final" href="/appintegration/"><span>App Integration Overview</span></a></li><li class="level-2"><a class="expandible" href="/sdk/"><span>List of SDKs</span></a><ul><li class="level-3"><a class="final" href="/sdk/java/"><span>Java & Android SDK</span></a></li><li class="level-3"><a class="final" href="/sdk/php/"><span>PHP SDK</span></a></li><li class="level-3"><a class="final" href="/sdk/python/"><span>Python SDK</span></a></li><li class="level-3"><a class="final" href="/sdk/ruby/"><span>Ruby SDK</span></a></li><li class="level-3"><a class="final" href="/sdk/community/"><span>Community Powered SDKs</span></a></li></ul></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Deploying an Engine</span></a><ul><li class="level-2"><a class="final active" href="/deploy/"><span>Deploying as a Web Service</span></a></li><li class="level-2"><a class="final" href="/cli/#en
gine-commands"><span>Engine Command-line Interface</span></a></li><li class="level-2"><a class="final" href="/deploy/engineparams/"><span>Setting Engine Parameters</span></a></li><li class="level-2"><a class="final" href="/deploy/enginevariants/"><span>Deploying Multiple Engine Variants</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Customizing an Engine</span></a><ul><li class="level-2"><a class="final" href="/customize/"><span>Learning DASE</span></a></li><li class="level-2"><a class="final" href="/customize/dase/"><span>Implement DASE</span></a></li><li class="level-2"><a class="final" href="/customize/troubleshooting/"><span>Troubleshooting Engine Development</span></a></li><li class="level-2"><a class="final" href="/api/current/#package"><span>Engine Scala APIs</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Collecting and Analyzing Data</span></a><ul><li class="level-2"><a class="final" href="/datacollection/
"><span>Event Server Overview</span></a></li><li class="level-2"><a class="final" href="/cli/#event-server-commands"><span>Event Server Command-line Interface</span></a></li><li class="level-2"><a class="final" href="/datacollection/eventapi/"><span>Collecting Data with REST/SDKs</span></a></li><li class="level-2"><a class="final" href="/datacollection/eventmodel/"><span>Events Modeling</span></a></li><li class="level-2"><a class="final" href="/datacollection/webhooks/"><span>Unifying Multichannel Data with Webhooks</span></a></li><li class="level-2"><a class="final" href="/datacollection/channel/"><span>Channel</span></a></li><li class="level-2"><a class="final" href="/datacollection/batchimport/"><span>Importing Data in Batch</span></a></li><li class="level-2"><a class="final" href="/datacollection/analytics/"><span>Using Analytics Tools</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Choosing an Algorithm(s)</span></a><ul><li class="level-2"><a c
lass="final" href="/algorithm/"><span>Built-in Algorithm Libraries</span></a></li><li class="level-2"><a class="final" href="/algorithm/switch/"><span>Switching to Another Algorithm</span></a></li><li class="level-2"><a class="final" href="/algorithm/multiple/"><span>Combining Multiple Algorithms</span></a></li><li class="level-2"><a class="final" href="/algorithm/custom/"><span>Adding Your Own Algorithms</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>ML Tuning and Evaluation</span></a><ul><li class="level-2"><a class="final" href="/evaluation/"><span>Overview</span></a></li><li class="level-2"><a class="final" href="/evaluation/paramtuning/"><span>Hyperparameter Tuning</span></a></li><li class="level-2"><a class="final" href="/evaluation/evaluationdashboard/"><span>Evaluation Dashboard</span></a></li><li class="level-2"><a class="final" href="/evaluation/metricchoose/"><span>Choosing Evaluation Metrics</span></a></li><li class="level-2"><a class="
final" href="/evaluation/metricbuild/"><span>Building Evaluation Metrics</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>System Architecture</span></a><ul><li class="level-2"><a class="final" href="/system/"><span>Architecture Overview</span></a></li><li class="level-2"><a class="final" href="/system/anotherdatastore/"><span>Using Another Data Store</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Engine Template Gallery</span></a><ul><li class="level-2"><a class="final" href="http://templates.prediction.io"><span>Browse</span></a></li><li class="level-2"><a class="final" href="/community/submit-template/"><span>Submit your Engine as a Template</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Demo Tutorials</span></a><ul><li class="level-2"><a class="final" href="/demo/tapster/"><span>Comics Recommendation Demo</span></a></li><li class="level-2"><a class="final" href="/demo/community/
"><span>Community Contributed Demo</span></a></li><li class="level-2"><a class="final" href="/demo/textclassification/"><span>Text Classification Engine Tutorial</span></a></li></ul></li><li class="level-1"><a class="expandible" href="/community/"><span>Getting Involved</span></a><ul><li class="level-2"><a class="final" href="/community/contribute-code/"><span>Contribute Code</span></a></li><li class="level-2"><a class="final" href="/community/contribute-documentation/"><span>Contribute Documentation</span></a></li><li class="level-2"><a class="final" href="/community/contribute-sdk/"><span>Contribute a SDK</span></a></li><li class="level-2"><a class="final" href="/community/contribute-webhook/"><span>Contribute a Webhook</span></a></li><li class="level-2"><a class="final" href="/community/projects/"><span>Community Projects</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Getting Help</span></a><ul><li class="level-2"><a class="final" href="/resourc
es/faq/"><span>FAQs</span></a></li><li class="level-2"><a class="final" href="/support/"><span>Community Support</span></a></li><li class="level-2"><a class="final" href="/support/#enterprise-support"><span>Enterprise Support</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Resources</span></a><ul><li class="level-2"><a class="final" href="/resources/intellij/"><span>Developing Engines with IntelliJ IDEA</span></a></li><li class="level-2"><a class="final" href="/resources/upgrade/"><span>Upgrade Instructions</span></a></li><li class="level-2"><a class="final" href="/resources/glossary/"><span>Glossary</span></a></li></ul></li></ul></nav></div><div class="col-md-9 col-sm-12"><div class="content-header hidden-md hidden-lg"><div id="breadcrumbs" class="hidden-sm hidden xs"><ul><li><a href="#">Deploying an Engine</a><span class="spacer">></span></li><li><span class="last">Deploying as a Web Service</span></li></ul></div><div id="page-title"><h1>Deploy
ing an Engine</h1></div></div><div id="table-of-content-wrapper"><h5>On this page</h5><aside id="table-of-contents"><ul> <li> <a href="#deploying-an-engine-the-first-time">Deploying an Engine the First Time</a> </li> <li> <a href="#update-model-with-new-data">Update Model with New Data</a> </li> <li> <a href="#specify-a-different-engine-port">Specify a Different Engine Port</a> </li> <li> <a href="#retrain-and-deploy-script">Retrain and Deploy Script</a> </li> </ul> </aside><hr/><a id="edit-page-link" href="https://github.com/apache/incubator-predictionio/tree/livedoc/docs/manual/source/deploy/index.html.md"><img src="/images/icons/edit-pencil-d6c1bb3d.png"/>Edit this page</a></div><div class="content-header hidden-sm hidden-xs"><div id="breadcrumbs" class="hidden-sm hidden xs"><ul><li><a href="#">Deploying an Engine</a><span class="spacer">></span></li><li><span class="last">Deploying as a Web Service</span></li></ul></div><div id="page-title"><h1>Deploying an Engine</h1></div><
/div><div class="content"><p>An engine must be <strong>built</strong> (i.e. <code>pio build</code>) and <strong>trained</strong> (i.e. <code>pio train</code>) before it can be deployed as a web service.</p><div class="alert-message warning"><p>The engine server is not protected by authentication, and the instructions below assume deployment in a trusted environment.</p></div><h2 id='deploying-an-engine-the-first-time' class='header-anchors'>Deploying an Engine the First Time</h2><p>After you have <a href="/start/download/">downloaded an Engine Template</a>, you can deploy it with these steps:</p> <ol> <li>Run <code>pio app new **your-app-name-here**</code> and specify the <code>appName</code> used in the template's <em>engine.json</em> file (you can set it there to your preference).</li> <li>Run <code>pio build</code> to update the engine</li> <li>Run <code>pio train</code> to train a predictive model with training data</li> <li>Run <code>pio deploy</code> to deploy the engine a
s a service</li> </ol> <p>A deployed engine listens to port 8000 by default. Your application can <a href="/appintegration/">send query to retrieve prediction</a> in real-time through the REST interface.</p><p><strong>Note</strong>: a new engine deployed as above will have no data to start with. Your engine may come with a <code>data/</code> directory with some sample data that you can import, not all have this. Check the quickstart instructions for your template.</p><h2 id='update-model-with-new-data' class='header-anchors'>Update Model with New Data</h2><p>You probably want to update the trained predictive model with newly collected data regularly. To do so, run the <code>pio train</code> and <code>pio deploy</code> commands again:</p><div class="highlight shell"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1
+2</pre></td><td class="code"><pre><span class="gp">$ </span>pio train
+<span class="gp">$ </span>pio deploy
+</pre></td></tr></tbody></table> </div> <p>For example, if you want to re-train the model every day, you may add this to your <em>crontab</em>:</p><div class="highlight shell"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1</pre></td><td class="code"><pre>0 0 <span class="k">*</span> <span class="k">*</span> <span class="k">*</span> <span class="nv">$PIO_HOME</span>/bin/pio train; <span class="nv">$PIO_HOME</span>/bin/pio deploy
+</pre></td></tr></tbody></table> </div> <p>where <em>$PIO_HOME</em> is the installation path of PredictionIO. See <a href="#retrain-and-deploy-script">Retrain and Deploy Script</a> below for a script ready for customization.</p><h2 id='specify-a-different-engine-port' class='header-anchors'>Specify a Different Engine Port</h2><p>By default, <code>pio deploy</code> deploys an engine on <strong>port 8000</strong>.</p><p>You can specify another port with an <em>--port</em> argument. For example, to deploy on port 8123</p><div class="highlight shell"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1</pre></td><td class="code"><pre>pio deploy --port 8123
+</pre></td></tr></tbody></table> </div> <p>You can also specify the binding IP with <em>--ip</em>, which is set to <em>localhost</em> if not specified. For example:</p><div class="highlight shell"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1</pre></td><td class="code"><pre>pio deploy --port 8123 --ip 1.2.3.4
+</pre></td></tr></tbody></table> </div> <h2 id='retrain-and-deploy-script' class='header-anchors'>Retrain and Deploy Script</h2><p>A retrain and deploy script is available <a href="https://github.com/apache/incubator-predictionio/tree/develop/examples/redeploy-script">in the <em>examples/redeploy-script</em> directory</a>.</p><p>To use the script, copy <em>local.sh.template</em> as <em>local.sh</em>, <em>redeploy.sh</em> as (say) <em>MyEngine_Redeploy_(production).sh</em> (Name of the script will appear as title of email) and put both files under the <em>scripts/</em> directory of your engine. Then, modify the settings inside both file, filling in details like <code>PIO_HOME</code>, <code>LOG_DIR</code>, <code>TARGET_EMAIL</code>, <code>ENGINE_JSON</code> and others. You need to do <code>pio build</code> once before using this script. This script only trains and deploys. If <code>pio train</code> or <code>pio deploy</code> fails for some reason, the running engine stays put in most
cases. If engine is retrained and deployed successfully, the email sent will have <em>Normal</em> in the title so you can set filtering rules.</p><p><code>mailutils</code> is used in this script. For Ubuntu, you can do <code>sudo update-alternatives --config mailx</code> and see if <code>/usr/bin/mail.mailutils</code> is selected. If you are using a server that blocks email, you will need to use services like SendGrid.</p><p>This script does not guarantee no down time since at some point during <code>pio deploy</code> the original engine is shut down. The down time is usually not more than a few seconds though it can be more.</p><p>The last thing to do is to add this to your <em>crontab</em>:</p><div class="highlight shell"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1</pre></td><td class="code"><pre>0 0 <span class="k">*</span> <span class="k">*</span> <span class="k">*</span> /path/to/script >/dev/null 2>/
dev/null <span class="c"># mute both stdout and stderr to supress email sent from cron</span>
+</pre></td></tr></tbody></table> </div> </div></div></div></div><footer><div class="container"><div class="seperator"></div><div class="row"><div class="col-md-4 col-md-push-8 col-xs-12"><div class="subscription-form-wrapper"><h4>Subscribe to our Newsletter</h4><form class="ajax-form" id="subscribe-form" method="POST" action="https://script.google.com/macros/s/AKfycbwhzeKCQJjQ52eVAqNT_vcklH07OITUO7wzOMDXvK6EGAWgaZgF/exec"><input class="required underlined-input" type="email" placeholder="Your email address" name="subscription_email" id="subscription_email"/><input class="pill-button" value="SUBSCRIBE" type="submit" data-state-normal="SUBSCRIBE" data-state-sucess="SUBSCRIBED!" data-state-loading="SENDING..." onclick="t($('#subscription_email').val());"/><p class="result"></p></form></div></div><div class="col-md-2 col-md-pull-4 col-xs-6 footer-link-column"><div class="footer-link-column-row"><h4>Community</h4><ul><li><a href="//docs.prediction.io/install/" target="blank">Download</a>
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<div class="row"><div class="col-md-9 col-sm-11 col-xs-11"><div class="hidden-md hidden-lg" id="mobile-page-heading-wrapper"><p>PredictionIO Docs</p><h4>Command Line</h4></div><h4 class="hidden-sm hidden-xs">PredictionIO Docs</h4></div><div class="col-md-3 col-sm-1 col-xs-1 hidden-md hidden-lg"><img id="left-menu-indicator" src="/images/icons/down-arrow-dfe9f7fe.png"/></div><div class="col-md-3 col-sm-12 col-xs-12 swiftype-wrapper"><div class="swiftype"><form class="search-form"><img class="search-box-toggler hidden-xs hidden-sm" src="/images/icons/search-glass-704bd4ff.png"/><div class="search-box"><img src="/images/icons/search-glass-704bd4ff.png"/><input type="text" id="st-search-input" class="st-search-input" placeholder="Search Doc..."/></div><img class="swiftype-row-hider hidden-md hidden-lg" src="/images/icons/drawer-toggle-active-fcbef12a.png"/></form></div></div><div class="mobile-left-menu-toggler hidden-md hidden-lg"></div></div></div></div><div id="page" class="container
-fluid"><div class="row"><div id="left-menu-wrapper" class="col-md-3"><nav id="nav-main"><ul><li class="level-1"><a class="expandible" href="/"><span>Apache PredictionIO (incubating) Documentation</span></a><ul><li class="level-2"><a class="final" href="/"><span>Welcome to Apache PredictionIO (incubating)</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Getting Started</span></a><ul><li class="level-2"><a class="final" href="/start/"><span>A Quick Intro</span></a></li><li class="level-2"><a class="final" href="/install/"><span>Installing Apache PredictionIO (incubating)</span></a></li><li class="level-2"><a class="final" href="/start/download/"><span>Downloading an Engine Template</span></a></li><li class="level-2"><a class="final" href="/start/deploy/"><span>Deploying Your First Engine</span></a></li><li class="level-2"><a class="final" href="/start/customize/"><span>Customizing the Engine</span></a></li></ul></li><li class="level-1"><a class="expan
dible" href="#"><span>Integrating with Your App</span></a><ul><li class="level-2"><a class="final" href="/appintegration/"><span>App Integration Overview</span></a></li><li class="level-2"><a class="expandible" href="/sdk/"><span>List of SDKs</span></a><ul><li class="level-3"><a class="final" href="/sdk/java/"><span>Java & Android SDK</span></a></li><li class="level-3"><a class="final" href="/sdk/php/"><span>PHP SDK</span></a></li><li class="level-3"><a class="final" href="/sdk/python/"><span>Python SDK</span></a></li><li class="level-3"><a class="final" href="/sdk/ruby/"><span>Ruby SDK</span></a></li><li class="level-3"><a class="final" href="/sdk/community/"><span>Community Powered SDKs</span></a></li></ul></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Deploying an Engine</span></a><ul><li class="level-2"><a class="final" href="/deploy/"><span>Deploying as a Web Service</span></a></li><li class="level-2"><a class="final" href="/cli/#engine-commands"><span>
Engine Command-line Interface</span></a></li><li class="level-2"><a class="final" href="/deploy/engineparams/"><span>Setting Engine Parameters</span></a></li><li class="level-2"><a class="final" href="/deploy/enginevariants/"><span>Deploying Multiple Engine Variants</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Customizing an Engine</span></a><ul><li class="level-2"><a class="final" href="/customize/"><span>Learning DASE</span></a></li><li class="level-2"><a class="final" href="/customize/dase/"><span>Implement DASE</span></a></li><li class="level-2"><a class="final" href="/customize/troubleshooting/"><span>Troubleshooting Engine Development</span></a></li><li class="level-2"><a class="final" href="/api/current/#package"><span>Engine Scala APIs</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Collecting and Analyzing Data</span></a><ul><li class="level-2"><a class="final" href="/datacollection/"><span>Event Server
Overview</span></a></li><li class="level-2"><a class="final" href="/cli/#event-server-commands"><span>Event Server Command-line Interface</span></a></li><li class="level-2"><a class="final" href="/datacollection/eventapi/"><span>Collecting Data with REST/SDKs</span></a></li><li class="level-2"><a class="final" href="/datacollection/eventmodel/"><span>Events Modeling</span></a></li><li class="level-2"><a class="final" href="/datacollection/webhooks/"><span>Unifying Multichannel Data with Webhooks</span></a></li><li class="level-2"><a class="final" href="/datacollection/channel/"><span>Channel</span></a></li><li class="level-2"><a class="final" href="/datacollection/batchimport/"><span>Importing Data in Batch</span></a></li><li class="level-2"><a class="final" href="/datacollection/analytics/"><span>Using Analytics Tools</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Choosing an Algorithm(s)</span></a><ul><li class="level-2"><a class="final" href="/a
lgorithm/"><span>Built-in Algorithm Libraries</span></a></li><li class="level-2"><a class="final" href="/algorithm/switch/"><span>Switching to Another Algorithm</span></a></li><li class="level-2"><a class="final" href="/algorithm/multiple/"><span>Combining Multiple Algorithms</span></a></li><li class="level-2"><a class="final" href="/algorithm/custom/"><span>Adding Your Own Algorithms</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>ML Tuning and Evaluation</span></a><ul><li class="level-2"><a class="final" href="/evaluation/"><span>Overview</span></a></li><li class="level-2"><a class="final" href="/evaluation/paramtuning/"><span>Hyperparameter Tuning</span></a></li><li class="level-2"><a class="final" href="/evaluation/evaluationdashboard/"><span>Evaluation Dashboard</span></a></li><li class="level-2"><a class="final" href="/evaluation/metricchoose/"><span>Choosing Evaluation Metrics</span></a></li><li class="level-2"><a class="final" href="/evaluat
ion/metricbuild/"><span>Building Evaluation Metrics</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>System Architecture</span></a><ul><li class="level-2"><a class="final" href="/system/"><span>Architecture Overview</span></a></li><li class="level-2"><a class="final" href="/system/anotherdatastore/"><span>Using Another Data Store</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Engine Template Gallery</span></a><ul><li class="level-2"><a class="final" href="http://templates.prediction.io"><span>Browse</span></a></li><li class="level-2"><a class="final" href="/community/submit-template/"><span>Submit your Engine as a Template</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Demo Tutorials</span></a><ul><li class="level-2"><a class="final" href="/demo/tapster/"><span>Comics Recommendation Demo</span></a></li><li class="level-2"><a class="final" href="/demo/community/"><span>Community Con
tributed Demo</span></a></li><li class="level-2"><a class="final" href="/demo/textclassification/"><span>Text Classification Engine Tutorial</span></a></li></ul></li><li class="level-1"><a class="expandible" href="/community/"><span>Getting Involved</span></a><ul><li class="level-2"><a class="final" href="/community/contribute-code/"><span>Contribute Code</span></a></li><li class="level-2"><a class="final" href="/community/contribute-documentation/"><span>Contribute Documentation</span></a></li><li class="level-2"><a class="final" href="/community/contribute-sdk/"><span>Contribute a SDK</span></a></li><li class="level-2"><a class="final" href="/community/contribute-webhook/"><span>Contribute a Webhook</span></a></li><li class="level-2"><a class="final" href="/community/projects/"><span>Community Projects</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Getting Help</span></a><ul><li class="level-2"><a class="final" href="/resources/faq/"><span>FAQs</
span></a></li><li class="level-2"><a class="final" href="/support/"><span>Community Support</span></a></li><li class="level-2"><a class="final" href="/support/#enterprise-support"><span>Enterprise Support</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Resources</span></a><ul><li class="level-2"><a class="final" href="/resources/intellij/"><span>Developing Engines with IntelliJ IDEA</span></a></li><li class="level-2"><a class="final" href="/resources/upgrade/"><span>Upgrade Instructions</span></a></li><li class="level-2"><a class="final" href="/resources/glossary/"><span>Glossary</span></a></li></ul></li></ul></nav></div><div class="col-md-9 col-sm-12"><div class="content-header hidden-md hidden-lg"><div id="page-title"><h1>Command Line</h1></div></div><div id="table-of-content-wrapper"><h5>On this page</h5><aside id="table-of-contents"><ul> <li> <a href="#overview">Overview</a> </li> <li> <a href="#general-commands">General Commands</a> </li> <li>
<a href="#event-server-commands">Event Server Commands</a> </li> <li> <a href="#engine-commands">Engine Commands</a> </li> </ul> </aside><hr/><a id="edit-page-link" href="https://github.com/apache/incubator-predictionio/tree/livedoc/docs/manual/source/cli/index.html.md"><img src="/images/icons/edit-pencil-d6c1bb3d.png"/>Edit this page</a></div><div class="content-header hidden-sm hidden-xs"><div id="page-title"><h1>Command Line</h1></div></div><div class="content"><h2 id='overview' class='header-anchors'>Overview</h2><p>Interaction with Apache PredictionIO (incubating) is done through the command line interface. It follows the format of:</p><p><code>pio <command> [options] <args>...</code></p><p>You can run <code>pio help</code> to see a list of all available commands and <code>pio help <command></code> to see details of the command.</p><p>Apache PredictionIO (incubating) commands can be separated into the following three categories.</p><h2 id='general-commands' cl
ass='header-anchors'>General Commands</h2><p><code>pio help</code> Display usage summary. <code>pio help <command></code> to read about a specific subcommand.</p><p><code>pio version</code> Displays the version of the installed PredictionIO.</p><p><code>pio status</code> Displays install path and running status of PredictionIO system and its dependencies.</p><h2 id='event-server-commands' class='header-anchors'>Event Server Commands</h2><p><code>pio eventserver</code> Launch the Event Server.</p><p><code>pio app</code> Manage apps that are used by the Event Server.</p><p><code>pio app data-delete <name></code> deletes all data associated with the app.</p><p><code>pio app delete <name></code> deletes the app and its data.</p><p> <code>--ip <value></code> IP to bind to. Default to localhost.</p><p> <code>--port <value></code> Port to bind to. Default to 7070.</p><p><code>pio accesskey</code> Manage app access keys.</p><h2 id='engine-commands' class='heade
r-anchors'>Engine Commands</h2><p>Engine commands need to be run from the directory that contains the engine project. <code>--debug</code> and <code>--verbose</code> flags will provide debug and third-party informational messages.</p><p><code>pio build</code> Build the engine at the current directory.</p><p><code>pio train</code> Kick off a training using an engine.</p><p><code>pio deploy</code> Deploy an engine as an engine server. If no instance ID is specified, it will deploy the latest instance.</p></div></div></div></div><footer><div class="container"><div class="seperator"></div><div class="row"><div class="col-md-4 col-md-push-8 col-xs-12"><div class="subscription-form-wrapper"><h4>Subscribe to our Newsletter</h4><form class="ajax-form" id="subscribe-form" method="POST" action="https://script.google.com/macros/s/AKfycbwhzeKCQJjQ52eVAqNT_vcklH07OITUO7wzOMDXvK6EGAWgaZgF/exec"><input class="required underlined-input" type="email" placeholder="Your email address" name="subscripti
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<div class="row"><div class="col-md-9 col-sm-11 col-xs-11"><div class="hidden-md hidden-lg" id="mobile-page-heading-wrapper"><p>PredictionIO Docs</p><h4>Contribute Code</h4></div><h4 class="hidden-sm hidden-xs">PredictionIO Docs</h4></div><div class="col-md-3 col-sm-1 col-xs-1 hidden-md hidden-lg"><img id="left-menu-indicator" src="/images/icons/down-arrow-dfe9f7fe.png"/></div><div class="col-md-3 col-sm-12 col-xs-12 swiftype-wrapper"><div class="swiftype"><form class="search-form"><img class="search-box-toggler hidden-xs hidden-sm" src="/images/icons/search-glass-704bd4ff.png"/><div class="search-box"><img src="/images/icons/search-glass-704bd4ff.png"/><input type="text" id="st-search-input" class="st-search-input" placeholder="Search Doc..."/></div><img class="swiftype-row-hider hidden-md hidden-lg" src="/images/icons/drawer-toggle-active-fcbef12a.png"/></form></div></div><div class="mobile-left-menu-toggler hidden-md hidden-lg"></div></div></div></div><div id="page" class="contai
ner-fluid"><div class="row"><div id="left-menu-wrapper" class="col-md-3"><nav id="nav-main"><ul><li class="level-1"><a class="expandible" href="/"><span>Apache PredictionIO (incubating) Documentation</span></a><ul><li class="level-2"><a class="final" href="/"><span>Welcome to Apache PredictionIO (incubating)</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Getting Started</span></a><ul><li class="level-2"><a class="final" href="/start/"><span>A Quick Intro</span></a></li><li class="level-2"><a class="final" href="/install/"><span>Installing Apache PredictionIO (incubating)</span></a></li><li class="level-2"><a class="final" href="/start/download/"><span>Downloading an Engine Template</span></a></li><li class="level-2"><a class="final" href="/start/deploy/"><span>Deploying Your First Engine</span></a></li><li class="level-2"><a class="final" href="/start/customize/"><span>Customizing the Engine</span></a></li></ul></li><li class="level-1"><a class="ex
pandible" href="#"><span>Integrating with Your App</span></a><ul><li class="level-2"><a class="final" href="/appintegration/"><span>App Integration Overview</span></a></li><li class="level-2"><a class="expandible" href="/sdk/"><span>List of SDKs</span></a><ul><li class="level-3"><a class="final" href="/sdk/java/"><span>Java & Android SDK</span></a></li><li class="level-3"><a class="final" href="/sdk/php/"><span>PHP SDK</span></a></li><li class="level-3"><a class="final" href="/sdk/python/"><span>Python SDK</span></a></li><li class="level-3"><a class="final" href="/sdk/ruby/"><span>Ruby SDK</span></a></li><li class="level-3"><a class="final" href="/sdk/community/"><span>Community Powered SDKs</span></a></li></ul></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Deploying an Engine</span></a><ul><li class="level-2"><a class="final" href="/deploy/"><span>Deploying as a Web Service</span></a></li><li class="level-2"><a class="final" href="/cli/#engine-commands"><sp
an>Engine Command-line Interface</span></a></li><li class="level-2"><a class="final" href="/deploy/engineparams/"><span>Setting Engine Parameters</span></a></li><li class="level-2"><a class="final" href="/deploy/enginevariants/"><span>Deploying Multiple Engine Variants</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Customizing an Engine</span></a><ul><li class="level-2"><a class="final" href="/customize/"><span>Learning DASE</span></a></li><li class="level-2"><a class="final" href="/customize/dase/"><span>Implement DASE</span></a></li><li class="level-2"><a class="final" href="/customize/troubleshooting/"><span>Troubleshooting Engine Development</span></a></li><li class="level-2"><a class="final" href="/api/current/#package"><span>Engine Scala APIs</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Collecting and Analyzing Data</span></a><ul><li class="level-2"><a class="final" href="/datacollection/"><span>Event Serv
er Overview</span></a></li><li class="level-2"><a class="final" href="/cli/#event-server-commands"><span>Event Server Command-line Interface</span></a></li><li class="level-2"><a class="final" href="/datacollection/eventapi/"><span>Collecting Data with REST/SDKs</span></a></li><li class="level-2"><a class="final" href="/datacollection/eventmodel/"><span>Events Modeling</span></a></li><li class="level-2"><a class="final" href="/datacollection/webhooks/"><span>Unifying Multichannel Data with Webhooks</span></a></li><li class="level-2"><a class="final" href="/datacollection/channel/"><span>Channel</span></a></li><li class="level-2"><a class="final" href="/datacollection/batchimport/"><span>Importing Data in Batch</span></a></li><li class="level-2"><a class="final" href="/datacollection/analytics/"><span>Using Analytics Tools</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Choosing an Algorithm(s)</span></a><ul><li class="level-2"><a class="final" href=
"/algorithm/"><span>Built-in Algorithm Libraries</span></a></li><li class="level-2"><a class="final" href="/algorithm/switch/"><span>Switching to Another Algorithm</span></a></li><li class="level-2"><a class="final" href="/algorithm/multiple/"><span>Combining Multiple Algorithms</span></a></li><li class="level-2"><a class="final" href="/algorithm/custom/"><span>Adding Your Own Algorithms</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>ML Tuning and Evaluation</span></a><ul><li class="level-2"><a class="final" href="/evaluation/"><span>Overview</span></a></li><li class="level-2"><a class="final" href="/evaluation/paramtuning/"><span>Hyperparameter Tuning</span></a></li><li class="level-2"><a class="final" href="/evaluation/evaluationdashboard/"><span>Evaluation Dashboard</span></a></li><li class="level-2"><a class="final" href="/evaluation/metricchoose/"><span>Choosing Evaluation Metrics</span></a></li><li class="level-2"><a class="final" href="/eval
uation/metricbuild/"><span>Building Evaluation Metrics</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>System Architecture</span></a><ul><li class="level-2"><a class="final" href="/system/"><span>Architecture Overview</span></a></li><li class="level-2"><a class="final" href="/system/anotherdatastore/"><span>Using Another Data Store</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Engine Template Gallery</span></a><ul><li class="level-2"><a class="final" href="http://templates.prediction.io"><span>Browse</span></a></li><li class="level-2"><a class="final" href="/community/submit-template/"><span>Submit your Engine as a Template</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Demo Tutorials</span></a><ul><li class="level-2"><a class="final" href="/demo/tapster/"><span>Comics Recommendation Demo</span></a></li><li class="level-2"><a class="final" href="/demo/community/"><span>Community
Contributed Demo</span></a></li><li class="level-2"><a class="final" href="/demo/textclassification/"><span>Text Classification Engine Tutorial</span></a></li></ul></li><li class="level-1"><a class="expandible" href="/community/"><span>Getting Involved</span></a><ul><li class="level-2"><a class="final active" href="/community/contribute-code/"><span>Contribute Code</span></a></li><li class="level-2"><a class="final" href="/community/contribute-documentation/"><span>Contribute Documentation</span></a></li><li class="level-2"><a class="final" href="/community/contribute-sdk/"><span>Contribute a SDK</span></a></li><li class="level-2"><a class="final" href="/community/contribute-webhook/"><span>Contribute a Webhook</span></a></li><li class="level-2"><a class="final" href="/community/projects/"><span>Community Projects</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Getting Help</span></a><ul><li class="level-2"><a class="final" href="/resources/faq/"><s
pan>FAQs</span></a></li><li class="level-2"><a class="final" href="/support/"><span>Community Support</span></a></li><li class="level-2"><a class="final" href="/support/#enterprise-support"><span>Enterprise Support</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Resources</span></a><ul><li class="level-2"><a class="final" href="/resources/intellij/"><span>Developing Engines with IntelliJ IDEA</span></a></li><li class="level-2"><a class="final" href="/resources/upgrade/"><span>Upgrade Instructions</span></a></li><li class="level-2"><a class="final" href="/resources/glossary/"><span>Glossary</span></a></li></ul></li></ul></nav></div><div class="col-md-9 col-sm-12"><div class="content-header hidden-md hidden-lg"><div id="breadcrumbs" class="hidden-sm hidden xs"><ul><li><a href="/community/">Getting Involved</a><span class="spacer">></span></li><li><span class="last">Contribute Code</span></li></ul></div><div id="page-title"><h1>Contribute Code</h1><
/div></div><div id="table-of-content-wrapper"><h5>On this page</h5><aside id="table-of-contents"><ul> <li> <a href="#areas-in-need-of-help">Areas in Need of Help</a> </li> <li> <a href="#how-to-report-an-issue">How to Report an Issue</a> </li> <li> <a href="#how-to-help-resolve-existing-issues">How to Help Resolve Existing Issues</a> </li> <li> <a href="#how-to-add-propose-a-new-feature">How to Add / Propose a New Feature</a> </li> <li> <a href="#how-to-issue-a-pull-request">How to Issue a Pull Request</a> </li> <li> <a href="#getting-started">Getting Started</a> </li> <li> <a href="#anatomy-of-apache-predictionio-incubating-code-tree">Anatomy of Apache PredictionIO (incubating) Code Tree</a> </li> </ul> </aside><hr/><a id="edit-page-link" href="https://github.com/apache/incubator-predictionio/tree/livedoc/docs/manual/source/community/contribute-code.html.md"><img src="/images/icons/edit-pencil-d6c1bb3d.png"/>Edit this page</a></div><div class="content-header hidden-sm hidden-xs"><d
iv id="breadcrumbs" class="hidden-sm hidden xs"><ul><li><a href="/community/">Getting Involved</a><span class="spacer">></span></li><li><span class="last">Contribute Code</span></li></ul></div><div id="page-title"><h1>Contribute Code</h1></div></div><div class="content"><p>Thank you for your interest in contributing to Apache PredictionIO (incubating). Our mission is to enable developers to build scalable machine learning applications easily. Here is how you can help with the project development. If you have any question regarding development at anytime, please free to <a href="mailto:dev-subscribe@predictionio.incubator.apache.org">subscribe</a> and post to the <a href="mailto:dev-subscribe@predictionio.incubator.apache.org">Development Mailing List</a>.</p><h2 id='areas-in-need-of-help' class='header-anchors'>Areas in Need of Help</h2><p>We accept contributions of all kinds at any time. We are compiling this list to show features that are highly sought after by the community.</
p> <ul> <li>Tests and CI</li> <li>Engine template, tutorials, and samples</li> <li>Client SDKs</li> <li>Building engines in Java (updating the Java controller API)</li> <li>Code clean up and refactoring</li> <li>Code and data pipeline optimization</li> <li>Developer experience (UX) improvement</li> </ul> <h2 id='how-to-report-an-issue' class='header-anchors'>How to Report an Issue</h2><p>If you wish to report an issue you found, you can do so on <a href="https://issues.apache.org/jira/browse/PIO">Apache PredictionIO (incubating) JIRA</a>.</p><h2 id='how-to-help-resolve-existing-issues' class='header-anchors'>How to Help Resolve Existing Issues</h2><p>In general, bug fixes should be done the same way as new features, but critical bug fixes will follow a different path.</p><h2 id='how-to-add-/-propose-a-new-feature' class='header-anchors'>How to Add / Propose a New Feature</h2> <ol> <li>To propose a new feature, simply <a href="mailto:dev-subscribe@predictionio.incubator.apache.org">s
ubscribe</a> and post your proposal to <a href="mailto:dev@predictionio.incubator.apache.org">Apache PredictionIO (incubating) Development Mailing List</a>.</li> <li>Discuss with the community and the core development team on what needs to be done, and lay down concrete plans on deliverables.</li> <li>Once solid plans are made, start creating tickets in the <a href="https://issues.apache.org/jira/browse/PIO">issue tracker</a>.</li> <li>Work side by side with other developers using Apache PredictionIO (incubating) Development Mailing List as primary mode of communication. You never know if someone else has a better idea. ;)</li> </ol> <h2 id='how-to-issue-a-pull-request' class='header-anchors'>How to Issue a Pull Request</h2><p>When you have finished your code, you can <a href="https://help.github.com/articles/creating-a-pull-request/">create a pull request</a> against the <strong>develop</strong> branch.</p> <ul> <li>The title must contain a tag associating with an existing JIRA tic
ket. You must create a ticket so that the infrastructure can correctly track issues across Apache JIRA and GitHub. If your ticket is <code>PIO-789</code>, your title must look something like <code>[PIO-789] Some short description</code>.</li> <li>Please also, in your commit message summary, include the JIRA ticket number similar to above.</li> <li>Make sure the title and description are clear and concise. For more details on writing a good commit message, check out <a href="http://tbaggery.com/2008/04/19/a-note-about-git-commit-messages.html">this guide</a>.</li> <li>If the change is visual, make sure to include a screenshot or GIF.</li> <li>Make sure it is being opened into the right branch.</li> <li>Make sure it has been rebased on top of that branch.</li> </ul> <div class="alert-message note"><p>When it is close to a release, and if there are major development ongoing, a release branch will be forked from the develop branch to stabilize the code for binary release. Please refer t
o the <em>git flow</em> methodology page for more information.</p></div><h2 id='getting-started' class='header-anchors'>Getting Started</h2><p>Apache PredictionIO (incubating) relies heavily on the <a href="http://nvie.com/posts/a-successful-git-branching-model/">git flow methodology</a>. Please make sure you read and understand it before you start your development. By default, cloning Apache PredictionIO (incubating) will put you in the <em>develop</em> branch, which in most cases is where all the latest development go to.</p><div class="alert-message note"><p>For core development, please follow the <a href="http://docs.scala-lang.org/style/">Scala Style Guide</a>.</p></div><h3 id='create-a-fork-of-the-apache-predictionio-(incubating)-repository' class='header-anchors'>Create a Fork of the Apache PredictionIO (incubating) Repository</h3> <ol> <li>Start by creating a GitHub account if you do not already have one.</li> <li>Go to <a href="https://github.com/PredictionIO/PredictionIO">
Apache PredictionIO (incubating)\u2019s GitHub mirror</a> and fork it to your own account.</li> <li>Clone your fork to your local machine.</li> </ol> <p>If you need additional help, please refer to <a href="https://help.github.com/articles/fork-a-repo/">https://help.github.com/articles/fork-a-repo/</a>.</p><h3 id='building-apache-predictionio-(incubating)-from-source' class='header-anchors'>Building Apache PredictionIO (incubating) from Source</h3><p>After the previous section, you should have a copy of Apache PredictionIO (incubating) in your local machine ready to be built.</p> <ol> <li>Make sure you are on the <em>develop</em> branch. You can double check by <code>git status</code> or simply <code>git checkout develop</code>.</li> <li>At the root of the repository, do <code>./make-distribution.sh</code> to build PredictionIO.</li> </ol> <h3 id='setting-up-the-environment' class='header-anchors'>Setting Up the Environment</h3><p>Apache PredictionIO (incubating) relies on 3rd party so
ftware to perform its tasks. To set them up, simply follow this <a href="http://docs.prediction.io/install/install-sourcecode/#installing-dependencies">documentation</a>.</p><h3 id='start-hacking' class='header-anchors'>Start Hacking</h3><p>You should have a Apache PredictionIO (incubating) development environment by now. Happy hacking!</p><h2 id='anatomy-of-apache-predictionio-(incubating)-code-tree' class='header-anchors'>Anatomy of Apache PredictionIO (incubating) Code Tree</h2><p>The following describes each directory\u2019s purpose.</p><h3 id='bin' class='header-anchors'>bin</h3><p>Shell scripts and any relevant components to go into the binary distribution. Utility shell scripts can also be included here.</p><h3 id='conf' class='header-anchors'>conf</h3><p>Configuration files that are used by both a source tree and binary distribution.</p><h3 id='core' class='header-anchors'>core</h3><p>Core Apache PredictionIO (incubating) code that provides the DASE controller API, core data st
ructures, and workflow creation and management code.</p><h3 id='data' class='header-anchors'>data</h3><p>Apache PredictionIO (incubating) Event Server, and backend-agnostic storage layer for event store and metadata store.</p><h3 id='docs' class='header-anchors'>docs</h3><p>Source code for <a href="http://predictionio.incubator.apache.org">http://predictionio.incubator.apache.org</a> site, and any other documentation support files.</p><h3 id='engines' class='header-anchors'>engines</h3><p>Obsolete built-in engines. To be removed.</p><h3 id='examples' class='header-anchors'>examples</h3><p>Complete code examples showing Apache PredictionIO (incubating)'s application.</p><h3 id='sbt' class='header-anchors'>sbt</h3><p>Embedded SBT (Simple Build Tool) launcher.</p><h3 id='templates' class='header-anchors'>templates</h3><p>Starting point of building your custom engine.</p><h3 id='tools' class='header-anchors'>tools</h3><p>Tools for running Apache PredictionIO (incubating). Contains p
rimarily the CLI (command-line interface) and its supporting code, and the experimental evaluation dashboard.</p></div></div></div></div><footer><div class="container"><div class="seperator"></div><div class="row"><div class="col-md-4 col-md-push-8 col-xs-12"><div class="subscription-form-wrapper"><h4>Subscribe to our Newsletter</h4><form class="ajax-form" id="subscribe-form" method="POST" action="https://script.google.com/macros/s/AKfycbwhzeKCQJjQ52eVAqNT_vcklH07OITUO7wzOMDXvK6EGAWgaZgF/exec"><input class="required underlined-input" type="email" placeholder="Your email address" name="subscription_email" id="subscription_email"/><input class="pill-button" value="SUBSCRIBE" type="submit" data-state-normal="SUBSCRIBE" data-state-sucess="SUBSCRIBED!" data-state-loading="SENDING..." onclick="t($('#subscription_email').val());"/><p class="result"></p></form></div></div><div class="col-md-2 col-md-pull-4 col-xs-6 footer-link-column"><div class="footer-link-column-row"><h4>Community</h4><u
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+fbq('track', "PageView");</script><script src="//use.typekit.net/mut4mjx.js"></script><script>try{Typekit.load();}catch(e){}</script></head><body><div id="global"><header><div class="container" id="header-wrapper"><div class="row"><div class="col-sm-12"><div id="logo-wrapper"><span id="drawer-toggle"></span><a href="#"></a><a href="http://prediction.io/"><img alt="PredictionIO" id="logo" src="/images/logos/logo-ee2b9bb3.png"/></a></div><div id="menu-wrapper"><div id="header-nav-options-wrapper"><ul><li><a href="/">Install & Doc</a></li> <li><a href="/support">Support</a></li> </ul></div><div id="pill-wrapper"><a class="pill left" href="//templates.prediction.io/">TEMPLATES</a> <a class="pill right" href="//github.com/PredictionIO/PredictionIO/">OPEN SOURCE</a></div></div><img class="mobile-search-bar-toggler hidden-md hidden-lg" src="/images/icons/search-glass-704bd4ff.png"/></div></div></div></header><div id="search-bar-row-wrapper"><div class="container-fluid" id="search-bar-row">
<div class="row"><div class="col-md-9 col-sm-11 col-xs-11"><div class="hidden-md hidden-lg" id="mobile-page-heading-wrapper"><p>PredictionIO Docs</p><h4>Contribute Documentation</h4></div><h4 class="hidden-sm hidden-xs">PredictionIO Docs</h4></div><div class="col-md-3 col-sm-1 col-xs-1 hidden-md hidden-lg"><img id="left-menu-indicator" src="/images/icons/down-arrow-dfe9f7fe.png"/></div><div class="col-md-3 col-sm-12 col-xs-12 swiftype-wrapper"><div class="swiftype"><form class="search-form"><img class="search-box-toggler hidden-xs hidden-sm" src="/images/icons/search-glass-704bd4ff.png"/><div class="search-box"><img src="/images/icons/search-glass-704bd4ff.png"/><input type="text" id="st-search-input" class="st-search-input" placeholder="Search Doc..."/></div><img class="swiftype-row-hider hidden-md hidden-lg" src="/images/icons/drawer-toggle-active-fcbef12a.png"/></form></div></div><div class="mobile-left-menu-toggler hidden-md hidden-lg"></div></div></div></div><div id="page" clas
s="container-fluid"><div class="row"><div id="left-menu-wrapper" class="col-md-3"><nav id="nav-main"><ul><li class="level-1"><a class="expandible" href="/"><span>Apache PredictionIO (incubating) Documentation</span></a><ul><li class="level-2"><a class="final" href="/"><span>Welcome to Apache PredictionIO (incubating)</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Getting Started</span></a><ul><li class="level-2"><a class="final" href="/start/"><span>A Quick Intro</span></a></li><li class="level-2"><a class="final" href="/install/"><span>Installing Apache PredictionIO (incubating)</span></a></li><li class="level-2"><a class="final" href="/start/download/"><span>Downloading an Engine Template</span></a></li><li class="level-2"><a class="final" href="/start/deploy/"><span>Deploying Your First Engine</span></a></li><li class="level-2"><a class="final" href="/start/customize/"><span>Customizing the Engine</span></a></li></ul></li><li class="level-1"><a
class="expandible" href="#"><span>Integrating with Your App</span></a><ul><li class="level-2"><a class="final" href="/appintegration/"><span>App Integration Overview</span></a></li><li class="level-2"><a class="expandible" href="/sdk/"><span>List of SDKs</span></a><ul><li class="level-3"><a class="final" href="/sdk/java/"><span>Java & Android SDK</span></a></li><li class="level-3"><a class="final" href="/sdk/php/"><span>PHP SDK</span></a></li><li class="level-3"><a class="final" href="/sdk/python/"><span>Python SDK</span></a></li><li class="level-3"><a class="final" href="/sdk/ruby/"><span>Ruby SDK</span></a></li><li class="level-3"><a class="final" href="/sdk/community/"><span>Community Powered SDKs</span></a></li></ul></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Deploying an Engine</span></a><ul><li class="level-2"><a class="final" href="/deploy/"><span>Deploying as a Web Service</span></a></li><li class="level-2"><a class="final" href="/cli/#engine-comm
ands"><span>Engine Command-line Interface</span></a></li><li class="level-2"><a class="final" href="/deploy/engineparams/"><span>Setting Engine Parameters</span></a></li><li class="level-2"><a class="final" href="/deploy/enginevariants/"><span>Deploying Multiple Engine Variants</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Customizing an Engine</span></a><ul><li class="level-2"><a class="final" href="/customize/"><span>Learning DASE</span></a></li><li class="level-2"><a class="final" href="/customize/dase/"><span>Implement DASE</span></a></li><li class="level-2"><a class="final" href="/customize/troubleshooting/"><span>Troubleshooting Engine Development</span></a></li><li class="level-2"><a class="final" href="/api/current/#package"><span>Engine Scala APIs</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Collecting and Analyzing Data</span></a><ul><li class="level-2"><a class="final" href="/datacollection/"><span>E
vent Server Overview</span></a></li><li class="level-2"><a class="final" href="/cli/#event-server-commands"><span>Event Server Command-line Interface</span></a></li><li class="level-2"><a class="final" href="/datacollection/eventapi/"><span>Collecting Data with REST/SDKs</span></a></li><li class="level-2"><a class="final" href="/datacollection/eventmodel/"><span>Events Modeling</span></a></li><li class="level-2"><a class="final" href="/datacollection/webhooks/"><span>Unifying Multichannel Data with Webhooks</span></a></li><li class="level-2"><a class="final" href="/datacollection/channel/"><span>Channel</span></a></li><li class="level-2"><a class="final" href="/datacollection/batchimport/"><span>Importing Data in Batch</span></a></li><li class="level-2"><a class="final" href="/datacollection/analytics/"><span>Using Analytics Tools</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Choosing an Algorithm(s)</span></a><ul><li class="level-2"><a class="fin
al" href="/algorithm/"><span>Built-in Algorithm Libraries</span></a></li><li class="level-2"><a class="final" href="/algorithm/switch/"><span>Switching to Another Algorithm</span></a></li><li class="level-2"><a class="final" href="/algorithm/multiple/"><span>Combining Multiple Algorithms</span></a></li><li class="level-2"><a class="final" href="/algorithm/custom/"><span>Adding Your Own Algorithms</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>ML Tuning and Evaluation</span></a><ul><li class="level-2"><a class="final" href="/evaluation/"><span>Overview</span></a></li><li class="level-2"><a class="final" href="/evaluation/paramtuning/"><span>Hyperparameter Tuning</span></a></li><li class="level-2"><a class="final" href="/evaluation/evaluationdashboard/"><span>Evaluation Dashboard</span></a></li><li class="level-2"><a class="final" href="/evaluation/metricchoose/"><span>Choosing Evaluation Metrics</span></a></li><li class="level-2"><a class="final" hr
ef="/evaluation/metricbuild/"><span>Building Evaluation Metrics</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>System Architecture</span></a><ul><li class="level-2"><a class="final" href="/system/"><span>Architecture Overview</span></a></li><li class="level-2"><a class="final" href="/system/anotherdatastore/"><span>Using Another Data Store</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Engine Template Gallery</span></a><ul><li class="level-2"><a class="final" href="http://templates.prediction.io"><span>Browse</span></a></li><li class="level-2"><a class="final" href="/community/submit-template/"><span>Submit your Engine as a Template</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Demo Tutorials</span></a><ul><li class="level-2"><a class="final" href="/demo/tapster/"><span>Comics Recommendation Demo</span></a></li><li class="level-2"><a class="final" href="/demo/community/"><span>C
ommunity Contributed Demo</span></a></li><li class="level-2"><a class="final" href="/demo/textclassification/"><span>Text Classification Engine Tutorial</span></a></li></ul></li><li class="level-1"><a class="expandible" href="/community/"><span>Getting Involved</span></a><ul><li class="level-2"><a class="final" href="/community/contribute-code/"><span>Contribute Code</span></a></li><li class="level-2"><a class="final active" href="/community/contribute-documentation/"><span>Contribute Documentation</span></a></li><li class="level-2"><a class="final" href="/community/contribute-sdk/"><span>Contribute a SDK</span></a></li><li class="level-2"><a class="final" href="/community/contribute-webhook/"><span>Contribute a Webhook</span></a></li><li class="level-2"><a class="final" href="/community/projects/"><span>Community Projects</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Getting Help</span></a><ul><li class="level-2"><a class="final" href="/resources
/faq/"><span>FAQs</span></a></li><li class="level-2"><a class="final" href="/support/"><span>Community Support</span></a></li><li class="level-2"><a class="final" href="/support/#enterprise-support"><span>Enterprise Support</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Resources</span></a><ul><li class="level-2"><a class="final" href="/resources/intellij/"><span>Developing Engines with IntelliJ IDEA</span></a></li><li class="level-2"><a class="final" href="/resources/upgrade/"><span>Upgrade Instructions</span></a></li><li class="level-2"><a class="final" href="/resources/glossary/"><span>Glossary</span></a></li></ul></li></ul></nav></div><div class="col-md-9 col-sm-12"><div class="content-header hidden-md hidden-lg"><div id="breadcrumbs" class="hidden-sm hidden xs"><ul><li><a href="/community/">Getting Involved</a><span class="spacer">></span></li><li><span class="last">Contribute Documentation</span></li></ul></div><div id="page-title"><h1>Con
tribute Documentation</h1></div></div><div id="table-of-content-wrapper"><h5>On this page</h5><aside id="table-of-contents"><ul> <li> <a href="#how-to-write-documentation">How to Write Documentation</a> </li> <li> <a href="#branching">Branching</a> </li> <li> <a href="#installing-locally">Installing Locally</a> </li> <li> <a href="#starting-the-server">Starting the Server</a> </li> <li> <a href="#building-the-site">Building the Site</a> </li> <li> <a href="#styleguide">Styleguide</a> </li> <li> <a href="#important-files">Important Files</a> </li> <li> <a href="#going-live">Going Live</a> </li> <li> <a href="#checking-the-site">Checking the Site</a> </li> <li> <a href="#license">License</a> </li> </ul> </aside><hr/><a id="edit-page-link" href="https://github.com/apache/incubator-predictionio/tree/livedoc/docs/manual/source/community/contribute-documentation.html.md"><img src="/images/icons/edit-pencil-d6c1bb3d.png"/>Edit this page</a></div><div class="content-header hidden-sm hidden-
xs"><div id="breadcrumbs" class="hidden-sm hidden xs"><ul><li><a href="/community/">Getting Involved</a><span class="spacer">></span></li><li><span class="last">Contribute Documentation</span></li></ul></div><div id="page-title"><h1>Contribute Documentation</h1></div></div><div class="content"><h2 id='how-to-write-documentation' class='header-anchors'>How to Write Documentation</h2><p>You can help improve the Apache PredictionIO (incubating) documentation by submitting tutorials, writing how-tos, fixing errors, and adding missing information. You can edit any page live on <a href="https://github.com/apache/incubator-predictionio">GitHub</a> by clicking the pencil icon on any page or open a <a href="https://help.github.com/articles/creating-a-pull-request/">Pull Request</a>.</p><h2 id='branching' class='header-anchors'>Branching</h2><p>Use the <code>livedoc</code> branch if you want to update the current documentation.</p><p>Use the <code>develop</code> branch if you want to write
documentation for the next release.</p><h2 id='installing-locally' class='header-anchors'>Installing Locally</h2><p>Apache PredictionIO (incubating) documentation uses <a href="http://middlemanapp.com/">Middleman</a> and is hosted on Apache.</p><p><a href="http://rubygems.org/">Gems</a> are managed with <a href="http://bundler.io/">Bundler</a>. Front end code with <a href="http://bower.io/">Bower</a>.</p><p>Requires <a href="https://www.ruby-lang.org/en/">Ruby</a> 2.1 or greater. We recommend <a href="http://rvm.io/">RVM</a> or <a href="https://github.com/sstephenson/rbenv">rbenv</a>.</p><div class="alert-message warning"><p><strong>OS X</strong> users you will need to install <a href="https://developer.apple.com/xcode/downloads/">Xcode Command Line Tools</a> with: <code>$ xcode-select --install</code> first.</p></div><p>You can install everything with the following commands:</p><div class="highlight shell"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="te
xt-align: right"><pre class="lineno">1
+2
+3</pre></td><td class="code"><pre><span class="gp">$ </span><span class="nb">cd </span>docs/manual
+<span class="gp">$ </span>gem install bundler
+<span class="gp">$ </span>bundle install
+</pre></td></tr></tbody></table> </div> <h2 id='starting-the-server' class='header-anchors'>Starting the Server</h2><p>Start the server with:</p><div class="highlight shell"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1</pre></td><td class="code"><pre><span class="gp">$ </span>bundle <span class="nb">exec </span>middleman server
+</pre></td></tr></tbody></table> </div> <p>This will start the local web server at <a href="http://localhost:4567/">localhost:4567</a>.</p><h2 id='building-the-site' class='header-anchors'>Building the Site</h2><p>Build the site with:</p><div class="highlight shell"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1</pre></td><td class="code"><pre><span class="gp">$ </span>bundle <span class="nb">exec </span>middleman build
+</pre></td></tr></tbody></table> </div> <h2 id='styleguide' class='header-anchors'>Styleguide</h2><p>Please follow this styleguide for any documentation contributions.</p><h3 id='text' class='header-anchors'>Text</h3><p>View our <a href="/samples/">Sample Typography</a> page for all posible styles.</p><h3 id='headings' class='header-anchors'>Headings</h3><p>The main heading <code>h1</code> is derived from the title data attribute:</p><div class="highlight shell"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1
+2
+3</pre></td><td class="code"><pre>---
+title: Page Title
+---
+</pre></td></tr></tbody></table> </div> <p>Start other headings with <code>h2</code>. Prefer the <code>## Heading</code> format in Markdown.</p><h3 id='links' class='header-anchors'>Links</h3><p>Internal links:</p> <ul> <li>Should start with / (relative to root).</li> <li>Should end with / (S3 requirement).</li> <li>Should <strong>not</strong> end with .html.</li> </ul> <p>Following these rules helps keep everything consistent and allows our version parser to correctly version links. Middleman is configured for directory indexes. Linking to a file in <code>sources/samples/index.html</code> should be done with <code>[Title](/sample/)</code>.</p><div class="highlight markdown"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1
+2
+3
+4
+5
+6</pre></td><td class="code"><pre><span class="p">[</span><span class="nv">Good</span><span class="p">](</span><span class="sx">/path/to/page/</span><span class="p">)</span>
+
+<span class="p">[</span><span class="nv">Bad</span><span class="p">](</span><span class="sx">../page</span><span class="p">)</span> Not relative to root!
+<span class="p">[</span><span class="nv">Bad</span><span class="p">](</span><span class="sx">page.html</span><span class="p">)</span> Do not use the .html extension!
+<span class="p">[</span><span class="nv">Bad</span><span class="p">](</span><span class="sx">/path/to/page</span><span class="p">)</span> Does not end with a /.
+
+</pre></td></tr></tbody></table> </div> <h3 id='images' class='header-anchors'>Images</h3><p>Images should be exactly 900px wide. <a href="https://chrome.google.com/webstore/detail/window-resizer/kkelicaakdanhinjdeammmilcgefonfh">Chrome Window Resizer</a> is an excellent extension for browser resizing.</p><div class="alert-message warning"><p><strong>OS X</strong> users please <a href="http://www.idownloadblog.com/2014/08/03/how-to-remove-the-shadow-window-screenshots-on-mac-os-x/">Disable Shadows</a> before taking a screenshot.</p></div><p>Images should only show the relevant tab/terminal. Hide any additional toolbars.</p><p>Images will <strong>automatically scale</strong> by default. If you want an image to remain a set size you can use a raw HTML tag like this:</p><div class="highlight shell"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1</pre></td><td class="code"><pre><img <span class="nv">src</span><span cla
ss="o">=</span><span class="s2">"/images/path/to/image.png"</span> <span class="nv">alt</span><span class="o">=</span><span class="s2">"Image"</span> <span class="nv">class</span><span class="o">=</span><span class="s2">"static"</span> />
+</pre></td></tr></tbody></table> </div> <h3 id='code-blocks' class='header-anchors'>Code Blocks</h3><p>Fenced code blocks are created using the <code>```language</code> format.</p><p>A example of each language is available on our <a href="/samples/languages">Language Samples</a> page.</p><h3 id='code-tabs' class='header-anchors'>Code Tabs</h3><p>Code tabs use the following HTML format:</p><div class="highlight html"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1
+2
+3
+4
+5
+6
+7
+8</pre></td><td class="code"><pre><span class="nt"><div</span> <span class="na">class=</span><span class="s">"tabs"</span><span class="nt">></span>
+ <span class="nt"><div</span> <span class="na">data-tab=</span><span class="s">"Tab Title"</span> <span class="na">data-lang=</span><span class="s">"language"</span><span class="nt">></span>
+ Markdown, code blocks, or HTML is OK inside a tab.
+ <span class="nt"></div></span>
+ <span class="nt"><div</span> <span class="na">data-tab=</span><span class="s">"Second Tab"</span> <span class="na">data-lang=</span><span class="s">"optional"</span><span class="nt">></span>
+ ...
+ <span class="nt"></div></span>
+<span class="nt"></div></span>
+</pre></td></tr></tbody></table> </div> <p>You can see an example of this on our <a href="/samples/tabs/">Tab Samples</a> page.</p><h3 id='seo' class='header-anchors'>SEO</h3><p>You can hide a page from the <code>sitemap.xml</code> file by setting the pages <a href="http://middlemanapp.com/basics/frontmatter/">Frontmater</a> like this:</p><div class="highlight markdown"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1
+2
+3
+4</pre></td><td class="code"><pre><span class="nn">---</span>
+<span class="s">title</span><span class="pi">:</span> <span class="s">Secret Page</span>
+<span class="s">hidden</span><span class="pi">:</span> <span class="s">true</span>
+<span class="nn">---</span>
+</pre></td></tr></tbody></table> </div> <h2 id='important-files' class='header-anchors'>Important Files</h2> <table><thead> <tr> <th>Description</th> <th>File</th> </tr> </thead><tbody> <tr> <td>Left side navigation.</td> <td><code>data/nav/main.yml</code></td> </tr> <tr> <td>Main site layout.</td> <td><code>source/layouts/layout.html.slim</code></td> </tr> <tr> <td>Custom Markdown renderer based on <a href="https://github.com/vmg/redcarpet">Redcarpet</a>.</td> <td><code>lib/custom_renderer.rb</code></td> </tr> <tr> <td>Custom TOC helper.</td> <td><code>helpers/table_of_contents_helpers.rb</code></td> </tr> </tbody></table> <h3 id='versions' class='header-anchors'>Versions</h3><p>Various site wide versions are defined in <code>data/versions.yml</code> and embedded with ERB like <code><%= data.versions.pio %></code>.</p><div class="alert-message note"><p>Files must end with a <code>.erb</code> extension to be processed as ERB.</p></div><h2 id='going-live' class='header-anchors'
>Going Live</h2><p>Pushing to the <code>livedoc</code> branch will update <a href="http://predictionio.incubator.apache.org">http://predictionio.incubator.apache.org</a> in about 5 minutes.</p><p>You can check the progress of each build on <a href="https://builds.apache.org/">Apache's Jenkins</a>.</p><div class="highlight shell"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1</pre></td><td class="code"><pre><span class="gp">$ </span>git push origin livedoc
+</pre></td></tr></tbody></table> </div> <h2 id='checking-the-site' class='header-anchors'>Checking the Site</h2><div class="alert-message warning"><p>The check rake task is still in <strong>beta</strong> however it is extremely useful for catching accidental errors.</p></div><div class="highlight shell"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1
+2</pre></td><td class="code"><pre><span class="gp">$ </span>bundle <span class="nb">exec </span>middleman build
+<span class="gp">$ </span>bundle <span class="nb">exec </span>rake check
+</pre></td></tr></tbody></table> </div> <p>The <code>rake check</code> task parses each HTML page in the <code>build</code> folder and checks it for common errors including 404s.</p><h2 id='license' class='header-anchors'>License</h2><p>Documentation is under a <a href="http://creativecommons.org/licenses/by-nc-sa/3.0/">Creative Commons Attribution-NonCommercial-ShareAlike 3.0 License</a>.</p></div></div></div></div><footer><div class="container"><div class="seperator"></div><div class="row"><div class="col-md-4 col-md-push-8 col-xs-12"><div class="subscription-form-wrapper"><h4>Subscribe to our Newsletter</h4><form class="ajax-form" id="subscribe-form" method="POST" action="https://script.google.com/macros/s/AKfycbwhzeKCQJjQ52eVAqNT_vcklH07OITUO7wzOMDXvK6EGAWgaZgF/exec"><input class="required underlined-input" type="email" placeholder="Your email address" name="subscription_email" id="subscription_email"/><input class="pill-button" value="SUBSCRIBE" type="submit" data-state-normal=
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+<!DOCTYPE html><html><head><title>Quick Start - Complementary Purchase Engine Template</title><meta charset="utf-8"/><meta content="IE=edge,chrome=1" http-equiv="X-UA-Compatible"/><meta name="viewport" content="width=device-width, initial-scale=1.0"/><meta class="swiftype" name="title" data-type="string" content="Quick Start - Complementary Purchase Engine Template"/><link rel="canonical" href="https://docs.prediction.io/templates/complementarypurchase/quickstart/"/><link href="/images/favicon/normal-b330020a.png" rel="shortcut icon"/><link href="/images/favicon/apple-c0febcf2.png" rel="apple-touch-icon"/><link href="//fonts.googleapis.com/css?family=Open+Sans:300italic,400italic,600italic,700italic,800italic,400,300,600,700,800" rel="stylesheet"/><link href="//maxcdn.bootstrapcdn.com/font-awesome/4.2.0/css/font-awesome.min.css" rel="stylesheet"/><link href="/stylesheets/application-3598c7d7.css" rel="stylesheet" type="text/css"/><!--[if lt IE 9]><script src="//cdnjs.cloudflare.com/
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+fbq('track', "PageView");</script><script src="//use.typekit.net/mut4mjx.js"></script><script>try{Typekit.load();}catch(e){}</script></head><body><div id="global"><header><div class="container" id="header-wrapper"><div class="row"><div class="col-sm-12"><div id="logo-wrapper"><span id="drawer-toggle"></span><a href="#"></a><a href="http://prediction.io/"><img alt="PredictionIO" id="logo" src="/images/logos/logo-ee2b9bb3.png"/></a></div><div id="menu-wrapper"><div id="header-nav-options-wrapper"><ul><li><a href="/">Install & Doc</a></li> <li><a href="/support">Support</a></li> </ul></div><div id="pill-wrapper"><a class="pill left" href="//templates.prediction.io/">TEMPLATES</a> <a class="pill right" href="//github.com/PredictionIO/PredictionIO/">OPEN SOURCE</a></div></div><img class="mobile-search-bar-toggler hidden-md hidden-lg" src="/images/icons/search-glass-704bd4ff.png"/></div></div></div></header><div id="search-bar-row-wrapper"><div class="container-fluid" id="search-bar-row">
<div class="row"><div class="col-md-9 col-sm-11 col-xs-11"><div class="hidden-md hidden-lg" id="mobile-page-heading-wrapper"><p>PredictionIO Docs</p><h4>Quick Start - Complementary Purchase Engine Template</h4></div><h4 class="hidden-sm hidden-xs">PredictionIO Docs</h4></div><div class="col-md-3 col-sm-1 col-xs-1 hidden-md hidden-lg"><img id="left-menu-indicator" src="/images/icons/down-arrow-dfe9f7fe.png"/></div><div class="col-md-3 col-sm-12 col-xs-12 swiftype-wrapper"><div class="swiftype"><form class="search-form"><img class="search-box-toggler hidden-xs hidden-sm" src="/images/icons/search-glass-704bd4ff.png"/><div class="search-box"><img src="/images/icons/search-glass-704bd4ff.png"/><input type="text" id="st-search-input" class="st-search-input" placeholder="Search Doc..."/></div><img class="swiftype-row-hider hidden-md hidden-lg" src="/images/icons/drawer-toggle-active-fcbef12a.png"/></form></div></div><div class="mobile-left-menu-toggler hidden-md hidden-lg"></div></div></d
iv></div><div id="page" class="container-fluid"><div class="row"><div id="left-menu-wrapper" class="col-md-3"><nav id="nav-main"><ul><li class="level-1"><a class="expandible" href="/"><span>Apache PredictionIO (incubating) Documentation</span></a><ul><li class="level-2"><a class="final" href="/"><span>Welcome to Apache PredictionIO (incubating)</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Getting Started</span></a><ul><li class="level-2"><a class="final" href="/start/"><span>A Quick Intro</span></a></li><li class="level-2"><a class="final" href="/install/"><span>Installing Apache PredictionIO (incubating)</span></a></li><li class="level-2"><a class="final" href="/start/download/"><span>Downloading an Engine Template</span></a></li><li class="level-2"><a class="final" href="/start/deploy/"><span>Deploying Your First Engine</span></a></li><li class="level-2"><a class="final" href="/start/customize/"><span>Customizing the Engine</span></a></li></ul>
</li><li class="level-1"><a class="expandible" href="#"><span>Integrating with Your App</span></a><ul><li class="level-2"><a class="final" href="/appintegration/"><span>App Integration Overview</span></a></li><li class="level-2"><a class="expandible" href="/sdk/"><span>List of SDKs</span></a><ul><li class="level-3"><a class="final" href="/sdk/java/"><span>Java & Android SDK</span></a></li><li class="level-3"><a class="final" href="/sdk/php/"><span>PHP SDK</span></a></li><li class="level-3"><a class="final" href="/sdk/python/"><span>Python SDK</span></a></li><li class="level-3"><a class="final" href="/sdk/ruby/"><span>Ruby SDK</span></a></li><li class="level-3"><a class="final" href="/sdk/community/"><span>Community Powered SDKs</span></a></li></ul></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Deploying an Engine</span></a><ul><li class="level-2"><a class="final" href="/deploy/"><span>Deploying as a Web Service</span></a></li><li class="level-2"><a class="fi
nal" href="/cli/#engine-commands"><span>Engine Command-line Interface</span></a></li><li class="level-2"><a class="final" href="/deploy/engineparams/"><span>Setting Engine Parameters</span></a></li><li class="level-2"><a class="final" href="/deploy/enginevariants/"><span>Deploying Multiple Engine Variants</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Customizing an Engine</span></a><ul><li class="level-2"><a class="final" href="/customize/"><span>Learning DASE</span></a></li><li class="level-2"><a class="final" href="/customize/dase/"><span>Implement DASE</span></a></li><li class="level-2"><a class="final" href="/customize/troubleshooting/"><span>Troubleshooting Engine Development</span></a></li><li class="level-2"><a class="final" href="/api/current/#package"><span>Engine Scala APIs</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Collecting and Analyzing Data</span></a><ul><li class="level-2"><a class="final" hre
f="/datacollection/"><span>Event Server Overview</span></a></li><li class="level-2"><a class="final" href="/cli/#event-server-commands"><span>Event Server Command-line Interface</span></a></li><li class="level-2"><a class="final" href="/datacollection/eventapi/"><span>Collecting Data with REST/SDKs</span></a></li><li class="level-2"><a class="final" href="/datacollection/eventmodel/"><span>Events Modeling</span></a></li><li class="level-2"><a class="final" href="/datacollection/webhooks/"><span>Unifying Multichannel Data with Webhooks</span></a></li><li class="level-2"><a class="final" href="/datacollection/channel/"><span>Channel</span></a></li><li class="level-2"><a class="final" href="/datacollection/batchimport/"><span>Importing Data in Batch</span></a></li><li class="level-2"><a class="final" href="/datacollection/analytics/"><span>Using Analytics Tools</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Choosing an Algorithm(s)</span></a><ul><li c
lass="level-2"><a class="final" href="/algorithm/"><span>Built-in Algorithm Libraries</span></a></li><li class="level-2"><a class="final" href="/algorithm/switch/"><span>Switching to Another Algorithm</span></a></li><li class="level-2"><a class="final" href="/algorithm/multiple/"><span>Combining Multiple Algorithms</span></a></li><li class="level-2"><a class="final" href="/algorithm/custom/"><span>Adding Your Own Algorithms</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>ML Tuning and Evaluation</span></a><ul><li class="level-2"><a class="final" href="/evaluation/"><span>Overview</span></a></li><li class="level-2"><a class="final" href="/evaluation/paramtuning/"><span>Hyperparameter Tuning</span></a></li><li class="level-2"><a class="final" href="/evaluation/evaluationdashboard/"><span>Evaluation Dashboard</span></a></li><li class="level-2"><a class="final" href="/evaluation/metricchoose/"><span>Choosing Evaluation Metrics</span></a></li><li class="
level-2"><a class="final" href="/evaluation/metricbuild/"><span>Building Evaluation Metrics</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>System Architecture</span></a><ul><li class="level-2"><a class="final" href="/system/"><span>Architecture Overview</span></a></li><li class="level-2"><a class="final" href="/system/anotherdatastore/"><span>Using Another Data Store</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Engine Template Gallery</span></a><ul><li class="level-2"><a class="final" href="http://templates.prediction.io"><span>Browse</span></a></li><li class="level-2"><a class="final" href="/community/submit-template/"><span>Submit your Engine as a Template</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Demo Tutorials</span></a><ul><li class="level-2"><a class="final" href="/demo/tapster/"><span>Comics Recommendation Demo</span></a></li><li class="level-2"><a class="final" hre
f="/demo/community/"><span>Community Contributed Demo</span></a></li><li class="level-2"><a class="final" href="/demo/textclassification/"><span>Text Classification Engine Tutorial</span></a></li></ul></li><li class="level-1"><a class="expandible" href="/community/"><span>Getting Involved</span></a><ul><li class="level-2"><a class="final" href="/community/contribute-code/"><span>Contribute Code</span></a></li><li class="level-2"><a class="final" href="/community/contribute-documentation/"><span>Contribute Documentation</span></a></li><li class="level-2"><a class="final" href="/community/contribute-sdk/"><span>Contribute a SDK</span></a></li><li class="level-2"><a class="final" href="/community/contribute-webhook/"><span>Contribute a Webhook</span></a></li><li class="level-2"><a class="final" href="/community/projects/"><span>Community Projects</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Getting Help</span></a><ul><li class="level-2"><a class="fi
nal" href="/resources/faq/"><span>FAQs</span></a></li><li class="level-2"><a class="final" href="/support/"><span>Community Support</span></a></li><li class="level-2"><a class="final" href="/support/#enterprise-support"><span>Enterprise Support</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Resources</span></a><ul><li class="level-2"><a class="final" href="/resources/intellij/"><span>Developing Engines with IntelliJ IDEA</span></a></li><li class="level-2"><a class="final" href="/resources/upgrade/"><span>Upgrade Instructions</span></a></li><li class="level-2"><a class="final" href="/resources/glossary/"><span>Glossary</span></a></li></ul></li></ul></nav></div><div class="col-md-9 col-sm-12"><div class="content-header hidden-md hidden-lg"><div id="page-title"><h1>Quick Start - Complementary Purchase Engine Template</h1></div></div><div id="table-of-content-wrapper"><h5>On this page</h5><aside id="table-of-contents"><ul> <li> <a href="#overview">Over
view</a> </li> <li> <a href="#usage">Usage</a> </li> <li> <a href="#1-install-and-run-predictionio">1. Install and Run PredictionIO</a> </li> <li> <a href="#2-create-a-new-engine-from-an-engine-template">2. Create a new Engine from an Engine Template</a> </li> <li> <a href="#3-generate-an-app-id-and-access-key">3. Generate an App ID and Access Key</a> </li> <li> <a href="#4-collecting-data">4. Collecting Data</a> </li> <li> <a href="#5-deploy-the-engine-as-a-service">5. Deploy the Engine as a Service</a> </li> <li> <a href="#6-use-the-engine">6. Use the Engine</a> </li> </ul> </aside><hr/><a id="edit-page-link" href="https://github.com/apache/incubator-predictionio/tree/livedoc/docs/manual/source/templates/complementarypurchase/quickstart.html.md.erb"><img src="/images/icons/edit-pencil-d6c1bb3d.png"/>Edit this page</a></div><div class="content-header hidden-sm hidden-xs"><div id="page-title"><h1>Quick Start - Complementary Purchase Engine Template</h1></div></div><div class="conten
t"><h2 id='overview' class='header-anchors'>Overview</h2><p>This engine template recommends the complementary items which most user frequently buy at the same time together with one or more items in the query.</p><h2 id='usage' class='header-anchors'>Usage</h2><h3 id='event-data-requirements' class='header-anchors'>Event Data Requirements</h3><p>By default, the template requires the following events to be collected:</p> <ul> <li>user 'buy' item events</li> </ul> <div class="alert-message info"><p>A correct eventTime should be used in order for engine to determine if the items being bought are in the same 'basket'.</p></div><div class="alert-message note"><p>You can customize to use other event.</p></div><h3 id='input-query' class='header-anchors'>Input Query</h3> <ul> <li>set of items</li> <li>num of recommends items per condition</li> </ul> <h3 id='output-predictedresult' class='header-anchors'>Output PredictedResult</h3> <ul> <li>array of condition and top n recomm
ended items given the condition. The engine will use each combination of the query items as condition.</li> </ul> <h2 id='1.-install-and-run-predictionio' class='header-anchors'>1. Install and Run PredictionIO</h2><p>First you need to <a href="/install">install PredictionIO 0.9.6</a> (if you haven't done it).</p><p>Let's say you have installed PredictionIO at <code>/home/yourname/PredictionIO/</code>. For convenience, add PredictionIO's binary command path to your <code>PATH</code>, i.e. <code>/home/yourname/PredictionIO/bin</code>:</p><div class="highlight shell"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1</pre></td><td class="code"><pre><span class="gp">$ </span><span class="nv">PATH</span><span class="o">=</span><span class="nv">$PATH</span>:/home/yourname/PredictionIO/bin; <span class="nb">export </span>PATH
+</pre></td></tr></tbody></table> </div> <div class="alert-message note"><p>If you launched <strong>PredictionIO AWS instance</strong>, the path is located at <code>/opt/PredictionIO/bin</code>.</p></div><p>Once you have completed the installation process, please make sure all the components (PredictionIO Event Server, Elasticsearch, and HBase) are up and running.</p><div class="alert-message note"><p>If you launched <strong>PredictionIO AWS instance</strong>, you can skip <code>pio-start-all</code>. All components should have been started automatically.</p></div><p>If you are using PostgreSQL or MySQL, run the following to start PredictionIO Event Server:</p><div class="highlight shell"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1</pre></td><td class="code"><pre><span class="gp">$ </span>pio eventserver &
+</pre></td></tr></tbody></table> </div> <p>If instead you are running HBase and Elasticsearch, run the following to start all PredictionIO Event Server, HBase, and Elasticsearch:</p><div class="highlight shell"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1</pre></td><td class="code"><pre><span class="gp">$ </span>pio-start-all
+</pre></td></tr></tbody></table> </div> <p>You can check the status by running:</p><div class="highlight shell"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1</pre></td><td class="code"><pre><span class="gp">$ </span>pio status
+</pre></td></tr></tbody></table> </div> <p>If everything is OK, you should see the following outputs:</p><div class="highlight shell"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1
+2
+3
+4</pre></td><td class="code"><pre>...
+
+<span class="o">(</span>sleeping 5 seconds <span class="k">for </span>all messages to show up...<span class="o">)</span>
+Your system is all ready to go.
+</pre></td></tr></tbody></table> </div> <div class="alert-message note"><p>To further troubleshoot, please see <a href="/resources/faq/#using-predictionio">FAQ - Using PredictionIO</a>.</p></div> <p><a href="#"></a></p> <h2 id='2.-create-a-new-engine-from-an-engine-template' class='header-anchors'>2. Create a new Engine from an Engine Template</h2><p>Now let's create a new engine called <em>MyComplementaryPurchase</em> by downloading the Complementary Purchase Engine Template. Go to a directory where you want to put your engine and run the following:</p><div class="highlight shell"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1
+2</pre></td><td class="code"><pre><span class="gp">$ </span>pio template get PredictionIO/template-scala-parallel-complementarypurchase MyComplementaryPurchase
+<span class="gp">$ </span><span class="nb">cd </span>MyComplementaryPurchase
+</pre></td></tr></tbody></table> </div> <p>A new directory <em>MyComplementaryPurchase</em> is created, where you can find the downloaded engine template.</p> <p><a href="#"></a></p> <h2 id='3.-generate-an-app-id-and-access-key' class='header-anchors'>3. Generate an App ID and Access Key</h2><p>You will need to create a new App in PredictionIO to store all the data of your app. The data collected will be used for machine learning modeling.</p><p>Let's assume you want to use this engine in an application named "MyApp1". Run the following to create a new app "MyApp1":</p><div class="highlight shell"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1</pre></td><td class="code"><pre><span class="gp">$ </span>pio app new MyApp1
+</pre></td></tr></tbody></table> </div> <p>You should find the following in the console output:</p><div class="highlight shell"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1
+2
+3
+4
+5
+6</pre></td><td class="code"><pre>...
+<span class="o">[</span>INFO] <span class="o">[</span>App<span class="nv">$]</span> Initialized Event Store <span class="k">for </span>this app ID: 1.
+<span class="o">[</span>INFO] <span class="o">[</span>App<span class="nv">$]</span> Created new app:
+<span class="o">[</span>INFO] <span class="o">[</span>App<span class="nv">$]</span> Name: MyApp1
+<span class="o">[</span>INFO] <span class="o">[</span>App<span class="nv">$]</span> ID: 1
+<span class="o">[</span>INFO] <span class="o">[</span>App<span class="nv">$]</span> Access Key: 3mZWDzci2D5YsqAnqNnXH9SB6Rg3dsTBs8iHkK6X2i54IQsIZI1eEeQQyMfs7b3F
+</pre></td></tr></tbody></table> </div> <p>Note that <em>App ID</em><em>, **Access Key</em>* are created for this App "MyApp1". You will need the <strong>Access Key</strong> when you collect data with EventServer for this App.</p><p>You can list all of the apps created its corresponding ID and Access Key by running the following command:</p><div class="highlight shell"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1</pre></td><td class="code"><pre><span class="gp">$ </span>pio app list
+</pre></td></tr></tbody></table> </div> <p>You should see a list of apps created. For example:</p><div class="highlight shell"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1
+2
+3
+4</pre></td><td class="code"><pre><span class="o">[</span>INFO] <span class="o">[</span>App<span class="nv">$]</span> Name | ID | Access Key | Allowed Event<span class="o">(</span>s<span class="o">)</span>
+<span class="o">[</span>INFO] <span class="o">[</span>App<span class="nv">$]</span> MyApp1 | 1 | 3mZWDzci2D5YsqAnqNnXH9SB6Rg3dsTBs8iHkK6X2i54IQsIZI1eEeQQyMfs7b3F | <span class="o">(</span>all<span class="o">)</span>
+<span class="o">[</span>INFO] <span class="o">[</span>App<span class="nv">$]</span> MyApp2 | 2 | io5lz6Eg4m3Xe4JZTBFE13GMAf1dhFl6ZteuJfrO84XpdOz9wRCrDU44EUaYuXq5 | <span class="o">(</span>all<span class="o">)</span>
+<span class="o">[</span>INFO] <span class="o">[</span>App<span class="nv">$]</span> Finished listing 2 app<span class="o">(</span>s<span class="o">)</span>.
+</pre></td></tr></tbody></table> </div> <p><a href="#"></a></p> <h2 id='4.-collecting-data' class='header-anchors'>4. Collecting Data</h2><p>Next, let's collect training data for this Engine. By default, Complementary Purchase Engine Template supports the following entities: <strong>user</strong>, <strong>item</strong>. A user buys an item. This template requires user-buy-item events.</p><p>Note that the engine requires correct buy event time being used in order to determine if the items being bought are in the same 'basket', which is configured by the 'basketWindow' parameter. Using an unreal event time for the buy events will cause an incorrect model. If you use SDK, the current time is used as event time by default.</p><div class="alert-message warning"><p>In particular, make sure correct event time is specified if you import data in batch (i.e. not in real time). If the event time is omitted, the SDK will use <strong>current time</strong> as event time which
is not the actual time of the buy event in this case!</p></div><p>You can send these events to PredictionIO Event Server in real-time easily by making a HTTP request or through the provided SDK. Please see <a href="/appintegration/">App Integration Overview</a> for more details how to integrate your app with SDK.</p><p>Let's try sending events to EventServer with the following <code>curl</code> commands (The corresponding SDK code is showed in other tabs).</p><p>Replace <code><ACCCESS_KEY></code> by the Access Key generated in above steps. Note that <code>localhost:7070</code> is the default URL of the Event Server.</p><p>For convenience, set your access key to the shell variable, run:</p><p><code>$ ACCESS_KEY=<ACCESS_KEY></code></p> <p><a href="#"></a></p> <p>When an user u0 buys item i0 on time <code>2014-11-02T09:39:45.618-08:00</code> (current time will be used if eventTime is not specified), you can send a buy event. Run the following <code>curl</code> command:<
/p><div class="tabs"> <ul class="control"> <li data-lang="json"><a href="#tab-6447e119-b861-4dd1-9db6-8f74d5417dc5">REST API</a></li> <li data-lang="python"><a href="#tab-314c92ee-5506-4f72-8689-1c1762e67e07">Python SDK</a></li> <li data-lang="php"><a href="#tab-b47cac14-8080-4edb-af39-8f6f16abb152">PHP SDK</a></li> <li data-lang="ruby"><a href="#tab-09c927d6-69a3-49c9-b0cd-b8c2b961a993">Ruby SDK</a></li> <li data-lang="java"><a href="#tab-b47a9271-8b3d-488e-b7ef-2fc33b95e633">Java SDK</a></li> </ul> <div data-tab="REST API" data-lang="json" id="tab-6447e119-b861-4dd1-9db6-8f74d5417dc5"> <div class="highlight shell"> <table style="border-spacing: 0"><tbody><tr> <td class="gutter gl" style="text-align: right"><pre class="lineno">1
+2
+3
+4
+5
+6
+7
+8
+9
+10</pre></td> <td class="code"><pre><span class="gp">$ </span>curl -i -X POST http://localhost:7070/events.json?accessKey<span class="o">=</span><span class="nv">$ACCESS_KEY</span> <span class="se">\</span>
+-H <span class="s2">"Content-Type: application/json"</span> <span class="se">\</span>
+-d <span class="s1">'{
+ "event" : "buy",
+ "entityType" : "user"
+ "entityId" : "u0",
+ "targetEntityType" : "item",
+ "targetEntityId" : "i0",
+ "eventTime" : "2014-11-02T09:39:45.618-08:00"
+}'</span>
+</pre></td> </tr></tbody></table> </div> </div> <div data-tab="Python SDK" data-lang="python" id="tab-314c92ee-5506-4f72-8689-1c1762e67e07"> <div class="highlight python"> <table style="border-spacing: 0"><tbody><tr> <td class="gutter gl" style="text-align: right"><pre class="lineno">1
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+27</pre></td> <td class="code"><pre><span class="kn">import</span> <span class="nn">predictionio</span>
+
+<span class="n">client</span> <span class="o">=</span> <span class="n">predictionio</span><span class="o">.</span><span class="n">EventClient</span><span class="p">(</span>
+ <span class="n">access_key</span><span class="o">=<</span><span class="n">ACCESS</span> <span class="n">KEY</span><span class="o">></span><span class="p">,</span>
+ <span class="n">url</span><span class="o">=<</span><span class="n">URL</span> <span class="n">OF</span> <span class="n">EVENTSERVER</span><span class="o">></span><span class="p">,</span>
+ <span class="n">threads</span><span class="o">=</span><span class="mi">5</span><span class="p">,</span>
+ <span class="n">qsize</span><span class="o">=</span><span class="mi">500</span>
+<span class="p">)</span>
+
+<span class="c"># A user buys an item (use current time as event time)</span>
+<span class="n">client</span><span class="o">.</span><span class="n">create_event</span><span class="p">(</span>
+ <span class="n">event</span><span class="o">=</span><span class="s">"buy"</span><span class="p">,</span>
+ <span class="n">entity_type</span><span class="o">=</span><span class="s">"user"</span><span class="p">,</span>
+ <span class="n">entity_id</span><span class="o">=<</span><span class="n">USER</span> <span class="n">ID</span><span class="o">></span><span class="p">,</span>
+ <span class="n">target_entity_type</span><span class="o">=</span><span class="s">"item"</span><span class="p">,</span>
+ <span class="n">target_entity_id</span><span class="o">=<</span><span class="n">ITEM</span> <span class="n">ID</span><span class="o">></span>
+<span class="p">)</span>
+
+<span class="c"># A user buys an item (explicitly specify event time)</span>
+<span class="n">client</span><span class="o">.</span><span class="n">create_event</span><span class="p">(</span>
+ <span class="n">event</span><span class="o">=</span><span class="s">"buy"</span><span class="p">,</span>
+ <span class="n">entity_type</span><span class="o">=</span><span class="s">"user"</span><span class="p">,</span>
+ <span class="n">entity_id</span><span class="o">=<</span><span class="n">USER</span> <span class="n">ID</span><span class="o">></span><span class="p">,</span>
+ <span class="n">target_entity_type</span><span class="o">=</span><span class="s">"item"</span><span class="p">,</span>
+ <span class="n">target_entity_id</span><span class="o">=<</span><span class="n">ITEM</span> <span class="n">ID</span><span class="o">></span><span class="p">,</span>
+ <span class="n">event_time</span><span class="o">=<</span><span class="n">EVENT_TIME</span><span class="o">></span>
+<span class="p">)</span>
+</pre></td> </tr></tbody></table> </div> </div> <div data-tab="PHP SDK" data-lang="php" id="tab-b47cac14-8080-4edb-af39-8f6f16abb152"> <div class="highlight php"> <table style="border-spacing: 0"><tbody><tr> <td class="gutter gl" style="text-align: right"><pre class="lineno">1
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+26</pre></td> <td class="code"><pre><span class="cp"><?php</span>
+<span class="k">require_once</span><span class="p">(</span><span class="s2">"vendor/autoload.php"</span><span class="p">);</span>
+<span class="k">use</span> <span class="nx">predictionio\EventClient</span><span class="p">;</span>
+
+<span class="nv">$client</span> <span class="o">=</span> <span class="k">new</span> <span class="nx">EventClient</span><span class="p">(</span><span class="o"><</span><span class="nx">ACCESS</span> <span class="nx">KEY</span><span class="o">></span><span class="p">,</span> <span class="o"><</span><span class="nx">URL</span> <span class="nx">OF</span> <span class="nx">EVENTSERVER</span><span class="o">></span><span class="p">);</span>
+
+<span class="c1">// A user buys an item (use current time as event time)
+</span><span class="nv">$client</span><span class="o">-></span><span class="na">createEvent</span><span class="p">(</span><span class="k">array</span><span class="p">(</span>
+ <span class="s1">'event'</span> <span class="o">=></span> <span class="s1">'buy'</span><span class="p">,</span>
+ <span class="s1">'entityType'</span> <span class="o">=></span> <span class="s1">'user'</span><span class="p">,</span>
+ <span class="s1">'entityId'</span> <span class="o">=></span> <span class="o"><</span><span class="nx">USER</span> <span class="nx">ID</span><span class="o">></span><span class="p">,</span>
+ <span class="s1">'targetEntityType'</span> <span class="o">=></span> <span class="s1">'item'</span><span class="p">,</span>
+ <span class="s1">'targetEntityId'</span> <span class="o">=></span> <span class="o"><</span><span class="nx">ITEM</span> <span class="nx">ID</span><span class="o">></span>
+<span class="p">));</span>
+
+<span class="c1">// A user buys an item (explicitly specify event time)
+</span><span class="nv">$client</span><span class="o">-></span><span class="na">createEvent</span><span class="p">(</span><span class="k">array</span><span class="p">(</span>
+ <span class="s1">'event'</span> <span class="o">=></span> <span class="s1">'buy'</span><span class="p">,</span>
+ <span class="s1">'entityType'</span> <span class="o">=></span> <span class="s1">'user'</span><span class="p">,</span>
+ <span class="s1">'entityId'</span> <span class="o">=></span> <span class="o"><</span><span class="nx">USER</span> <span class="nx">ID</span><span class="o">></span><span class="p">,</span>
+ <span class="s1">'targetEntityType'</span> <span class="o">=></span> <span class="s1">'item'</span><span class="p">,</span>
+ <span class="s1">'targetEntityId'</span> <span class="o">=></span> <span class="o"><</span><span class="nx">ITEM</span> <span class="nx">ID</span><span class="o">></span><span class="p">,</span>
+ <span class="s1">'eventTime'</span> <span class="o">=></span> <span class="o"><</span><span class="nx">EVENT_TIME</span><span class="o">></span>
+<span class="p">));</span>
+
+<span class="cp">?></span>
+</pre></td> </tr></tbody></table> </div> </div> <div data-tab="Ruby SDK" data-lang="ruby" id="tab-09c927d6-69a3-49c9-b0cd-b8c2b961a993"> <div class="highlight ruby"> <table style="border-spacing: 0"><tbody><tr> <td class="gutter gl" style="text-align: right"><pre class="lineno">1
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+23</pre></td> <td class="code"><pre><span class="c1"># Create a client object.</span>
+<span class="n">client</span> <span class="o">=</span> <span class="no">PredictionIO</span><span class="o">::</span><span class="no">EventClient</span><span class="p">.</span><span class="nf">new</span><span class="p">(</span><span class="o"><</span><span class="no">ACCESS</span> <span class="no">KEY</span><span class="o">></span><span class="p">,</span> <span class="o"><</span><span class="no">URL</span> <span class="no">OF</span> <span class="no">EVENTSERVER</span><span class="o">></span><span class="p">)</span>
+
+<span class="c1"># A user buys an item (use current time as event time)</span>
+<span class="n">client</span><span class="p">.</span><span class="nf">create_event</span><span class="p">(</span>
+ <span class="s1">'buy'</span><span class="p">,</span>
+ <span class="s1">'user'</span><span class="p">,</span>
+ <span class="o"><</span><span class="no">USER</span> <span class="no">ID</span><span class="o">></span><span class="p">,</span> <span class="p">{</span>
+ <span class="s1">'targetEntityType'</span> <span class="o">=></span> <span class="s1">'item'</span><span class="p">,</span>
+ <span class="s1">'targetEntityId'</span> <span class="o">=></span> <span class="o"><</span><span class="no">ITEM</span> <span class="no">ID</span><span class="o">></span>
+ <span class="p">}</span>
+<span class="p">)</span>
+
+<span class="c1"># A user buys an item (explicitly specify event time)</span>
+<span class="n">client</span><span class="p">.</span><span class="nf">create_event</span><span class="p">(</span>
+ <span class="s1">'buy'</span><span class="p">,</span>
+ <span class="s1">'user'</span><span class="p">,</span>
+ <span class="o"><</span><span class="no">USER</span> <span class="no">ID</span><span class="o">></span><span class="p">,</span> <span class="p">{</span>
+ <span class="s1">'targetEntityType'</span> <span class="o">=></span> <span class="s1">'item'</span><span class="p">,</span>
+ <span class="s1">'targetEntityId'</span> <span class="o">=></span> <span class="o"><</span><span class="no">ITEM</span> <span class="no">ID</span><span class="o">></span><span class="p">,</span>
+ <span class="s1">'eventTime'</span> <span class="o">=></span> <span class="o"><</span><span class="no">EVENT_TIME</span><span class="o">></span>
+ <span class="p">}</span>
+<span class="p">)</span>
+</pre></td> </tr></tbody></table> </div> </div> <div data-tab="Java SDK" data-lang="java" id="tab-b47a9271-8b3d-488e-b7ef-2fc33b95e633"> <div class="highlight java"> <table style="border-spacing: 0"><tbody><tr> <td class="gutter gl" style="text-align: right"><pre class="lineno">1
+2
+3
+4
+5
+6
+7
+8
+9
+10
+11
+12
+13
+14
+15
+16
+17
+18
+19
+20
+21
+22
+23
+24
+25</pre></td> <td class="code"><pre><span class="kn">import</span> <span class="nn">io.prediction.Event</span><span class="o">;</span>
+<span class="kn">import</span> <span class="nn">io.prediction.EventClient</span><span class="o">;</span>
+
+<span class="kn">import</span> <span class="nn">com.google.common.collect.ImmutableList</span><span class="o">;</span>
+
+<span class="n">EventClient</span> <span class="n">client</span> <span class="o">=</span> <span class="k">new</span> <span class="n">EventClient</span><span class="o">(<</span><span class="n">ACCESS</span> <span class="n">KEY</span><span class="o">>,</span> <span class="o"><</span><span class="n">URL</span> <span class="n">OF</span> <span class="n">EVENTSERVER</span><span class="o">>);</span>
+
+<span class="c1">// A user buys an item (use current time as event time)</span>
+<span class="n">Event</span> <span class="n">buyEvent</span> <span class="o">=</span> <span class="k">new</span> <span class="n">Event</span><span class="o">()</span>
+ <span class="o">.</span><span class="na">event</span><span class="o">(</span><span class="s">"buy"</span><span class="o">)</span>
+ <span class="o">.</span><span class="na">entityType</span><span class="o">(</span><span class="s">"user"</span><span class="o">)</span>
+ <span class="o">.</span><span class="na">entityId</span><span class="o">(<</span><span class="n">USER_ID</span><span class="o">>)</span>
+ <span class="o">.</span><span class="na">targetEntityType</span><span class="o">(</span><span class="s">"item"</span><span class="o">)</span>
+ <span class="o">.</span><span class="na">targetEntityId</span><span class="o">(<</span><span class="n">ITEM_ID</span><span class="o">>)</span>
+<span class="n">client</span><span class="o">.</span><span class="na">createEvent</span><span class="o">(</span><span class="n">buyEvent</span><span class="o">);</span>
+
+<span class="c1">// A user buys an item (explicitly specify event time)</span>
+<span class="n">Event</span> <span class="n">buyEvent</span> <span class="o">=</span> <span class="k">new</span> <span class="n">Event</span><span class="o">()</span>
+ <span class="o">.</span><span class="na">event</span><span class="o">(</span><span class="s">"buy"</span><span class="o">)</span>
+ <span class="o">.</span><span class="na">entityType</span><span class="o">(</span><span class="s">"user"</span><span class="o">)</span>
+ <span class="o">.</span><span class="na">entityId</span><span class="o">(<</span><span class="n">USER_ID</span><span class="o">>)</span>
+ <span class="o">.</span><span class="na">targetEntityType</span><span class="o">(</span><span class="s">"item"</span><span class="o">)</span>
+ <span class="o">.</span><span class="na">targetEntityId</span><span class="o">(<</span><span class="n">ITEM_ID</span><span class="o">>)</span>
+ <span class="o">.</span><span class="na">eventTime</span><span class="o">(<</span><span class="n">EVENT_TIME</span><span class="o">>)</span>
+<span class="n">client</span><span class="o">.</span><span class="na">createEvent</span><span class="o">(</span><span class="n">buyEvent</span><span class="o">);</span>
+</pre></td> </tr></tbody></table> </div> </div> </div> <p><h3 id='query-event-server' class='header-anchors'>Query Event Server</h3><p>Now let's query the EventServer and see if these events are imported successfully.</p><p>Go to following URL with your browser:</p><p><code><a href="http://localhost:7070/events.json?accessKey=&lt;YOUR_ACCESS_KEY">http://localhost:7070/events.json?accessKey=&lt;YOUR_ACCESS_KEY</a>></code></p><p>or run the following command in terminal:</p><div class="highlight shell"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1</pre></td><td class="code"><pre><span class="gp">$ </span>curl -i -X GET <span class="s2">"<a href="http://localhost:7070/events.json?accessKey=">http://localhost:7070/events.json?accessKey=</a></span><span class="nv">$ACCESS_KEY</span><span class="s2">"</span>
+</pre></td></tr></tbody></table> </div> <div class="alert-message note"><p>Note that you should quote the entire URL by using single or double quotes when you run the <code>curl</code> command.</p></div><p>It should return the imported events in JSON format. You can refer to <a href="/datacollection/eventapi/#debugging-recipes">Event Server Debugging Recipes</a> for more different ways to query Event Server.</p></p><h3 id='import-more-sample-data' class='header-anchors'>Import More Sample Data</h3><p>This engine requires more data in order to train a useful model. Instead of sending more events one by one in real time, for quickstart demonstration purpose, we are going to use a script to import more events in batch.</p> <p>A Python import script <code>import_eventserver.py</code> is provided to import sample data. The script generates some frequent item sets (prefix with "s"), some other random items (prefix with "i") and a few popular items (prefix with "p&
quot;). Then each user (with user ID "u1" to "u10") performs 5 buy transactions (buy events are within 10 seconds in each transcation). In each transcation, the user may or may not buy some random items, always buy one of the popular items and buy 2 or more items in one of the frequent item sets.</p><p>First, you will need to install Python SDK in order to run the sample data import script. To install Python SDK, run:</p><div class="highlight shell"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1</pre></td><td class="code"><pre><span class="gp">$ </span>pip install predictionio
+</pre></td></tr></tbody></table> </div> <p>or</p><div class="highlight shell"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1</pre></td><td class="code"><pre><span class="gp">$ </span>easy_install predictionio
+</pre></td></tr></tbody></table> </div> <div class="alert-message note"><p>You may need <code>sudo</code> access if you have permission issue. (ie. <code>sudo pip install predictionio</code>)</p></div> <p><a href="#"></a></p> <p>Make sure you are under the <code>MyComplementaryPurchase</code> directory. Execute the following to import the data (Replace the value of access_key parameter with your <strong>Access Key</strong>):</p><div class="highlight shell"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1
+2</pre></td><td class="code"><pre><span class="gp">$ </span><span class="nb">cd </span>MyComplementaryPurchase
+<span class="gp">$ </span>python data/import_eventserver.py --access_key 3mZWDzci2D5YsqAnqNnXH9SB6Rg3dsTBs8iHkK6X2i54IQsIZI1eEeQQyMfs7b3F
+</pre></td></tr></tbody></table> </div> <p>You should see the following output:</p><div class="highlight shell"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1
+2
+3
+4
+5
+6
+7</pre></td><td class="code"><pre>...
+User u10 buys item i20 at 2014-10-19 15:42:35.618000-07:53
+User u10 buys item i5 at 2014-10-19 15:42:45.618000-07:53
+User u10 buys item p3 at 2014-10-19 15:42:55.618000-07:53
+User u10 buys item s2i3 at 2014-10-19 15:43:05.618000-07:53
+User u10 buys item s2i1 at 2014-10-19 15:43:15.618000-07:53
+225 events are imported.
+</pre></td></tr></tbody></table> </div> <p><a href="#"></a></p><div class="alert-message warning"><p>If you see error <strong>TypeError: <strong>init</strong>() got an unexpected keyword argument 'access_key'</strong>, please update the Python SDK to the latest version.</p></div><p>You can query the event server again as described previously to check the imported events.</p> <h2 id='5.-deploy-the-engine-as-a-service' class='header-anchors'>5. Deploy the Engine as a Service</h2><p>Now you can build, train, and deploy the engine. First, make sure you are under the <code>MyComplementaryPurchase</code> directory.</p><div class="highlight shell"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1</pre></td><td class="code"><pre><span class="gp">$ </span><span class="nb">cd </span>MyComplementaryPurchase
+</pre></td></tr></tbody></table> </div> <h3 id='engine.json' class='header-anchors'>Engine.json</h3><p>Under the directory, you should find an <code>engine.json</code> file; this is where you specify parameters for the engine.</p><div class="alert-message warning"><p>Modify this file to make sure the <code>appName</code> parameter match your <strong>App Name</strong> you created earlier (e.g. "MyApp1" if you follow the quickstart).</p></div><div class="highlight shell"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1
+2
+3
+4
+5
+6
+7</pre></td><td class="code"><pre> ...
+ <span class="s2">"datasource"</span>: <span class="o">{</span>
+ <span class="s2">"params"</span> : <span class="o">{</span>
+ <span class="s2">"appName"</span>: <span class="s2">"MyApp1"</span>
+ <span class="o">}</span>
+ <span class="o">}</span>,
+ ...
+</pre></td></tr></tbody></table> </div> <div class="alert-message note"><p>You may see <code>appId</code> in engine.json instead, which means you are using old template. In this case, make sure the <code>appId</code> defined in the file match your <strong>App ID</strong>. Alternatively, you can download the latest version of the template or follow our <a href="/resources/upgrade/#upgrade-to-0.9.2">upgrade instructions</a> to modify the template to use <code>appName</code> as parameter.</p></div> <p><a href="#"></a></p> <p><h3 id='building' class='header-anchors'>Building</h3><p>Start with building your <em>MyComplementaryPurchase</em> engine. Run the following command:</p><div class="highlight shell"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1</pre></td><td class="code"><pre><span class="gp">$ </span>pio build --verbose
+</pre></td></tr></tbody></table> </div> <p>This command should take few minutes for the first time; all subsequent builds should be less than a minute. You can also run it without <code>--verbose</code> if you don't want to see all the log messages.</p><p>Upon successful build, you should see a console message similar to the following.</p><div class="highlight shell"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1</pre></td><td class="code"><pre><span class="o">[</span>INFO] <span class="o">[</span>Console<span class="nv">$]</span> Your engine is ready <span class="k">for </span>training.
+</pre></td></tr></tbody></table> </div> <h3 id='training-the-predictive-model' class='header-anchors'>Training the Predictive Model</h3><p>To train your engine, run the following command:</p><div class="highlight shell"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1</pre></td><td class="code"><pre><span class="gp">$ </span>pio train
+</pre></td></tr></tbody></table> </div> <p>When your engine is trained successfully, you should see a console message similar to the following.</p><div class="highlight shell"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1</pre></td><td class="code"><pre><span class="o">[</span>INFO] <span class="o">[</span>CoreWorkflow<span class="nv">$]</span> Training completed successfully.
+</pre></td></tr></tbody></table> </div> <h3 id='deploying-the-engine' class='header-anchors'>Deploying the Engine</h3><p>Now your engine is ready to deploy. Run:</p><div class="highlight shell"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1</pre></td><td class="code"><pre><span class="gp">$ </span>pio deploy
+</pre></td></tr></tbody></table> </div> <p>When the engine is deployed successfully and running, you should see a console message similar to the following:</p><div class="highlight shell"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1
+2</pre></td><td class="code"><pre><span class="o">[</span>INFO] <span class="o">[</span>HttpListener] Bound to /0.0.0.0:8000
+<span class="o">[</span>INFO] <span class="o">[</span>MasterActor] Bind successful. Ready to serve.
+</pre></td></tr></tbody></table> </div> <p>Do not kill the deployed engine process.</p><p>By default, the deployed engine binds to <a href="http://localhost:8000"><a href="http://localhost:8000">http://localhost:8000</a></a>. You can visit that page in your web browser to check its status.</p><p><img alt="Engine Status" src="/images/engine-server-3246414b.png"/></p></p><h2 id='6.-use-the-engine' class='header-anchors'>6. Use the Engine</h2><p>Now, You can query the engine. For example, return top 3 items which are frequently bought with item "s2i1". You can sending this JSON '{ "items" : ["s2i1"], "num" : 3 }' to the deployed engine. The engine will return a JSON with the recommeded items.</p><p>If you include one or more items in the query, the engine will use each combination of the query items as condition, and return recommended items if there is any for this condition. For example, if you query items are ["A", "B&qu
ot;], then the engine will use ["A"], ["B"], and ["A", "B"] as condition and try to find top n recommended items for each combination.</p><p>You can simply send a query by making a HTTP request or through the <code>EngineClient</code> of an SDK.</p><p>With the deployed engine running, open another temrinal and run the following <code>curl</code> command or use SDK to send the query:</p><div class="tabs"> <ul class="control"> <li data-lang="json"><a href="#tab-ff5c9260-98a2-46c4-a383-8143d95d283a">REST API</a></li> <li data-lang="python"><a href="#tab-2914cf7d-3730-4d66-973f-649a27610042">Python SDK</a></li> <li data-lang="php"><a href="#tab-e73c6f1f-fa24-4d2b-9f06-4442213b6327">PHP SDK</a></li> <li data-lang="ruby"><a href="#tab-985b5d7a-46b7-4aec-ab60-44d7470921f2">Ruby SDK</a></li> <li data-lang="java"><a href="#tab-c598075a-bcc0-4dd9-bbc4-0f1d3c6b7412">Java SDK</a></li> </ul> <div data-tab="REST API" data-lang="json" id="tab-ff5c9260-98a2-4
6c4-a383-8143d95d283a"> <div class="highlight shell"> <table style="border-spacing: 0"><tbody><tr> <td class="gutter gl" style="text-align: right"><pre class="lineno">1
+2
+3
+4
+5
+6
+7</pre></td> <td class="code"><pre><span class="gp">$ </span>curl -H <span class="s2">"Content-Type: application/json"</span> <span class="se">\</span>
+-d <span class="s1">'{
+ "items" : ["s2i1"],
+ "num" : 3
+}'</span> <span class="se">\</span>
+http://localhost:8000/queries.json
+
+</pre></td> </tr></tbody></table> </div> </div> <div data-tab="Python SDK" data-lang="python" id="tab-2914cf7d-3730-4d66-973f-649a27610042"> <div class="highlight python"> <table style="border-spacing: 0"><tbody><tr> <td class="gutter gl" style="text-align: right"><pre class="lineno">1
+2
+3
+4
+5
+6</pre></td> <td class="code"><pre><span class="kn">import</span> <span class="nn">predictionio</span>
+<span class="n">engine_client</span> <span class="o">=</span> <span class="n">predictionio</span><span class="o">.</span><span class="n">EngineClient</span><span class="p">(</span><span class="n">url</span><span class="o">=</span><span class="s">"http://localhost:8000"</span><span class="p">)</span>
+<span class="k">print</span> <span class="n">engine_client</span><span class="o">.</span><span class="n">send_query</span><span class="p">({</span>
+ <span class="s">"items"</span> <span class="p">:</span> <span class="p">[</span><span class="s">"s2i1"</span><span class="p">],</span>
+ <span class="s">"num"</span> <span class="p">:</span> <span class="mi">3</span>
+<span class="p">})</span>
+</pre></td> </tr></tbody></table> </div> </div> <div data-tab="PHP SDK" data-lang="php" id="tab-e73c6f1f-fa24-4d2b-9f06-4442213b6327"> <div class="highlight php"> <table style="border-spacing: 0"><tbody><tr> <td class="gutter gl" style="text-align: right"><pre class="lineno">1
+2
+3
+4
+5
+6
+7
+8
+9
+10
+11
+12
+13
+14</pre></td> <td class="code"><pre><span class="cp"><?php</span>
+<span class="k">require_once</span><span class="p">(</span><span class="s2">"vendor/autoload.php"</span><span class="p">);</span>
+<span class="k">use</span> <span class="nx">predictionio\EngineClient</span><span class="p">;</span>
+
+<span class="nv">$client</span> <span class="o">=</span> <span class="k">new</span> <span class="nx">EngineClient</span><span class="p">(</span><span class="s1">'http://localhost:8000'</span><span class="p">);</span>
+
+<span class="nv">$response</span> <span class="o">=</span> <span class="nv">$client</span><span class="o">-></span><span class="na">sendQuery</span><span class="p">(</span><span class="k">array</span><span class="p">(</span>
+ <span class="s1">'items'</span> <span class="o">=></span> <span class="k">array</span><span class="p">(</span><span class="s1">'s2i1'</span><span class="p">),</span>
+ <span class="s1">'num'</span> <span class="o">=></span> <span class="mi">3</span>
+<span class="p">));</span>
+
+<span class="nb">print_r</span><span class="p">(</span><span class="nv">$response</span><span class="p">);</span>
+
+<span class="cp">?></span>
+</pre></td> </tr></tbody></table> </div> </div> <div data-tab="Ruby SDK" data-lang="ruby" id="tab-985b5d7a-46b7-4aec-ab60-44d7470921f2"> <div class="highlight ruby"> <table style="border-spacing: 0"><tbody><tr> <td class="gutter gl" style="text-align: right"><pre class="lineno">1
+2
+3
+4
+5
+6
+7
+8
+9
+10</pre></td> <td class="code"><pre><span class="c1"># Create client object.</span>
+<span class="n">client</span> <span class="o">=</span> <span class="no">PredictionIO</span><span class="o">::</span><span class="no">EngineClient</span><span class="p">.</span><span class="nf">new</span><span class="p">(</span><span class="s1">'http://localhost:8000'</span><span class="p">)</span>
+
+<span class="c1"># Query PredictionIO.</span>
+<span class="n">response</span> <span class="o">=</span> <span class="n">client</span><span class="p">.</span><span class="nf">send_query</span><span class="p">(</span>
+ <span class="s1">'items'</span> <span class="o">=></span> <span class="p">[</span><span class="s1">'s2i1'</span><span class="p">],</span>
+ <span class="s1">'num'</span> <span class="o">=></span> <span class="mi">3</span>
+<span class="p">)</span>
+
+<span class="nb">puts</span> <span class="n">response</span>
+</pre></td> </tr></tbody></table> </div> </div> <div data-tab="Java SDK" data-lang="java" id="tab-c598075a-bcc0-4dd9-bbc4-0f1d3c6b7412"> <div class="highlight java"> <table style="border-spacing: 0"><tbody><tr> <td class="gutter gl" style="text-align: right"><pre class="lineno">1
+2
+3
+4
+5
+6
+7
+8
+9
+10
+11
+12
+13
+14
+15</pre></td> <td class="code"><pre><span class="kn">import</span> <span class="nn">com.google.common.collect.ImmutableMap</span><span class="o">;</span>
+<span class="kn">import</span> <span class="nn">com.google.common.collect.ImmutableList</span><span class="o">;</span>
+<span class="kn">import</span> <span class="nn">com.google.gson.JsonObject</span><span class="o">;</span>
+
+<span class="kn">import</span> <span class="nn">io.prediction.EngineClient</span><span class="o">;</span>
+
+<span class="c1">// create client object</span>
+<span class="n">EngineClient</span> <span class="n">engineClient</span> <span class="o">=</span> <span class="k">new</span> <span class="n">EngineClient</span><span class="o">(</span><span class="s">"http://localhost:8000"</span><span class="o">);</span>
+
+<span class="c1">// query</span>
+
+<span class="n">JsonObject</span> <span class="n">response</span> <span class="o">=</span> <span class="n">engineClient</span><span class="o">.</span><span class="na">sendQuery</span><span class="o">(</span><span class="n">ImmutableMap</span><span class="o">.<</span><span class="n">String</span><span class="o">,</span> <span class="n">Object</span><span class="o">></span><span class="n">of</span><span class="o">(</span>
+ <span class="s">"items"</span><span class="o">,</span> <span class="n">ImmutableList</span><span class="o">.</span><span class="na">of</span><span class="o">(</span><span class="s">"s2i1"</span><span class="o">),</span>
+ <span class="s">"num"</span><span class="o">,</span> <span class="mi">3</span>
+<span class="o">));</span>
+</pre></td> </tr></tbody></table> </div> </div> </div> <p>The following is sample JSON response. The <code>cond</code> field is one of the combination of query items used as condition to determine other frequently bought items with this condition, followed by top items. If there are multiple conditions with recommended items found, the <code>rules</code> array will contain mutliple elements, and each correspond to the condition.</p><div class="highlight shell"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1
+2
+3
+4
+5
+6
+7
+8
+9
+10
+11
+12
+13
+14
+15
+16
+17
+18
+19
+20
+21</pre></td><td class="code"><pre><span class="o">{</span>
+ <span class="s2">"rules"</span>:[
+ <span class="o">{</span>
+ <span class="s2">"cond"</span>:[<span class="s2">"s2i1"</span><span class="o">]</span>,
+ <span class="s2">"itemScores"</span>:[
+ <span class="o">{</span>
+ <span class="s2">"item"</span>:<span class="s2">"s2i2"</span>,
+ <span class="s2">"support"</span>:0.2,
+ <span class="s2">"confidence"</span>:0.9090909090909091,
+ <span class="s2">"lift"</span>:3.787878787878788
+ <span class="o">}</span>,
+ <span class="o">{</span>
+ <span class="s2">"item"</span>:<span class="s2">"s2i3"</span>,
+ <span class="s2">"support"</span>:0.14,
+ <span class="s2">"confidence"</span>:0.6363636363636364,
+ <span class="s2">"lift"</span>:3.535353535353535
+ <span class="o">}</span>
+ <span class="o">]</span>
+ <span class="o">}</span>
+ <span class="o">]</span>
+<span class="o">}</span>
+</pre></td></tr></tbody></table> </div> <p><em>MyComplementaryPurchase</em> is now running.</p><div class="alert-message info"><p>To update the model periodically with new data, simply set up a cron job to call <code>pio train</code> and <code>pio deploy</code>. The engine will continue to serve prediction results during the re-train process. After the training is completed, <code>pio deploy</code> will automatically shutdown the existing engine server and bring up a new process on the same port.</p></div><div class="alert-message info"><p><strong>Note that if you import a <em>large</em> data set</strong> and the training seems to be taking forever or getting stuck, it's likely that there is not enough executor memory. It's recommended to setup a Spark standalone cluster, you'll need to specify more driver and executor memory when training with a large data set. Please see <a href="/resources/faq/#engine-training">FAQ here</a> for instructions.</p></div> <h4 id='<a-href=
"/templates/complementarypurchase/dase/">next:-dase-components-explained</a>' class='header-anchors' ><a href="/templates/complementarypurchase/dase/">Next: DASE Components Explained</a></h4></div></div></div></div><footer><div class="container"><div class="seperator"></div><div class="row"><div class="col-md-4 col-md-push-8 col-xs-12"><div class="subscription-form-wrapper"><h4>Subscribe to our Newsletter</h4><form class="ajax-form" id="subscribe-form" method="POST" action="https://script.google.com/macros/s/AKfycbwhzeKCQJjQ52eVAqNT_vcklH07OITUO7wzOMDXvK6EGAWgaZgF/exec"><input class="required underlined-input" type="email" placeholder="Your email address" name="subscription_email" id="subscription_email"/><input class="pill-button" value="SUBSCRIBE" type="submit" data-state-normal="SUBSCRIBE" data-state-sucess="SUBSCRIBED!" data-state-loading="SENDING..." onclick="t($('#subscription_email').val());"/><p class="result"></p></form></div></div><div class="col-md-2 col-md-pull-4 col-xs-
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@@ -0,0 +1,115 @@
+<!DOCTYPE html><html><head><title>Reading Custom Properties (Classification)</title><meta charset="utf-8"/><meta content="IE=edge,chrome=1" http-equiv="X-UA-Compatible"/><meta name="viewport" content="width=device-width, initial-scale=1.0"/><meta class="swiftype" name="title" data-type="string" content="Reading Custom Properties (Classification)"/><link rel="canonical" href="https://docs.prediction.io/templates/classification/reading-custom-properties/"/><link href="/images/favicon/normal-b330020a.png" rel="shortcut icon"/><link href="/images/favicon/apple-c0febcf2.png" rel="apple-touch-icon"/><link href="//fonts.googleapis.com/css?family=Open+Sans:300italic,400italic,600italic,700italic,800italic,400,300,600,700,800" rel="stylesheet"/><link href="//maxcdn.bootstrapcdn.com/font-awesome/4.2.0/css/font-awesome.min.css" rel="stylesheet"/><link href="/stylesheets/application-3598c7d7.css" rel="stylesheet" type="text/css"/><!--[if lt IE 9]><script src="//cdnjs.cloudflare.com/ajax/libs/ht
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<div class="row"><div class="col-md-9 col-sm-11 col-xs-11"><div class="hidden-md hidden-lg" id="mobile-page-heading-wrapper"><p>PredictionIO Docs</p><h4>Reading Custom Properties (Classification)</h4></div><h4 class="hidden-sm hidden-xs">PredictionIO Docs</h4></div><div class="col-md-3 col-sm-1 col-xs-1 hidden-md hidden-lg"><img id="left-menu-indicator" src="/images/icons/down-arrow-dfe9f7fe.png"/></div><div class="col-md-3 col-sm-12 col-xs-12 swiftype-wrapper"><div class="swiftype"><form class="search-form"><img class="search-box-toggler hidden-xs hidden-sm" src="/images/icons/search-glass-704bd4ff.png"/><div class="search-box"><img src="/images/icons/search-glass-704bd4ff.png"/><input type="text" id="st-search-input" class="st-search-input" placeholder="Search Doc..."/></div><img class="swiftype-row-hider hidden-md hidden-lg" src="/images/icons/drawer-toggle-active-fcbef12a.png"/></form></div></div><div class="mobile-left-menu-toggler hidden-md hidden-lg"></div></div></div></div><
div id="page" class="container-fluid"><div class="row"><div id="left-menu-wrapper" class="col-md-3"><nav id="nav-main"><ul><li class="level-1"><a class="expandible" href="/"><span>Apache PredictionIO (incubating) Documentation</span></a><ul><li class="level-2"><a class="final" href="/"><span>Welcome to Apache PredictionIO (incubating)</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Getting Started</span></a><ul><li class="level-2"><a class="final" href="/start/"><span>A Quick Intro</span></a></li><li class="level-2"><a class="final" href="/install/"><span>Installing Apache PredictionIO (incubating)</span></a></li><li class="level-2"><a class="final" href="/start/download/"><span>Downloading an Engine Template</span></a></li><li class="level-2"><a class="final" href="/start/deploy/"><span>Deploying Your First Engine</span></a></li><li class="level-2"><a class="final" href="/start/customize/"><span>Customizing the Engine</span></a></li></ul></li><li c
lass="level-1"><a class="expandible" href="#"><span>Integrating with Your App</span></a><ul><li class="level-2"><a class="final" href="/appintegration/"><span>App Integration Overview</span></a></li><li class="level-2"><a class="expandible" href="/sdk/"><span>List of SDKs</span></a><ul><li class="level-3"><a class="final" href="/sdk/java/"><span>Java & Android SDK</span></a></li><li class="level-3"><a class="final" href="/sdk/php/"><span>PHP SDK</span></a></li><li class="level-3"><a class="final" href="/sdk/python/"><span>Python SDK</span></a></li><li class="level-3"><a class="final" href="/sdk/ruby/"><span>Ruby SDK</span></a></li><li class="level-3"><a class="final" href="/sdk/community/"><span>Community Powered SDKs</span></a></li></ul></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Deploying an Engine</span></a><ul><li class="level-2"><a class="final" href="/deploy/"><span>Deploying as a Web Service</span></a></li><li class="level-2"><a class="final" href=
"/cli/#engine-commands"><span>Engine Command-line Interface</span></a></li><li class="level-2"><a class="final" href="/deploy/engineparams/"><span>Setting Engine Parameters</span></a></li><li class="level-2"><a class="final" href="/deploy/enginevariants/"><span>Deploying Multiple Engine Variants</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Customizing an Engine</span></a><ul><li class="level-2"><a class="final" href="/customize/"><span>Learning DASE</span></a></li><li class="level-2"><a class="final" href="/customize/dase/"><span>Implement DASE</span></a></li><li class="level-2"><a class="final" href="/customize/troubleshooting/"><span>Troubleshooting Engine Development</span></a></li><li class="level-2"><a class="final" href="/api/current/#package"><span>Engine Scala APIs</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Collecting and Analyzing Data</span></a><ul><li class="level-2"><a class="final" href="/dataco
llection/"><span>Event Server Overview</span></a></li><li class="level-2"><a class="final" href="/cli/#event-server-commands"><span>Event Server Command-line Interface</span></a></li><li class="level-2"><a class="final" href="/datacollection/eventapi/"><span>Collecting Data with REST/SDKs</span></a></li><li class="level-2"><a class="final" href="/datacollection/eventmodel/"><span>Events Modeling</span></a></li><li class="level-2"><a class="final" href="/datacollection/webhooks/"><span>Unifying Multichannel Data with Webhooks</span></a></li><li class="level-2"><a class="final" href="/datacollection/channel/"><span>Channel</span></a></li><li class="level-2"><a class="final" href="/datacollection/batchimport/"><span>Importing Data in Batch</span></a></li><li class="level-2"><a class="final" href="/datacollection/analytics/"><span>Using Analytics Tools</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Choosing an Algorithm(s)</span></a><ul><li class="leve
l-2"><a class="final" href="/algorithm/"><span>Built-in Algorithm Libraries</span></a></li><li class="level-2"><a class="final" href="/algorithm/switch/"><span>Switching to Another Algorithm</span></a></li><li class="level-2"><a class="final" href="/algorithm/multiple/"><span>Combining Multiple Algorithms</span></a></li><li class="level-2"><a class="final" href="/algorithm/custom/"><span>Adding Your Own Algorithms</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>ML Tuning and Evaluation</span></a><ul><li class="level-2"><a class="final" href="/evaluation/"><span>Overview</span></a></li><li class="level-2"><a class="final" href="/evaluation/paramtuning/"><span>Hyperparameter Tuning</span></a></li><li class="level-2"><a class="final" href="/evaluation/evaluationdashboard/"><span>Evaluation Dashboard</span></a></li><li class="level-2"><a class="final" href="/evaluation/metricchoose/"><span>Choosing Evaluation Metrics</span></a></li><li class="level-2"><
a class="final" href="/evaluation/metricbuild/"><span>Building Evaluation Metrics</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>System Architecture</span></a><ul><li class="level-2"><a class="final" href="/system/"><span>Architecture Overview</span></a></li><li class="level-2"><a class="final" href="/system/anotherdatastore/"><span>Using Another Data Store</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Engine Template Gallery</span></a><ul><li class="level-2"><a class="final" href="http://templates.prediction.io"><span>Browse</span></a></li><li class="level-2"><a class="final" href="/community/submit-template/"><span>Submit your Engine as a Template</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Demo Tutorials</span></a><ul><li class="level-2"><a class="final" href="/demo/tapster/"><span>Comics Recommendation Demo</span></a></li><li class="level-2"><a class="final" href="/demo/c
ommunity/"><span>Community Contributed Demo</span></a></li><li class="level-2"><a class="final" href="/demo/textclassification/"><span>Text Classification Engine Tutorial</span></a></li></ul></li><li class="level-1"><a class="expandible" href="/community/"><span>Getting Involved</span></a><ul><li class="level-2"><a class="final" href="/community/contribute-code/"><span>Contribute Code</span></a></li><li class="level-2"><a class="final" href="/community/contribute-documentation/"><span>Contribute Documentation</span></a></li><li class="level-2"><a class="final" href="/community/contribute-sdk/"><span>Contribute a SDK</span></a></li><li class="level-2"><a class="final" href="/community/contribute-webhook/"><span>Contribute a Webhook</span></a></li><li class="level-2"><a class="final" href="/community/projects/"><span>Community Projects</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Getting Help</span></a><ul><li class="level-2"><a class="final" href=
"/resources/faq/"><span>FAQs</span></a></li><li class="level-2"><a class="final" href="/support/"><span>Community Support</span></a></li><li class="level-2"><a class="final" href="/support/#enterprise-support"><span>Enterprise Support</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Resources</span></a><ul><li class="level-2"><a class="final" href="/resources/intellij/"><span>Developing Engines with IntelliJ IDEA</span></a></li><li class="level-2"><a class="final" href="/resources/upgrade/"><span>Upgrade Instructions</span></a></li><li class="level-2"><a class="final" href="/resources/glossary/"><span>Glossary</span></a></li></ul></li></ul></nav></div><div class="col-md-9 col-sm-12"><div class="content-header hidden-md hidden-lg"><div id="page-title"><h1>Reading Custom Properties (Classification)</h1></div></div><div id="table-of-content-wrapper"><a id="edit-page-link" href="https://github.com/apache/incubator-predictionio/tree/livedoc/docs/manual/so
urce/templates/classification/reading-custom-properties.html.md"><img src="/images/icons/edit-pencil-d6c1bb3d.png"/>Edit this page</a></div><div class="content-header hidden-sm hidden-xs"><div id="page-title"><h1>Reading Custom Properties (Classification)</h1></div></div><div class="content"><p>By default, the classification template reads 4 properties of a user entity: "attr0", "attr1", "attr2" and "plan". You can modify the <a href="/templates/classification/dase/#data">default DataSource</a> to read to read your custom properties or different Entity Type.</p><p>In this example, we modify DataSource to read properties "featureA", "featureB", "featureC", "featureD" and "label" for entity type "item".</p> <blockquote> <blockquote> <p>Note: you also need import events with these properties accordingly.</p></blockquote> </blockquote> <p>Modify the <code>readTraining()</code> in DataSour
ce.scala:</p> <ul> <li>modify the <code>entityType</code> parameter</li> <li>modify the list of properties names in the <code>required</code> parameter</li> <li>modify how to create the <code>LabeledPoint</code> object using the entity properties</li> </ul> <div class="highlight scala"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1
+2
+3
+4
+5
+6
+7
+8
+9
+10
+11
+12
+13
+14
+15
+16
+17
+18
+19
+20
+21
+22
+23
+24
+25
+26
+27
+28
+29
+30</pre></td><td class="code"><pre> <span class="k">def</span> <span class="n">readTraining</span><span class="o">(</span><span class="n">sc</span><span class="k">:</span> <span class="kt">SparkContext</span><span class="o">)</span><span class="k">:</span> <span class="kt">TrainingData</span> <span class="o">=</span> <span class="o">{</span>
+ <span class="o">...</span>
+ <span class="k">val</span> <span class="n">labeledPoints</span><span class="k">:</span> <span class="kt">RDD</span><span class="o">[</span><span class="kt">LabeledPoint</span><span class="o">]</span> <span class="k">=</span> <span class="n">eventsDb</span><span class="o">.</span><span class="n">aggregateProperties</span><span class="o">(</span>
+ <span class="n">appId</span> <span class="k">=</span> <span class="n">dsp</span><span class="o">.</span><span class="n">appId</span><span class="o">,</span>
+ <span class="n">entityType</span> <span class="k">=</span> <span class="s">"item"</span><span class="o">,</span> <span class="c1">// MODIFFIED HERE
+</span> <span class="n">required</span> <span class="k">=</span> <span class="nc">Some</span><span class="o">(</span><span class="nc">List</span><span class="o">(</span> <span class="c1">// MODIFIED HERE
+</span> <span class="s">"featureA"</span><span class="o">,</span> <span class="s">"featureB"</span><span class="o">,</span> <span class="s">"featureC"</span><span class="o">,</span> <span class="s">"featureD"</span><span class="o">,</span> <span class="s">"label"</span><span class="o">)))(</span><span class="n">sc</span><span class="o">)</span>
+ <span class="c1">// aggregateProperties() returns RDD pair of
+</span> <span class="c1">// entity ID and its aggregated properties
+</span> <span class="o">.</span><span class="n">map</span> <span class="o">{</span> <span class="k">case</span> <span class="o">(</span><span class="n">entityId</span><span class="o">,</span> <span class="n">properties</span><span class="o">)</span> <span class="k">=></span>
+ <span class="k">try</span> <span class="o">{</span>
+ <span class="c1">// MODIFIED HERE
+</span> <span class="nc">LabeledPoint</span><span class="o">(</span><span class="n">properties</span><span class="o">.</span><span class="n">get</span><span class="o">[</span><span class="kt">Double</span><span class="o">](</span><span class="s">"label"</span><span class="o">),</span>
+ <span class="nc">Vectors</span><span class="o">.</span><span class="n">dense</span><span class="o">(</span><span class="nc">Array</span><span class="o">(</span>
+ <span class="n">properties</span><span class="o">.</span><span class="n">get</span><span class="o">[</span><span class="kt">Double</span><span class="o">](</span><span class="s">"featureA"</span><span class="o">),</span>
+ <span class="n">properties</span><span class="o">.</span><span class="n">get</span><span class="o">[</span><span class="kt">Double</span><span class="o">](</span><span class="s">"featureB"</span><span class="o">),</span>
+ <span class="n">properties</span><span class="o">.</span><span class="n">get</span><span class="o">[</span><span class="kt">Double</span><span class="o">](</span><span class="s">"featureC"</span><span class="o">),</span>
+ <span class="n">properties</span><span class="o">.</span><span class="n">get</span><span class="o">[</span><span class="kt">Double</span><span class="o">](</span><span class="s">"featureD"</span><span class="o">)</span>
+ <span class="o">))</span>
+ <span class="o">)</span>
+ <span class="o">}</span> <span class="k">catch</span> <span class="o">{</span>
+ <span class="k">case</span> <span class="n">e</span><span class="k">:</span> <span class="kt">Exception</span> <span class="o">=></span> <span class="o">{</span>
+ <span class="n">logger</span><span class="o">.</span><span class="n">error</span><span class="o">(</span><span class="n">s</span><span class="s">"Failed to get properties ${properties} of"</span> <span class="o">+</span>
+ <span class="n">s</span><span class="s">" ${entityId}. Exception: ${e}."</span><span class="o">)</span>
+ <span class="k">throw</span> <span class="n">e</span>
+ <span class="o">}</span>
+ <span class="o">}</span>
+ <span class="o">}</span>
+ <span class="o">...</span>
+ <span class="o">}</span>
+</pre></td></tr></tbody></table> </div> <p>Lastly, redefine the Query class parameters to take in four double values: featureA, featureB, featureC, and featureD. Now, to send a query, the field names must be changed accordingly:</p><div class="highlight shell"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1</pre></td><td class="code"><pre><span class="gp">$ </span>curl -H <span class="s2">"Content-Type: application/json"</span> -d <span class="s1">'{ "featureA":2, "featureB":0, "featureC":0, "featureD":0 }'</span> http://localhost:8000/queries.json
+</pre></td></tr></tbody></table> </div> <p>That's it! Now your classifcation engine is using different properties as training data.</p></div></div></div></div><footer><div class="container"><div class="seperator"></div><div class="row"><div class="col-md-4 col-md-push-8 col-xs-12"><div class="subscription-form-wrapper"><h4>Subscribe to our Newsletter</h4><form class="ajax-form" id="subscribe-form" method="POST" action="https://script.google.com/macros/s/AKfycbwhzeKCQJjQ52eVAqNT_vcklH07OITUO7wzOMDXvK6EGAWgaZgF/exec"><input class="required underlined-input" type="email" placeholder="Your email address" name="subscription_email" id="subscription_email"/><input class="pill-button" value="SUBSCRIBE" type="submit" data-state-normal="SUBSCRIBE" data-state-sucess="SUBSCRIBED!" data-state-loading="SENDING..." onclick="t($('#subscription_email').val());"/><p class="result"></p></form></div></div><div class="col-md-2 col-md-pull-4 col-xs-6 footer-link-column"><div class="footer-link-column
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<div class="row"><div class="col-md-9 col-sm-11 col-xs-11"><div class="hidden-md hidden-lg" id="mobile-page-heading-wrapper"><p>PredictionIO Docs</p><h4>Installing Apache PredictionIO (incubating) from Source Code</h4></div><h4 class="hidden-sm hidden-xs">PredictionIO Docs</h4></div><div class="col-md-3 col-sm-1 col-xs-1 hidden-md hidden-lg"><img id="left-menu-indicator" src="/images/icons/down-arrow-dfe9f7fe.png"/></div><div class="col-md-3 col-sm-12 col-xs-12 swiftype-wrapper"><div class="swiftype"><form class="search-form"><img class="search-box-toggler hidden-xs hidden-sm" src="/images/icons/search-glass-704bd4ff.png"/><div class="search-box"><img src="/images/icons/search-glass-704bd4ff.png"/><input type="text" id="st-search-input" class="st-search-input" placeholder="Search Doc..."/></div><img class="swiftype-row-hider hidden-md hidden-lg" src="/images/icons/drawer-toggle-active-fcbef12a.png"/></form></div></div><div class="mobile-left-menu-toggler hidden-md hidden-lg"></div><
/div></div></div><div id="page" class="container-fluid"><div class="row"><div id="left-menu-wrapper" class="col-md-3"><nav id="nav-main"><ul><li class="level-1"><a class="expandible" href="/"><span>Apache PredictionIO (incubating) Documentation</span></a><ul><li class="level-2"><a class="final" href="/"><span>Welcome to Apache PredictionIO (incubating)</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Getting Started</span></a><ul><li class="level-2"><a class="final" href="/start/"><span>A Quick Intro</span></a></li><li class="level-2"><a class="final" href="/install/"><span>Installing Apache PredictionIO (incubating)</span></a></li><li class="level-2"><a class="final" href="/start/download/"><span>Downloading an Engine Template</span></a></li><li class="level-2"><a class="final" href="/start/deploy/"><span>Deploying Your First Engine</span></a></li><li class="level-2"><a class="final" href="/start/customize/"><span>Customizing the Engine</span></a></
li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Integrating with Your App</span></a><ul><li class="level-2"><a class="final" href="/appintegration/"><span>App Integration Overview</span></a></li><li class="level-2"><a class="expandible" href="/sdk/"><span>List of SDKs</span></a><ul><li class="level-3"><a class="final" href="/sdk/java/"><span>Java & Android SDK</span></a></li><li class="level-3"><a class="final" href="/sdk/php/"><span>PHP SDK</span></a></li><li class="level-3"><a class="final" href="/sdk/python/"><span>Python SDK</span></a></li><li class="level-3"><a class="final" href="/sdk/ruby/"><span>Ruby SDK</span></a></li><li class="level-3"><a class="final" href="/sdk/community/"><span>Community Powered SDKs</span></a></li></ul></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Deploying an Engine</span></a><ul><li class="level-2"><a class="final" href="/deploy/"><span>Deploying as a Web Service</span></a></li><li class="level-2"><a c
lass="final" href="/cli/#engine-commands"><span>Engine Command-line Interface</span></a></li><li class="level-2"><a class="final" href="/deploy/engineparams/"><span>Setting Engine Parameters</span></a></li><li class="level-2"><a class="final" href="/deploy/enginevariants/"><span>Deploying Multiple Engine Variants</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Customizing an Engine</span></a><ul><li class="level-2"><a class="final" href="/customize/"><span>Learning DASE</span></a></li><li class="level-2"><a class="final" href="/customize/dase/"><span>Implement DASE</span></a></li><li class="level-2"><a class="final" href="/customize/troubleshooting/"><span>Troubleshooting Engine Development</span></a></li><li class="level-2"><a class="final" href="/api/current/#package"><span>Engine Scala APIs</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Collecting and Analyzing Data</span></a><ul><li class="level-2"><a class="fi
nal" href="/datacollection/"><span>Event Server Overview</span></a></li><li class="level-2"><a class="final" href="/cli/#event-server-commands"><span>Event Server Command-line Interface</span></a></li><li class="level-2"><a class="final" href="/datacollection/eventapi/"><span>Collecting Data with REST/SDKs</span></a></li><li class="level-2"><a class="final" href="/datacollection/eventmodel/"><span>Events Modeling</span></a></li><li class="level-2"><a class="final" href="/datacollection/webhooks/"><span>Unifying Multichannel Data with Webhooks</span></a></li><li class="level-2"><a class="final" href="/datacollection/channel/"><span>Channel</span></a></li><li class="level-2"><a class="final" href="/datacollection/batchimport/"><span>Importing Data in Batch</span></a></li><li class="level-2"><a class="final" href="/datacollection/analytics/"><span>Using Analytics Tools</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Choosing an Algorithm(s)</span></a><
ul><li class="level-2"><a class="final" href="/algorithm/"><span>Built-in Algorithm Libraries</span></a></li><li class="level-2"><a class="final" href="/algorithm/switch/"><span>Switching to Another Algorithm</span></a></li><li class="level-2"><a class="final" href="/algorithm/multiple/"><span>Combining Multiple Algorithms</span></a></li><li class="level-2"><a class="final" href="/algorithm/custom/"><span>Adding Your Own Algorithms</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>ML Tuning and Evaluation</span></a><ul><li class="level-2"><a class="final" href="/evaluation/"><span>Overview</span></a></li><li class="level-2"><a class="final" href="/evaluation/paramtuning/"><span>Hyperparameter Tuning</span></a></li><li class="level-2"><a class="final" href="/evaluation/evaluationdashboard/"><span>Evaluation Dashboard</span></a></li><li class="level-2"><a class="final" href="/evaluation/metricchoose/"><span>Choosing Evaluation Metrics</span></a></li><li
class="level-2"><a class="final" href="/evaluation/metricbuild/"><span>Building Evaluation Metrics</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>System Architecture</span></a><ul><li class="level-2"><a class="final" href="/system/"><span>Architecture Overview</span></a></li><li class="level-2"><a class="final" href="/system/anotherdatastore/"><span>Using Another Data Store</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Engine Template Gallery</span></a><ul><li class="level-2"><a class="final" href="http://templates.prediction.io"><span>Browse</span></a></li><li class="level-2"><a class="final" href="/community/submit-template/"><span>Submit your Engine as a Template</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Demo Tutorials</span></a><ul><li class="level-2"><a class="final" href="/demo/tapster/"><span>Comics Recommendation Demo</span></a></li><li class="level-2"><a class="fi
nal" href="/demo/community/"><span>Community Contributed Demo</span></a></li><li class="level-2"><a class="final" href="/demo/textclassification/"><span>Text Classification Engine Tutorial</span></a></li></ul></li><li class="level-1"><a class="expandible" href="/community/"><span>Getting Involved</span></a><ul><li class="level-2"><a class="final" href="/community/contribute-code/"><span>Contribute Code</span></a></li><li class="level-2"><a class="final" href="/community/contribute-documentation/"><span>Contribute Documentation</span></a></li><li class="level-2"><a class="final" href="/community/contribute-sdk/"><span>Contribute a SDK</span></a></li><li class="level-2"><a class="final" href="/community/contribute-webhook/"><span>Contribute a Webhook</span></a></li><li class="level-2"><a class="final" href="/community/projects/"><span>Community Projects</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Getting Help</span></a><ul><li class="level-2"><a c
lass="final" href="/resources/faq/"><span>FAQs</span></a></li><li class="level-2"><a class="final" href="/support/"><span>Community Support</span></a></li><li class="level-2"><a class="final" href="/support/#enterprise-support"><span>Enterprise Support</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Resources</span></a><ul><li class="level-2"><a class="final" href="/resources/intellij/"><span>Developing Engines with IntelliJ IDEA</span></a></li><li class="level-2"><a class="final" href="/resources/upgrade/"><span>Upgrade Instructions</span></a></li><li class="level-2"><a class="final" href="/resources/glossary/"><span>Glossary</span></a></li></ul></li></ul></nav></div><div class="col-md-9 col-sm-12"><div class="content-header hidden-md hidden-lg"><div id="page-title"><h1>Installing Apache PredictionIO (incubating) from Source Code</h1></div></div><div id="table-of-content-wrapper"><h5>On this page</h5><aside id="table-of-contents"><ul> <li> <a href=
"#building">Building</a> </li> <li> <a href="#installing-dependencies">Installing Dependencies</a> </li> </ul> </aside><hr/><a id="edit-page-link" href="https://github.com/apache/incubator-predictionio/tree/livedoc/docs/manual/source/install/install-sourcecode.html.md.erb"><img src="/images/icons/edit-pencil-d6c1bb3d.png"/>Edit this page</a></div><div class="content-header hidden-sm hidden-xs"><div id="page-title"><h1>Installing Apache PredictionIO (incubating) from Source Code</h1></div></div><div class="content"><div class="alert-message info"><p>Assuming you are following the directory structure in the followoing, replace <code>/home/abc</code> with your own home directory wherever you see it.</p></div><h2 id='building' class='header-anchors'>Building</h2><p>Run the following to download and build Apache PredictionIO (incubating) from its source code.</p><div class="highlight shell"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre c
lass="lineno">1
+2
+3
+4</pre></td><td class="code"><pre><span class="gp">$ </span>git clone https://github.com/apache/incubator-predictionio.git
+<span class="gp">$ </span><span class="nb">cd </span>incubator-predictionio
+<span class="gp">$ </span>git checkout master
+<span class="gp">$ </span>./make-distribution.sh
+</pre></td></tr></tbody></table> </div> <p>You should see something like the following when it finishes building successfully.</p><div class="highlight shell"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1
+2
+3
+4
+5</pre></td><td class="code"><pre>...
+PredictionIO-0.9.6/sbt/sbt
+PredictionIO-0.9.6/conf/
+PredictionIO-0.9.6/conf/pio-env.sh
+PredictionIO binary distribution created at PredictionIO-0.9.6.tar.gz
+</pre></td></tr></tbody></table> </div> <p>Extract the binary distribution you have just built.</p><div class="highlight shell"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1</pre></td><td class="code"><pre><span class="gp">$ </span>tar zxvf PredictionIO-0.9.6.tar.gz
+</pre></td></tr></tbody></table> </div> <h2 id='installing-dependencies' class='header-anchors'>Installing Dependencies</h2><p>Let us install dependencies inside a subdirectory of the Apache PredictionIO (incubating) installation. By following this convention, you can use Apache PredictionIO (incubating)'s default configuration as is.</p><div class="highlight shell"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1</pre></td><td class="code"><pre><span class="gp">$ </span>mkdir PredictionIO-0.9.6/vendors
+</pre></td></tr></tbody></table> </div> <h3 id='spark-setup' class='header-anchors'>Spark Setup</h3><p><a href="http://spark.apache.org">Apache Spark</a> is the default processing engine for PredictionIO. Download and extract it.</p><div class="highlight shell"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1
+2</pre></td><td class="code"><pre><span class="gp">$ </span>wget http://d3kbcqa49mib13.cloudfront.net/spark-1.5.1-bin-hadoop2.6.tgz
+<span class="gp">$ </span>tar zxvfC spark-1.5.1-bin-hadoop2.6.tgz PredictionIO-0.9.6/vendors
+</pre></td></tr></tbody></table> </div> <div class="alert-message info"><p>If you decide to install Apache Spark to another location, you must edit <code>PredictionIO-0.9.6/conf/pio-env.sh</code> and change the <code>SPARK_HOME</code> variable to point to your own Apache Spark installation.</p></div><h3 id='storage-setup' class='header-anchors'>Storage Setup</h3><h4 id='postgresql-setup' class='header-anchors'>PostgreSQL Setup</h4><p>Setting up <a href="http://www.postgresql.org/">PostgreSQL</a> to work with PredictionIO.</p><p>Make sure you have PostgreSQL installed. For Mac Users, <a href="brew.sh">Homebrew</a> is recommended and can be used as</p><div class="highlight shell"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1</pre></td><td class="code"><pre><span class="gp">$ </span>brew install postgresql
+</pre></td></tr></tbody></table> </div> <p>or on Ubuntu: <code> apt-get install postgresql-9.4 </code></p><p>Now that PostgreSQL is installed use the following comands</p><p><code>$ createdb pio</code> </p><p>If you get an error of the form <code>could not connect to server: No such file or directory</code>, then you must first start the server manually,:</p><p><code>$ pg_ctl -D /usr/local/var/postgres -l /usr/local/var/postgres/server.log start</code></p><p>Finally use the command:</p><p>`$ psql -c "create user pio with password 'pio'"</p><p>Your configuration in <code>pio-env.sh</code> is now compatible to run with PostgreSQL.</p><h4 id='hbase-and-elasticsearch-setup' class='header-anchors'>HBase and Elasticsearch Setup</h4><h5 id='elasticsearch-setup' class='header-anchors'>Elasticsearch Setup</h5><div class="alert-message warning"><p>You may skip this section if you are using PostgreSQL or MySQL.</p></div><p><a href="http://www.elasticsearch.org/">Elasticsearch
</a> is the default metadata store for PredictionIO. Download and extract it.</p><div class="highlight shell"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1
+2</pre></td><td class="code"><pre><span class="gp">$ </span>wget https://download.elasticsearch.org/elasticsearch/elasticsearch/elasticsearch-1.4.4.tar.gz
+<span class="gp">$ </span>tar zxvfC elasticsearch-1.4.4.tar.gz PredictionIO-0.9.6/vendors
+</pre></td></tr></tbody></table> </div> <div class="alert-message info"><p>If you decide to install Elasticsearch to another location, you must edit <code>PredictionIO-0.9.6/conf/pio-env.sh</code> and change the <code>PIO_STORAGE_SOURCES_ELASTICSEARCH_HOME</code> variable to point to your own Elasticsearch installation.</p></div><div class="alert-message info"><p>If you are using a shared network, change the <code>network.host</code> line in <code>PredictionIO-0.9.6/vendors/elasticsearch-1.4.4/config/elasticsearch.yml</code> to <code>network.host: 127.0.0.1</code> because by default, Elasticsearch looks for other machines on the network upon setup and you may run into weird errors if there are other machines that is also running Elasticsearch.</p></div><p>If you are not using the default setting at <code>localhost</code>, you may change the following in <code>PredictionIO-0.9.6/conf/pio-env.sh</code> to fit your setup.</p><div class="highlight shell"><table style="border-spacing: 0"
><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1
+2
+3</pre></td><td class="code"><pre><span class="nv">PIO_STORAGE_SOURCES_ELASTICSEARCH_TYPE</span><span class="o">=</span>elasticsearch
+<span class="nv">PIO_STORAGE_SOURCES_ELASTICSEARCH_HOSTS</span><span class="o">=</span>localhost
+<span class="nv">PIO_STORAGE_SOURCES_ELASTICSEARCH_PORTS</span><span class="o">=</span>9300
+</pre></td></tr></tbody></table> </div> <h5 id='<a-name="hbase"></a>hbase-setup' class='header-anchors' ><a name="hbase"></a>HBase Setup</h5><div class="alert-message warning"><p>You may skip this section if you are using PostgreSQL or MySQL.</p></div><p><a href="http://hbase.apache.org">HBase</a> is the default event data store for PredictionIO. Download and extract it.</p><div class="highlight shell"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1
+2</pre></td><td class="code"><pre><span class="gp">$ </span>wget http://archive.apache.org/dist/hbase/hbase-1.0.0/hbase-1.0.0-bin.tar.gz
+<span class="gp">$ </span>tar zxvfC hbase-1.0.0-bin.tar.gz PredictionIO-0.9.6/vendors
+</pre></td></tr></tbody></table> </div> <div class="alert-message info"><p>If you decide to install HBase to another location, you must edit <code>PredictionIO-0.9.6/conf/pio-env.sh</code> and change the <code>PIO_STORAGE_SOURCES_HBASE_HOME</code> variable to point to your own HBase installation.</p></div><p>You will need to at least add a minimal configuration to HBase to start it in standalone mode. Details can be found <a href="http://hbase.apache.org/book/quickstart.html">here</a>. Here, we are showing a sample minimal configuration.</p><div class="alert-message info"><p>For production deployment, run a fully distributed HBase configuration.</p></div><p>Edit <code>PredictionIO-0.9.6/vendors/hbase-1.0.0/conf/hbase-site.xml</code>.</p><div class="highlight shell"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1
+2
+3
+4
+5
+6
+7
+8
+9
+10</pre></td><td class="code"><pre><configuration>
+ <property>
+ <name>hbase.rootdir</name>
+ <value>file:///home/abc/PredictionIO-0.9.6/vendors/hbase-1.0.0/data</value>
+ </property>
+ <property>
+ <name>hbase.zookeeper.property.dataDir</name>
+ <value>/home/abc/PredictionIO-0.9.6/vendors/hbase-1.0.0/zookeeper</value>
+ </property>
+</configuration>
+</pre></td></tr></tbody></table> </div> <div class="alert-message info"><p>HBase will create <code>hbase.rootdir</code> automatically to store its data.</p></div><p>Edit <code>PredictionIO-0.9.6/vendors/hbase-1.0.0/conf/hbase-env.sh</code> to set <code>JAVA_HOME</code> for the cluster. For example:</p><div class="highlight shell"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1</pre></td><td class="code"><pre><span class="nb">export </span><span class="nv">JAVA_HOME</span><span class="o">=</span>/usr/lib/jvm/java-8-oracle/jre
+</pre></td></tr></tbody></table> </div> <p>For Mac users, use this instead (change <code>1.8</code> to <code>1.7</code> if you have Java 7 installed):</p><div class="highlight shell"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1</pre></td><td class="code"><pre><span class="nb">export </span><span class="nv">JAVA_HOME</span><span class="o">=</span><span class="sb">`</span>/usr/libexec/java_home -v 1.8<span class="sb">`</span>
+</pre></td></tr></tbody></table> </div> <p>In addition, you must set your environment variable <code>JAVA_HOME</code>. For example, in <code>/home/abc/.bashrc</code> add the following line:</p><div class="highlight shell"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1</pre></td><td class="code"><pre><span class="nb">export </span><span class="nv">JAVA_HOME</span><span class="o">=</span>/usr/lib/jvm/java-8-oracle
+</pre></td></tr></tbody></table> </div> <h3 id='start-predictionio-and-dependent-services' class='header-anchors'>Start PredictionIO and Dependent Services</h3><div class="alert-message warning"><p>If you are using PostgreSQL or MySQL, skip <code>pio-start-all</code> and <code>pio-stop-all</code>, and do <code>PredictionIO-0.9.6/bin/pio eventserver &</code> instead.</p></div><p>Simply do <code>PredictionIO-0.9.6/bin/pio-start-all</code> and you should see something similar to the following:</p><div class="highlight shell"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1
+2
+3
+4
+5
+6
+7</pre></td><td class="code"><pre><span class="gp">$ </span>PredictionIO-0.9.6/bin/pio-start-all
+Starting Elasticsearch...
+Starting HBase...
+starting master, logging to /home/abc/PredictionIO-0.9.6/vendors/hbase-1.0.0/bin/../logs/hbase-abc-master-yourhost.local.out
+Waiting 10 seconds <span class="k">for </span>HBase to fully initialize...
+Starting PredictionIO Event Server...
+<span class="err">$</span>
+</pre></td></tr></tbody></table> </div> <p>You may use <code>jps</code> to verify that you have everything started:</p><div class="highlight shell"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1
+2
+3
+4
+5
+6</pre></td><td class="code"><pre><span class="gp">$ </span>jps -l
+15344 org.apache.hadoop.hbase.master.HMaster
+15409 io.prediction.tools.console.Console
+15256 org.elasticsearch.bootstrap.Elasticsearch
+15469 sun.tools.jps.Jps
+<span class="err">$</span>
+</pre></td></tr></tbody></table> </div> <p>A running setup will have these up and running:</p> <ul> <li>io.prediction.tools.console.Console</li> <li>org.apache.hadoop.hbase.master.HMaster</li> <li>org.elasticsearch.bootstrap.Elasticsearch</li> </ul> <p>At any time, you can run <code>PredictionIO-0.9.6/bin/pio status</code> to check the status of the dependencies.</p><p>Now you have installed everything you need!</p><p>You can proceed to <a href="/start/download">Choosing an Engine Template</a>, or continue the QuickStart guide of the Engine template if you have already chosen one.</p> </div></div></div></div><footer><div class="container"><div class="seperator"></div><div class="row"><div class="col-md-4 col-md-push-8 col-xs-12"><div class="subscription-form-wrapper"><h4>Subscribe to our Newsletter</h4><form class="ajax-form" id="subscribe-form" method="POST" action="https://script.google.com/macros/s/AKfycbwhzeKCQJjQ52eVAqNT_vcklH07OITUO7wzOMDXvK6EGAWgaZgF/exec"><input class="requi
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<div class="row"><div class="col-md-9 col-sm-11 col-xs-11"><div class="hidden-md hidden-lg" id="mobile-page-heading-wrapper"><p>PredictionIO Docs</p><h4>Installing PredictionIO with Vagrant (VirtualBox)</h4></div><h4 class="hidden-sm hidden-xs">PredictionIO Docs</h4></div><div class="col-md-3 col-sm-1 col-xs-1 hidden-md hidden-lg"><img id="left-menu-indicator" src="/images/icons/down-arrow-dfe9f7fe.png"/></div><div class="col-md-3 col-sm-12 col-xs-12 swiftype-wrapper"><div class="swiftype"><form class="search-form"><img class="search-box-toggler hidden-xs hidden-sm" src="/images/icons/search-glass-704bd4ff.png"/><div class="search-box"><img src="/images/icons/search-glass-704bd4ff.png"/><input type="text" id="st-search-input" class="st-search-input" placeholder="Search Doc..."/></div><img class="swiftype-row-hider hidden-md hidden-lg" src="/images/icons/drawer-toggle-active-fcbef12a.png"/></form></div></div><div class="mobile-left-menu-toggler hidden-md hidden-lg"></div></div></div>
</div><div id="page" class="container-fluid"><div class="row"><div id="left-menu-wrapper" class="col-md-3"><nav id="nav-main"><ul><li class="level-1"><a class="expandible" href="/"><span>Apache PredictionIO (incubating) Documentation</span></a><ul><li class="level-2"><a class="final" href="/"><span>Welcome to Apache PredictionIO (incubating)</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Getting Started</span></a><ul><li class="level-2"><a class="final" href="/start/"><span>A Quick Intro</span></a></li><li class="level-2"><a class="final" href="/install/"><span>Installing Apache PredictionIO (incubating)</span></a></li><li class="level-2"><a class="final" href="/start/download/"><span>Downloading an Engine Template</span></a></li><li class="level-2"><a class="final" href="/start/deploy/"><span>Deploying Your First Engine</span></a></li><li class="level-2"><a class="final" href="/start/customize/"><span>Customizing the Engine</span></a></li></ul></l
i><li class="level-1"><a class="expandible" href="#"><span>Integrating with Your App</span></a><ul><li class="level-2"><a class="final" href="/appintegration/"><span>App Integration Overview</span></a></li><li class="level-2"><a class="expandible" href="/sdk/"><span>List of SDKs</span></a><ul><li class="level-3"><a class="final" href="/sdk/java/"><span>Java & Android SDK</span></a></li><li class="level-3"><a class="final" href="/sdk/php/"><span>PHP SDK</span></a></li><li class="level-3"><a class="final" href="/sdk/python/"><span>Python SDK</span></a></li><li class="level-3"><a class="final" href="/sdk/ruby/"><span>Ruby SDK</span></a></li><li class="level-3"><a class="final" href="/sdk/community/"><span>Community Powered SDKs</span></a></li></ul></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Deploying an Engine</span></a><ul><li class="level-2"><a class="final" href="/deploy/"><span>Deploying as a Web Service</span></a></li><li class="level-2"><a class="final
" href="/cli/#engine-commands"><span>Engine Command-line Interface</span></a></li><li class="level-2"><a class="final" href="/deploy/engineparams/"><span>Setting Engine Parameters</span></a></li><li class="level-2"><a class="final" href="/deploy/enginevariants/"><span>Deploying Multiple Engine Variants</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Customizing an Engine</span></a><ul><li class="level-2"><a class="final" href="/customize/"><span>Learning DASE</span></a></li><li class="level-2"><a class="final" href="/customize/dase/"><span>Implement DASE</span></a></li><li class="level-2"><a class="final" href="/customize/troubleshooting/"><span>Troubleshooting Engine Development</span></a></li><li class="level-2"><a class="final" href="/api/current/#package"><span>Engine Scala APIs</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Collecting and Analyzing Data</span></a><ul><li class="level-2"><a class="final" href="
/datacollection/"><span>Event Server Overview</span></a></li><li class="level-2"><a class="final" href="/cli/#event-server-commands"><span>Event Server Command-line Interface</span></a></li><li class="level-2"><a class="final" href="/datacollection/eventapi/"><span>Collecting Data with REST/SDKs</span></a></li><li class="level-2"><a class="final" href="/datacollection/eventmodel/"><span>Events Modeling</span></a></li><li class="level-2"><a class="final" href="/datacollection/webhooks/"><span>Unifying Multichannel Data with Webhooks</span></a></li><li class="level-2"><a class="final" href="/datacollection/channel/"><span>Channel</span></a></li><li class="level-2"><a class="final" href="/datacollection/batchimport/"><span>Importing Data in Batch</span></a></li><li class="level-2"><a class="final" href="/datacollection/analytics/"><span>Using Analytics Tools</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Choosing an Algorithm(s)</span></a><ul><li clas
s="level-2"><a class="final" href="/algorithm/"><span>Built-in Algorithm Libraries</span></a></li><li class="level-2"><a class="final" href="/algorithm/switch/"><span>Switching to Another Algorithm</span></a></li><li class="level-2"><a class="final" href="/algorithm/multiple/"><span>Combining Multiple Algorithms</span></a></li><li class="level-2"><a class="final" href="/algorithm/custom/"><span>Adding Your Own Algorithms</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>ML Tuning and Evaluation</span></a><ul><li class="level-2"><a class="final" href="/evaluation/"><span>Overview</span></a></li><li class="level-2"><a class="final" href="/evaluation/paramtuning/"><span>Hyperparameter Tuning</span></a></li><li class="level-2"><a class="final" href="/evaluation/evaluationdashboard/"><span>Evaluation Dashboard</span></a></li><li class="level-2"><a class="final" href="/evaluation/metricchoose/"><span>Choosing Evaluation Metrics</span></a></li><li class="lev
el-2"><a class="final" href="/evaluation/metricbuild/"><span>Building Evaluation Metrics</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>System Architecture</span></a><ul><li class="level-2"><a class="final" href="/system/"><span>Architecture Overview</span></a></li><li class="level-2"><a class="final" href="/system/anotherdatastore/"><span>Using Another Data Store</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Engine Template Gallery</span></a><ul><li class="level-2"><a class="final" href="http://templates.prediction.io"><span>Browse</span></a></li><li class="level-2"><a class="final" href="/community/submit-template/"><span>Submit your Engine as a Template</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Demo Tutorials</span></a><ul><li class="level-2"><a class="final" href="/demo/tapster/"><span>Comics Recommendation Demo</span></a></li><li class="level-2"><a class="final" href="
/demo/community/"><span>Community Contributed Demo</span></a></li><li class="level-2"><a class="final" href="/demo/textclassification/"><span>Text Classification Engine Tutorial</span></a></li></ul></li><li class="level-1"><a class="expandible" href="/community/"><span>Getting Involved</span></a><ul><li class="level-2"><a class="final" href="/community/contribute-code/"><span>Contribute Code</span></a></li><li class="level-2"><a class="final" href="/community/contribute-documentation/"><span>Contribute Documentation</span></a></li><li class="level-2"><a class="final" href="/community/contribute-sdk/"><span>Contribute a SDK</span></a></li><li class="level-2"><a class="final" href="/community/contribute-webhook/"><span>Contribute a Webhook</span></a></li><li class="level-2"><a class="final" href="/community/projects/"><span>Community Projects</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Getting Help</span></a><ul><li class="level-2"><a class="final
" href="/resources/faq/"><span>FAQs</span></a></li><li class="level-2"><a class="final" href="/support/"><span>Community Support</span></a></li><li class="level-2"><a class="final" href="/support/#enterprise-support"><span>Enterprise Support</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Resources</span></a><ul><li class="level-2"><a class="final" href="/resources/intellij/"><span>Developing Engines with IntelliJ IDEA</span></a></li><li class="level-2"><a class="final" href="/resources/upgrade/"><span>Upgrade Instructions</span></a></li><li class="level-2"><a class="final" href="/resources/glossary/"><span>Glossary</span></a></li></ul></li></ul></nav></div><div class="col-md-9 col-sm-12"><div class="content-header hidden-md hidden-lg"><div id="page-title"><h1>Installing PredictionIO with Vagrant (VirtualBox)</h1></div></div><div id="table-of-content-wrapper"><h5>On this page</h5><aside id="table-of-contents"><ul> <li> <a href="#install-virtualbox">
Install VirtualBox</a> </li> <li> <a href="#install-vagrant">Install Vagrant</a> </li> <li> <a href="#bring-up-predictoinio-vm-with-vagrant">Bring up PredictoinIO VM with Vagrant</a> </li> <li> <a href="#using-the-predictionio-vm">Using the PredictionIO VM</a> </li> </ul> </aside><hr/><a id="edit-page-link" href="https://github.com/apache/incubator-predictionio/tree/livedoc/docs/manual/source/install/install-vagrant.html.md.erb"><img src="/images/icons/edit-pencil-d6c1bb3d.png"/>Edit this page</a></div><div class="content-header hidden-sm hidden-xs"><div id="page-title"><h1>Installing PredictionIO with Vagrant (VirtualBox)</h1></div></div><div class="content"><div class="alert-message warning"><p>Running PredictionIO with Vagrant is intended for the purposes of simple tests in an isolated environment. Due to resource limitation and overhead of virtual machine (VM), it runs much more slowly or may encounter memory issue. We recommend using Linux or Mac machine for serious usage.</p><
/div><h2 id='install-virtualbox' class='header-anchors'>Install VirtualBox</h2><p>If you don't have VirtualBox installed, please follow the instructions in the <a href="https://www.virtualbox.org/wiki/Downloads">VirtualBox site</a> to download and install it. After installation is done, you don't need to setup anything in Virtual Box. Vagrant will do it for you later.</p><h2 id='install-vagrant' class='header-anchors'>Install Vagrant</h2><p>If you don't have Vagrant installed, please follow the instructions in the the <a href="https://www.vagrantup.com/downloads.html">Vagrant site</a> to download and install it.</p><h2 id='bring-up-predictoinio-vm-with-vagrant' class='header-anchors'>Bring up PredictoinIO VM with Vagrant</h2><p>Get the latest vagrant setup from github and make sure in master branch:</p><div class="highlight shell"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1
+2
+3</pre></td><td class="code"><pre><span class="gp">$ </span>git clone https://github.com/PredictionIO/PredictionIO-Vagrant.git
+<span class="gp">$ </span><span class="nb">cd </span>PredictionIO-Vagrant/
+<span class="gp">$ </span>git checkout master
+</pre></td></tr></tbody></table> </div> <p>Inside the directory <code>PredictionIO-Vagrant/</code>, you will find a file named <code>Vagrantfile</code> which is the configuration file used by Vagrant to setup the VM. You may modify this file if you want to change the VM configuration.</p><p>For example, if you want to change the memory of the VM, you can locate the following line in the <code>Vagrantfile</code> and change the value passed to the <code>memory</code> parameter (default is 2048MB):</p><div class="highlight shell"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1</pre></td><td class="code"><pre> v.customize <span class="o">[</span><span class="s2">"modifyvm"</span>, :id, <span class="s2">"--cpuexecutioncap"</span>, <span class="s2">"90"</span>, <span class="s2">"--memory"</span>, <span class="s2">"2048"</span><span class="o">]</span>
+</pre></td></tr></tbody></table> </div> <p>In the directory <code>PredictionIO-Vagrant/</code>, bring up PredictionIO VM by running:</p><div class="highlight shell"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1</pre></td><td class="code"><pre><span class="gp">$ </span>vagrant up
+</pre></td></tr></tbody></table> </div> <div class="alert-message info"><p>When you run <code>vagrant up</code> for the first time, it will download the base box ubuntu/trusty64 if you don't have it. Then it will also install all necessary libraries and setup PredictionIO in the virtual machine.</p></div><p>When it finishes successfully, you should see somthing like the following:</p><div class="highlight shell"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1
+2
+3
+4
+5
+6
+7
+8
+9
+10
+11</pre></td><td class="code"><pre><span class="gp">==> </span>default: Installation <span class="k">done</span>!
+<span class="gp">==> </span>default: --------------------------------------------------------------------------------
+<span class="gp">==> </span>default: Installation of PredictionIO 0.9.6 <span class="nb">complete</span>!
+<span class="gp">==> </span>default: IMPORTANT: You still have to start PredictionIO and dependencies manually:
+<span class="gp">==> </span>default: Run: <span class="s1">'pio-start-all'</span>
+<span class="gp">==> </span>default: Check the status with: <span class="s1">'pio status'</span>
+<span class="gp">==> </span>default: Use: <span class="s1">'pio [train|deploy|...]'</span> commands
+<span class="gp">==> </span>default: Please report any problems to: support@prediction.io
+<span class="gp">==> </span>default: Documentation at: http://docs.prediction.io
+<span class="gp">==> </span>default: --------------------------------------------------------------------------------
+<span class="gp">==> </span>default: Finish PredictionIO installation.
+</pre></td></tr></tbody></table> </div> <p>That's it! Now you have a PredictionIO VM running!</p><p>Please see the following notes regarding how to use PredictionIO VM with vagrant.</p><h2 id='using-the-predictionio-vm' class='header-anchors'>Using the PredictionIO VM</h2><h3 id='login-to-the-vm' class='header-anchors'>Login to the VM</h3><p>You could ssh to the VM by running the following from your host machine in the same directory where you run <code>vagrant up</code> (i.e. PredictionIO-Vagrant/)</p><div class="highlight shell"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1</pre></td><td class="code"><pre><span class="gp">$ </span>vagrant ssh
+</pre></td></tr></tbody></table> </div> <p>Then your console prompt becomes something like the following, which means you have logged into the VM:</p><div class="highlight shell"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1</pre></td><td class="code"><pre>vagrant@vagrant-ubuntu-trusty-64:~<span class="err">$</span>
+</pre></td></tr></tbody></table> </div> <p>One you've logged into the VM, you can proceed to <a href="/start/download">Choosing an Engine Template</a> or continue the QuickStart of the Engine template you have chosen.</p><h3 id='shutdown-and-bring-up-predictionio-vm-again' class='header-anchors'>Shutdown and bring up PredictionIO VM again</h3><p>When you are not using PredictionIO VM, you should shut down VM properly, by running the following <strong>in the host machine</strong> (not inside VM):</p><div class="highlight shell"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1</pre></td><td class="code"><pre><span class="gp">$ </span>vagrant halt
+</pre></td></tr></tbody></table> </div> <div class="alert-message warning"><p>If you didn't shut down VM properly or you ran <code>vagrant suspend</code>, the VM may go to suspend state. HBase may not be running propoerly next time when you run <code>vagrant up.</code> In this case, you can always run <code>vagrant halt</code> to do a clean shutdown first before run <code>vagrant up</code> again.</p></div><p>Then you can run <code>vagrant up</code> again later to bring up the PredicitonIO VM again.</p><div class="highlight shell"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1</pre></td><td class="code"><pre><span class="gp">$ </span>vagrant up
+</pre></td></tr></tbody></table> </div> <p>When it's ready, you should see the following:</p><div class="highlight shell"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1
+2
+3
+4
+5
+6</pre></td><td class="code"><pre><span class="gp">==> </span>default: --------------------------------------------------------------------------------
+<span class="gp">==> </span>default: PredictionIO VM is up!
+<span class="gp">==> </span>default: You could run <span class="s1">'pio status'</span> inside VM <span class="o">(</span><span class="s1">'vagrant ssh'</span> to VM first<span class="o">)</span> to confirm <span class="k">if </span>PredictionIO is ready.
+<span class="gp">==> </span>default: IMPORTANT: You still have to start the eventserver manually <span class="o">(</span>inside VM<span class="o">)</span>:
+<span class="gp">==> </span>default: Run: <span class="s1">'pio eventserver'</span>
+<span class="gp">==> </span>default: --------------------------------------------------------------------------------
+</pre></td></tr></tbody></table> </div> </div></div></div></div><footer><div class="container"><div class="seperator"></div><div class="row"><div class="col-md-4 col-md-push-8 col-xs-12"><div class="subscription-form-wrapper"><h4>Subscribe to our Newsletter</h4><form class="ajax-form" id="subscribe-form" method="POST" action="https://script.google.com/macros/s/AKfycbwhzeKCQJjQ52eVAqNT_vcklH07OITUO7wzOMDXvK6EGAWgaZgF/exec"><input class="required underlined-input" type="email" placeholder="Your email address" name="subscription_email" id="subscription_email"/><input class="pill-button" value="SUBSCRIBE" type="submit" data-state-normal="SUBSCRIBE" data-state-sucess="SUBSCRIBED!" data-state-loading="SENDING..." onclick="t($('#subscription_email').val());"/><p class="result"></p></form></div></div><div class="col-md-2 col-md-pull-4 col-xs-6 footer-link-column"><div class="footer-link-column-row"><h4>Community</h4><ul><li><a href="//docs.prediction.io/install/" target="blank">Download</a>
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class="container-fluid"><div class="row"><div id="left-menu-wrapper" class="col-md-3"><nav id="nav-main"><ul><li class="level-1"><a class="expandible" href="/"><span>Apache PredictionIO (incubating) Documentation</span></a><ul><li class="level-2"><a class="final" href="/"><span>Welcome to Apache PredictionIO (incubating)</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Getting Started</span></a><ul><li class="level-2"><a class="final" href="/start/"><span>A Quick Intro</span></a></li><li class="level-2"><a class="final" href="/install/"><span>Installing Apache PredictionIO (incubating)</span></a></li><li class="level-2"><a class="final" href="/start/download/"><span>Downloading an Engine Template</span></a></li><li class="level-2"><a class="final" href="/start/deploy/"><span>Deploying Your First Engine</span></a></li><li class="level-2"><a class="final" href="/start/customize/"><span>Customizing the Engine</span></a></li></ul></li><li class="level-1
"><a class="expandible" href="#"><span>Integrating with Your App</span></a><ul><li class="level-2"><a class="final" href="/appintegration/"><span>App Integration Overview</span></a></li><li class="level-2"><a class="expandible" href="/sdk/"><span>List of SDKs</span></a><ul><li class="level-3"><a class="final" href="/sdk/java/"><span>Java & Android SDK</span></a></li><li class="level-3"><a class="final" href="/sdk/php/"><span>PHP SDK</span></a></li><li class="level-3"><a class="final" href="/sdk/python/"><span>Python SDK</span></a></li><li class="level-3"><a class="final" href="/sdk/ruby/"><span>Ruby SDK</span></a></li><li class="level-3"><a class="final" href="/sdk/community/"><span>Community Powered SDKs</span></a></li></ul></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Deploying an Engine</span></a><ul><li class="level-2"><a class="final" href="/deploy/"><span>Deploying as a Web Service</span></a></li><li class="level-2"><a class="final" href="/cli/#engine
-commands"><span>Engine Command-line Interface</span></a></li><li class="level-2"><a class="final" href="/deploy/engineparams/"><span>Setting Engine Parameters</span></a></li><li class="level-2"><a class="final" href="/deploy/enginevariants/"><span>Deploying Multiple Engine Variants</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Customizing an Engine</span></a><ul><li class="level-2"><a class="final" href="/customize/"><span>Learning DASE</span></a></li><li class="level-2"><a class="final" href="/customize/dase/"><span>Implement DASE</span></a></li><li class="level-2"><a class="final" href="/customize/troubleshooting/"><span>Troubleshooting Engine Development</span></a></li><li class="level-2"><a class="final" href="/api/current/#package"><span>Engine Scala APIs</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Collecting and Analyzing Data</span></a><ul><li class="level-2"><a class="final" href="/datacollection/"><s
pan>Event Server Overview</span></a></li><li class="level-2"><a class="final" href="/cli/#event-server-commands"><span>Event Server Command-line Interface</span></a></li><li class="level-2"><a class="final" href="/datacollection/eventapi/"><span>Collecting Data with REST/SDKs</span></a></li><li class="level-2"><a class="final" href="/datacollection/eventmodel/"><span>Events Modeling</span></a></li><li class="level-2"><a class="final" href="/datacollection/webhooks/"><span>Unifying Multichannel Data with Webhooks</span></a></li><li class="level-2"><a class="final" href="/datacollection/channel/"><span>Channel</span></a></li><li class="level-2"><a class="final" href="/datacollection/batchimport/"><span>Importing Data in Batch</span></a></li><li class="level-2"><a class="final" href="/datacollection/analytics/"><span>Using Analytics Tools</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Choosing an Algorithm(s)</span></a><ul><li class="level-2"><a class
="final" href="/algorithm/"><span>Built-in Algorithm Libraries</span></a></li><li class="level-2"><a class="final" href="/algorithm/switch/"><span>Switching to Another Algorithm</span></a></li><li class="level-2"><a class="final" href="/algorithm/multiple/"><span>Combining Multiple Algorithms</span></a></li><li class="level-2"><a class="final" href="/algorithm/custom/"><span>Adding Your Own Algorithms</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>ML Tuning and Evaluation</span></a><ul><li class="level-2"><a class="final" href="/evaluation/"><span>Overview</span></a></li><li class="level-2"><a class="final" href="/evaluation/paramtuning/"><span>Hyperparameter Tuning</span></a></li><li class="level-2"><a class="final" href="/evaluation/evaluationdashboard/"><span>Evaluation Dashboard</span></a></li><li class="level-2"><a class="final" href="/evaluation/metricchoose/"><span>Choosing Evaluation Metrics</span></a></li><li class="level-2"><a class="fina
l" href="/evaluation/metricbuild/"><span>Building Evaluation Metrics</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>System Architecture</span></a><ul><li class="level-2"><a class="final" href="/system/"><span>Architecture Overview</span></a></li><li class="level-2"><a class="final" href="/system/anotherdatastore/"><span>Using Another Data Store</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Engine Template Gallery</span></a><ul><li class="level-2"><a class="final" href="http://templates.prediction.io"><span>Browse</span></a></li><li class="level-2"><a class="final" href="/community/submit-template/"><span>Submit your Engine as a Template</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Demo Tutorials</span></a><ul><li class="level-2"><a class="final" href="/demo/tapster/"><span>Comics Recommendation Demo</span></a></li><li class="level-2"><a class="final" href="/demo/community/"><s
pan>Community Contributed Demo</span></a></li><li class="level-2"><a class="final" href="/demo/textclassification/"><span>Text Classification Engine Tutorial</span></a></li></ul></li><li class="level-1"><a class="expandible" href="/community/"><span>Getting Involved</span></a><ul><li class="level-2"><a class="final" href="/community/contribute-code/"><span>Contribute Code</span></a></li><li class="level-2"><a class="final" href="/community/contribute-documentation/"><span>Contribute Documentation</span></a></li><li class="level-2"><a class="final" href="/community/contribute-sdk/"><span>Contribute a SDK</span></a></li><li class="level-2"><a class="final" href="/community/contribute-webhook/"><span>Contribute a Webhook</span></a></li><li class="level-2"><a class="final" href="/community/projects/"><span>Community Projects</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Getting Help</span></a><ul><li class="level-2"><a class="final" href="/resources/f
aq/"><span>FAQs</span></a></li><li class="level-2"><a class="final" href="/support/"><span>Community Support</span></a></li><li class="level-2"><a class="final" href="/support/#enterprise-support"><span>Enterprise Support</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Resources</span></a><ul><li class="level-2"><a class="final" href="/resources/intellij/"><span>Developing Engines with IntelliJ IDEA</span></a></li><li class="level-2"><a class="final" href="/resources/upgrade/"><span>Upgrade Instructions</span></a></li><li class="level-2"><a class="final" href="/resources/glossary/"><span>Glossary</span></a></li></ul></li></ul></nav></div><div class="col-md-9 col-sm-12"><div class="content-header hidden-md hidden-lg"><div id="page-title"><h1>Launching PredictionIO on AWS</h1></div></div><div id="table-of-content-wrapper"><h5>On this page</h5><aside id="table-of-contents"><ul> <li> <a href="#prerequisites">Prerequisites</a> </li> <li> <a href="#access
-aws-marketplace">Access AWS Marketplace</a> </li> <li> <a href="#using-1-click-launch">Using 1-Click Launch</a> </li> <li> <a href="#setting-security-group">Setting Security Group</a> </li> <li> <a href="#start-using-predictionio">Start Using PredictionIO</a> </li> </ul> </aside><hr/><a id="edit-page-link" href="https://github.com/apache/incubator-predictionio/tree/livedoc/docs/manual/source/install/launch-aws.html.md.erb"><img src="/images/icons/edit-pencil-d6c1bb3d.png"/>Edit this page</a></div><div class="content-header hidden-sm hidden-xs"><div id="page-title"><h1>Launching PredictionIO on AWS</h1></div></div><div class="content"><p>Deploying PredictionIO on Amazon Web Services is extremely easy thanks to AWS Marketplace. As long as you have access to AWS, you can launch a ready-to-use PredictionIO Amazon EC2 instance with a single click.</p><h2 id='prerequisites' class='header-anchors'>Prerequisites</h2> <ul> <li>Amazon Web Services account</li> <li>Amazon EC2</li> </ul> <h2 i
d='access-aws-marketplace' class='header-anchors'>Access AWS Marketplace</h2><p>Visit <a href="https://aws.amazon.com/marketplace/pp/B00RPIFSYS/">PredictionIO product's page on AWS Marketplace</a> and sign in with your AWS account.</p><h2 id='using-1-click-launch' class='header-anchors'>Using 1-Click Launch</h2><p>You should see the following screen after you have logged in.</p><p><img alt="alt text" src="/images/awsm-product-1be37f9d.png"/></p><p>Under the big yellow "Continue" botton, select the region where you want to launch the PredictionIO EC2 instance, then click "Continue".</p><p><img alt="alt text" src="/images/awsm-1click-9d9ac1c4.png"/></p><p>Review your instance's settings before launching. For quick prototyping work, we recommend using the "memory optimized" instances for the cheapest memory configurations at least the "Memory Optimized R3 (r3.large)" or for larger datasets the "(r3.xlarge)".</p><h2 id='setting-s
ecurity-group' class='header-anchors'>Setting Security Group</h2><p>The default security group, marked by "AutogenByAWSMP", has the following ports opened to public:</p> <ul> <li>22 (SSH)</li> <li>7070 (PredictionIO Event Server)</li> <li>8000 (PredictionIO Server)</li> <li>8080 (Spark Master)</li> <li>9200 (Elasticsearch)</li> </ul> <h2 id='start-using-predictionio' class='header-anchors'>Start Using PredictionIO</h2><p>It may take a few minutes after the EC2 instance has launched for all PredictionIO components to become ready. When they are ready, you may connect to your instance, see <a href="http://docs.aws.amazon.com/AWSEC2/latest/UserGuide/ec2-connect-to-instance-linux.html">AWS documentation</a> for more details.</p><p>Once you connect to your instance, you can find PredictionIO at <code>/opt/PredictionIO</code> and the binary command path is <code>/opt/PredictionIO/bin</code>.</p><p>You can proceed to <a href="/start/download">Choosing an Engine Template</a>, or c
ontinue the QuickStart guide of the Engine template if you have already chosen one.</p> <div class="alert-message note"><p>The AWS instance will have all PredictionIO components automatically started for you, so you could safely skip the <strong>pio-start-all</strong> command as described in QuickStart.</p></div></div></div></div></div><footer><div class="container"><div class="seperator"></div><div class="row"><div class="col-md-4 col-md-push-8 col-xs-12"><div class="subscription-form-wrapper"><h4>Subscribe to our Newsletter</h4><form class="ajax-form" id="subscribe-form" method="POST" action="https://script.google.com/macros/s/AKfycbwhzeKCQJjQ52eVAqNT_vcklH07OITUO7wzOMDXvK6EGAWgaZgF/exec"><input class="required underlined-input" type="email" placeholder="Your email address" name="subscription_email" id="subscription_email"/><input class="pill-button" value="SUBSCRIBE" type="submit" data-state-normal="SUBSCRIBE" data-state-sucess="SUBSCRIBED!" data-state-loading="SENDING..." onclic
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ainer-fluid"><div class="row"><div id="left-menu-wrapper" class="col-md-3"><nav id="nav-main"><ul><li class="level-1"><a class="expandible" href="/"><span>Apache PredictionIO (incubating) Documentation</span></a><ul><li class="level-2"><a class="final" href="/"><span>Welcome to Apache PredictionIO (incubating)</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Getting Started</span></a><ul><li class="level-2"><a class="final" href="/start/"><span>A Quick Intro</span></a></li><li class="level-2"><a class="final" href="/install/"><span>Installing Apache PredictionIO (incubating)</span></a></li><li class="level-2"><a class="final" href="/start/download/"><span>Downloading an Engine Template</span></a></li><li class="level-2"><a class="final" href="/start/deploy/"><span>Deploying Your First Engine</span></a></li><li class="level-2"><a class="final" href="/start/customize/"><span>Customizing the Engine</span></a></li></ul></li><li class="level-1"><a class="
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rver Overview</span></a></li><li class="level-2"><a class="final" href="/cli/#event-server-commands"><span>Event Server Command-line Interface</span></a></li><li class="level-2"><a class="final" href="/datacollection/eventapi/"><span>Collecting Data with REST/SDKs</span></a></li><li class="level-2"><a class="final" href="/datacollection/eventmodel/"><span>Events Modeling</span></a></li><li class="level-2"><a class="final" href="/datacollection/webhooks/"><span>Unifying Multichannel Data with Webhooks</span></a></li><li class="level-2"><a class="final" href="/datacollection/channel/"><span>Channel</span></a></li><li class="level-2"><a class="final" href="/datacollection/batchimport/"><span>Importing Data in Batch</span></a></li><li class="level-2"><a class="final" href="/datacollection/analytics/"><span>Using Analytics Tools</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Choosing an Algorithm(s)</span></a><ul><li class="level-2"><a class="final" hre
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s="container-fluid"><div class="row"><div id="left-menu-wrapper" class="col-md-3"><nav id="nav-main"><ul><li class="level-1"><a class="expandible" href="/"><span>Apache PredictionIO (incubating) Documentation</span></a><ul><li class="level-2"><a class="final" href="/"><span>Welcome to Apache PredictionIO (incubating)</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Getting Started</span></a><ul><li class="level-2"><a class="final" href="/start/"><span>A Quick Intro</span></a></li><li class="level-2"><a class="final" href="/install/"><span>Installing Apache PredictionIO (incubating)</span></a></li><li class="level-2"><a class="final" href="/start/download/"><span>Downloading an Engine Template</span></a></li><li class="level-2"><a class="final" href="/start/deploy/"><span>Deploying Your First Engine</span></a></li><li class="level-2"><a class="final" href="/start/customize/"><span>Customizing the Engine</span></a></li></ul></li><li class="level-1"><a
class="expandible" href="#"><span>Integrating with Your App</span></a><ul><li class="level-2"><a class="final" href="/appintegration/"><span>App Integration Overview</span></a></li><li class="level-2"><a class="expandible" href="/sdk/"><span>List of SDKs</span></a><ul><li class="level-3"><a class="final" href="/sdk/java/"><span>Java & Android SDK</span></a></li><li class="level-3"><a class="final" href="/sdk/php/"><span>PHP SDK</span></a></li><li class="level-3"><a class="final" href="/sdk/python/"><span>Python SDK</span></a></li><li class="level-3"><a class="final" href="/sdk/ruby/"><span>Ruby SDK</span></a></li><li class="level-3"><a class="final" href="/sdk/community/"><span>Community Powered SDKs</span></a></li></ul></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Deploying an Engine</span></a><ul><li class="level-2"><a class="final" href="/deploy/"><span>Deploying as a Web Service</span></a></li><li class="level-2"><a class="final" href="/cli/#engine-comm
ands"><span>Engine Command-line Interface</span></a></li><li class="level-2"><a class="final" href="/deploy/engineparams/"><span>Setting Engine Parameters</span></a></li><li class="level-2"><a class="final" href="/deploy/enginevariants/"><span>Deploying Multiple Engine Variants</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Customizing an Engine</span></a><ul><li class="level-2"><a class="final" href="/customize/"><span>Learning DASE</span></a></li><li class="level-2"><a class="final" href="/customize/dase/"><span>Implement DASE</span></a></li><li class="level-2"><a class="final" href="/customize/troubleshooting/"><span>Troubleshooting Engine Development</span></a></li><li class="level-2"><a class="final" href="/api/current/#package"><span>Engine Scala APIs</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Collecting and Analyzing Data</span></a><ul><li class="level-2"><a class="final" href="/datacollection/"><span>E
vent Server Overview</span></a></li><li class="level-2"><a class="final" href="/cli/#event-server-commands"><span>Event Server Command-line Interface</span></a></li><li class="level-2"><a class="final" href="/datacollection/eventapi/"><span>Collecting Data with REST/SDKs</span></a></li><li class="level-2"><a class="final" href="/datacollection/eventmodel/"><span>Events Modeling</span></a></li><li class="level-2"><a class="final" href="/datacollection/webhooks/"><span>Unifying Multichannel Data with Webhooks</span></a></li><li class="level-2"><a class="final" href="/datacollection/channel/"><span>Channel</span></a></li><li class="level-2"><a class="final" href="/datacollection/batchimport/"><span>Importing Data in Batch</span></a></li><li class="level-2"><a class="final" href="/datacollection/analytics/"><span>Using Analytics Tools</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Choosing an Algorithm(s)</span></a><ul><li class="level-2"><a class="fin
al" href="/algorithm/"><span>Built-in Algorithm Libraries</span></a></li><li class="level-2"><a class="final" href="/algorithm/switch/"><span>Switching to Another Algorithm</span></a></li><li class="level-2"><a class="final" href="/algorithm/multiple/"><span>Combining Multiple Algorithms</span></a></li><li class="level-2"><a class="final" href="/algorithm/custom/"><span>Adding Your Own Algorithms</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>ML Tuning and Evaluation</span></a><ul><li class="level-2"><a class="final" href="/evaluation/"><span>Overview</span></a></li><li class="level-2"><a class="final" href="/evaluation/paramtuning/"><span>Hyperparameter Tuning</span></a></li><li class="level-2"><a class="final" href="/evaluation/evaluationdashboard/"><span>Evaluation Dashboard</span></a></li><li class="level-2"><a class="final" href="/evaluation/metricchoose/"><span>Choosing Evaluation Metrics</span></a></li><li class="level-2"><a class="final" hr
ef="/evaluation/metricbuild/"><span>Building Evaluation Metrics</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>System Architecture</span></a><ul><li class="level-2"><a class="final" href="/system/"><span>Architecture Overview</span></a></li><li class="level-2"><a class="final active" href="/system/anotherdatastore/"><span>Using Another Data Store</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Engine Template Gallery</span></a><ul><li class="level-2"><a class="final" href="http://templates.prediction.io"><span>Browse</span></a></li><li class="level-2"><a class="final" href="/community/submit-template/"><span>Submit your Engine as a Template</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Demo Tutorials</span></a><ul><li class="level-2"><a class="final" href="/demo/tapster/"><span>Comics Recommendation Demo</span></a></li><li class="level-2"><a class="final" href="/demo/community/">
<span>Community Contributed Demo</span></a></li><li class="level-2"><a class="final" href="/demo/textclassification/"><span>Text Classification Engine Tutorial</span></a></li></ul></li><li class="level-1"><a class="expandible" href="/community/"><span>Getting Involved</span></a><ul><li class="level-2"><a class="final" href="/community/contribute-code/"><span>Contribute Code</span></a></li><li class="level-2"><a class="final" href="/community/contribute-documentation/"><span>Contribute Documentation</span></a></li><li class="level-2"><a class="final" href="/community/contribute-sdk/"><span>Contribute a SDK</span></a></li><li class="level-2"><a class="final" href="/community/contribute-webhook/"><span>Contribute a Webhook</span></a></li><li class="level-2"><a class="final" href="/community/projects/"><span>Community Projects</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Getting Help</span></a><ul><li class="level-2"><a class="final" href="/resources
/faq/"><span>FAQs</span></a></li><li class="level-2"><a class="final" href="/support/"><span>Community Support</span></a></li><li class="level-2"><a class="final" href="/support/#enterprise-support"><span>Enterprise Support</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Resources</span></a><ul><li class="level-2"><a class="final" href="/resources/intellij/"><span>Developing Engines with IntelliJ IDEA</span></a></li><li class="level-2"><a class="final" href="/resources/upgrade/"><span>Upgrade Instructions</span></a></li><li class="level-2"><a class="final" href="/resources/glossary/"><span>Glossary</span></a></li></ul></li></ul></nav></div><div class="col-md-9 col-sm-12"><div class="content-header hidden-md hidden-lg"><div id="breadcrumbs" class="hidden-sm hidden xs"><ul><li><a href="#">System Architecture</a><span class="spacer">></span></li><li><span class="last">Using Another Data Store</span></li></ul></div><div id="page-title"><h1>Using Anot
her Data Store</h1></div></div><div id="table-of-content-wrapper"><h5>On this page</h5><aside id="table-of-contents"><ul> <li> <a href="#concepts">Concepts</a> </li> <li> <a href="#data-store-configuration">Data Store Configuration</a> </li> <li> <a href="#adding-support-of-other-backends">Adding Support of Other Backends</a> </li> </ul> </aside><hr/><a id="edit-page-link" href="https://github.com/apache/incubator-predictionio/tree/livedoc/docs/manual/source/system/anotherdatastore.html.md"><img src="/images/icons/edit-pencil-d6c1bb3d.png"/>Edit this page</a></div><div class="content-header hidden-sm hidden-xs"><div id="breadcrumbs" class="hidden-sm hidden xs"><ul><li><a href="#">System Architecture</a><span class="spacer">></span></li><li><span class="last">Using Another Data Store</span></li></ul></div><div id="page-title"><h1>Using Another Data Store</h1></div></div><div class="content"><p>PredictionIO has a thin storage layer to abstract meta data, event data, and model data
access. The layer defines a set of standard interfaces to support multiple data store backends. PredictionIO users can configure the backend of choice through configuration files or environmental variables. Engine developers need not worry about the actual underlying storage architecture. Advanced developers can implement their own backend driver as an external library.</p><h2 id='concepts' class='header-anchors'>Concepts</h2><p>In this section, we will visit some storage layer concepts that are common to users, engine developers, and advanced developers:</p> <ul> <li><p><strong>Repository</strong> is the highest level of data access abstraction and is where all engines and PredictionIO itself access data with.</p></li> <li><p><strong>Source</strong> is the actual data store backend that provide data access. A source is an implementation of the set of data access interfaces defined by <em>repositories</em>.</p></li> </ul> <p>Each of them will be explained in detail below:</p><h3 id=
'repositories' class='header-anchors'>Repositories</h3><p><em>Repository</em> is the highest level of data access abstraction and is where all engines and PredictionIO itself access data with.</p><p>The storage layer currently defines three mandatory data repositories: <em>meta data</em>, <em>event data</em>, and <em>model data</em>. Each repository has its own set of data access interfaces.</p> <ul> <li><p><strong>Meta data</strong> is used by PredictionIO to store engine training and evaluation information. Commands like <code>pio build</code>, <code>pio train</code>, <code>pio deploy</code>, and <code>pio eval</code> all access meta data.</p></li> <li><p><strong>Event data</strong> is used by the Event Server to collect events, and by engines to source data.</p></li> <li><p><strong>Model data</strong> is used by PredictionIO for automatic persistence of trained models.</p></li> </ul> <p>The following configuration variables are used for configure these repositories:</p> <ul> <li>
<em>Meta data</em> is configured by the <code>PIO_STORAGE_REPOSITORIES_METADATA_XXX</code> variables.</li> <li><em>Event data</em> is configured by the <code>PIO_STORAGE_REPOSITORIES_EVENTDATA_XXX</code> variables.</li> <li><em>Model data</em> is configured by the <code>PIO_STORAGE_REPOSITORIES_MODELDATA_XXX</code> variables.</li> </ul> <p>Configuration variables will be explained in more details in later sections below (see Data Store Configuration).</p><p>For example, you may see the following configuration variables defined in <code>conf/pio-env.sh</code></p><div class="highlight shell"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1
+2
+3
+4
+5
+6
+7
+8</pre></td><td class="code"><pre><span class="nv">PIO_STORAGE_REPOSITORIES_METADATA_NAME</span><span class="o">=</span>predictionio_metadata
+<span class="nv">PIO_STORAGE_REPOSITORIES_METADATA_SOURCE</span><span class="o">=</span>ELASTICSEARCH
+
+<span class="nv">PIO_STORAGE_REPOSITORIES_EVENTDATA_NAME</span><span class="o">=</span>predictionio_eventdata
+<span class="nv">PIO_STORAGE_REPOSITORIES_EVENTDATA_SOURCE</span><span class="o">=</span>HBASE
+
+<span class="nv">PIO_STORAGE_REPOSITORIES_MODELDATA_NAME</span><span class="o">=</span>pio_
+<span class="nv">PIO_STORAGE_REPOSITORIES_MODELDATA_SOURCE</span><span class="o">=</span>LOCALFS
+</pre></td></tr></tbody></table> </div> <p>The configuration variable with the <em>NAME</em> suffix controls the namespace used by the <em>source</em>.</p><p>The configuration variable with the <em>SOURCE</em> suffix points to the actual <strong>source</strong> that will back this repository. <em>Source</em> will be explained below.</p><h3 id='sources' class='header-anchors'>Sources</h3><p><em>Sources</em> are actual data store backends that provide data access. A source is an implementation of the set of data access interfaces defined by <em>repositories</em>.</p><p>PredictionIO comes with the following sources:</p> <ul> <li><p><strong>JDBC</strong> (tested on MySQL and PostgreSQL):</p> <ul> <li>Type name is <strong>jdbc</strong>.</li> <li>Can be used for <em>Meta Data</em>, <em>Event Data</em> and <em>Model Data</em> repositories</li> </ul></li> <li><p><strong>Elasticsearch</strong>:</p> <ul> <li>Type name is <strong>elasticsearch</strong></li> <li>Can be used for <em>Meta Data</e
m> repository</li> </ul></li> <li><p><strong>Apache HBase</strong>:</p> <ul> <li>Type name is <strong>hbase</strong></li> <li>Can be used for <em>Event Data</em> repository</li> </ul></li> <li><p><strong>Local file system</strong>:</p> <ul> <li>Type name is <strong>localfs</strong></li> <li>Can be used for <em>Model Data</em> repository</li> </ul></li> <li><p><strong>HDFS</strong>:</p> <ul> <li>Type name is <strong>hdfs</strong>.</li> <li>Can be used for <em>Model Data</em> repository</li> </ul></li> </ul> <p>Each repository can be configured to use different sources as shown above.</p><p>Each source has its own set of configuration parameters. Configuration variables will be explained in more details in later sections below (see Data Store Configuration).</p><p>The following is an example source configuration with name "PGSQL" with type <code>jdbc</code>:</p><div class="highlight shell"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: r
ight"><pre class="lineno">1
+2
+3
+4</pre></td><td class="code"><pre><span class="nv">PIO_STORAGE_SOURCES_PGSQL_TYPE</span><span class="o">=</span>jdbc
+<span class="nv">PIO_STORAGE_SOURCES_PGSQL_URL</span><span class="o">=</span>jdbc:postgresql:predictionio
+<span class="nv">PIO_STORAGE_SOURCES_PGSQL_USERNAME</span><span class="o">=</span>pio
+<span class="nv">PIO_STORAGE_SOURCES_PGSQL_PASSWORD</span><span class="o">=</span>pio
+</pre></td></tr></tbody></table> </div> <p>The following is an example of using this source "PGSQL" for the <em>meta data</em> repository:</p><div class="highlight shell"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1
+2</pre></td><td class="code"><pre><span class="nv">PIO_STORAGE_REPOSITORIES_METADATA_NAME</span><span class="o">=</span>predictionio_metadata
+<span class="nv">PIO_STORAGE_REPOSITORIES_METADATA_SOURCE</span><span class="o">=</span>PGSQL
+</pre></td></tr></tbody></table> </div> <h2 id='data-store-configuration' class='header-anchors'>Data Store Configuration</h2><p>Data store configuration is done by settings environmental variables. If you set them inside <code>conf/pio-env.sh</code>, they will be automatically available whenever you perform a <code>pio</code> command, e.g. <code>pio train</code>.</p><p>Notice that all variables are prefixed by <code>PIO_STORAGE_</code>.</p><h3 id='repositories-configuration' class='header-anchors'>Repositories Configuration</h3><p>Variable Format: <code>PIO_STORAGE_REPOSITORIES_<REPO>_<KEY></code></p><p>Configuration variables of repositories are prefixed by <code>PIO_STORAGE_REPOSITORIES_</code>, followed by the repository name (e.g. <code>METADATA</code>), and then either <code>NAME</code> or <code>SOURCE</code>.</p><p>Consider the following example:</p><div class="highlight shell"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: ri
ght"><pre class="lineno">1
+2</pre></td><td class="code"><pre><span class="nv">PIO_STORAGE_REPOSITORIES_METADATA_NAME</span><span class="o">=</span>predictionio_metadata
+<span class="nv">PIO_STORAGE_REPOSITORIES_METADATA_SOURCE</span><span class="o">=</span>PGSQL
+</pre></td></tr></tbody></table> </div> <p>The above configures PredictionIO to look for a source configured with the name <code>PGSQL</code>, and use <code>predictionio_metadata</code> as the namespace within such source. There is no restriction on namespace usage by the source, so behavior may vary. As an example, the official JDBC source uses the namespace as database table prefix.</p><h3 id='sources-configuration' class='header-anchors'>Sources Configuration</h3><p>Variable Format: <code>PIO_STORAGE_SOURCES_<NAME>_<KEY></code></p><p>Configuration variables of sources are prefixed by <code>PIO_STORAGE_SOURCES_</code>, followed by the source name of choice (e.g. <code>PGSQL</code>, <code>MYSQL</code>, <code>HBASE</code>, etc), and a configuration <code>KEY</code>.</p><div class="alert-message info"><p>The <code>TYPE</code> configuration key is mandatory. It is used by PredictionIO to determine the actual driver type to load.</p></div><p>Depending on what the source <co
de>TYPE</code> is, different configuration keys are required.</p><h4 id='jdbc-configuration' class='header-anchors'>JDBC Configuration</h4><p>Variable Format: <code>PIO_STORAGE_SOURCES_[NAME]_TYPE=jdbc</code></p><p>Supported Repositories: <strong>meta</strong>, <strong>event</strong>, <strong>model</strong></p><p>Tested on: MySQL 5.1+, PostgreSQL 9.1+</p><p>When <code>TYPE</code> is set to <code>jdbc</code>, the following configuration keys are supported.</p> <ul> <li><p> URL (mandatory)</p><p>The value must be a valid JDBC URL that points to a database, e.g. <code>PIO_STORAGE_SOURCES_PGSQL_URL=jdbc:postgresql:predictionio</code></p></li> <li><p> USERNAME (mandatory)</p><p>The value must be a valid, non-empty username for the JDBC connection, e.g. <code>PIO_STORAGE_SOURCES_PGSQL_USERNAME=pio_user</code></p></li> <li><p> PASSWORD (mandatory)</p><p>The value must be a valid, non-empty password for the JDBC connection, e.g. <code>PIO_STORAGE_SOURCES_PGSQL_PASSWORD=pio_user_password</co
de></p></li> <li><p> PARTITIONS (optional, default to 4)</p><p>This value is used by Apache Spark to determine the number of partitions to use when it reads from the JDBC connection, e.g. <code>PIO_STORAGE_SOURCES_PGSQL_PARTITIONS=4</code></p></li> <li><p> CONNECTIONS (optional, default to 8)</p><p>This value is used by scalikejdbc library to determine the max size of connection pool, e.g. <code>PIO_STORAGE_SOURCES_PGSQL_CONNECTIONS=8</code></p></li> <li><p> INDEX (optional since v0.9.6, default to disabled)</p><p>This value is used by creating indexes on entityId and entityType columns to improve performance when findByEntity function is called. Note that these columns of entityId and entityType will be created as varchar(255), e.g. <code>PIO_STORAGE_SOURCES_PGSQL_INDEX=enabled</code></p></li> </ul> <h4 id='apache-hbase-configuration' class='header-anchors'>Apache HBase Configuration</h4><p>Variable Format: <code>PIO_STORAGE_SOURCES_[NAME]_TYPE=hbase</code></p><p>Supported Reposito
ries: <strong>event</strong></p><p>Tested on: Apache HBase 0.98.5+, 1.0.0+</p><p>When <code>TYPE</code> is set to <code>hbase</code>, no other configuration keys are required. Other client side HBase configuration must be done through <code>hbase-site.xml</code> pointed by the <code>HBASE_CONF_DIR</code> configuration variable.</p><h4 id='elasticsearch-configuration' class='header-anchors'>Elasticsearch Configuration</h4><p>Variable Format: <code>PIO_STORAGE_SOURCES_[NAME]_TYPE=elasticsearch</code></p><p>Supported Repositories: <strong>meta</strong></p><p>When <code>TYPE</code> is set to <code>elasticsearch</code>, the following configuration keys are supported.</p> <ul> <li><p> HOSTS (mandatory)</p><p>Comma-separated list of hostnames, e.g. <code>PIO_STORAGE_SOURCES_ES_HOSTS=es1,es2,es3</code></p></li> <li><p> PORTS (mandatory)</p><p>Comma-separated list of ports that corresponds to <code>HOSTS</code>, e.g. <code>PIO_STORAGE_SOURCES_ES_PORTS=9200,9200,9222</code></p></li> <li><p> C
LUSTERNAME (optional, default to <code>elasticsearch</code>)</p><p>Elasticsearch cluster name, e.g. <code>PIO_STORAGE_SOURCES_ES_CLUSTERNAME=myescluster</code></p></li> </ul> <div class="alert-message info"><p>Other advanced Elasticsearch parameters can be set by pointing <code>ES_CONF_DIR</code> configuration variable to the location of <code>elasticsearch.yml</code>.</p></div><h4 id='local-file-system-configuration' class='header-anchors'>Local File System Configuration</h4><p>Variable Format: <code>PIO_STORAGE_SOURCES_[NAME]_TYPE=localfs</code></p><p>Supported Repositories: <strong>model</strong></p><p>When <code>TYPE</code> is set to <code>localfs</code>, the following configuration keys are supported.</p> <ul> <li><p> PATH (mandatory)</p><p>File system path at where models are stored, e.g. <code>PIO_STORAGE_SOURCES_FS_PATH=/mymodels</code></p></li> </ul> <h4 id='hdfs-configuration' class='header-anchors'>HDFS Configuration</h4><p>Variable Format: <code>PIO_STORAGE_SOURCES_[NAME
]_TYPE=hdfs</code></p><p>Supported Repositories: <strong>model</strong></p><p>When <code>TYPE</code> is set to <code>hdfs</code>, the following configuration keys are supported.</p> <ul> <li><p> PATH (mandatory)</p><p>HDFS path at where models are stored, e.g. <code>PIO_STORAGE_SOURCES_HDFS_PATH=/mymodels</code></p></li> </ul> <h2 id='adding-support-of-other-backends' class='header-anchors'>Adding Support of Other Backends</h2><p>It is quite straightforward to implement support of other backends. A good starting point is to reference the JDBC implementation inside the <a href="https://github.com/PredictionIO/PredictionIO/tree/develop/data/src/main/scala/io/prediction/data/storage/jdbc">io.prediction.data.storage.jdbc package</a>.</p><p>Contributions of different backends implementation is highly encouraged. To start contributing, please refer to <a href="/community/contribute-code/">this guide</a>.</p><h3 id='deploying-your-custom-backend-support-as-a-plugin' class='header-anchors'>
Deploying Your Custom Backend Support as a Plugin</h3><p>It is possible to deploy your custom backend implementation as a standalone JAR apart from the main PredictionIO binary distribution. The following is an outline of how this can be achieved.</p> <ol> <li><p> Create an SBT project with a library dependency on PredictionIO's data access base traits (inside the <code>data</code> artifact).</p></li> <li><p> Implement traits that you intend to support, and package everything into a big fat JAR (e.g. sbt-assembly).</p></li> <li><p> Create a directory named <code>plugins</code> inside PredictionIO binary installation.</p></li> <li><p> Copy the JAR from step 2 to <code>plugins</code>.</p></li> <li><p> In storage configuration, specify <code>TYPE</code> as your complete package name. As an example, if you have implemented all your traits under the package name <code>org.mystorage.jdbc</code>, use something like</p><div class="highlight shell"><table style="border-spacing: 0"><tbody
><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1
+2
+3</pre></td><td class="code"><pre><span class="nv">PIO_STORAGE_SOURCES_MYJDBC_TYPE</span><span class="o">=</span>org.mystorage.jdbc
+...
+<span class="nv">PIO_STORAGE_REPOSITORIES_METADATA_SOURCE</span><span class="o">=</span>MYJDBC
+</pre></td></tr></tbody></table> </div> <p>to instruct PredictionIO to pick up <code>StorageClient</code> from the appropriate package.</p></li> <li><p> Now you should be able to use your custom source and assign it to different repositories as you wish.</p></li> </ol> </div></div></div></div><footer><div class="container"><div class="seperator"></div><div class="row"><div class="col-md-4 col-md-push-8 col-xs-12"><div class="subscription-form-wrapper"><h4>Subscribe to our Newsletter</h4><form class="ajax-form" id="subscribe-form" method="POST" action="https://script.google.com/macros/s/AKfycbwhzeKCQJjQ52eVAqNT_vcklH07OITUO7wzOMDXvK6EGAWgaZgF/exec"><input class="required underlined-input" type="email" placeholder="Your email address" name="subscription_email" id="subscription_email"/><input class="pill-button" value="SUBSCRIBE" type="submit" data-state-normal="SUBSCRIBE" data-state-sucess="SUBSCRIBED!" data-state-loading="SENDING..." onclick="t($('#subscription_email').val());"/><p c
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<div class="row"><div class="col-md-9 col-sm-11 col-xs-11"><div class="hidden-md hidden-lg" id="mobile-page-heading-wrapper"><p>PredictionIO Docs</p><h4>Dimensionality Reduction With PredictionIO</h4></div><h4 class="hidden-sm hidden-xs">PredictionIO Docs</h4></div><div class="col-md-3 col-sm-1 col-xs-1 hidden-md hidden-lg"><img id="left-menu-indicator" src="/images/icons/down-arrow-dfe9f7fe.png"/></div><div class="col-md-3 col-sm-12 col-xs-12 swiftype-wrapper"><div class="swiftype"><form class="search-form"><img class="search-box-toggler hidden-xs hidden-sm" src="/images/icons/search-glass-704bd4ff.png"/><div class="search-box"><img src="/images/icons/search-glass-704bd4ff.png"/><input type="text" id="st-search-input" class="st-search-input" placeholder="Search Doc..."/></div><img class="swiftype-row-hider hidden-md hidden-lg" src="/images/icons/drawer-toggle-active-fcbef12a.png"/></form></div></div><div class="mobile-left-menu-toggler hidden-md hidden-lg"></div></div></div></div><
div id="page" class="container-fluid"><div class="row"><div id="left-menu-wrapper" class="col-md-3"><nav id="nav-main"><ul><li class="level-1"><a class="expandible" href="/"><span>Apache PredictionIO (incubating) Documentation</span></a><ul><li class="level-2"><a class="final" href="/"><span>Welcome to Apache PredictionIO (incubating)</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Getting Started</span></a><ul><li class="level-2"><a class="final" href="/start/"><span>A Quick Intro</span></a></li><li class="level-2"><a class="final" href="/install/"><span>Installing Apache PredictionIO (incubating)</span></a></li><li class="level-2"><a class="final" href="/start/download/"><span>Downloading an Engine Template</span></a></li><li class="level-2"><a class="final" href="/start/deploy/"><span>Deploying Your First Engine</span></a></li><li class="level-2"><a class="final" href="/start/customize/"><span>Customizing the Engine</span></a></li></ul></li><li c
lass="level-1"><a class="expandible" href="#"><span>Integrating with Your App</span></a><ul><li class="level-2"><a class="final" href="/appintegration/"><span>App Integration Overview</span></a></li><li class="level-2"><a class="expandible" href="/sdk/"><span>List of SDKs</span></a><ul><li class="level-3"><a class="final" href="/sdk/java/"><span>Java & Android SDK</span></a></li><li class="level-3"><a class="final" href="/sdk/php/"><span>PHP SDK</span></a></li><li class="level-3"><a class="final" href="/sdk/python/"><span>Python SDK</span></a></li><li class="level-3"><a class="final" href="/sdk/ruby/"><span>Ruby SDK</span></a></li><li class="level-3"><a class="final" href="/sdk/community/"><span>Community Powered SDKs</span></a></li></ul></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Deploying an Engine</span></a><ul><li class="level-2"><a class="final" href="/deploy/"><span>Deploying as a Web Service</span></a></li><li class="level-2"><a class="final" href=
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llection/"><span>Event Server Overview</span></a></li><li class="level-2"><a class="final" href="/cli/#event-server-commands"><span>Event Server Command-line Interface</span></a></li><li class="level-2"><a class="final" href="/datacollection/eventapi/"><span>Collecting Data with REST/SDKs</span></a></li><li class="level-2"><a class="final" href="/datacollection/eventmodel/"><span>Events Modeling</span></a></li><li class="level-2"><a class="final" href="/datacollection/webhooks/"><span>Unifying Multichannel Data with Webhooks</span></a></li><li class="level-2"><a class="final" href="/datacollection/channel/"><span>Channel</span></a></li><li class="level-2"><a class="final" href="/datacollection/batchimport/"><span>Importing Data in Batch</span></a></li><li class="level-2"><a class="final" href="/datacollection/analytics/"><span>Using Analytics Tools</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Choosing an Algorithm(s)</span></a><ul><li class="leve
l-2"><a class="final" href="/algorithm/"><span>Built-in Algorithm Libraries</span></a></li><li class="level-2"><a class="final" href="/algorithm/switch/"><span>Switching to Another Algorithm</span></a></li><li class="level-2"><a class="final" href="/algorithm/multiple/"><span>Combining Multiple Algorithms</span></a></li><li class="level-2"><a class="final" href="/algorithm/custom/"><span>Adding Your Own Algorithms</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>ML Tuning and Evaluation</span></a><ul><li class="level-2"><a class="final" href="/evaluation/"><span>Overview</span></a></li><li class="level-2"><a class="final" href="/evaluation/paramtuning/"><span>Hyperparameter Tuning</span></a></li><li class="level-2"><a class="final" href="/evaluation/evaluationdashboard/"><span>Evaluation Dashboard</span></a></li><li class="level-2"><a class="final" href="/evaluation/metricchoose/"><span>Choosing Evaluation Metrics</span></a></li><li class="level-2"><
a class="final" href="/evaluation/metricbuild/"><span>Building Evaluation Metrics</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>System Architecture</span></a><ul><li class="level-2"><a class="final" href="/system/"><span>Architecture Overview</span></a></li><li class="level-2"><a class="final" href="/system/anotherdatastore/"><span>Using Another Data Store</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Engine Template Gallery</span></a><ul><li class="level-2"><a class="final" href="http://templates.prediction.io"><span>Browse</span></a></li><li class="level-2"><a class="final" href="/community/submit-template/"><span>Submit your Engine as a Template</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Demo Tutorials</span></a><ul><li class="level-2"><a class="final" href="/demo/tapster/"><span>Comics Recommendation Demo</span></a></li><li class="level-2"><a class="final" href="/demo/c
ommunity/"><span>Community Contributed Demo</span></a></li><li class="level-2"><a class="final" href="/demo/textclassification/"><span>Text Classification Engine Tutorial</span></a></li></ul></li><li class="level-1"><a class="expandible" href="/community/"><span>Getting Involved</span></a><ul><li class="level-2"><a class="final" href="/community/contribute-code/"><span>Contribute Code</span></a></li><li class="level-2"><a class="final" href="/community/contribute-documentation/"><span>Contribute Documentation</span></a></li><li class="level-2"><a class="final" href="/community/contribute-sdk/"><span>Contribute a SDK</span></a></li><li class="level-2"><a class="final" href="/community/contribute-webhook/"><span>Contribute a Webhook</span></a></li><li class="level-2"><a class="final" href="/community/projects/"><span>Community Projects</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Getting Help</span></a><ul><li class="level-2"><a class="final" href=
"/resources/faq/"><span>FAQs</span></a></li><li class="level-2"><a class="final" href="/support/"><span>Community Support</span></a></li><li class="level-2"><a class="final" href="/support/#enterprise-support"><span>Enterprise Support</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Resources</span></a><ul><li class="level-2"><a class="final" href="/resources/intellij/"><span>Developing Engines with IntelliJ IDEA</span></a></li><li class="level-2"><a class="final" href="/resources/upgrade/"><span>Upgrade Instructions</span></a></li><li class="level-2"><a class="final" href="/resources/glossary/"><span>Glossary</span></a></li></ul></li></ul></nav></div><div class="col-md-9 col-sm-12"><div class="content-header hidden-md hidden-lg"><div id="page-title"><h1>Dimensionality Reduction With PredictionIO</h1></div></div><div id="table-of-content-wrapper"><h5>On this page</h5><aside id="table-of-contents"><ul> <li> <a href="#data-example">Data Example</a> </l
i> <li> <a href="#principal-component-analysis">Principal Component Analysis</a> </li> <li> <a href="#modifying-the-engine-template">Modifying the Engine Template</a> </li> <li> <a href="#testing-the-engine">Testing the Engine</a> </li> </ul> </aside><hr/><a id="edit-page-link" href="https://github.com/apache/incubator-predictionio/tree/livedoc/docs/manual/source/machinelearning/dimensionalityreduction.html.md"><img src="/images/icons/edit-pencil-d6c1bb3d.png"/>Edit this page</a></div><div class="content-header hidden-sm hidden-xs"><div id="page-title"><h1>Dimensionality Reduction With PredictionIO</h1></div></div><div class="content"><p>The purpose of this guide is to teach developers how to incorporate "dimensionality reduction" into a PredictionIO engine <a href="https://en.wikipedia.org/wiki/Principal_component_analysis">Principal Component Analysis</a> (PCA) on the <a href="https://www.kaggle.com/c/digit-recognizer">MNIST digit recognition dataset</a>. To do this, you
will be modifying the PredictionIO <a href="http://templates.prediction.io/PredictionIO/template-scala-parallel-classification">classification engine template</a>. This guide will demonstrate how to import the specific data set in batch, and also how to change the engine components in order to incorporate the new sample data and implement PCA.</p><p>In machine learning, specifically in <a href="http://en.wikipedia.org/wiki/Supervised_learning">supervised learning</a>, the general problem at hand is to predict a numeric outcome \(y\) from a numeric vector \(\bf{x}\). The different components of \(\bf{x}\) are called <strong>features</strong>, and usually represent observed values such as a hospital patient's age, weight, height, sex, etc. There are subtle issues that begin to arise as the number of features contained in each feature vector increases. We briefly list some of the issues that arise as the number of features grows in size:</p> <ul> <li><p><strong>Computation:</stron
g> The time complexity of machine learning algorithms often times depends on the number of features used. That is, the more features one uses for prediction, the more time it takes to train a model.</p></li> <li><p><strong>Prediction Performance:</strong> Often times there will be features that, when used in training, will actually decrease the predictive performance of a particular algorithm. </p></li> <li><p><strong>Curse of Dimensionality:</strong> It is harder to make inference and predictions in high dimensional spaces simply due to the fact that we need to sample a lot more observations. Think about it in this way, suppose that we sample 100 points lying on a flat solid square, and 100 points in a solid cube. The 100 points from the square will likely take up a larger proportion of its area, in comparison to the proportion of the cube's volume that the points sampled from it occupy. Hence we would need to sample more points from the cube in order to get better estimates of
the different properties of the cube, such as height, length, and width. This is shown in the following figure:</p></li> </ul> <table><thead> <tr> <th>100 Points Sampled From Unit Square</th> <th>100 Points Sampled From Unit Cube</th> </tr> </thead><tbody> <tr> <td></td> <td></td> </tr> <tr> <td><img alt="Square Samples" src="/images/machinelearning/featureselection/square100-df83c1ae.png"/></td> <td><img alt="Cube Samples" src="/images/machinelearning/featureselection/cube100-a8fe5433.png"/></td> </tr> <tr> <td></td> <td></td> </tr> </tbody></table> <p>Dimensionality reduction is the process of applying a transformation to your feature vectors in order to produce a vector with the same or less number of features. Principal component Analysis (PCA) is a technique for dimensionality reduction. This can be treated as a data processing technique, and so with respect to the <a href="/customize/">DASE</a> framework, it will fall into the Data Preparator engine component. </p><p>This gui
de will also help to solidify the concept of taking an engine template and customizing it for a particular use case: hand-written numeric digit recognition.</p><h2 id='data-example' class='header-anchors'>Data Example</h2><p>As a guiding example, a base data set, the <a href="https://www.kaggle.com/c/digit-recognizer/data">MNIST digit recognition dataset</a>, is used. This is a perfect data set for dimensionality reduction, for, in this data set, the features that will be used for learning are pixel entries in a \(28 \times 28\) pixel image. There is really no direct interpretation of any one feature, so that you do not lose anything in applying a transformation that will treat the features as <a href="https://en.wikipedia.org/wiki/Linear_combination">linear combinations</a> of some set "convenient" vectors. </p><p>Now, we first pull the <a href="http://templates.prediction.io/PredictionIO/template-scala-parallel-classification">classification engine template</a> via the f
ollowing bash line</p><div class="highlight shell"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1</pre></td><td class="code"><pre>pio template get PredictionIO/template-scala-parallel-classification <Your new engine directory>
+</pre></td></tr></tbody></table> </div> <p>You should immediately be prompted with the following message:</p><div class="highlight shell"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1</pre></td><td class="code"><pre>Please enter the template<span class="s1">'s Scala package name (e.g. com.mycompany):
+</span></pre></td></tr></tbody></table> </div> <p>Go ahead and input <code>FeatureReduction</code>, and feel free to just press enter for the remaining message prompts. For the remainder of this guide, you will be working in your new engine directory, so go ahead and <code>cd</code> into your new engine directory. At this point, go ahead and run the command </p><div class="highlight shell"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1</pre></td><td class="code"><pre>pio build
+</pre></td></tr></tbody></table> </div> <p>This will make sure that the PredictionIO dependency version for your project matches the version installed on your computer. Now, download the MNIST <code>train.csv</code> data set from the link above, and put this file in the <code>data</code> directory contained in the new engine directory. </p><h3 id='<strong>optional</strong>:-visualizing-observations' class='header-anchors' ><strong>Optional</strong>: Visualizing Observations</h3><p>If you want to actually convert the observation pixel data to an image go ahead and create a Python script called <code>picture_processing.py</code> into your data directory and copy and paste the following code into the script:</p><div class="highlight python"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1
+2
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+21
+22</pre></td><td class="code"><pre><span class="kn">from</span> <span class="nn">PIL</span> <span class="kn">import</span> <span class="n">Image</span>
+<span class="kn">import</span> <span class="nn">sys</span>
+
+<span class="n">obs_num</span> <span class="o">=</span> <span class="nb">int</span><span class="p">(</span><span class="n">sys</span><span class="o">.</span><span class="n">argv</span><span class="p">[</span><span class="mi">1</span><span class="p">])</span>
+
+<span class="n">f</span> <span class="o">=</span> <span class="nb">open</span><span class="p">(</span><span class="s">'./data/train.csv'</span><span class="p">,</span> <span class="s">'r'</span><span class="p">)</span><span class="o">.</span><span class="n">read</span><span class="p">()</span><span class="o">.</span><span class="n">split</span><span class="p">(</span><span class="s">'</span><span class="se">\n</span><span class="s">'</span><span class="p">)</span>
+<span class="n">var_names</span> <span class="o">=</span> <span class="n">f</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span><span class="o">.</span><span class="n">split</span><span class="p">(</span><span class="s">','</span><span class="p">)</span>
+<span class="n">f</span> <span class="o">=</span> <span class="n">f</span><span class="p">[</span><span class="mi">1</span> <span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">]</span>
+<span class="n">f</span> <span class="o">=</span> <span class="p">[</span><span class="nb">list</span><span class="p">(</span><span class="nb">map</span><span class="p">(</span><span class="nb">int</span><span class="p">,</span> <span class="n">x</span><span class="p">[</span><span class="mi">1</span> <span class="p">:</span> <span class="p">]))</span> <span class="k">for</span> <span class="n">x</span> <span class="ow">in</span> <span class="p">(</span><span class="n">y</span><span class="o">.</span><span class="n">split</span><span class="p">(</span><span class="s">","</span><span class="p">)</span> <span class="k">for</span> <span class="n">y</span> <span class="ow">in</span> <span class="n">f</span><span class="p">)]</span>
+
+
+<span class="k">def</span> <span class="nf">create_image</span><span class="p">(</span><span class="n">pixel_array</span><span class="p">):</span>
+ <span class="n">img</span> <span class="o">=</span> <span class="n">Image</span><span class="o">.</span><span class="n">new</span><span class="p">(</span><span class="s">'RGB'</span><span class="p">,</span> <span class="p">(</span><span class="mi">28</span><span class="p">,</span> <span class="mi">28</span><span class="p">))</span>
+ <span class="n">pixels</span> <span class="o">=</span> <span class="n">img</span><span class="o">.</span><span class="n">load</span><span class="p">()</span>
+ <span class="n">count</span> <span class="o">=</span> <span class="mi">0</span>
+ <span class="k">for</span> <span class="n">i</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="n">img</span><span class="o">.</span><span class="n">size</span><span class="p">[</span><span class="mi">0</span><span class="p">]):</span>
+ <span class="k">for</span> <span class="n">j</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="n">img</span><span class="o">.</span><span class="n">size</span><span class="p">[</span><span class="mi">1</span><span class="p">]):</span>
+ <span class="n">pixels</span><span class="p">[</span><span class="n">i</span><span class="p">,</span> <span class="n">j</span><span class="p">]</span> <span class="o">=</span> <span class="p">(</span><span class="n">i</span><span class="p">,</span> <span class="n">j</span><span class="p">,</span> <span class="n">pixel_array</span><span class="p">[</span><span class="n">count</span><span class="p">])</span>
+ <span class="n">count</span> <span class="o">+=</span> <span class="mi">1</span>
+ <span class="k">return</span> <span class="n">img</span>
+
+<span class="n">create_image</span><span class="p">(</span><span class="n">f</span><span class="p">[</span><span class="n">obs_num</span><span class="p">])</span><span class="o">.</span><span class="n">show</span><span class="p">()</span>
+</pre></td></tr></tbody></table> </div> <p>To use this run the following line:</p><div class="highlight shell"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1</pre></td><td class="code"><pre>python data/picture_processing.py k
+</pre></td></tr></tbody></table> </div> <p>where you will replace <code>k</code> with an integer between 0 and 41999 (referring to an observation number). This script uses the <a href="https://python-pillow.github.io/">Python pillow</a> library, and, if you have it installed, the above command should open up a window with an image of a hand-written numerical digit.</p><h3 id='importing-the-data' class='header-anchors'>Importing the Data</h3><p>You will use the <a href="/sdk/python/">PredictionIO Python SDK</a> to prepare the data for batch import. Go ahead and create a Python script called <code>export_events.py</code> in the same <code>data</code> directory, and copy and paste the following code:</p><div class="highlight python"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1
+2
+3
+4
+5
+6
+7
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+9
+10
+11
+12
+13
+14
+15
+16
+17
+18
+19
+20
+21
+22
+23
+24
+25
+26
+27
+28
+29
+30
+31
+32
+33
+34
+35</pre></td><td class="code"><pre><span class="s">"""
+Import digit recognition data.
+"""</span>
+
+<span class="kn">import</span> <span class="nn">predictionio</span>
+<span class="kn">import</span> <span class="nn">argparse</span>
+<span class="kn">import</span> <span class="nn">pytz</span>
+<span class="kn">from</span> <span class="nn">datetime</span> <span class="kn">import</span> <span class="n">datetime</span>
+
+<span class="c">### Remove the variable name line, and last line.</span>
+<span class="n">f</span> <span class="o">=</span> <span class="nb">open</span><span class="p">(</span><span class="s">"./data/train.csv"</span><span class="p">,</span> <span class="s">"r"</span><span class="p">)</span><span class="o">.</span><span class="n">read</span><span class="p">()</span><span class="o">.</span><span class="n">split</span><span class="p">(</span><span class="s">"</span><span class="se">\n</span><span class="s">"</span><span class="p">)[</span><span class="mi">1</span> <span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">]</span>
+
+<span class="c">### Separate your observations into a tuple (label, pixel list).</span>
+<span class="n">f</span> <span class="o">=</span> <span class="p">[(</span><span class="nb">int</span><span class="p">(</span><span class="n">x</span><span class="p">[</span><span class="mi">0</span><span class="p">]),</span> <span class="nb">list</span><span class="p">(</span><span class="nb">map</span><span class="p">(</span><span class="nb">int</span><span class="p">,</span> <span class="n">x</span><span class="p">[</span><span class="mi">1</span> <span class="p">:</span> <span class="p">])))</span> <span class="k">for</span> <span class="n">x</span> <span class="ow">in</span> <span class="p">(</span><span class="n">y</span><span class="o">.</span><span class="n">split</span><span class="p">(</span><span class="s">","</span><span class="p">)</span> <span class="k">for</span> <span class="n">y</span> <span class="ow">in</span> <span class="n">f</span><span class="p">)]</span>
+
+<span class="c">### JSON event exporter.</span>
+<span class="n">exporter</span> <span class="o">=</span> <span class="n">predictionio</span><span class="o">.</span><span class="n">FileExporter</span><span class="p">(</span><span class="s">"./data/digits.json"</span><span class="p">)</span>
+
+
+<span class="n">count</span> <span class="o">=</span> <span class="mi">0</span>
+<span class="k">print</span><span class="p">(</span><span class="s">"Exporting events to JSON batch file........"</span><span class="p">)</span>
+<span class="k">for</span> <span class="n">elem</span> <span class="ow">in</span> <span class="n">f</span><span class="p">:</span>
+ <span class="n">exporter</span><span class="o">.</span><span class="n">create_event</span><span class="p">(</span>
+ <span class="n">event</span><span class="o">=</span><span class="s">"digitData"</span><span class="p">,</span>
+ <span class="n">entity_type</span><span class="o">=</span><span class="s">"digit"</span><span class="p">,</span>
+ <span class="n">entity_id</span><span class="o">=</span><span class="nb">str</span><span class="p">(</span><span class="n">count</span><span class="p">),</span> <span class="c"># use the count num as user ID</span>
+ <span class="n">properties</span><span class="o">=</span> <span class="p">{</span>
+ <span class="s">"label"</span><span class="p">:</span><span class="n">elem</span><span class="p">[</span><span class="mi">0</span><span class="p">],</span>
+ <span class="s">"features"</span><span class="p">:</span><span class="nb">str</span><span class="p">(</span><span class="n">elem</span><span class="p">[</span><span class="mi">1</span><span class="p">])[</span><span class="mi">1</span> <span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">]</span>
+ <span class="p">},</span>
+ <span class="n">event_time</span> <span class="o">=</span> <span class="n">datetime</span><span class="o">.</span><span class="n">now</span><span class="p">(</span><span class="n">pytz</span><span class="o">.</span><span class="n">utc</span><span class="p">)</span>
+ <span class="p">)</span>
+ <span class="n">count</span> <span class="o">+=</span> <span class="mi">1</span>
+<span class="k">print</span><span class="p">(</span><span class="s">"Exported {} events."</span><span class="o">.</span><span class="n">format</span><span class="p">(</span><span class="nb">str</span><span class="p">(</span><span class="n">count</span><span class="p">)))</span>
+
+</pre></td></tr></tbody></table> </div> <p>This will import the data into the <a href="/datacollection/">event server</a> in a manner that will facilitate its processing in the Classification engine, although you will also need to modify the engine accordingly. In your new engine directory, run the above script via the following:</p><div class="highlight shell"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1</pre></td><td class="code"><pre>python data/export_events.py
+</pre></td></tr></tbody></table> </div> <p>This will create a file <code>digits.json</code> in your engine <code>data</code> directory. We will create a new application called <code>FeatureReduction</code> via the command:</p><div class="highlight shell"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1</pre></td><td class="code"><pre>pio app new FeatureReduction
+</pre></td></tr></tbody></table> </div> <p>This will create an application associated to an application ID and an access key. To import the data, you use the command in your engine directory:</p><div class="highlight shell"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1</pre></td><td class="code"><pre>pio import --appid <Your application ID> --input data/digits.json
+</pre></td></tr></tbody></table> </div> <p>If the data has been successfully imported, you should see output of the form:</p><div class="highlight shell"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1
+2
+3
+4
+5</pre></td><td class="code"><pre>...
+<span class="o">[</span>INFO] <span class="o">[</span>Remoting] Starting remoting
+<span class="o">[</span>INFO] <span class="o">[</span>Remoting] Remoting started; listening on addresses :[akka.tcp://sparkDriver@10.0.0.30:65523]
+<span class="o">[</span>INFO] <span class="o">[</span>FileToEvents<span class="nv">$]</span> Events are imported.
+<span class="o">[</span>INFO] <span class="o">[</span>FileToEvents<span class="nv">$]</span> Done.
+</pre></td></tr></tbody></table> </div> <p>The data is now in the event server.</p><h2 id='principal-component-analysis' class='header-anchors'>Principal Component Analysis</h2><p>PCA begins with the data matrix \(\bf X\) whose rows are feature vectors corresponding to a set of observations. In our case, each row represents the pixel information of the corresponding hand-written numerc digit image. The model then computes the <a href="https://en.wikipedia.org/wiki/Covariance_matrix">covariance matrix</a> estimated from the data matrix \(\bf X\). The algorithm then takes the covariance matrix and computes the <a href="https://en.wikipedia.org/wiki/Eigenvalues_and_eigenvectors">eigenvectors</a> that correspond to its \(k\) (some integer) largest <a href="https://en.wikipedia.org/wiki/Eigenvalues_and_eigenvectors">eigenvalues</a>. The data matrix is then mapped to the space generated by these \(k\) vectors, which are called the \(k\) <strong>ptincipal components</strong> of \(\bf X\).
What this is doing is mapping the data observations into a lower-dimensional space that explains the largest variability in the data (contains the most information). The algorithm for implementing PCA is listed as follows:</p><h3 id='pca-algorithm' class='header-anchors'>PCA Algorithm</h3><p><strong>Input:</strong> \(N \times p\) data matrix \(\bf X\); \(k \leq p\), the number of desired features.</p><p><strong>1.</strong> For each column in the data matrix: compute the average of all the entries contained in the column, and then subtract this average from each of the column entries. </p><p><strong>2.</strong> Compute the \(k\) eigenvectors corresponding to the \(k\) largest eigenvalues of the matrix obtained in the first step.</p><p><strong>Output:</strong> \(p \times k\) matrix \(P\) whose \(k\) rows are the eigenvectors computed in the second step.</p><p>Now, to transform a \(p \times 1\) feature vector \(\bf {x}\), you multiply by the matrix \(P^T\). Now, the vector \(P^T {\bf x
}\) is a feature vector with only \(k\) components, which has accomplished the desired dimensionality reduction. Also, as a side note, the first step in the algorithm reduces the covariance matrix computation to that of only performing <a href="https://spark.apache.org/docs/1.3.1/mllib-dimensionality-reduction.html#singular-value-decomposition-svd">SVD</a> on matrix obtained from step 1, which is numerically preferred, and necessary to extract the required eigenvectors.</p><h2 id='modifying-the-engine-template' class='header-anchors'>Modifying the Engine Template</h2><p>We will be modifying the engine template by first re-defining our <code>Query</code> class located in the <code>Engine.scala</code> script as follows:</p><div class="highlight scala"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1
+2
+3</pre></td><td class="code"><pre><span class="k">class</span> <span class="nc">Query</span><span class="o">(</span>
+ <span class="k">val</span> <span class="n">features</span> <span class="k">:</span> <span class="kt">String</span>
+<span class="o">)</span> <span class="k">extends</span> <span class="nc">Serializable</span>
+</pre></td></tr></tbody></table> </div> <p>We will continue to make the required engine modifications by following the <a href="/customize/">DASE</a> workflow. The next step is then to modify the engine's <code>DataSource</code> class which is the engine component in charge of reading the data from the event server.</p><h3 id='data-source-modifications' class='header-anchors'>Data Source Modifications</h3><p>The following changes will be made to the <code>DataSource</code> class. We will redefine the method <code>readTraining</code> as follows:</p><div class="highlight scala"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1
+2
+3
+4
+5
+6
+7
+8
+9
+10
+11
+12
+13
+14
+15
+16
+17
+18</pre></td><td class="code"><pre><span class="o">...</span>
+
+<span class="k">override</span>
+ <span class="k">def</span> <span class="n">readTraining</span><span class="o">(</span><span class="n">sc</span><span class="k">:</span> <span class="kt">SparkContext</span><span class="o">)</span><span class="k">:</span> <span class="kt">TrainingData</span> <span class="o">=</span> <span class="o">{</span>
+
+ <span class="k">val</span> <span class="n">data</span> <span class="k">:</span> <span class="kt">RDD</span><span class="o">[</span><span class="kt">Observation</span><span class="o">]</span> <span class="k">=</span> <span class="nc">PEventStore</span><span class="o">.</span><span class="n">find</span><span class="o">(</span>
+ <span class="n">appName</span> <span class="k">=</span> <span class="n">dsp</span><span class="o">.</span><span class="n">appName</span><span class="o">,</span>
+ <span class="n">entityType</span> <span class="k">=</span> <span class="nc">Some</span><span class="o">(</span><span class="s">"digit"</span><span class="o">),</span>
+ <span class="n">eventNames</span> <span class="k">=</span> <span class="nc">Some</span><span class="o">(</span><span class="nc">List</span><span class="o">(</span><span class="s">"digitData"</span><span class="o">))</span>
+ <span class="o">)(</span><span class="n">sc</span><span class="o">).</span><span class="n">map</span><span class="o">(</span><span class="n">e</span> <span class="k">=></span> <span class="nc">Observation</span><span class="o">(</span>
+ <span class="n">e</span><span class="o">.</span><span class="n">properties</span><span class="o">.</span><span class="n">get</span><span class="o">[</span><span class="kt">Double</span><span class="o">](</span><span class="s">"label"</span><span class="o">),</span>
+ <span class="n">e</span><span class="o">.</span><span class="n">properties</span><span class="o">.</span><span class="n">get</span><span class="o">[</span><span class="kt">String</span><span class="o">](</span><span class="s">"features"</span><span class="o">)</span>
+ <span class="o">))</span>
+
+ <span class="k">new</span> <span class="nc">TrainingData</span><span class="o">(</span><span class="n">data</span><span class="o">)</span>
+ <span class="o">}</span>
+
+<span class="o">...</span>
+</pre></td></tr></tbody></table> </div> <p>This is essentially just making sure that the <code>entityType</code>, <code>eventName</code>, and <code>properties</code> fields match those specified in the script <code>export_events.py</code>. Also, a new class is introduced called <code>Observation</code> to serve as a wrapper for each data point's response and feature attributes, and the <code>TrainingData</code> is modified to hold an RDD of type <code>Observation</code> (instead of <code>LabeledPoints</code>):</p><div class="highlight scala"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1
+2
+3
+4
+5
+6
+7
+8</pre></td><td class="code"><pre><span class="k">case</span> <span class="k">class</span> <span class="nc">Observation</span> <span class="o">(</span>
+ <span class="n">label</span> <span class="k">:</span> <span class="kt">Double</span><span class="o">,</span>
+ <span class="n">features</span> <span class="k">:</span> <span class="kt">String</span>
+<span class="o">)</span>
+
+<span class="k">class</span> <span class="nc">TrainingData</span><span class="o">(</span>
+ <span class="k">val</span> <span class="n">observations</span><span class="k">:</span> <span class="kt">RDD</span><span class="o">[</span><span class="kt">Observation</span><span class="o">]</span>
+<span class="o">)</span> <span class="k">extends</span> <span class="nc">Serializable</span>
+</pre></td></tr></tbody></table> </div> <p>This also means that the <code>readEval</code> method must be redefined in a similar fashion:</p><div class="highlight scala"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1
+2
+3
+4
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+18
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+21
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+24
+25
+26
+27
+28
+29
+30
+31
+32
+33
+34
+35
+36
+37</pre></td><td class="code"><pre> <span class="k">override</span>
+ <span class="k">def</span> <span class="n">readEval</span><span class="o">(</span><span class="n">sc</span><span class="k">:</span> <span class="kt">SparkContext</span><span class="o">)</span>
+ <span class="k">:</span> <span class="kt">Seq</span><span class="o">[(</span><span class="kt">TrainingData</span>, <span class="kt">EmptyEvaluationInfo</span>, <span class="kt">RDD</span><span class="o">[(</span><span class="kt">Query</span>, <span class="kt">ActualResult</span><span class="o">)])]</span> <span class="k">=</span> <span class="o">{</span>
+ <span class="n">require</span><span class="o">(</span><span class="n">dsp</span><span class="o">.</span><span class="n">evalK</span><span class="o">.</span><span class="n">nonEmpty</span><span class="o">,</span> <span class="s">"DataSourceParams.evalK must not be None"</span><span class="o">)</span>
+
+ <span class="c1">// The following code reads the data from data store. It is equivalent to
+</span> <span class="c1">// the readTraining method. We copy-and-paste the exact code here for
+</span> <span class="c1">// illustration purpose, a recommended approach is to factor out this logic
+</span> <span class="c1">// into a helper function and have both readTraining and readEval call the
+</span> <span class="c1">// helper.
+</span> <span class="k">val</span> <span class="n">data</span> <span class="k">:</span> <span class="kt">RDD</span><span class="o">[</span><span class="kt">Observation</span><span class="o">]</span> <span class="k">=</span> <span class="nc">PEventStore</span><span class="o">.</span><span class="n">find</span><span class="o">(</span>
+ <span class="n">appName</span> <span class="k">=</span> <span class="n">dsp</span><span class="o">.</span><span class="n">appName</span><span class="o">,</span>
+ <span class="n">entityType</span> <span class="k">=</span> <span class="nc">Some</span><span class="o">(</span><span class="s">"digit"</span><span class="o">),</span>
+ <span class="n">eventNames</span> <span class="k">=</span> <span class="nc">Some</span><span class="o">(</span><span class="nc">List</span><span class="o">(</span><span class="s">"digitData"</span><span class="o">))</span>
+ <span class="o">)(</span><span class="n">sc</span><span class="o">).</span><span class="n">map</span><span class="o">(</span><span class="n">e</span> <span class="k">=></span> <span class="nc">Observation</span><span class="o">(</span>
+ <span class="n">e</span><span class="o">.</span><span class="n">properties</span><span class="o">.</span><span class="n">get</span><span class="o">[</span><span class="kt">Double</span><span class="o">](</span><span class="s">"label"</span><span class="o">),</span>
+ <span class="n">e</span><span class="o">.</span><span class="n">properties</span><span class="o">.</span><span class="n">get</span><span class="o">[</span><span class="kt">String</span><span class="o">](</span><span class="s">"features"</span><span class="o">)</span>
+ <span class="o">)).</span><span class="n">cache</span>
+ <span class="c1">// End of reading from data store
+</span>
+ <span class="c1">// K-fold splitting
+</span> <span class="k">val</span> <span class="n">evalK</span> <span class="k">=</span> <span class="n">dsp</span><span class="o">.</span><span class="n">evalK</span><span class="o">.</span><span class="n">get</span>
+ <span class="k">val</span> <span class="n">indexedPoints</span><span class="k">:</span> <span class="kt">RDD</span><span class="o">[(</span><span class="kt">Observation</span>, <span class="kt">Long</span><span class="o">)]</span> <span class="k">=</span> <span class="n">data</span><span class="o">.</span><span class="n">zipWithIndex</span><span class="o">()</span>
+
+ <span class="o">(</span><span class="mi">0</span> <span class="n">until</span> <span class="n">evalK</span><span class="o">).</span><span class="n">map</span> <span class="o">{</span> <span class="n">idx</span> <span class="k">=></span>
+ <span class="k">val</span> <span class="n">trainingPoints</span> <span class="k">=</span> <span class="n">indexedPoints</span><span class="o">.</span><span class="n">filter</span><span class="o">(</span><span class="k">_</span><span class="o">.</span><span class="n">_2</span> <span class="o">%</span> <span class="n">evalK</span> <span class="o">!=</span> <span class="n">idx</span><span class="o">).</span><span class="n">map</span><span class="o">(</span><span class="k">_</span><span class="o">.</span><span class="n">_1</span><span class="o">)</span>
+ <span class="k">val</span> <span class="n">testingPoints</span> <span class="k">=</span> <span class="n">indexedPoints</span><span class="o">.</span><span class="n">filter</span><span class="o">(</span><span class="k">_</span><span class="o">.</span><span class="n">_2</span> <span class="o">%</span> <span class="n">evalK</span> <span class="o">==</span> <span class="n">idx</span><span class="o">).</span><span class="n">map</span><span class="o">(</span><span class="k">_</span><span class="o">.</span><span class="n">_1</span><span class="o">)</span>
+
+ <span class="o">(</span>
+ <span class="k">new</span> <span class="nc">TrainingData</span><span class="o">(</span><span class="n">trainingPoints</span><span class="o">),</span>
+ <span class="k">new</span> <span class="nc">EmptyEvaluationInfo</span><span class="o">(),</span>
+ <span class="n">testingPoints</span><span class="o">.</span><span class="n">map</span> <span class="o">{</span>
+ <span class="n">p</span> <span class="k">=></span> <span class="o">(</span><span class="k">new</span> <span class="nc">Query</span><span class="o">(</span><span class="n">p</span><span class="o">.</span><span class="n">features</span><span class="o">),</span> <span class="k">new</span> <span class="nc">ActualResult</span><span class="o">(</span><span class="n">p</span><span class="o">.</span><span class="n">label</span><span class="o">))</span>
+ <span class="o">}</span>
+ <span class="o">)</span>
+ <span class="o">}</span>
+ <span class="o">}</span>
+</pre></td></tr></tbody></table> </div> <p>The motivation for defining the <code>Observation</code> class is to make it easy to maintain the format of the data as it was imported, and to help you look at each RDD element as a data observation in its original format. All of the data processing will be taken care of via the <code>Preparator</code> class.</p><h3 id='preparator-modifications' class='header-anchors'>Preparator Modifications</h3><p>Remember that the Data Preparator is the engine component that takes care of the necessary data processing prior to the fitting of a predictive model in the Algorithm component. Hence this stage is where you will implement PCA. </p><p>To make sure there is no confusion, replace the import statements in the <code>Preparator.scala</code> script with the following:</p><div class="highlight scala"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1
+2
+3
+4
+5
+6
+7</pre></td><td class="code"><pre><span class="k">import</span> <span class="nn">io.prediction.controller.</span><span class="o">{</span><span class="nc">Params</span><span class="o">,</span> <span class="nc">PPreparator</span><span class="o">}</span>
+<span class="k">import</span> <span class="nn">org.apache.spark.SparkContext</span>
+<span class="k">import</span> <span class="nn">org.apache.spark.mllib.feature.</span><span class="o">{</span><span class="nc">StandardScaler</span><span class="o">,</span> <span class="nc">StandardScalerModel</span><span class="o">}</span>
+<span class="k">import</span> <span class="nn">org.apache.spark.mllib.linalg.distributed.RowMatrix</span>
+<span class="k">import</span> <span class="nn">org.apache.spark.mllib.linalg.</span><span class="o">{</span><span class="nc">DenseVector</span><span class="o">,</span> <span class="nc">Vectors</span><span class="o">,</span> <span class="nc">Vector</span><span class="o">}</span>
+<span class="k">import</span> <span class="nn">org.apache.spark.rdd.RDD</span>
+<span class="k">import</span> <span class="nn">org.apache.spark.mllib.regression.LabeledPoint</span>
+</pre></td></tr></tbody></table> </div> <p>Also, note that the PCA algorithm requires you to specify the hyperparameter \(k\), or the desired number of features. Thus you will first define a parameter class <code>PreparatorParams</code>:</p><div class="highlight scala"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1
+2
+3</pre></td><td class="code"><pre><span class="k">case</span> <span class="k">class</span> <span class="nc">PreparatorParams</span> <span class="o">(</span>
+<span class="n">numFeatures</span> <span class="k">:</span> <span class="kt">Int</span>
+<span class="o">)</span> <span class="k">extends</span> <span class="nc">Params</span>
+</pre></td></tr></tbody></table> </div> <p>The next step is to implement the algorithm discussed in the above digression. This will all be done in the <code>PreparedData</code> class. </p><p>Remember that the classes <code>Observation</code> and <code>Query</code> store the pixel features as a string separated by <code>", "</code>. Hence, for data processing, you first need a function, <code>string2Vector</code>, that will transform the feature strings to vectors. Now, you will need a function, <code>scaler</code>, that centers your observations (step 1 in PCA algorithm). Luckily, the <code>StandardScaler</code> and <code>StandardScalerModel</code> classes implemented in Spark MLLib can easily take care of this for you. The last part will be to actually compute the SVD of the data matrix which can also be easily done in MLLib. All this will be implemented in the <code>PreparedData</code> class which you will redefine as follows:</p><div class="highlight scala"><table style
="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1
+2
+3
+4
+5
+6
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+9
+10
+11
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+36</pre></td><td class="code"><pre><span class="k">class</span> <span class="nc">PreparedData</span><span class="o">(</span>
+ <span class="k">val</span> <span class="n">data</span> <span class="k">:</span> <span class="kt">RDD</span><span class="o">[</span><span class="kt">Observation</span><span class="o">],</span>
+ <span class="k">val</span> <span class="n">pp</span> <span class="k">:</span> <span class="kt">PreparatorParams</span>
+<span class="o">)</span> <span class="k">extends</span> <span class="nc">Serializable</span> <span class="o">{</span>
+
+
+ <span class="c1">/// Data Transformation Tools
+</span>
+ <span class="c1">// Transform features string member to a MLLib Vector.
+</span> <span class="k">private</span> <span class="k">val</span> <span class="n">string2Vector</span> <span class="k">:</span> <span class="o">(</span><span class="kt">String</span> <span class="o">=></span> <span class="kt">Vector</span><span class="o">)</span> <span class="k">=</span> <span class="o">(</span><span class="n">e</span> <span class="k">:</span> <span class="kt">String</span><span class="o">)</span> <span class="k">=></span> <span class="nc">Vectors</span><span class="o">.</span><span class="n">dense</span><span class="o">(</span>
+ <span class="n">e</span><span class="o">.</span><span class="n">split</span><span class="o">(</span><span class="s">", "</span><span class="o">).</span><span class="n">map</span><span class="o">(</span><span class="k">_</span><span class="o">.</span><span class="n">toDouble</span><span class="o">)</span>
+ <span class="o">)</span>
+
+ <span class="c1">// Create function for centering data.
+</span> <span class="k">private</span> <span class="k">val</span> <span class="n">scaler</span> <span class="k">:</span> <span class="kt">StandardScalerModel</span> <span class="o">=</span> <span class="k">new</span> <span class="nc">StandardScaler</span><span class="o">(</span><span class="kc">true</span><span class="o">,</span> <span class="kc">false</span><span class="o">).</span><span class="n">fit</span><span class="o">(</span>
+ <span class="n">data</span><span class="o">.</span><span class="n">map</span><span class="o">(</span><span class="n">e</span> <span class="k">=></span> <span class="n">string2Vector</span><span class="o">(</span><span class="n">e</span><span class="o">.</span><span class="n">features</span><span class="o">))</span>
+ <span class="o">)</span>
+
+ <span class="c1">// Compute PCA output matrix.
+</span> <span class="k">private</span> <span class="k">val</span> <span class="n">pcaMatrix</span> <span class="k">=</span> <span class="k">new</span> <span class="nc">RowMatrix</span><span class="o">(</span><span class="n">data</span><span class="o">.</span><span class="n">map</span><span class="o">(</span>
+ <span class="n">e</span> <span class="k">=></span> <span class="n">string2Vector</span><span class="o">(</span><span class="n">e</span><span class="o">.</span><span class="n">features</span><span class="o">)</span>
+ <span class="o">)).</span><span class="n">computePrincipalComponents</span><span class="o">(</span><span class="n">pp</span><span class="o">.</span><span class="n">numFeatures</span><span class="o">).</span><span class="n">transpose</span>
+
+ <span class="c1">/// Observation transformation.
+</span> <span class="k">def</span> <span class="n">transform</span> <span class="o">(</span><span class="n">features</span> <span class="k">:</span> <span class="kt">String</span><span class="o">)</span><span class="k">:</span> <span class="kt">Vector</span> <span class="o">=</span> <span class="o">{</span>
+ <span class="n">pcaMatrix</span><span class="o">.</span><span class="n">multiply</span><span class="o">(</span>
+ <span class="k">new</span> <span class="nc">DenseVector</span><span class="o">(</span><span class="n">scaler</span><span class="o">.</span><span class="n">transform</span><span class="o">(</span><span class="n">string2Vector</span><span class="o">(</span><span class="n">features</span><span class="o">)).</span><span class="n">toArray</span><span class="o">)</span>
+ <span class="o">)</span>
+ <span class="o">}</span>
+
+ <span class="c1">// Data for inputting into learning Algorithm.
+</span> <span class="k">val</span> <span class="n">transformedData</span> <span class="k">:</span> <span class="kt">RDD</span><span class="o">[</span><span class="kt">LabeledPoint</span><span class="o">]</span> <span class="k">=</span> <span class="n">data</span><span class="o">.</span><span class="n">map</span><span class="o">(</span><span class="n">e</span> <span class="k">=></span> <span class="nc">LabeledPoint</span><span class="o">(</span>
+ <span class="n">e</span><span class="o">.</span><span class="n">label</span><span class="o">,</span>
+ <span class="n">transform</span><span class="o">(</span><span class="n">e</span><span class="o">.</span><span class="n">features</span><span class="o">)</span>
+ <span class="o">))</span>
+<span class="o">}</span>
+</pre></td></tr></tbody></table> </div> <p>The function <code>transform</code> takes the string features and outputs a post-PCA feature vector. This is not made a private class member since it must also be used in transforming future queries. The member <code>transformedData</code> is the data set represented as an object that can be simply thrown into a classification model!</p><p>The final step is to incorporate the <code>PreparatorParams</code> into the <code>Preparator</code> class. This requires very little editing:</p><div class="highlight scala"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1
+2
+3
+4
+5
+6</pre></td><td class="code"><pre><span class="k">class</span> <span class="nc">Preparator</span> <span class="o">(</span><span class="n">pp</span><span class="k">:</span> <span class="kt">PreparatorParams</span><span class="o">)</span> <span class="k">extends</span> <span class="nc">PPreparator</span><span class="o">[</span><span class="kt">TrainingData</span>, <span class="kt">PreparedData</span><span class="o">]</span> <span class="o">{</span>
+
+ <span class="k">def</span> <span class="n">prepare</span><span class="o">(</span><span class="n">sc</span><span class="k">:</span> <span class="kt">SparkContext</span><span class="o">,</span> <span class="n">trainingData</span><span class="k">:</span> <span class="kt">TrainingData</span><span class="o">)</span><span class="k">:</span> <span class="kt">PreparedData</span> <span class="o">=</span> <span class="o">{</span>
+ <span class="k">new</span> <span class="nc">PreparedData</span><span class="o">(</span><span class="n">trainingData</span><span class="o">.</span><span class="n">observations</span><span class="o">,</span> <span class="n">pp</span><span class="o">)</span>
+ <span class="o">}</span>
+<span class="o">}</span>
+</pre></td></tr></tbody></table> </div> <p>The Data Preparator engine component is now complete, and we can move on to the Algorithm component.</p><h3 id='algorithm-modifications' class='header-anchors'>Algorithm Modifications</h3><p>The default algorithm used in the classification template is Naive Bayes. Now, this is a <a href="https://en.wikipedia.org/wiki/Probabilistic_classification">probabilistic classifier</a> that makes certain assumptions about the data that do not really match the format of the PCA-transformed data. In particular, it assumes that the vectors consist of counts. In particular, this means it assumes non-negative feature values. However, upon applying PCA on the data, you have no guarantees that you will have purely non-negative features. Given this, you will delete the script <code>NaiveBayesAlgorithm.scala</code>, and create one called <code>LRAlgorithm.scala</code> (in the <code>src/main/scala/</code> directory) which implements <a href="https://en.wikipedi
a.org/wiki/Multinomial_logistic_regression">Multinomial Logistic Regression</a>. </p><p>The implementation details are not discussed in this guide, as the point of this guide is to show how to incorporate <strong>dimensionality reduction</strong> techniques by incorporating PCA. The latter paragraph is mentioned in order to emphasize the fact that applying the PCA transformation (or possibly other dimensionality reduction techniques) will largely remove the interpretability of features, so that model assumptions relying on such interpretations may no longer be satisfied. This is just something to keep in mind.</p><p>The following code is taken from the <a href="http://templates.prediction.io/PredictionIO/template-scala-parallel-textclassification">text classification engine template</a> and adapted to match the project definitions. Copy and paste into the new scala script, <code>LRAlgorithm.scala</code>: </p><div class="highlight scala"><table style="border-spacing: 0"><tbody><tr><t
d class="gutter gl" style="text-align: right"><pre class="lineno">1
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+110</pre></td><td class="code"><pre><span class="k">package</span> <span class="nn">FeatureReduction</span>
+
+<span class="k">import</span> <span class="nn">io.prediction.controller.Params</span>
+<span class="k">import</span> <span class="nn">io.prediction.controller.P2LAlgorithm</span>
+<span class="k">import</span> <span class="nn">org.apache.spark.SparkContext</span>
+<span class="k">import</span> <span class="nn">org.apache.spark.ml.classification.LogisticRegression</span>
+<span class="k">import</span> <span class="nn">org.apache.spark.sql.DataFrame</span>
+<span class="k">import</span> <span class="nn">org.apache.spark.sql.functions</span>
+<span class="k">import</span> <span class="nn">org.apache.spark.sql.SQLContext</span>
+<span class="k">import</span> <span class="nn">org.apache.spark.sql.UserDefinedFunction</span>
+<span class="k">import</span> <span class="nn">scala.math._</span>
+
+
+<span class="k">case</span> <span class="k">class</span> <span class="nc">LRAlgorithmParams</span> <span class="o">(</span>
+<span class="n">regParam</span> <span class="k">:</span> <span class="kt">Double</span>
+<span class="o">)</span> <span class="k">extends</span> <span class="nc">Params</span>
+
+
+<span class="k">class</span> <span class="nc">LRAlgorithm</span><span class="o">(</span>
+<span class="k">val</span> <span class="n">sap</span><span class="k">:</span> <span class="kt">LRAlgorithmParams</span>
+<span class="o">)</span> <span class="k">extends</span> <span class="n">P2LAlgorithm</span><span class="o">[</span><span class="kt">PreparedData</span>, <span class="kt">LRModel</span>, <span class="kt">Query</span>, <span class="kt">PredictedResult</span><span class="o">]</span> <span class="o">{</span>
+
+ <span class="c1">// Train your model.
+</span> <span class="k">def</span> <span class="n">train</span><span class="o">(</span><span class="n">sc</span><span class="k">:</span> <span class="kt">SparkContext</span><span class="o">,</span> <span class="n">pd</span><span class="k">:</span> <span class="kt">PreparedData</span><span class="o">)</span><span class="k">:</span> <span class="kt">LRModel</span> <span class="o">=</span> <span class="o">{</span>
+ <span class="k">new</span> <span class="nc">LRModel</span><span class="o">(</span><span class="n">sc</span><span class="o">,</span> <span class="n">pd</span><span class="o">,</span> <span class="n">sap</span><span class="o">.</span><span class="n">regParam</span><span class="o">)</span>
+ <span class="o">}</span>
+
+ <span class="c1">// Prediction method for trained model.
+</span> <span class="k">def</span> <span class="n">predict</span><span class="o">(</span><span class="n">model</span><span class="k">:</span> <span class="kt">LRModel</span><span class="o">,</span> <span class="n">query</span><span class="k">:</span> <span class="kt">Query</span><span class="o">)</span><span class="k">:</span> <span class="kt">PredictedResult</span> <span class="o">=</span> <span class="o">{</span>
+ <span class="n">model</span><span class="o">.</span><span class="n">predict</span><span class="o">(</span><span class="n">query</span><span class="o">.</span><span class="n">features</span><span class="o">)</span>
+ <span class="o">}</span>
+<span class="o">}</span>
+
+<span class="k">class</span> <span class="nc">LRModel</span> <span class="o">(</span>
+<span class="n">sc</span> <span class="k">:</span> <span class="kt">SparkContext</span><span class="o">,</span>
+<span class="n">pd</span> <span class="k">:</span> <span class="kt">PreparedData</span><span class="o">,</span>
+<span class="n">regParam</span> <span class="k">:</span> <span class="kt">Double</span>
+<span class="o">)</span> <span class="k">extends</span> <span class="nc">Serializable</span> <span class="o">{</span>
+
+ <span class="c1">// 1. Import SQLContext for creating DataFrame.
+</span> <span class="k">private</span> <span class="k">val</span> <span class="n">sql</span> <span class="k">:</span> <span class="kt">SQLContext</span> <span class="o">=</span> <span class="k">new</span> <span class="nc">SQLContext</span><span class="o">(</span><span class="n">sc</span><span class="o">)</span>
+ <span class="k">import</span> <span class="nn">sql.implicits._</span>
+
+ <span class="c1">// 2. Initialize logistic regression model with regularization parameter.
+</span> <span class="k">private</span> <span class="k">val</span> <span class="n">lr</span> <span class="k">=</span> <span class="k">new</span> <span class="nc">LogisticRegression</span><span class="o">()</span>
+ <span class="o">.</span><span class="n">setMaxIter</span><span class="o">(</span><span class="mi">100</span><span class="o">)</span>
+ <span class="o">.</span><span class="n">setThreshold</span><span class="o">(</span><span class="mf">0.5</span><span class="o">)</span>
+ <span class="o">.</span><span class="n">setRegParam</span><span class="o">(</span><span class="n">regParam</span><span class="o">)</span>
+
+ <span class="k">private</span> <span class="k">val</span> <span class="n">labels</span> <span class="k">:</span> <span class="kt">Seq</span><span class="o">[</span><span class="kt">Double</span><span class="o">]</span> <span class="k">=</span> <span class="n">pd</span><span class="o">.</span><span class="n">transformedData</span><span class="o">.</span><span class="n">map</span><span class="o">(</span><span class="n">e</span> <span class="k">=></span> <span class="n">e</span><span class="o">.</span><span class="n">label</span><span class="o">).</span><span class="n">distinct</span><span class="o">.</span><span class="n">collect</span><span class="o">.</span><span class="n">toSeq</span>
+
+ <span class="k">private</span> <span class="k">case</span> <span class="k">class</span> <span class="nc">LREstimate</span> <span class="o">(</span>
+ <span class="n">coefficients</span> <span class="k">:</span> <span class="kt">Array</span><span class="o">[</span><span class="kt">Double</span><span class="o">],</span>
+ <span class="n">intercept</span> <span class="k">:</span> <span class="kt">Double</span>
+ <span class="o">)</span> <span class="k">extends</span> <span class="nc">Serializable</span>
+
+ <span class="k">private</span> <span class="k">val</span> <span class="n">data</span> <span class="k">=</span> <span class="n">labels</span><span class="o">.</span><span class="n">foldLeft</span><span class="o">(</span><span class="n">pd</span><span class="o">.</span><span class="n">transformedData</span><span class="o">.</span><span class="n">toDF</span><span class="o">)(</span> <span class="c1">//transform to Spark DataFrame
+</span>
+ <span class="c1">// Add the different binary columns for each label.
+</span> <span class="o">(</span><span class="n">data</span> <span class="k">:</span> <span class="kt">DataFrame</span><span class="o">,</span> <span class="n">label</span> <span class="k">:</span> <span class="kt">Double</span><span class="o">)</span> <span class="k">=></span> <span class="o">{</span>
+ <span class="c1">// function: multiclass labels --> binary labels
+</span> <span class="k">val</span> <span class="n">f</span> <span class="k">:</span> <span class="kt">UserDefinedFunction</span> <span class="o">=</span> <span class="n">functions</span><span class="o">.</span><span class="n">udf</span><span class="o">((</span><span class="n">e</span> <span class="k">:</span> <span class="kt">Double</span><span class="o">)</span> <span class="k">=></span> <span class="k">if</span> <span class="o">(</span><span class="n">e</span> <span class="o">==</span> <span class="n">label</span><span class="o">)</span> <span class="mf">1.0</span> <span class="k">else</span> <span class="mf">0.0</span><span class="o">)</span>
+
+ <span class="n">data</span><span class="o">.</span><span class="n">withColumn</span><span class="o">(</span><span class="n">label</span><span class="o">.</span><span class="n">toInt</span><span class="o">.</span><span class="n">toString</span><span class="o">,</span> <span class="n">f</span><span class="o">(</span><span class="n">data</span><span class="o">(</span><span class="s">"label"</span><span class="o">)))</span>
+ <span class="o">}</span>
+ <span class="o">)</span>
+
+ <span class="c1">// 3. Create a logistic regression model for each class.
+</span> <span class="k">private</span> <span class="k">val</span> <span class="n">lrModels</span> <span class="k">:</span> <span class="kt">Seq</span><span class="o">[(</span><span class="kt">Double</span>, <span class="kt">LREstimate</span><span class="o">)]</span> <span class="k">=</span> <span class="n">labels</span><span class="o">.</span><span class="n">map</span><span class="o">(</span>
+ <span class="n">label</span> <span class="k">=></span> <span class="o">{</span>
+ <span class="k">val</span> <span class="n">lab</span> <span class="k">=</span> <span class="n">label</span><span class="o">.</span><span class="n">toInt</span><span class="o">.</span><span class="n">toString</span>
+
+ <span class="k">val</span> <span class="n">fit</span> <span class="k">=</span> <span class="n">lr</span><span class="o">.</span><span class="n">setLabelCol</span><span class="o">(</span><span class="n">lab</span><span class="o">).</span><span class="n">fit</span><span class="o">(</span>
+ <span class="n">data</span><span class="o">.</span><span class="n">select</span><span class="o">(</span><span class="n">lab</span><span class="o">,</span> <span class="s">"features"</span><span class="o">)</span>
+ <span class="o">)</span>
+
+ <span class="c1">// Return (label, feature coefficients, and intercept term.
+</span> <span class="o">(</span><span class="n">label</span><span class="o">,</span> <span class="nc">LREstimate</span><span class="o">(</span><span class="n">fit</span><span class="o">.</span><span class="n">weights</span><span class="o">.</span><span class="n">toArray</span><span class="o">,</span> <span class="n">fit</span><span class="o">.</span><span class="n">intercept</span><span class="o">))</span>
+
+ <span class="o">}</span>
+ <span class="o">)</span>
+
+ <span class="c1">// 4. Enable vector inner product for prediction.
+</span>
+ <span class="k">private</span> <span class="k">def</span> <span class="n">innerProduct</span> <span class="o">(</span><span class="n">x</span> <span class="k">:</span> <span class="kt">Array</span><span class="o">[</span><span class="kt">Double</span><span class="o">],</span> <span class="n">y</span> <span class="k">:</span> <span class="kt">Array</span><span class="o">[</span><span class="kt">Double</span><span class="o">])</span> <span class="k">:</span> <span class="kt">Double</span> <span class="o">=</span> <span class="o">{</span>
+ <span class="n">x</span><span class="o">.</span><span class="n">zip</span><span class="o">(</span><span class="n">y</span><span class="o">).</span><span class="n">map</span><span class="o">(</span><span class="n">e</span> <span class="k">=></span> <span class="n">e</span><span class="o">.</span><span class="n">_1</span> <span class="o">*</span> <span class="n">e</span><span class="o">.</span><span class="n">_2</span><span class="o">).</span><span class="n">sum</span>
+ <span class="o">}</span>
+
+ <span class="c1">// 5. Define prediction rule.
+</span> <span class="k">def</span> <span class="n">predict</span><span class="o">(</span><span class="n">text</span> <span class="k">:</span> <span class="kt">String</span><span class="o">)</span><span class="k">:</span> <span class="kt">PredictedResult</span> <span class="o">=</span> <span class="o">{</span>
+ <span class="k">val</span> <span class="n">x</span><span class="k">:</span> <span class="kt">Array</span><span class="o">[</span><span class="kt">Double</span><span class="o">]</span> <span class="k">=</span> <span class="n">pd</span><span class="o">.</span><span class="n">transform</span><span class="o">(</span><span class="n">text</span><span class="o">).</span><span class="n">toArray</span>
+
+ <span class="c1">// Logistic Regression binary formula for positive probability.
+</span> <span class="c1">// According to MLLib documentation, class labeled 0 is used as pivot.
+</span> <span class="c1">// Thus, we are using:
+</span> <span class="c1">// log(p1/p0) = log(p1/(1 - p1)) = b0 + xTb =: z
+</span> <span class="c1">// p1 = exp(z) * (1 - p1)
+</span> <span class="c1">// p1 * (1 + exp(z)) = exp(z)
+</span> <span class="c1">// p1 = exp(z)/(1 + exp(z))
+</span> <span class="k">val</span> <span class="n">pred</span> <span class="k">=</span> <span class="n">lrModels</span><span class="o">.</span><span class="n">map</span><span class="o">(</span>
+ <span class="n">e</span> <span class="k">=></span> <span class="o">{</span>
+ <span class="k">val</span> <span class="n">z</span> <span class="k">=</span> <span class="n">exp</span><span class="o">(</span><span class="n">innerProduct</span><span class="o">(</span><span class="n">e</span><span class="o">.</span><span class="n">_2</span><span class="o">.</span><span class="n">coefficients</span><span class="o">,</span> <span class="n">x</span><span class="o">)</span> <span class="o">+</span> <span class="n">e</span><span class="o">.</span><span class="n">_2</span><span class="o">.</span><span class="n">intercept</span><span class="o">)</span>
+ <span class="o">(</span><span class="n">e</span><span class="o">.</span><span class="n">_1</span><span class="o">,</span> <span class="n">z</span> <span class="o">/</span> <span class="o">(</span><span class="mi">1</span> <span class="o">+</span> <span class="n">z</span><span class="o">))</span>
+ <span class="o">}</span>
+ <span class="o">).</span><span class="n">maxBy</span><span class="o">(</span><span class="k">_</span><span class="o">.</span><span class="n">_2</span><span class="o">)</span>
+
+ <span class="k">new</span> <span class="nc">PredictedResult</span><span class="o">(</span><span class="n">pred</span><span class="o">.</span><span class="n">_1</span><span class="o">)</span>
+ <span class="o">}</span>
+
+<span class="o">}</span>
+</pre></td></tr></tbody></table> </div> <h3 id='serving-modifications' class='header-anchors'>Serving Modifications</h3><p>Since you did not make any modifications in the definition of the class <code>PredictedResult</code>, the Serving engine component does not need to be modified.</p><h3 id='evaluation-modifications' class='header-anchors'>Evaluation Modifications</h3><p>Here the only modifications you need to make are in the <code>EngineParamsList</code> object:</p><div class="highlight scala"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1
+2
+3
+4
+5
+6
+7
+8
+9
+10
+11
+12
+13
+14
+15
+16
+17
+18</pre></td><td class="code"><pre><span class="k">object</span> <span class="nc">EngineParamsList</span> <span class="k">extends</span> <span class="nc">EngineParamsGenerator</span> <span class="o">{</span>
+ <span class="c1">// Define list of EngineParams used in Evaluation
+</span>
+ <span class="c1">// First, we define the base engine params. It specifies the appId from which
+</span> <span class="c1">// the data is read, and a evalK parameter is used to define the
+</span> <span class="c1">// cross-validation.
+</span> <span class="k">private</span><span class="o">[</span><span class="kt">this</span><span class="o">]</span> <span class="k">val</span> <span class="n">baseEP</span> <span class="k">=</span> <span class="nc">EngineParams</span><span class="o">(</span>
+ <span class="n">dataSourceParams</span> <span class="k">=</span> <span class="nc">DataSourceParams</span><span class="o">(</span><span class="n">appName</span> <span class="k">=</span> <span class="s">"FeatureReduction"</span><span class="o">,</span> <span class="n">evalK</span> <span class="k">=</span> <span class="nc">Some</span><span class="o">(</span><span class="mi">3</span><span class="o">)),</span>
+ <span class="n">preparatorParams</span> <span class="k">=</span> <span class="nc">PreparatorParams</span><span class="o">(</span><span class="n">numFeatures</span> <span class="k">=</span> <span class="mi">250</span><span class="o">))</span>
+
+ <span class="c1">// Second, we specify the engine params list by explicitly listing all
+</span> <span class="c1">// algorithm parameters. In this case, we evaluate 3 engine params, each with
+</span> <span class="c1">// a different algorithm params value.
+</span> <span class="n">engineParamsList</span> <span class="k">=</span> <span class="nc">Seq</span><span class="o">(</span>
+ <span class="n">baseEP</span><span class="o">.</span><span class="n">copy</span><span class="o">(</span><span class="n">algorithmParamsList</span> <span class="k">=</span> <span class="nc">Seq</span><span class="o">((</span><span class="s">"lr"</span><span class="o">,</span> <span class="nc">LRAlgorithmParams</span><span class="o">(</span><span class="mf">0.5</span><span class="o">)))),</span>
+ <span class="n">baseEP</span><span class="o">.</span><span class="n">copy</span><span class="o">(</span><span class="n">algorithmParamsList</span> <span class="k">=</span> <span class="nc">Seq</span><span class="o">((</span><span class="s">"lr"</span><span class="o">,</span> <span class="nc">LRAlgorithmParams</span><span class="o">(</span><span class="mf">2.5</span><span class="o">)))),</span>
+ <span class="n">baseEP</span><span class="o">.</span><span class="n">copy</span><span class="o">(</span><span class="n">algorithmParamsList</span> <span class="k">=</span> <span class="nc">Seq</span><span class="o">((</span><span class="s">"lr"</span><span class="o">,</span> <span class="nc">LRAlgorithmParams</span><span class="o">(</span><span class="mf">7.5</span><span class="o">)))))</span>
+<span class="o">}</span>
+</pre></td></tr></tbody></table> </div> <p>The main modifications reflect the change in algorithm, and the addition of the <code>PreparatorParams</code> class. This concludes the modifications to the DASE components. There are only a few modifications left:</p><h3 id='other-engine-modifications' class='header-anchors'>Other Engine Modifications</h3><p>There are two last modifications before we have a working template. First, since you deleted the <code>NaiveBayesAlgorithm.scala</code> script and replaced it with the <code>LRAlgorithm.scala</code> script, you must modify the <code>ClassificationEngine</code> object:</p><div class="highlight scala"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1
+2
+3
+4
+5
+6
+7
+8
+9
+10
+11</pre></td><td class="code"><pre><span class="k">object</span> <span class="nc">ClassificationEngine</span> <span class="k">extends</span> <span class="nc">EngineFactory</span> <span class="o">{</span>
+ <span class="k">def</span> <span class="n">apply</span><span class="o">()</span> <span class="k">=</span> <span class="o">{</span>
+ <span class="k">new</span> <span class="nc">Engine</span><span class="o">(</span>
+ <span class="n">classOf</span><span class="o">[</span><span class="kt">DataSource</span><span class="o">],</span>
+ <span class="n">classOf</span><span class="o">[</span><span class="kt">Preparator</span><span class="o">],</span>
+ <span class="nc">Map</span><span class="o">(</span>
+ <span class="s">"lr"</span> <span class="o">-></span> <span class="n">classOf</span><span class="o">[</span><span class="kt">LRAlgorithm</span><span class="o">]</span>
+ <span class="o">),</span> <span class="n">classOf</span><span class="o">[</span><span class="kt">Serving</span><span class="o">]</span>
+ <span class="o">)</span>
+ <span class="o">}</span>
+<span class="o">}</span>
+</pre></td></tr></tbody></table> </div> <p>Next you will have to also modify the <code>engine.json</code> file, which is where you set the different component parameters:</p><div class="highlight json"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1
+2
+3
+4
+5
+6
+7
+8
+9
+10
+11
+12
+13
+14
+15
+16
+17
+18
+19
+20
+21
+22
+23</pre></td><td class="code"><pre><span class="p">{</span><span class="w">
+ </span><span class="s2">"id"</span><span class="p">:</span><span class="w"> </span><span class="s2">"default"</span><span class="p">,</span><span class="w">
+ </span><span class="s2">"description"</span><span class="p">:</span><span class="w"> </span><span class="s2">"Default settings"</span><span class="p">,</span><span class="w">
+ </span><span class="s2">"engineFactory"</span><span class="p">:</span><span class="w"> </span><span class="s2">"FeatureReduction.ClassificationEngine"</span><span class="p">,</span><span class="w">
+ </span><span class="s2">"datasource"</span><span class="p">:</span><span class="w"> </span><span class="p">{</span><span class="w">
+ </span><span class="s2">"params"</span><span class="p">:</span><span class="w"> </span><span class="p">{</span><span class="w">
+ </span><span class="s2">"appName"</span><span class="p">:</span><span class="w"> </span><span class="s2">"FeatureReduction"</span><span class="w">
+ </span><span class="p">}</span><span class="w">
+ </span><span class="p">},</span><span class="w">
+ </span><span class="s2">"preparator"</span><span class="p">:{</span><span class="w">
+ </span><span class="s2">"params"</span><span class="p">:</span><span class="w"> </span><span class="p">{</span><span class="w">
+ </span><span class="s2">"numFeatures"</span><span class="p">:</span><span class="w"> </span><span class="mi">250</span><span class="w">
+ </span><span class="p">}</span><span class="w">
+ </span><span class="p">},</span><span class="w">
+ </span><span class="s2">"algorithms"</span><span class="p">:</span><span class="w"> </span><span class="p">[</span><span class="w">
+ </span><span class="p">{</span><span class="w">
+ </span><span class="s2">"name"</span><span class="p">:</span><span class="w"> </span><span class="s2">"lr"</span><span class="p">,</span><span class="w">
+ </span><span class="s2">"params"</span><span class="p">:</span><span class="w"> </span><span class="p">{</span><span class="w">
+ </span><span class="s2">"regParam"</span><span class="p">:</span><span class="w"> </span><span class="mf">1.0</span><span class="w">
+ </span><span class="p">}</span><span class="w">
+ </span><span class="p">}</span><span class="w">
+ </span><span class="p">]</span><span class="w">
+</span><span class="p">}</span><span class="w">
+</span></pre></td></tr></tbody></table> </div> <h2 id='testing-the-engine' class='header-anchors'>Testing the Engine</h2><p>Congratulations, the engine is now ready to go. Firstly, go ahead and run the following command again:</p><div class="highlight shell"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1</pre></td><td class="code"><pre>pio build
+</pre></td></tr></tbody></table> </div> <p>The easiest way to begin testing it right away is to do an evaluation:</p><div class="highlight shell"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1</pre></td><td class="code"><pre>pio <span class="nb">eval </span>FeatureReduction.AccuracyEvaluation FeatureReduction.EngineParamsList
+</pre></td></tr></tbody></table> </div> <p>Given the current evaluation settings and logistic regression implementation (multinomial logistic regression from binary logistic regression): evalK = 3, 3 parameters being tested, and 10 different classes this will be creating a binary logistic regression model \(3 \times 3 \times 10 = 90\) times, so that it will take some time to run locally on your machine. You can decrease the latter number of models by: (a) decreasing evalK to 2, or (b) reduce the number of parameters being tested to one or two. You can also increase the driver and executor memory to increase performance:</p><div class="highlight shell"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1</pre></td><td class="code"><pre>pio <span class="nb">eval </span>FeatureReduction.AccuracyEvaluation FeatureReduction.EngineParamsList -- --driver-memory xG --executor-memory yG
+</pre></td></tr></tbody></table> </div> <p>Here <code>x</code> and <code>y</code> should be replaced by whole numbers. Alternatively, you can train and deploy your engine as usual:</p><div class="highlight shell"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1
+2</pre></td><td class="code"><pre>pio train
+pio deploy
+</pre></td></tr></tbody></table> </div> <p>To query it, you will first need some test data. Go ahead and <a href="https://www.kaggle.com/c/digit-recognizer/data">download</a> the <code>test.csv</code> file and place it in the <code>data</code> directory. This contains 28,000 unlabeled pixel images. Next create the Python script <code>query.py</code> in the same data directory, and copy and paste the following:</p><div class="highlight python"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1
+2
+3
+4
+5
+6
+7
+8
+9
+10
+11
+12
+13
+14
+15
+16
+17
+18
+19
+20
+21
+22
+23
+24
+25
+26
+27</pre></td><td class="code"><pre><span class="kn">from</span> <span class="nn">PIL</span> <span class="kn">import</span> <span class="n">Image</span>
+<span class="kn">import</span> <span class="nn">sys</span>
+<span class="kn">import</span> <span class="nn">os</span>
+
+<span class="n">obs_num</span> <span class="o">=</span> <span class="nb">int</span><span class="p">(</span><span class="n">sys</span><span class="o">.</span><span class="n">argv</span><span class="p">[</span><span class="mi">1</span><span class="p">])</span>
+
+<span class="n">f</span> <span class="o">=</span> <span class="nb">open</span><span class="p">(</span><span class="s">'./data/test.csv'</span><span class="p">,</span> <span class="s">'r'</span><span class="p">)</span><span class="o">.</span><span class="n">read</span><span class="p">()</span><span class="o">.</span><span class="n">split</span><span class="p">(</span><span class="s">'</span><span class="se">\n</span><span class="s">'</span><span class="p">)</span>
+<span class="n">var_names</span> <span class="o">=</span> <span class="n">f</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span><span class="o">.</span><span class="n">split</span><span class="p">(</span><span class="s">','</span><span class="p">)</span>
+<span class="n">f</span> <span class="o">=</span> <span class="n">f</span><span class="p">[</span><span class="mi">1</span> <span class="p">:</span> <span class="o">-</span><span class="mi">1</span><span class="p">]</span>
+<span class="n">f</span> <span class="o">=</span> <span class="p">[</span><span class="nb">list</span><span class="p">(</span><span class="nb">map</span><span class="p">(</span><span class="nb">int</span><span class="p">,</span> <span class="n">x</span><span class="p">))</span> <span class="k">for</span> <span class="n">x</span> <span class="ow">in</span> <span class="p">(</span><span class="n">y</span><span class="o">.</span><span class="n">split</span><span class="p">(</span><span class="s">","</span><span class="p">)</span> <span class="k">for</span> <span class="n
<TRUNCATED>
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+<!DOCTYPE html><html><head><title>DASE Components Explained (E-Commerce Recommendation)</title><meta charset="utf-8"/><meta content="IE=edge,chrome=1" http-equiv="X-UA-Compatible"/><meta name="viewport" content="width=device-width, initial-scale=1.0"/><meta class="swiftype" name="title" data-type="string" content="DASE Components Explained (E-Commerce Recommendation)"/><link rel="canonical" href="https://docs.prediction.io/templates/ecommercerecommendation/dase/"/><link href="/images/favicon/normal-b330020a.png" rel="shortcut icon"/><link href="/images/favicon/apple-c0febcf2.png" rel="apple-touch-icon"/><link href="//fonts.googleapis.com/css?family=Open+Sans:300italic,400italic,600italic,700italic,800italic,400,300,600,700,800" rel="stylesheet"/><link href="//maxcdn.bootstrapcdn.com/font-awesome/4.2.0/css/font-awesome.min.css" rel="stylesheet"/><link href="/stylesheets/application-3598c7d7.css" rel="stylesheet" type="text/css"/><!--[if lt IE 9]><script src="//cdnjs.cloudflare.com/aj
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+fbq('track', "PageView");</script><script src="//use.typekit.net/mut4mjx.js"></script><script>try{Typekit.load();}catch(e){}</script></head><body><div id="global"><header><div class="container" id="header-wrapper"><div class="row"><div class="col-sm-12"><div id="logo-wrapper"><span id="drawer-toggle"></span><a href="#"></a><a href="http://prediction.io/"><img alt="PredictionIO" id="logo" src="/images/logos/logo-ee2b9bb3.png"/></a></div><div id="menu-wrapper"><div id="header-nav-options-wrapper"><ul><li><a href="/">Install & Doc</a></li> <li><a href="/support">Support</a></li> </ul></div><div id="pill-wrapper"><a class="pill left" href="//templates.prediction.io/">TEMPLATES</a> <a class="pill right" href="//github.com/PredictionIO/PredictionIO/">OPEN SOURCE</a></div></div><img class="mobile-search-bar-toggler hidden-md hidden-lg" src="/images/icons/search-glass-704bd4ff.png"/></div></div></div></header><div id="search-bar-row-wrapper"><div class="container-fluid" id="search-bar-row">
<div class="row"><div class="col-md-9 col-sm-11 col-xs-11"><div class="hidden-md hidden-lg" id="mobile-page-heading-wrapper"><p>PredictionIO Docs</p><h4>DASE Components Explained (E-Commerce Recommendation)</h4></div><h4 class="hidden-sm hidden-xs">PredictionIO Docs</h4></div><div class="col-md-3 col-sm-1 col-xs-1 hidden-md hidden-lg"><img id="left-menu-indicator" src="/images/icons/down-arrow-dfe9f7fe.png"/></div><div class="col-md-3 col-sm-12 col-xs-12 swiftype-wrapper"><div class="swiftype"><form class="search-form"><img class="search-box-toggler hidden-xs hidden-sm" src="/images/icons/search-glass-704bd4ff.png"/><div class="search-box"><img src="/images/icons/search-glass-704bd4ff.png"/><input type="text" id="st-search-input" class="st-search-input" placeholder="Search Doc..."/></div><img class="swiftype-row-hider hidden-md hidden-lg" src="/images/icons/drawer-toggle-active-fcbef12a.png"/></form></div></div><div class="mobile-left-menu-toggler hidden-md hidden-lg"></div></div></
div></div><div id="page" class="container-fluid"><div class="row"><div id="left-menu-wrapper" class="col-md-3"><nav id="nav-main"><ul><li class="level-1"><a class="expandible" href="/"><span>Apache PredictionIO (incubating) Documentation</span></a><ul><li class="level-2"><a class="final" href="/"><span>Welcome to Apache PredictionIO (incubating)</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Getting Started</span></a><ul><li class="level-2"><a class="final" href="/start/"><span>A Quick Intro</span></a></li><li class="level-2"><a class="final" href="/install/"><span>Installing Apache PredictionIO (incubating)</span></a></li><li class="level-2"><a class="final" href="/start/download/"><span>Downloading an Engine Template</span></a></li><li class="level-2"><a class="final" href="/start/deploy/"><span>Deploying Your First Engine</span></a></li><li class="level-2"><a class="final" href="/start/customize/"><span>Customizing the Engine</span></a></li></ul
></li><li class="level-1"><a class="expandible" href="#"><span>Integrating with Your App</span></a><ul><li class="level-2"><a class="final" href="/appintegration/"><span>App Integration Overview</span></a></li><li class="level-2"><a class="expandible" href="/sdk/"><span>List of SDKs</span></a><ul><li class="level-3"><a class="final" href="/sdk/java/"><span>Java & Android SDK</span></a></li><li class="level-3"><a class="final" href="/sdk/php/"><span>PHP SDK</span></a></li><li class="level-3"><a class="final" href="/sdk/python/"><span>Python SDK</span></a></li><li class="level-3"><a class="final" href="/sdk/ruby/"><span>Ruby SDK</span></a></li><li class="level-3"><a class="final" href="/sdk/community/"><span>Community Powered SDKs</span></a></li></ul></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Deploying an Engine</span></a><ul><li class="level-2"><a class="final" href="/deploy/"><span>Deploying as a Web Service</span></a></li><li class="level-2"><a class="f
inal" href="/cli/#engine-commands"><span>Engine Command-line Interface</span></a></li><li class="level-2"><a class="final" href="/deploy/engineparams/"><span>Setting Engine Parameters</span></a></li><li class="level-2"><a class="final" href="/deploy/enginevariants/"><span>Deploying Multiple Engine Variants</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Customizing an Engine</span></a><ul><li class="level-2"><a class="final" href="/customize/"><span>Learning DASE</span></a></li><li class="level-2"><a class="final" href="/customize/dase/"><span>Implement DASE</span></a></li><li class="level-2"><a class="final" href="/customize/troubleshooting/"><span>Troubleshooting Engine Development</span></a></li><li class="level-2"><a class="final" href="/api/current/#package"><span>Engine Scala APIs</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Collecting and Analyzing Data</span></a><ul><li class="level-2"><a class="final" hr
ef="/datacollection/"><span>Event Server Overview</span></a></li><li class="level-2"><a class="final" href="/cli/#event-server-commands"><span>Event Server Command-line Interface</span></a></li><li class="level-2"><a class="final" href="/datacollection/eventapi/"><span>Collecting Data with REST/SDKs</span></a></li><li class="level-2"><a class="final" href="/datacollection/eventmodel/"><span>Events Modeling</span></a></li><li class="level-2"><a class="final" href="/datacollection/webhooks/"><span>Unifying Multichannel Data with Webhooks</span></a></li><li class="level-2"><a class="final" href="/datacollection/channel/"><span>Channel</span></a></li><li class="level-2"><a class="final" href="/datacollection/batchimport/"><span>Importing Data in Batch</span></a></li><li class="level-2"><a class="final" href="/datacollection/analytics/"><span>Using Analytics Tools</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Choosing an Algorithm(s)</span></a><ul><li
class="level-2"><a class="final" href="/algorithm/"><span>Built-in Algorithm Libraries</span></a></li><li class="level-2"><a class="final" href="/algorithm/switch/"><span>Switching to Another Algorithm</span></a></li><li class="level-2"><a class="final" href="/algorithm/multiple/"><span>Combining Multiple Algorithms</span></a></li><li class="level-2"><a class="final" href="/algorithm/custom/"><span>Adding Your Own Algorithms</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>ML Tuning and Evaluation</span></a><ul><li class="level-2"><a class="final" href="/evaluation/"><span>Overview</span></a></li><li class="level-2"><a class="final" href="/evaluation/paramtuning/"><span>Hyperparameter Tuning</span></a></li><li class="level-2"><a class="final" href="/evaluation/evaluationdashboard/"><span>Evaluation Dashboard</span></a></li><li class="level-2"><a class="final" href="/evaluation/metricchoose/"><span>Choosing Evaluation Metrics</span></a></li><li class=
"level-2"><a class="final" href="/evaluation/metricbuild/"><span>Building Evaluation Metrics</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>System Architecture</span></a><ul><li class="level-2"><a class="final" href="/system/"><span>Architecture Overview</span></a></li><li class="level-2"><a class="final" href="/system/anotherdatastore/"><span>Using Another Data Store</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Engine Template Gallery</span></a><ul><li class="level-2"><a class="final" href="http://templates.prediction.io"><span>Browse</span></a></li><li class="level-2"><a class="final" href="/community/submit-template/"><span>Submit your Engine as a Template</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Demo Tutorials</span></a><ul><li class="level-2"><a class="final" href="/demo/tapster/"><span>Comics Recommendation Demo</span></a></li><li class="level-2"><a class="final" hr
ef="/demo/community/"><span>Community Contributed Demo</span></a></li><li class="level-2"><a class="final" href="/demo/textclassification/"><span>Text Classification Engine Tutorial</span></a></li></ul></li><li class="level-1"><a class="expandible" href="/community/"><span>Getting Involved</span></a><ul><li class="level-2"><a class="final" href="/community/contribute-code/"><span>Contribute Code</span></a></li><li class="level-2"><a class="final" href="/community/contribute-documentation/"><span>Contribute Documentation</span></a></li><li class="level-2"><a class="final" href="/community/contribute-sdk/"><span>Contribute a SDK</span></a></li><li class="level-2"><a class="final" href="/community/contribute-webhook/"><span>Contribute a Webhook</span></a></li><li class="level-2"><a class="final" href="/community/projects/"><span>Community Projects</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Getting Help</span></a><ul><li class="level-2"><a class="f
inal" href="/resources/faq/"><span>FAQs</span></a></li><li class="level-2"><a class="final" href="/support/"><span>Community Support</span></a></li><li class="level-2"><a class="final" href="/support/#enterprise-support"><span>Enterprise Support</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Resources</span></a><ul><li class="level-2"><a class="final" href="/resources/intellij/"><span>Developing Engines with IntelliJ IDEA</span></a></li><li class="level-2"><a class="final" href="/resources/upgrade/"><span>Upgrade Instructions</span></a></li><li class="level-2"><a class="final" href="/resources/glossary/"><span>Glossary</span></a></li></ul></li></ul></nav></div><div class="col-md-9 col-sm-12"><div class="content-header hidden-md hidden-lg"><div id="page-title"><h1>DASE Components Explained (E-Commerce Recommendation)</h1></div></div><div id="table-of-content-wrapper"><h5>On this page</h5><aside id="table-of-contents"><ul> <li> <a href="#the-engine-d
esign">The Engine Design</a> </li> <li> <a href="#data">Data</a> </li> <li> <a href="#algorithm">Algorithm</a> </li> <li> <a href="#serving">Serving</a> </li> </ul> </aside><hr/><a id="edit-page-link" href="https://github.com/apache/incubator-predictionio/tree/livedoc/docs/manual/source/templates/ecommercerecommendation/dase.html.md.erb"><img src="/images/icons/edit-pencil-d6c1bb3d.png"/>Edit this page</a></div><div class="content-header hidden-sm hidden-xs"><div id="page-title"><h1>DASE Components Explained (E-Commerce Recommendation)</h1></div></div><div class="content"><p>PredictionIO's DASE architecture brings the separation-of-concerns design principle to predictive engine development. DASE stands for the following components of an engine:</p> <ul> <li><strong>D</strong>ata - includes Data Source and Data Preparator</li> <li><strong>A</strong>lgorithm(s)</li> <li><strong>S</strong>erving</li> <li><strong>E</strong>valuator</li> </ul> <p><p>Let's look at the code and see
how you can customize the engine you built from the E-Commerce Recommendation Engine Template.</p><div class="alert-message note"><p>Evaluator will not be covered in this tutorial.</p></div></p><h2 id='the-engine-design' class='header-anchors'>The Engine Design</h2><p>As you can see from the Quick Start, <em>MyECommerceRecommendation</em> takes a JSON prediction query, e.g. <code>{ "user": "u1", "num": 4 }</code>, and return a JSON predicted result. In MyECommerceRecommendation/src/main/scala/<strong><em>Engine.scala</em></strong>, the <code>Query</code> case class defines the format of such <strong>query</strong>:</p><div class="highlight scala"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1
+2
+3
+4
+5
+6
+7</pre></td><td class="code"><pre><span class="k">case</span> <span class="k">class</span> <span class="nc">Query</span><span class="o">(</span>
+ <span class="n">user</span><span class="k">:</span> <span class="kt">String</span><span class="o">,</span>
+ <span class="n">num</span><span class="k">:</span> <span class="kt">Int</span><span class="o">,</span>
+ <span class="n">categories</span><span class="k">:</span> <span class="kt">Option</span><span class="o">[</span><span class="kt">Set</span><span class="o">[</span><span class="kt">String</span><span class="o">]],</span>
+ <span class="n">whiteList</span><span class="k">:</span> <span class="kt">Option</span><span class="o">[</span><span class="kt">Set</span><span class="o">[</span><span class="kt">String</span><span class="o">]],</span>
+ <span class="n">blackList</span><span class="k">:</span> <span class="kt">Option</span><span class="o">[</span><span class="kt">Set</span><span class="o">[</span><span class="kt">String</span><span class="o">]]</span>
+<span class="o">)</span> <span class="k">extends</span> <span class="nc">Serializable</span>
+</pre></td></tr></tbody></table> </div> <p>The <code>PredictedResult</code> case class defines the format of <strong>predicted result</strong>, such as</p><div class="highlight json"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1
+2
+3
+4
+5
+6</pre></td><td class="code"><pre><span class="p">{</span><span class="s2">"itemScores"</span><span class="p">:[</span><span class="w">
+ </span><span class="p">{</span><span class="s2">"item"</span><span class="p">:</span><span class="mi">22</span><span class="p">,</span><span class="s2">"score"</span><span class="p">:</span><span class="mf">4.07</span><span class="p">},</span><span class="w">
+ </span><span class="p">{</span><span class="s2">"item"</span><span class="p">:</span><span class="mi">62</span><span class="p">,</span><span class="s2">"score"</span><span class="p">:</span><span class="mf">4.05</span><span class="p">},</span><span class="w">
+ </span><span class="p">{</span><span class="s2">"item"</span><span class="p">:</span><span class="mi">75</span><span class="p">,</span><span class="s2">"score"</span><span class="p">:</span><span class="mf">4.04</span><span class="p">},</span><span class="w">
+ </span><span class="p">{</span><span class="s2">"item"</span><span class="p">:</span><span class="mi">68</span><span class="p">,</span><span class="s2">"score"</span><span class="p">:</span><span class="mf">3.81</span><span class="p">}</span><span class="w">
+</span><span class="p">]}</span><span class="w">
+</span></pre></td></tr></tbody></table> </div> <p>with:</p><div class="highlight scala"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1
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+ <span class="n">itemScores</span><span class="k">:</span> <span class="kt">Array</span><span class="o">[</span><span class="kt">ItemScore</span><span class="o">]</span>
+<span class="o">)</span> <span class="k">extends</span> <span class="nc">Serializable</span>
+
+<span class="k">case</span> <span class="k">class</span> <span class="nc">ItemScore</span><span class="o">(</span>
+ <span class="n">item</span><span class="k">:</span> <span class="kt">String</span><span class="o">,</span>
+ <span class="n">score</span><span class="k">:</span> <span class="kt">Double</span>
+<span class="o">)</span> <span class="k">extends</span> <span class="nc">Serializable</span>
+</pre></td></tr></tbody></table> </div> <p>Finally, <code>ECommerceRecommendationEngine</code> is the <em>Engine Factory</em> that defines the components this engine will use: Data Source, Data Preparator, Algorithm(s) and Serving components.</p><div class="highlight scala"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1
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+9</pre></td><td class="code"><pre><span class="k">object</span> <span class="nc">ECommerceRecommendationEngine</span> <span class="k">extends</span> <span class="nc">IEngineFactory</span> <span class="o">{</span>
+ <span class="k">def</span> <span class="n">apply</span><span class="o">()</span> <span class="k">=</span> <span class="o">{</span>
+ <span class="k">new</span> <span class="nc">Engine</span><span class="o">(</span>
+ <span class="n">classOf</span><span class="o">[</span><span class="kt">DataSource</span><span class="o">],</span>
+ <span class="n">classOf</span><span class="o">[</span><span class="kt">Preparator</span><span class="o">],</span>
+ <span class="nc">Map</span><span class="o">(</span><span class="s">"ecomm"</span> <span class="o">-></span> <span class="n">classOf</span><span class="o">[</span><span class="kt">ECommAlgorithm</span><span class="o">]),</span>
+ <span class="n">classOf</span><span class="o">[</span><span class="kt">Serving</span><span class="o">])</span>
+ <span class="o">}</span>
+<span class="o">}</span>
+</pre></td></tr></tbody></table> </div> <h3 id='spark-mllib' class='header-anchors'>Spark MLlib</h3><p>The PredictionIO E-Commerce Recommendation Engine Template integrates Spark's MLlib ALS algorithm under the DASE architecture. We will take a closer look at the DASE code below.</p><p>The MLlib ALS algorithm takes training data of RDD type, i.e. <code>RDD[Rating]</code> and train a model, which is a <code>MatrixFactorizationModel</code> object.</p><p>You can visit <a href="https://spark.apache.org/docs/latest/mllib-collaborative-filtering.html">here</a> to learn more about MLlib's ALS collaborative filtering algorithm.</p><h2 id='data' class='header-anchors'>Data</h2><p>In the DASE architecture, data is prepared by 2 components sequentially: <em>DataSource</em> and <em>DataPreparator</em>. They take data from the data store and prepare them for Algorithm.</p><h3 id='data-source' class='header-anchors'>Data Source</h3><p>In MyECommerceRecommendation/src/main/scala/<strong><e
m>DataSource.scala</em></strong>, the <code>readTraining</code> method of class <code>DataSource</code> reads and selects data from the <em>Event Store</em> (data store of the <em>Event Server</em>). It returns <code>TrainingData</code>.</p><div class="highlight scala"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1
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+
+<span class="k">class</span> <span class="nc">DataSource</span><span class="o">(</span><span class="k">val</span> <span class="n">dsp</span><span class="k">:</span> <span class="kt">DataSourceParams</span><span class="o">)</span>
+ <span class="k">extends</span> <span class="nc">PDataSource</span><span class="o">[</span><span class="kt">TrainingData</span>,
+ <span class="kt">EmptyEvaluationInfo</span>, <span class="kt">Query</span>, <span class="kt">EmptyActualResult</span><span class="o">]</span> <span class="o">{</span>
+
+ <span class="nd">@transient</span> <span class="k">lazy</span> <span class="k">val</span> <span class="n">logger</span> <span class="k">=</span> <span class="nc">Logger</span><span class="o">[</span><span class="kt">this.</span><span class="k">type</span><span class="o">]</span>
+
+ <span class="k">override</span>
+ <span class="k">def</span> <span class="n">readTraining</span><span class="o">(</span><span class="n">sc</span><span class="k">:</span> <span class="kt">SparkContext</span><span class="o">)</span><span class="k">:</span> <span class="kt">TrainingData</span> <span class="o">=</span> <span class="o">{</span>
+
+ <span class="c1">// create a RDD of (entityID, User)
+</span> <span class="k">val</span> <span class="n">usersRDD</span><span class="k">:</span> <span class="kt">RDD</span><span class="o">[(</span><span class="kt">String</span>, <span class="kt">User</span><span class="o">)]</span> <span class="k">=</span> <span class="nc">PEventStore</span><span class="o">.</span><span class="n">aggregateProperties</span><span class="o">(...)</span> <span class="o">...</span>
+
+ <span class="c1">// create a RDD of (entityID, Item)
+</span> <span class="k">val</span> <span class="n">itemsRDD</span><span class="k">:</span> <span class="kt">RDD</span><span class="o">[(</span><span class="kt">String</span>, <span class="kt">Item</span><span class="o">)]</span> <span class="k">=</span> <span class="nc">PEventStore</span><span class="o">.</span><span class="n">aggregateProperties</span><span class="o">(...)</span> <span class="o">...</span>
+
+ <span class="c1">// get all "user" "view" or "buy" "item" events from event store
+</span> <span class="k">val</span> <span class="n">eventsRDD</span><span class="k">:</span> <span class="kt">RDD</span><span class="o">[</span><span class="kt">Event</span><span class="o">]</span> <span class="k">=</span> <span class="nc">PEventStore</span><span class="o">.</span><span class="n">find</span><span class="o">(...)</span> <span class="o">...</span>
+
+ <span class="c1">// filter all view events
+</span> <span class="k">val</span> <span class="n">viewEventsRDD</span><span class="k">:</span> <span class="kt">RDD</span><span class="o">[</span><span class="kt">ViewEvent</span><span class="o">]</span> <span class="k">=</span> <span class="n">eventsRDD</span><span class="o">.</span><span class="n">filter</span> <span class="o">{</span> <span class="o">...</span> <span class="o">}</span> <span class="o">...</span>
+
+ <span class="c1">// filter all buy events
+</span> <span class="k">val</span> <span class="n">buyEventsRDD</span><span class="k">:</span> <span class="kt">RDD</span><span class="o">[</span><span class="kt">BuyEvent</span><span class="o">]</span> <span class="k">=</span> <span class="n">eventsRDD</span><span class="o">.</span><span class="n">filter</span> <span class="o">{</span> <span class="o">...}</span> <span class="o">...</span>
+
+ <span class="k">new</span> <span class="nc">TrainingData</span><span class="o">(</span>
+ <span class="n">users</span> <span class="k">=</span> <span class="n">usersRDD</span><span class="o">,</span>
+ <span class="n">items</span> <span class="k">=</span> <span class="n">itemsRDD</span><span class="o">,</span>
+ <span class="n">viewEvents</span> <span class="k">=</span> <span class="n">viewEventsRDD</span><span class="o">,</span>
+ <span class="n">buyEvents</span> <span class="k">=</span> <span class="n">buyEventsRDD</span>
+ <span class="o">)</span>
+ <span class="o">}</span>
+<span class="o">}</span>
+</pre></td></tr></tbody></table> </div> <p>PredictionIO automatically loads the parameters of <em>datasource</em> specified in MyECommerceRecommendation/<strong><em>engine.json</em></strong>, including <em>appName</em>, to <code>dsp</code>.</p><p>In <strong><em>engine.json</em></strong>:</p><div class="highlight shell"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1
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+ ...
+ <span class="s2">"datasource"</span>: <span class="o">{</span>
+ <span class="s2">"params"</span> : <span class="o">{</span>
+ <span class="s2">"appName"</span>: <span class="s2">"MyApp1"</span>
+ <span class="o">}</span>
+ <span class="o">}</span>,
+ ...
+<span class="o">}</span>
+</pre></td></tr></tbody></table> </div> <p>In <code>readTraining()</code>, <code>PEventStore</code> is an object which provides function to access dataa that is collected by PredictionIO Event Server.</p><p>This E-Commerce Recommendation Engine Template requires "user" and "item" entities that are set by events.</p><p><code>PEventStore.aggregateProperties(...)</code> aggregates properties of the <code>user</code> and <code>item</code> that are set, unset, or delete by special events <strong>$set</strong>, <strong>$unset</strong> and <strong>$delete</strong>. Please refer to <a href="/datacollection/eventapi/#note-about-properties">Event API</a> for more details of using these events.</p><p>The following code aggregates the properties of <code>user</code> and then map each result to a <code>User()</code> object.</p><div class="highlight scala"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1
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+18</pre></td><td class="code"><pre>
+ <span class="c1">// create a RDD of (entityID, User)
+</span> <span class="k">val</span> <span class="n">usersRDD</span><span class="k">:</span> <span class="kt">RDD</span><span class="o">[(</span><span class="kt">String</span>, <span class="kt">User</span><span class="o">)]</span> <span class="k">=</span> <span class="nc">PEventStore</span><span class="o">.</span><span class="n">aggregateProperties</span><span class="o">(</span>
+ <span class="n">appName</span> <span class="k">=</span> <span class="n">dsp</span><span class="o">.</span><span class="n">appName</span><span class="o">,</span>
+ <span class="n">entityType</span> <span class="k">=</span> <span class="s">"user"</span>
+ <span class="o">)(</span><span class="n">sc</span><span class="o">).</span><span class="n">map</span> <span class="o">{</span> <span class="k">case</span> <span class="o">(</span><span class="n">entityId</span><span class="o">,</span> <span class="n">properties</span><span class="o">)</span> <span class="k">=></span>
+ <span class="k">val</span> <span class="n">user</span> <span class="k">=</span> <span class="k">try</span> <span class="o">{</span>
+ <span class="nc">User</span><span class="o">()</span>
+ <span class="o">}</span> <span class="k">catch</span> <span class="o">{</span>
+ <span class="k">case</span> <span class="n">e</span><span class="k">:</span> <span class="kt">Exception</span> <span class="o">=></span> <span class="o">{</span>
+ <span class="n">logger</span><span class="o">.</span><span class="n">error</span><span class="o">(</span><span class="n">s</span><span class="s">"Failed to get properties ${properties} of"</span> <span class="o">+</span>
+ <span class="n">s</span><span class="s">" user ${entityId}. Exception: ${e}."</span><span class="o">)</span>
+ <span class="k">throw</span> <span class="n">e</span>
+ <span class="o">}</span>
+ <span class="o">}</span>
+ <span class="o">(</span><span class="n">entityId</span><span class="o">,</span> <span class="n">user</span><span class="o">)</span>
+ <span class="o">}.</span><span class="n">cache</span><span class="o">()</span>
+
+</pre></td></tr></tbody></table> </div> <p>In the template, <code>User()</code> object is a simple dummy as a placeholder for you to customize and expand.</p><p>Similarly, the following code aggregates <code>item</code> properties and then map each result to an <code>Item()</code> object. By default, this template assumes each item has an optional property <code>categories</code>, which is a list of String.</p><div class="highlight scala"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1
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+17</pre></td><td class="code"><pre> <span class="c1">// create a RDD of (entityID, Item)
+</span> <span class="k">val</span> <span class="n">itemsRDD</span><span class="k">:</span> <span class="kt">RDD</span><span class="o">[(</span><span class="kt">String</span>, <span class="kt">Item</span><span class="o">)]</span> <span class="k">=</span> <span class="nc">PEventStore</span><span class="o">.</span><span class="n">aggregateProperties</span><span class="o">(</span>
+ <span class="n">appName</span> <span class="k">=</span> <span class="n">dsp</span><span class="o">.</span><span class="n">appName</span><span class="o">,</span>
+ <span class="n">entityType</span> <span class="k">=</span> <span class="s">"item"</span>
+ <span class="o">)(</span><span class="n">sc</span><span class="o">).</span><span class="n">map</span> <span class="o">{</span> <span class="k">case</span> <span class="o">(</span><span class="n">entityId</span><span class="o">,</span> <span class="n">properties</span><span class="o">)</span> <span class="k">=></span>
+ <span class="k">val</span> <span class="n">item</span> <span class="k">=</span> <span class="k">try</span> <span class="o">{</span>
+ <span class="c1">// Assume categories is optional property of item.
+</span> <span class="nc">Item</span><span class="o">(</span><span class="n">categories</span> <span class="k">=</span> <span class="n">properties</span><span class="o">.</span><span class="n">getOpt</span><span class="o">[</span><span class="kt">List</span><span class="o">[</span><span class="kt">String</span><span class="o">]](</span><span class="s">"categories"</span><span class="o">))</span>
+ <span class="o">}</span> <span class="k">catch</span> <span class="o">{</span>
+ <span class="k">case</span> <span class="n">e</span><span class="k">:</span> <span class="kt">Exception</span> <span class="o">=></span> <span class="o">{</span>
+ <span class="n">logger</span><span class="o">.</span><span class="n">error</span><span class="o">(</span><span class="n">s</span><span class="s">"Failed to get properties ${properties} of"</span> <span class="o">+</span>
+ <span class="n">s</span><span class="s">" item ${entityId}. Exception: ${e}."</span><span class="o">)</span>
+ <span class="k">throw</span> <span class="n">e</span>
+ <span class="o">}</span>
+ <span class="o">}</span>
+ <span class="o">(</span><span class="n">entityId</span><span class="o">,</span> <span class="n">item</span><span class="o">)</span>
+ <span class="o">}.</span><span class="n">cache</span><span class="o">()</span>
+</pre></td></tr></tbody></table> </div> <p>The <code>Item</code> case class is defined as</p><div class="highlight scala"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1</pre></td><td class="code"><pre><span class="k">case</span> <span class="k">class</span> <span class="nc">Item</span><span class="o">(</span><span class="n">categories</span><span class="k">:</span> <span class="kt">Option</span><span class="o">[</span><span class="kt">List</span><span class="o">[</span><span class="kt">String</span><span class="o">]])</span>
+</pre></td></tr></tbody></table> </div> <p><code>PEventStore.find(...)</code> specifies the events that you want to read. In this case, "user view item" and "user buy item" events are read</p><div class="highlight scala"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1
+2
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+ <span class="c1">// get all "user" "view" "item" events
+</span> <span class="k">val</span> <span class="n">eventsRDD</span><span class="k">:</span> <span class="kt">RDD</span><span class="o">[</span><span class="kt">Event</span><span class="o">]</span> <span class="k">=</span> <span class="nc">PEventStore</span><span class="o">.</span><span class="n">find</span><span class="o">(</span>
+ <span class="n">appName</span> <span class="k">=</span> <span class="n">dsp</span><span class="o">.</span><span class="n">appName</span><span class="o">,</span>
+ <span class="n">entityType</span> <span class="k">=</span> <span class="nc">Some</span><span class="o">(</span><span class="s">"user"</span><span class="o">),</span>
+ <span class="n">eventNames</span> <span class="k">=</span> <span class="nc">Some</span><span class="o">(</span><span class="nc">List</span><span class="o">(</span><span class="s">"view"</span><span class="o">,</span> <span class="s">"buy"</span><span class="o">)),</span>
+ <span class="c1">// targetEntityType is optional field of an event.
+</span> <span class="n">targetEntityType</span> <span class="k">=</span> <span class="nc">Some</span><span class="o">(</span><span class="nc">Some</span><span class="o">(</span><span class="s">"item"</span><span class="o">)))(</span><span class="n">sc</span><span class="o">)</span>
+ <span class="o">.</span><span class="n">cache</span><span class="o">()</span>
+
+</pre></td></tr></tbody></table> </div> <p>Note that <code>.cache()</code> is used to cache the RDD data into memory since eventsRDD will be used multiple times later.</p><p>Then we filter the events we are intersted in and map the event to a <code>ViewEvent</code> object.</p><div class="highlight scala"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1
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+ <span class="k">val</span> <span class="n">viewEventsRDD</span><span class="k">:</span> <span class="kt">RDD</span><span class="o">[</span><span class="kt">ViewEvent</span><span class="o">]</span> <span class="k">=</span> <span class="n">eventsRDD</span>
+ <span class="o">.</span><span class="n">filter</span> <span class="o">{</span> <span class="n">event</span> <span class="k">=></span> <span class="n">event</span><span class="o">.</span><span class="n">event</span> <span class="o">==</span> <span class="s">"view"</span> <span class="o">}</span>
+ <span class="o">.</span><span class="n">map</span> <span class="o">{</span> <span class="n">event</span> <span class="k">=></span>
+ <span class="k">try</span> <span class="o">{</span>
+ <span class="nc">ViewEvent</span><span class="o">(</span>
+ <span class="n">user</span> <span class="k">=</span> <span class="n">event</span><span class="o">.</span><span class="n">entityId</span><span class="o">,</span>
+ <span class="n">item</span> <span class="k">=</span> <span class="n">event</span><span class="o">.</span><span class="n">targetEntityId</span><span class="o">.</span><span class="n">get</span><span class="o">,</span>
+ <span class="n">t</span> <span class="k">=</span> <span class="n">event</span><span class="o">.</span><span class="n">eventTime</span><span class="o">.</span><span class="n">getMillis</span>
+ <span class="o">)</span>
+ <span class="o">}</span> <span class="k">catch</span> <span class="o">{</span>
+ <span class="k">case</span> <span class="n">e</span><span class="k">:</span> <span class="kt">Exception</span> <span class="o">=></span>
+ <span class="n">logger</span><span class="o">.</span><span class="n">error</span><span class="o">(</span><span class="n">s</span><span class="s">"Cannot convert ${event} to ViewEvent."</span> <span class="o">+</span>
+ <span class="n">s</span><span class="s">" Exception: ${e}."</span><span class="o">)</span>
+ <span class="k">throw</span> <span class="n">e</span>
+ <span class="o">}</span>
+ <span class="o">}</span>
+</pre></td></tr></tbody></table> </div> <p><code>ViewEvent</code> case class is defined as:</p><div class="highlight scala"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1</pre></td><td class="code"><pre><span class="k">case</span> <span class="k">class</span> <span class="nc">ViewEvent</span><span class="o">(</span><span class="n">user</span><span class="k">:</span> <span class="kt">String</span><span class="o">,</span> <span class="n">item</span><span class="k">:</span> <span class="kt">String</span><span class="o">,</span> <span class="n">t</span><span class="k">:</span> <span class="kt">Long</span><span class="o">)</span>
+</pre></td></tr></tbody></table> </div> <p>We filter buy event in similar way and map to <code>BuyEvent</code> object for later use.</p><div class="highlight scala"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1
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+ <span class="k">val</span> <span class="n">buyEventsRDD</span><span class="k">:</span> <span class="kt">RDD</span><span class="o">[</span><span class="kt">BuyEvent</span><span class="o">]</span> <span class="k">=</span> <span class="n">eventsRDD</span>
+ <span class="o">.</span><span class="n">filter</span> <span class="o">{</span> <span class="n">event</span> <span class="k">=></span> <span class="n">event</span><span class="o">.</span><span class="n">event</span> <span class="o">==</span> <span class="s">"buy"</span> <span class="o">}</span>
+ <span class="o">.</span><span class="n">map</span> <span class="o">{</span> <span class="n">event</span> <span class="k">=></span>
+ <span class="k">try</span> <span class="o">{</span>
+ <span class="nc">BuyEvent</span><span class="o">(</span>
+ <span class="n">user</span> <span class="k">=</span> <span class="n">event</span><span class="o">.</span><span class="n">entityId</span><span class="o">,</span>
+ <span class="n">item</span> <span class="k">=</span> <span class="n">event</span><span class="o">.</span><span class="n">targetEntityId</span><span class="o">.</span><span class="n">get</span><span class="o">,</span>
+ <span class="n">t</span> <span class="k">=</span> <span class="n">event</span><span class="o">.</span><span class="n">eventTime</span><span class="o">.</span><span class="n">getMillis</span>
+ <span class="o">)</span>
+ <span class="o">}</span> <span class="k">catch</span> <span class="o">{</span>
+ <span class="k">case</span> <span class="n">e</span><span class="k">:</span> <span class="kt">Exception</span> <span class="o">=></span>
+ <span class="n">logger</span><span class="o">.</span><span class="n">error</span><span class="o">(</span><span class="n">s</span><span class="s">"Cannot convert ${event} to BuyEvent."</span> <span class="o">+</span>
+ <span class="n">s</span><span class="s">" Exception: ${e}."</span><span class="o">)</span>
+ <span class="k">throw</span> <span class="n">e</span>
+ <span class="o">}</span>
+ <span class="o">}</span>
+
+</pre></td></tr></tbody></table> </div> <p><code>BuyEvent</code> case class is defined as:</p><div class="highlight scala"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1</pre></td><td class="code"><pre><span class="k">case</span> <span class="k">class</span> <span class="nc">BuyEvent</span><span class="o">(</span><span class="n">user</span><span class="k">:</span> <span class="kt">String</span><span class="o">,</span> <span class="n">item</span><span class="k">:</span> <span class="kt">String</span><span class="o">,</span> <span class="n">t</span><span class="k">:</span> <span class="kt">Long</span><span class="o">)</span>
+</pre></td></tr></tbody></table> </div> <div class="alert-message info"><p>For flexibility, this template is designed to support user ID and item ID in String.</p></div><p><code>TrainingData</code> contains an RDD of <code>User</code>, <code>Item</code> and <code>ViewEvent</code> objects. The class definition of <code>TrainingData</code> is:</p><div class="highlight scala"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1
+2
+3
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+6</pre></td><td class="code"><pre><span class="k">class</span> <span class="nc">TrainingData</span><span class="o">(</span>
+ <span class="k">val</span> <span class="n">users</span><span class="k">:</span> <span class="kt">RDD</span><span class="o">[(</span><span class="kt">String</span>, <span class="kt">User</span><span class="o">)],</span>
+ <span class="k">val</span> <span class="n">items</span><span class="k">:</span> <span class="kt">RDD</span><span class="o">[(</span><span class="kt">String</span>, <span class="kt">Item</span><span class="o">)],</span>
+ <span class="k">val</span> <span class="n">viewEvents</span><span class="k">:</span> <span class="kt">RDD</span><span class="o">[</span><span class="kt">ViewEvent</span><span class="o">],</span>
+ <span class="k">val</span> <span class="n">buyEvents</span><span class="k">:</span> <span class="kt">RDD</span><span class="o">[</span><span class="kt">BuyEvent</span><span class="o">]</span>
+<span class="o">)</span> <span class="k">extends</span> <span class="nc">Serializable</span> <span class="o">{</span> <span class="o">...</span> <span class="o">}</span>
+</pre></td></tr></tbody></table> </div> <p>PredictionIO then passes the returned <code>TrainingData</code> object to <em>Data Preparator</em>.</p><div class="alert-message note"><p>You could modify the DataSource to read other event other than the default <strong>view</strong> or <strong>buy</strong>.</p></div><h3 id='data-preparator' class='header-anchors'>Data Preparator</h3><p>In MyECommerceRecommendation/src/main/scala/<strong><em>Preparator.scala</em></strong>, the <code>prepare</code> method of class <code>Preparator</code> takes <code>TrainingData</code> as its input and performs any necessary feature selection and data processing tasks. At the end, it returns <code>PreparedData</code> which should contain the data <em>Algorithm</em> needs.</p><p>By default, <code>prepare</code> simply copies the unprocessed <code>TrainingData</code> data to <code>PreparedData</code>:</p><div class="highlight scala"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text
-align: right"><pre class="lineno">1
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+ <span class="k">extends</span> <span class="nc">PPreparator</span><span class="o">[</span><span class="kt">TrainingData</span>, <span class="kt">PreparedData</span><span class="o">]</span> <span class="o">{</span>
+
+ <span class="k">def</span> <span class="n">prepare</span><span class="o">(</span><span class="n">sc</span><span class="k">:</span> <span class="kt">SparkContext</span><span class="o">,</span> <span class="n">trainingData</span><span class="k">:</span> <span class="kt">TrainingData</span><span class="o">)</span><span class="k">:</span> <span class="kt">PreparedData</span> <span class="o">=</span> <span class="o">{</span>
+ <span class="k">new</span> <span class="nc">PreparedData</span><span class="o">(</span>
+ <span class="n">users</span> <span class="k">=</span> <span class="n">trainingData</span><span class="o">.</span><span class="n">users</span><span class="o">,</span>
+ <span class="n">items</span> <span class="k">=</span> <span class="n">trainingData</span><span class="o">.</span><span class="n">items</span><span class="o">,</span>
+ <span class="n">viewEvents</span> <span class="k">=</span> <span class="n">trainingData</span><span class="o">.</span><span class="n">viewEvents</span><span class="o">,</span>
+ <span class="n">buyEvents</span> <span class="k">=</span> <span class="n">trainingData</span><span class="o">.</span><span class="n">buyEvents</span><span class="o">)</span>
+ <span class="o">}</span>
+<span class="o">}</span>
+
+<span class="k">class</span> <span class="nc">PreparedData</span><span class="o">(</span>
+ <span class="k">val</span> <span class="n">users</span><span class="k">:</span> <span class="kt">RDD</span><span class="o">[(</span><span class="kt">String</span>, <span class="kt">User</span><span class="o">)],</span>
+ <span class="k">val</span> <span class="n">items</span><span class="k">:</span> <span class="kt">RDD</span><span class="o">[(</span><span class="kt">String</span>, <span class="kt">Item</span><span class="o">)],</span>
+ <span class="k">val</span> <span class="n">viewEvents</span><span class="k">:</span> <span class="kt">RDD</span><span class="o">[</span><span class="kt">ViewEvent</span><span class="o">],</span>
+ <span class="k">val</span> <span class="n">buyEvents</span><span class="k">:</span> <span class="kt">RDD</span><span class="o">[</span><span class="kt">BuyEvent</span><span class="o">]</span>
+<span class="o">)</span> <span class="k">extends</span> <span class="nc">Serializable</span>
+</pre></td></tr></tbody></table> </div> <p>PredictionIO passes the returned <code>PreparedData</code> object to Algorithm's <code>train</code> function.</p><h2 id='algorithm' class='header-anchors'>Algorithm</h2><p>In MyECommerceRecommendation/src/main/scala/<strong><em>ECommAlgorithm.scala</em></strong>, the two methods of the algorithm class are <code>train</code> and <code>predict</code>. <code>train</code> is responsible for training the predictive model;<code>predict</code> is responsible for using this model to make prediction.</p><h3 id='algorithm-parameters' class='header-anchors'>Algorithm parameters</h3><p>The ECommAlgorithm takes the following parameters, as defined by the <code>ECommAlgorithmParams</code> case class:</p><div class="highlight scala"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1
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+ <span class="n">appName</span><span class="k">:</span> <span class="kt">String</span><span class="o">,</span>
+ <span class="n">unseenOnly</span><span class="k">:</span> <span class="kt">Boolean</span><span class="o">,</span>
+ <span class="n">seenEvents</span><span class="k">:</span> <span class="kt">List</span><span class="o">[</span><span class="kt">String</span><span class="o">],</span>
+ <span class="n">similarEvents</span><span class="k">:</span> <span class="kt">List</span><span class="o">[</span><span class="kt">String</span><span class="o">],</span>
+ <span class="n">rank</span><span class="k">:</span> <span class="kt">Int</span><span class="o">,</span>
+ <span class="n">numIterations</span><span class="k">:</span> <span class="kt">Int</span><span class="o">,</span>
+ <span class="n">lambda</span><span class="k">:</span> <span class="kt">Double</span><span class="o">,</span>
+ <span class="n">seed</span><span class="k">:</span> <span class="kt">Option</span><span class="o">[</span><span class="kt">Long</span><span class="o">]</span>
+<span class="o">)</span> <span class="k">extends</span> <span class="nc">Params</span>
+</pre></td></tr></tbody></table> </div> <p>Parameter description:</p> <ul> <li><strong>appName</strong>: Your App name. Events defined by "seenEvents" and "similarEvents" will be read from this app during <code>predict</code>.</li> <li><strong>unseenOnly</strong>: true or false. Set to true if you want to recommmend unseen items only. Seen items are defined by <em>seenEvents</em> which mean if the user has these events on the items, then it's treated as <em>seen</em>.</li> <li><strong>seenEvents</strong>: A list of user-to-item events which will be treated as <em>seen</em> events. Used when <em>unseenOnly</em> is set to true.</li> <li><strong>similarEvents</strong>: A list of user-item-item events which will be used to find similar items to the items which the user has performend these events on.</li> <li><strong>rank</strong>: Parameter of the MLlib ALS algorithm. Number of latent features.</li> <li><strong>numIterations</strong>: Parameter of the MLlib ALS
algorithm. Number of iterations.</li> <li><strong>lambda</strong>: Regularization parameter of the MLlib ALS algorithm.</li> <li><strong>seed</strong>: Optional. A random seed of the MLlib ALS algorithm. Specify a fixed value if want to have deterministic result.</li> </ul> <h3 id='train(...)' class='header-anchors'>train(...)</h3><p><code>train</code> is called when you run <strong>pio train</strong>. This is where MLlib ALS algorithm, i.e. <code>ALS.trainImplicit()</code>, is used to train a predictive model. In addition, we also count the number of items being bought for each item as default model which will be used when there is no ALS model avaiable or other useful information about the user is avaiable during <code>predict</code>.</p><div class="highlight scala"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1
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+ <span class="k">def</span> <span class="n">train</span><span class="o">(</span><span class="n">sc</span><span class="k">:</span> <span class="kt">SparkContext</span><span class="o">,</span> <span class="n">data</span><span class="k">:</span> <span class="kt">PreparedData</span><span class="o">)</span><span class="k">:</span> <span class="kt">ECommModel</span> <span class="o">=</span> <span class="o">{</span>
+ <span class="o">...</span>
+
+ <span class="c1">// create User and item's String ID to integer index BiMap
+</span> <span class="k">val</span> <span class="n">userStringIntMap</span> <span class="k">=</span> <span class="nc">BiMap</span><span class="o">.</span><span class="n">stringInt</span><span class="o">(</span><span class="n">data</span><span class="o">.</span><span class="n">users</span><span class="o">.</span><span class="n">keys</span><span class="o">)</span>
+ <span class="k">val</span> <span class="n">itemStringIntMap</span> <span class="k">=</span> <span class="nc">BiMap</span><span class="o">.</span><span class="n">stringInt</span><span class="o">(</span><span class="n">data</span><span class="o">.</span><span class="n">items</span><span class="o">.</span><span class="n">keys</span><span class="o">)</span>
+
+ <span class="c1">// generate MLlibRating data for ALS algorithm
+</span> <span class="k">val</span> <span class="n">mllibRatings</span><span class="k">:</span> <span class="kt">RDD</span><span class="o">[</span><span class="kt">MLlibRating</span><span class="o">]</span> <span class="k">=</span> <span class="n">genMLlibRating</span><span class="o">(</span>
+ <span class="n">userStringIntMap</span> <span class="k">=</span> <span class="n">userStringIntMap</span><span class="o">,</span>
+ <span class="n">itemStringIntMap</span> <span class="k">=</span> <span class="n">itemStringIntMap</span><span class="o">,</span>
+ <span class="n">data</span> <span class="k">=</span> <span class="n">data</span>
+ <span class="o">)</span>
+
+ <span class="c1">// seed for MLlib ALS
+</span> <span class="k">val</span> <span class="n">seed</span> <span class="k">=</span> <span class="n">ap</span><span class="o">.</span><span class="n">seed</span><span class="o">.</span><span class="n">getOrElse</span><span class="o">(</span><span class="nc">System</span><span class="o">.</span><span class="n">nanoTime</span><span class="o">)</span>
+
+ <span class="k">val</span> <span class="n">m</span> <span class="k">=</span> <span class="nc">ALS</span><span class="o">.</span><span class="n">trainImplicit</span><span class="o">(</span>
+ <span class="n">ratings</span> <span class="k">=</span> <span class="n">mllibRatings</span><span class="o">,</span>
+ <span class="n">rank</span> <span class="k">=</span> <span class="n">ap</span><span class="o">.</span><span class="n">rank</span><span class="o">,</span>
+ <span class="n">iterations</span> <span class="k">=</span> <span class="n">ap</span><span class="o">.</span><span class="n">numIterations</span><span class="o">,</span>
+ <span class="n">lambda</span> <span class="k">=</span> <span class="n">ap</span><span class="o">.</span><span class="n">lambda</span><span class="o">,</span>
+ <span class="n">blocks</span> <span class="k">=</span> <span class="o">-</span><span class="mi">1</span><span class="o">,</span>
+ <span class="n">alpha</span> <span class="k">=</span> <span class="mf">1.0</span><span class="o">,</span>
+ <span class="n">seed</span> <span class="k">=</span> <span class="n">seed</span><span class="o">)</span>
+
+ <span class="o">...</span>
+
+ <span class="c1">// count the number of items being bought for recommendation popular items as default case
+</span> <span class="k">val</span> <span class="n">popularCount</span> <span class="k">=</span> <span class="n">trainDefault</span><span class="o">(</span>
+ <span class="n">userStringIntMap</span> <span class="k">=</span> <span class="n">userStringIntMap</span><span class="o">,</span>
+ <span class="n">itemStringIntMap</span> <span class="k">=</span> <span class="n">itemStringIntMap</span><span class="o">,</span>
+ <span class="n">data</span> <span class="k">=</span> <span class="n">data</span>
+ <span class="o">)</span>
+ <span class="o">...</span>
+
+ <span class="o">}</span>
+
+</pre></td></tr></tbody></table> </div> <h4 id='working-with-spark-mllib's-als.trainimplicit(....)' class='header-anchors'>Working with Spark MLlib's ALS.trainImplicit(....)</h4><p>MLlib ALS does not support <code>String</code> user ID and item ID. <code>ALS.trainImplicit</code> thus also assumes int-only <code>Rating</code> object. First, you can rename MLlib's Integer-only <code>Rating</code> to <code>MLlibRating</code> for clarity:</p><div class="highlight shell"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1</pre></td><td class="code"><pre>import org.apache.spark.mllib.recommendation.<span class="o">{</span>Rating <span class="o">=</span>> MLlibRating<span class="o">}</span>
+</pre></td></tr></tbody></table> </div> <p>In order to use MLlib's ALS algorithm, we need to convert the <code>viewEvents</code> into <code>MLlibRating</code>. There are two things we need to handle:</p> <ol> <li>Map user and item String ID of the ViewEvent into Integer ID, as required by <code>MLlibRating</code>.</li> <li><code>ViewEvent</code> object is an implicit event that does not have an explicit rating value. <code>ALS.trainImplicit()</code> supports implicit preference. If the <code>MLlibRating</code> has higher rating value, it means higher confidence that the user prefers the item. Hence we can aggregate how many times the user has viewed the item to indicate the confidence level that the user may prefer the item.</li> </ol> <p>You create a bi-directional map with <code>BiMap.stringInt</code> which maps each String record to an Integer index.</p><div class="highlight scala"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pr
e class="lineno">1
+2</pre></td><td class="code"><pre><span class="k">val</span> <span class="n">userStringIntMap</span> <span class="k">=</span> <span class="nc">BiMap</span><span class="o">.</span><span class="n">stringInt</span><span class="o">(</span><span class="n">data</span><span class="o">.</span><span class="n">users</span><span class="o">.</span><span class="n">keys</span><span class="o">)</span>
+<span class="k">val</span> <span class="n">itemStringIntMap</span> <span class="k">=</span> <span class="nc">BiMap</span><span class="o">.</span><span class="n">stringInt</span><span class="o">(</span><span class="n">data</span><span class="o">.</span><span class="n">items</span><span class="o">.</span><span class="n">keys</span><span class="o">)</span>
+</pre></td></tr></tbody></table> </div> <p>Then convert the user and item String ID in each ViewEvent to Int with these BiMaps. We use default -1 if the user or item String ID couldn't be found in the BiMap and filter out these events with invalid user and item ID later. After filtering, we use <code>reduceByKey()</code> to add up all values for the same key (uindex, iindex) and then finally map to <code>MLlibRating</code> object. You can find the code inside the function <code>genMLlibRating()</code>:</p><div class="highlight scala"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1
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+ <span class="k">def</span> <span class="n">genMLlibRating</span><span class="o">(</span>
+ <span class="n">userStringIntMap</span><span class="k">:</span> <span class="kt">BiMap</span><span class="o">[</span><span class="kt">String</span>, <span class="kt">Int</span><span class="o">],</span>
+ <span class="n">itemStringIntMap</span><span class="k">:</span> <span class="kt">BiMap</span><span class="o">[</span><span class="kt">String</span>, <span class="kt">Int</span><span class="o">],</span>
+ <span class="n">data</span><span class="k">:</span> <span class="kt">PreparedData</span><span class="o">)</span><span class="k">:</span> <span class="kt">RDD</span><span class="o">[</span><span class="kt">MLlibRating</span><span class="o">]</span> <span class="k">=</span> <span class="o">{</span>
+
+ <span class="k">val</span> <span class="n">mllibRatings</span> <span class="k">=</span> <span class="n">data</span><span class="o">.</span><span class="n">viewEvents</span>
+ <span class="o">.</span><span class="n">map</span> <span class="o">{</span> <span class="n">r</span> <span class="k">=></span>
+ <span class="c1">// Convert user and item String IDs to Int index for MLlib
+</span> <span class="k">val</span> <span class="n">uindex</span> <span class="k">=</span> <span class="n">userStringIntMap</span><span class="o">.</span><span class="n">getOrElse</span><span class="o">(</span><span class="n">r</span><span class="o">.</span><span class="n">user</span><span class="o">,</span> <span class="o">-</span><span class="mi">1</span><span class="o">)</span>
+ <span class="k">val</span> <span class="n">iindex</span> <span class="k">=</span> <span class="n">itemStringIntMap</span><span class="o">.</span><span class="n">getOrElse</span><span class="o">(</span><span class="n">r</span><span class="o">.</span><span class="n">item</span><span class="o">,</span> <span class="o">-</span><span class="mi">1</span><span class="o">)</span>
+
+ <span class="k">if</span> <span class="o">(</span><span class="n">uindex</span> <span class="o">==</span> <span class="o">-</span><span class="mi">1</span><span class="o">)</span>
+ <span class="n">logger</span><span class="o">.</span><span class="n">info</span><span class="o">(</span><span class="n">s</span><span class="s">"Couldn't convert nonexistent user ID ${r.user}"</span>
+ <span class="o">+</span> <span class="s">" to Int index."</span><span class="o">)</span>
+
+ <span class="k">if</span> <span class="o">(</span><span class="n">iindex</span> <span class="o">==</span> <span class="o">-</span><span class="mi">1</span><span class="o">)</span>
+ <span class="n">logger</span><span class="o">.</span><span class="n">info</span><span class="o">(</span><span class="n">s</span><span class="s">"Couldn't convert nonexistent item ID ${r.item}"</span>
+ <span class="o">+</span> <span class="s">" to Int index."</span><span class="o">)</span>
+
+ <span class="o">((</span><span class="n">uindex</span><span class="o">,</span> <span class="n">iindex</span><span class="o">),</span> <span class="mi">1</span><span class="o">)</span>
+ <span class="o">}</span>
+ <span class="o">.</span><span class="n">filter</span> <span class="o">{</span> <span class="k">case</span> <span class="o">((</span><span class="n">u</span><span class="o">,</span> <span class="n">i</span><span class="o">),</span> <span class="n">v</span><span class="o">)</span> <span class="k">=></span>
+ <span class="c1">// keep events with valid user and item index
+</span> <span class="o">(</span><span class="n">u</span> <span class="o">!=</span> <span class="o">-</span><span class="mi">1</span><span class="o">)</span> <span class="o">&&</span> <span class="o">(</span><span class="n">i</span> <span class="o">!=</span> <span class="o">-</span><span class="mi">1</span><span class="o">)</span>
+ <span class="o">}</span>
+ <span class="o">.</span><span class="n">reduceByKey</span><span class="o">(</span><span class="k">_</span> <span class="o">+</span> <span class="k">_</span><span class="o">)</span> <span class="c1">// aggregate all view events of same user-item pair
+</span> <span class="o">.</span><span class="n">map</span> <span class="o">{</span> <span class="k">case</span> <span class="o">((</span><span class="n">u</span><span class="o">,</span> <span class="n">i</span><span class="o">),</span> <span class="n">v</span><span class="o">)</span> <span class="k">=></span>
+ <span class="c1">// MLlibRating requires integer index for user and item
+</span> <span class="nc">MLlibRating</span><span class="o">(</span><span class="n">u</span><span class="o">,</span> <span class="n">i</span><span class="o">,</span> <span class="n">v</span><span class="o">)</span>
+ <span class="o">}</span>
+ <span class="o">.</span><span class="n">cache</span><span class="o">()</span>
+
+ <span class="n">mllibRatings</span>
+ <span class="o">}</span>
+
+</pre></td></tr></tbody></table> </div> <div class="alert-message note"><p>You can customize this function if you want to convert other events to MLlibRating or need different ways to aggreagte the events into MLlibRating.</p></div><p>In addition to <code>RDD[MLlibRating]</code>, <code>ALS.trainImplicit</code> takes the following parameters: <em>rank</em>, <em>iterations</em>, <em>lambda</em> and <em>seed</em>.</p><p>The values of these parameters are specified in <em>algorithms</em> of MyECommerceRecommendation/<strong><em>engine.json</em></strong>:</p><div class="highlight shell"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1
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+ ...
+ <span class="s2">"algorithms"</span>: <span class="o">[</span>
+ <span class="o">{</span>
+ <span class="s2">"name"</span>: <span class="s2">"als"</span>,
+ <span class="s2">"params"</span>: <span class="o">{</span>
+ <span class="s2">"appName"</span>: <span class="s2">"MyApp1"</span>,
+ <span class="s2">"unseenOnly"</span>: <span class="nb">true</span>,
+ <span class="s2">"seenEvents"</span>: <span class="o">[</span><span class="s2">"buy"</span>, <span class="s2">"view"</span><span class="o">]</span>,
+ <span class="s2">"similarEvents"</span> : <span class="o">[</span><span class="s2">"view"</span><span class="o">]</span>
+ <span class="s2">"rank"</span>: 10,
+ <span class="s2">"numIterations"</span> : 20,
+ <span class="s2">"lambda"</span>: 0.01,
+ <span class="s2">"seed"</span>: 3
+ <span class="o">}</span>
+ <span class="o">}</span>
+ <span class="o">]</span>
+ ...
+<span class="o">}</span>
+</pre></td></tr></tbody></table> </div> <p>The parameters <code>appName</code>, <code>unseenOnly</code>, <code>seenEvents</code> and <code>similarEvents</code> are used during <code>predict()</code>, which will be explained later.</p><p>PredictionIO will automatically loads these values into the constructor <code>ap</code>, which has a corresponding case case <code>ECommAlgorithmParams</code>.</p><p>The <code>seed</code> parameter is an optional parameter, which is used by MLlib ALS algorithm internally to generate random values. If the <code>seed</code> is not specified, current system time would be used and hence each train may produce different reuslts. Specify a fixed value for the <code>seed</code> if you want to have deterministic result (For example, when you are testing).</p><p><code>ALS.trainImplicit()</code> returns a <code>MatrixFactorizationModel</code> model which contains two RDDs: userFeatures and productFeatures. They correspond to the user X latent features matrix a
nd item X latent features matrix, respectively.</p><p>In addition to the latent feature vector, the item properties (e.g. categories) and popular count are also used during <code>predict()</code>. Hence, we also save these data along with the feature vector by joining them and then collect the data as local Map. Each item is represented by a <code>ProductModel</code> class, which cosists of the <code>item</code> information, <code>features</code> calculated by ALS, and <code>count</code> returned by <code>trainDefault()</code>.</p><div class="highlight scala"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1
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+<span class="k">case</span> <span class="k">class</span> <span class="nc">ProductModel</span><span class="o">(</span>
+ <span class="n">item</span><span class="k">:</span> <span class="kt">Item</span><span class="o">,</span>
+ <span class="n">features</span><span class="k">:</span> <span class="kt">Option</span><span class="o">[</span><span class="kt">Array</span><span class="o">[</span><span class="kt">Double</span><span class="o">]],</span> <span class="c1">// features by ALS
+</span> <span class="n">count</span><span class="k">:</span> <span class="kt">Int</span> <span class="c1">// popular count for default score
+</span><span class="o">)</span>
+
+</pre></td></tr></tbody></table> </div> <div class="highlight scala"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1
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+</span> <span class="k">val</span> <span class="n">productFeatures</span><span class="k">:</span> <span class="kt">Map</span><span class="o">[</span><span class="kt">Int</span>, <span class="o">(</span><span class="kt">Item</span>, <span class="kt">Option</span><span class="o">[</span><span class="kt">Array</span><span class="o">[</span><span class="kt">Double</span><span class="o">]])]</span> <span class="k">=</span>
+ <span class="n">items</span><span class="o">.</span><span class="n">leftOuterJoin</span><span class="o">(</span><span class="n">m</span><span class="o">.</span><span class="n">productFeatures</span><span class="o">).</span><span class="n">collectAsMap</span><span class="o">.</span><span class="n">toMap</span>
+
+ <span class="o">...</span>
+
+ <span class="k">val</span> <span class="n">productModels</span><span class="k">:</span> <span class="kt">Map</span><span class="o">[</span><span class="kt">Int</span>, <span class="kt">ProductModel</span><span class="o">]</span> <span class="k">=</span> <span class="n">productFeatures</span>
+ <span class="o">.</span><span class="n">map</span> <span class="o">{</span> <span class="k">case</span> <span class="o">(</span><span class="n">index</span><span class="o">,</span> <span class="o">(</span><span class="n">item</span><span class="o">,</span> <span class="n">features</span><span class="o">))</span> <span class="k">=></span>
+ <span class="k">val</span> <span class="n">pm</span> <span class="k">=</span> <span class="nc">ProductModel</span><span class="o">(</span>
+ <span class="n">item</span> <span class="k">=</span> <span class="n">item</span><span class="o">,</span>
+ <span class="n">features</span> <span class="k">=</span> <span class="n">features</span><span class="o">,</span>
+ <span class="c1">// NOTE: use getOrElse because popularCount may not contain all items.
+</span> <span class="n">count</span> <span class="k">=</span> <span class="n">popularCount</span><span class="o">.</span><span class="n">getOrElse</span><span class="o">(</span><span class="n">index</span><span class="o">,</span> <span class="mi">0</span><span class="o">)</span>
+ <span class="o">)</span>
+ <span class="o">(</span><span class="n">index</span><span class="o">,</span> <span class="n">pm</span><span class="o">)</span>
+ <span class="o">}</span>
+
+ <span class="k">new</span> <span class="nc">ECommModel</span><span class="o">(</span>
+ <span class="n">rank</span> <span class="k">=</span> <span class="n">m</span><span class="o">.</span><span class="n">rank</span><span class="o">,</span>
+ <span class="n">userFeatures</span> <span class="k">=</span> <span class="n">userFeatures</span><span class="o">,</span>
+ <span class="n">productModels</span> <span class="k">=</span> <span class="n">productModels</span><span class="o">,</span>
+ <span class="n">userStringIntMap</span> <span class="k">=</span> <span class="n">userStringIntMap</span><span class="o">,</span>
+ <span class="n">itemStringIntMap</span> <span class="k">=</span> <span class="n">itemStringIntMap</span>
+ <span class="o">)</span>
+
+</pre></td></tr></tbody></table> </div> <p>Note that <code>leftOuterJoin</code> is used because the productFeatures returned by ALS may not contain all items.</p><p>The <code>ECommModel</code> is defined as the following:</p><div class="highlight scala"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1
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+ <span class="k">val</span> <span class="n">rank</span><span class="k">:</span> <span class="kt">Int</span><span class="o">,</span>
+ <span class="k">val</span> <span class="n">userFeatures</span><span class="k">:</span> <span class="kt">Map</span><span class="o">[</span><span class="kt">Int</span>, <span class="kt">Array</span><span class="o">[</span><span class="kt">Double</span><span class="o">]],</span>
+ <span class="k">val</span> <span class="n">productModels</span><span class="k">:</span> <span class="kt">Map</span><span class="o">[</span><span class="kt">Int</span>, <span class="kt">ProductModel</span><span class="o">],</span>
+ <span class="k">val</span> <span class="n">userStringIntMap</span><span class="k">:</span> <span class="kt">BiMap</span><span class="o">[</span><span class="kt">String</span>, <span class="kt">Int</span><span class="o">],</span>
+ <span class="k">val</span> <span class="n">itemStringIntMap</span><span class="k">:</span> <span class="kt">BiMap</span><span class="o">[</span><span class="kt">String</span>, <span class="kt">Int</span><span class="o">]</span>
+<span class="o">)</span> <span class="k">extends</span> <span class="nc">Serializable</span> <span class="o">{</span> <span class="o">...</span> <span class="o">}</span>
+</pre></td></tr></tbody></table> </div> <p>PredictionIO will automatically store the returned model after training, i.e. <code>ECommModel</code> in this example.</p><h3 id='predict(...)' class='header-anchors'>predict(...)</h3><p><code>predict</code> is called when you send a JSON query to <a href="http://localhost:8000/queries.json">http://localhost:8000/queries.json</a>. PredictionIO converts the query, such as <code>{ "user": "u1", "num": 4 }</code> to the <code>Query</code> class you defined previously.</p><p>We can use the userFeatures and productFeatures stored in ECommModel to calculate the scores of items for the user.</p><p>This template also supports additional business logic features, such as filtering items by categories, recommending items in the white list, excluding items in the black list, recommend unseen items only, and exclude unavaiable items defined in constraint event.</p><p>The <code>predict()</code> function does the following:</
p> <ol> <li>Convert the item in query's whilteList from string ID to integer index</li> <li>Get a list seen items by the user (defined by parmater <code>seenEvents</code>)</li> <li>Get the latest unavailableItems which is used to exclude unavailable items for all users</li> <li>Combine query's blackList, seenItems, and unavailableItems into a final black list of items to be excluded from recommendation.</li> <li>Get the user feature vector from the ECommModel.</li> <li>If there is feature vector for the user, recommend top N items based on the user feature and prodcut features.</li> <li>If there is no feature vector for the user, use the recent items acted by the user (defined by <code>similarEvents</code> parameter) to recommend similar items.</li> <li>If there is no recent <code>similarEvents</code> available for the user, popular items are then recommended (added in template version 0.4.0).</li> </ol> <p>Only items which satisfy the <code>isCandidate()</code> condition wi
ll be recommended. By default, the item can be recommended if:</p> <ul> <li>it belongs to one of the categories defined in query.</li> <li>it is one of the white list items if white list is defined.</li> <li>it is not in the black list.</li> </ul> <div class="alert-message info"><p>You can easily modify <code>isCandidate()</code> checking or related logic if you have different requirements or condition to determine if an item is a candidate item to be recommended.</p></div><div class="highlight scala"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1
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+ <span class="k">def</span> <span class="n">predict</span><span class="o">(</span><span class="n">model</span><span class="k">:</span> <span class="kt">ECommModel</span><span class="o">,</span> <span class="n">query</span><span class="k">:</span> <span class="kt">Query</span><span class="o">)</span><span class="k">:</span> <span class="kt">PredictedResult</span> <span class="o">=</span> <span class="o">{</span>
+
+ <span class="k">val</span> <span class="n">userFeatures</span> <span class="k">=</span> <span class="n">model</span><span class="o">.</span><span class="n">userFeatures</span>
+ <span class="k">val</span> <span class="n">productFeatures</span> <span class="k">=</span> <span class="n">model</span><span class="o">.</span><span class="n">productFeatures</span>
+
+ <span class="c1">// convert whiteList's string ID to integer index
+</span> <span class="k">val</span> <span class="n">whiteList</span><span class="k">:</span> <span class="kt">Option</span><span class="o">[</span><span class="kt">Set</span><span class="o">[</span><span class="kt">Int</span><span class="o">]]</span> <span class="k">=</span> <span class="n">query</span><span class="o">.</span><span class="n">whiteList</span><span class="o">.</span><span class="n">map</span><span class="o">(</span> <span class="n">set</span> <span class="k">=></span>
+ <span class="n">set</span><span class="o">.</span><span class="n">map</span><span class="o">(</span><span class="n">model</span><span class="o">.</span><span class="n">itemStringIntMap</span><span class="o">.</span><span class="n">get</span><span class="o">(</span><span class="k">_</span><span class="o">)).</span><span class="n">flatten</span>
+ <span class="o">)</span>
+
+ <span class="c1">// generate final blackList based on additional constraints
+</span> <span class="k">val</span> <span class="n">finalBlackList</span><span class="k">:</span> <span class="kt">Set</span><span class="o">[</span><span class="kt">Int</span><span class="o">]</span> <span class="k">=</span> <span class="n">genBlackList</span><span class="o">(</span><span class="n">query</span> <span class="k">=</span> <span class="n">query</span><span class="o">)</span>
+ <span class="c1">// convert seen Items list from String ID to interger Index
+</span> <span class="o">.</span><span class="n">flatMap</span><span class="o">(</span><span class="n">x</span> <span class="k">=></span> <span class="n">model</span><span class="o">.</span><span class="n">itemStringIntMap</span><span class="o">.</span><span class="n">get</span><span class="o">(</span><span class="n">x</span><span class="o">))</span>
+
+ <span class="c1">// look up user feature from model
+</span> <span class="k">val</span> <span class="n">userFeature</span> <span class="k">=</span>
+ <span class="n">model</span><span class="o">.</span><span class="n">userStringIntMap</span><span class="o">.</span><span class="n">get</span><span class="o">(</span><span class="n">query</span><span class="o">.</span><span class="n">user</span><span class="o">).</span><span class="n">map</span> <span class="o">{</span> <span class="n">userIndex</span> <span class="k">=></span>
+ <span class="n">userFeatures</span><span class="o">.</span><span class="n">get</span><span class="o">(</span><span class="n">userIndex</span><span class="o">)</span>
+ <span class="o">}</span>
+ <span class="c1">// flatten Option[Option[Array[Double]]] to Option[Array[Double]]
+</span> <span class="o">.</span><span class="n">flatten</span>
+
+ <span class="k">val</span> <span class="n">topScores</span><span class="k">:</span> <span class="kt">Array</span><span class="o">[(</span><span class="kt">Int</span>, <span class="kt">Double</span><span class="o">)]</span> <span class="k">=</span> <span class="k">if</span> <span class="o">(</span><span class="n">userFeature</span><span class="o">.</span><span class="n">isDefined</span><span class="o">)</span> <span class="o">{</span>
+ <span class="c1">// the user has feature vector
+</span> <span class="n">predictKnownUser</span><span class="o">(</span>
+ <span class="n">userFeature</span> <span class="k">=</span> <span class="n">userFeature</span><span class="o">.</span><span class="n">get</span><span class="o">,</span>
+ <span class="n">productModels</span> <span class="k">=</span> <span class="n">productModels</span><span class="o">,</span>
+ <span class="n">query</span> <span class="k">=</span> <span class="n">query</span><span class="o">,</span>
+ <span class="n">whiteList</span> <span class="k">=</span> <span class="n">whiteList</span><span class="o">,</span>
+ <span class="n">blackList</span> <span class="k">=</span> <span class="n">finalBlackList</span>
+ <span class="o">)</span>
+ <span class="o">}</span> <span class="k">else</span> <span class="o">{</span>
+ <span class="c1">// the user doesn't have feature vector.
+</span> <span class="c1">// For example, new user is created after model is trained.
+</span> <span class="n">logger</span><span class="o">.</span><span class="n">info</span><span class="o">(</span><span class="n">s</span><span class="s">"No userFeature found for user ${query.user}."</span><span class="o">)</span>
+
+ <span class="c1">// check if the user has recent events on some items
+</span> <span class="k">val</span> <span class="n">recentItems</span><span class="k">:</span> <span class="kt">Set</span><span class="o">[</span><span class="kt">String</span><span class="o">]</span> <span class="k">=</span> <span class="n">getRecentItems</span><span class="o">(</span><span class="n">query</span><span class="o">)</span>
+ <span class="k">val</span> <span class="n">recentList</span><span class="k">:</span> <span class="kt">Set</span><span class="o">[</span><span class="kt">Int</span><span class="o">]</span> <span class="k">=</span> <span class="n">recentItems</span><span class="o">.</span><span class="n">flatMap</span> <span class="o">(</span><span class="n">x</span> <span class="k">=></span>
+ <span class="n">model</span><span class="o">.</span><span class="n">itemStringIntMap</span><span class="o">.</span><span class="n">get</span><span class="o">(</span><span class="n">x</span><span class="o">))</span>
+
+ <span class="k">val</span> <span class="n">recentFeatures</span><span class="k">:</span> <span class="kt">Vector</span><span class="o">[</span><span class="kt">Array</span><span class="o">[</span><span class="kt">Double</span><span class="o">]]</span> <span class="k">=</span> <span class="n">recentList</span><span class="o">.</span><span class="n">toVector</span>
+ <span class="c1">// productModels may not contain the requested item
+</span> <span class="o">.</span><span class="n">map</span> <span class="o">{</span> <span class="n">i</span> <span class="k">=></span>
+ <span class="n">productModels</span><span class="o">.</span><span class="n">get</span><span class="o">(</span><span class="n">i</span><span class="o">).</span><span class="n">flatMap</span> <span class="o">{</span> <span class="n">pm</span> <span class="k">=></span> <span class="n">pm</span><span class="o">.</span><span class="n">features</span> <span class="o">}</span>
+ <span class="o">}.</span><span class="n">flatten</span>
+
+ <span class="k">if</span> <span class="o">(</span><span class="n">recentFeatures</span><span class="o">.</span><span class="n">isEmpty</span><span class="o">)</span> <span class="o">{</span>
+ <span class="n">logger</span><span class="o">.</span><span class="n">info</span><span class="o">(</span><span class="n">s</span><span class="s">"No features vector for recent items ${recentItems}."</span><span class="o">)</span>
+ <span class="n">predictDefault</span><span class="o">(</span>
+ <span class="n">productModels</span> <span class="k">=</span> <span class="n">productModels</span><span class="o">,</span>
+ <span class="n">query</span> <span class="k">=</span> <span class="n">query</span><span class="o">,</span>
+ <span class="n">whiteList</span> <span class="k">=</span> <span class="n">whiteList</span><span class="o">,</span>
+ <span class="n">blackList</span> <span class="k">=</span> <span class="n">finalBlackList</span>
+ <span class="o">)</span>
+ <span class="o">}</span> <span class="k">else</span> <span class="o">{</span>
+ <span class="n">predictSimilar</span><span class="o">(</span>
+ <span class="n">recentFeatures</span> <span class="k">=</span> <span class="n">recentFeatures</span><span class="o">,</span>
+ <span class="n">productModels</span> <span class="k">=</span> <span class="n">productModels</span><span class="o">,</span>
+ <span class="n">query</span> <span class="k">=</span> <span class="n">query</span><span class="o">,</span>
+ <span class="n">whiteList</span> <span class="k">=</span> <span class="n">whiteList</span><span class="o">,</span>
+ <span class="n">blackList</span> <span class="k">=</span> <span class="n">finalBlackList</span>
+ <span class="o">)</span>
+ <span class="o">}</span>
+ <span class="o">}</span>
+
+ <span class="o">...</span>
+ <span class="o">}</span>
+</pre></td></tr></tbody></table> </div> <p>Note that the item IDs in top N results are the <code>Int</code> indices. You map them back to <code>String</code> with <code>itemIntStringMap</code> before they are returned.</p><div class="highlight scala"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1
+2
+3
+4
+5
+6
+7
+8
+9</pre></td><td class="code"><pre> <span class="k">val</span> <span class="n">itemScores</span> <span class="k">=</span> <span class="n">topScores</span><span class="o">.</span><span class="n">map</span> <span class="o">{</span> <span class="k">case</span> <span class="o">(</span><span class="n">i</span><span class="o">,</span> <span class="n">s</span><span class="o">)</span> <span class="k">=></span>
+ <span class="k">new</span> <span class="nc">ItemScore</span><span class="o">(</span>
+ <span class="c1">// convert item int index back to string ID
+</span> <span class="n">item</span> <span class="k">=</span> <span class="n">model</span><span class="o">.</span><span class="n">itemIntStringMap</span><span class="o">(</span><span class="n">i</span><span class="o">),</span>
+ <span class="n">score</span> <span class="k">=</span> <span class="n">s</span>
+ <s
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tainer-fluid"><div class="row"><div id="left-menu-wrapper" class="col-md-3"><nav id="nav-main"><ul><li class="level-1"><a class="expandible" href="/"><span>Apache PredictionIO (incubating) Documentation</span></a><ul><li class="level-2"><a class="final" href="/"><span>Welcome to Apache PredictionIO (incubating)</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Getting Started</span></a><ul><li class="level-2"><a class="final" href="/start/"><span>A Quick Intro</span></a></li><li class="level-2"><a class="final" href="/install/"><span>Installing Apache PredictionIO (incubating)</span></a></li><li class="level-2"><a class="final" href="/start/download/"><span>Downloading an Engine Template</span></a></li><li class="level-2"><a class="final" href="/start/deploy/"><span>Deploying Your First Engine</span></a></li><li class="level-2"><a class="final" href="/start/customize/"><span>Customizing the Engine</span></a></li></ul></li><li class="level-1"><a class=
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ation/metricbuild/"><span>Building Evaluation Metrics</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>System Architecture</span></a><ul><li class="level-2"><a class="final" href="/system/"><span>Architecture Overview</span></a></li><li class="level-2"><a class="final" href="/system/anotherdatastore/"><span>Using Another Data Store</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Engine Template Gallery</span></a><ul><li class="level-2"><a class="final" href="http://templates.prediction.io"><span>Browse</span></a></li><li class="level-2"><a class="final" href="/community/submit-template/"><span>Submit your Engine as a Template</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Demo Tutorials</span></a><ul><li class="level-2"><a class="final" href="/demo/tapster/"><span>Comics Recommendation Demo</span></a></li><li class="level-2"><a class="final" href="/demo/community/"><span>Community C
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<div class="row"><div class="col-md-9 col-sm-11 col-xs-11"><div class="hidden-md hidden-lg" id="mobile-page-heading-wrapper"><p>PredictionIO Docs</p><h4>How-To (Classification)</h4></div><h4 class="hidden-sm hidden-xs">PredictionIO Docs</h4></div><div class="col-md-3 col-sm-1 col-xs-1 hidden-md hidden-lg"><img id="left-menu-indicator" src="/images/icons/down-arrow-dfe9f7fe.png"/></div><div class="col-md-3 col-sm-12 col-xs-12 swiftype-wrapper"><div class="swiftype"><form class="search-form"><img class="search-box-toggler hidden-xs hidden-sm" src="/images/icons/search-glass-704bd4ff.png"/><div class="search-box"><img src="/images/icons/search-glass-704bd4ff.png"/><input type="text" id="st-search-input" class="st-search-input" placeholder="Search Doc..."/></div><img class="swiftype-row-hider hidden-md hidden-lg" src="/images/icons/drawer-toggle-active-fcbef12a.png"/></form></div></div><div class="mobile-left-menu-toggler hidden-md hidden-lg"></div></div></div></div><div id="page" class
="container-fluid"><div class="row"><div id="left-menu-wrapper" class="col-md-3"><nav id="nav-main"><ul><li class="level-1"><a class="expandible" href="/"><span>Apache PredictionIO (incubating) Documentation</span></a><ul><li class="level-2"><a class="final" href="/"><span>Welcome to Apache PredictionIO (incubating)</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Getting Started</span></a><ul><li class="level-2"><a class="final" href="/start/"><span>A Quick Intro</span></a></li><li class="level-2"><a class="final" href="/install/"><span>Installing Apache PredictionIO (incubating)</span></a></li><li class="level-2"><a class="final" href="/start/download/"><span>Downloading an Engine Template</span></a></li><li class="level-2"><a class="final" href="/start/deploy/"><span>Deploying Your First Engine</span></a></li><li class="level-2"><a class="final" href="/start/customize/"><span>Customizing the Engine</span></a></li></ul></li><li class="level-1"><a c
lass="expandible" href="#"><span>Integrating with Your App</span></a><ul><li class="level-2"><a class="final" href="/appintegration/"><span>App Integration Overview</span></a></li><li class="level-2"><a class="expandible" href="/sdk/"><span>List of SDKs</span></a><ul><li class="level-3"><a class="final" href="/sdk/java/"><span>Java & Android SDK</span></a></li><li class="level-3"><a class="final" href="/sdk/php/"><span>PHP SDK</span></a></li><li class="level-3"><a class="final" href="/sdk/python/"><span>Python SDK</span></a></li><li class="level-3"><a class="final" href="/sdk/ruby/"><span>Ruby SDK</span></a></li><li class="level-3"><a class="final" href="/sdk/community/"><span>Community Powered SDKs</span></a></li></ul></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Deploying an Engine</span></a><ul><li class="level-2"><a class="final" href="/deploy/"><span>Deploying as a Web Service</span></a></li><li class="level-2"><a class="final" href="/cli/#engine-comma
nds"><span>Engine Command-line Interface</span></a></li><li class="level-2"><a class="final" href="/deploy/engineparams/"><span>Setting Engine Parameters</span></a></li><li class="level-2"><a class="final" href="/deploy/enginevariants/"><span>Deploying Multiple Engine Variants</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Customizing an Engine</span></a><ul><li class="level-2"><a class="final" href="/customize/"><span>Learning DASE</span></a></li><li class="level-2"><a class="final" href="/customize/dase/"><span>Implement DASE</span></a></li><li class="level-2"><a class="final" href="/customize/troubleshooting/"><span>Troubleshooting Engine Development</span></a></li><li class="level-2"><a class="final" href="/api/current/#package"><span>Engine Scala APIs</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Collecting and Analyzing Data</span></a><ul><li class="level-2"><a class="final" href="/datacollection/"><span>Ev
ent Server Overview</span></a></li><li class="level-2"><a class="final" href="/cli/#event-server-commands"><span>Event Server Command-line Interface</span></a></li><li class="level-2"><a class="final" href="/datacollection/eventapi/"><span>Collecting Data with REST/SDKs</span></a></li><li class="level-2"><a class="final" href="/datacollection/eventmodel/"><span>Events Modeling</span></a></li><li class="level-2"><a class="final" href="/datacollection/webhooks/"><span>Unifying Multichannel Data with Webhooks</span></a></li><li class="level-2"><a class="final" href="/datacollection/channel/"><span>Channel</span></a></li><li class="level-2"><a class="final" href="/datacollection/batchimport/"><span>Importing Data in Batch</span></a></li><li class="level-2"><a class="final" href="/datacollection/analytics/"><span>Using Analytics Tools</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Choosing an Algorithm(s)</span></a><ul><li class="level-2"><a class="fina
l" href="/algorithm/"><span>Built-in Algorithm Libraries</span></a></li><li class="level-2"><a class="final" href="/algorithm/switch/"><span>Switching to Another Algorithm</span></a></li><li class="level-2"><a class="final" href="/algorithm/multiple/"><span>Combining Multiple Algorithms</span></a></li><li class="level-2"><a class="final" href="/algorithm/custom/"><span>Adding Your Own Algorithms</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>ML Tuning and Evaluation</span></a><ul><li class="level-2"><a class="final" href="/evaluation/"><span>Overview</span></a></li><li class="level-2"><a class="final" href="/evaluation/paramtuning/"><span>Hyperparameter Tuning</span></a></li><li class="level-2"><a class="final" href="/evaluation/evaluationdashboard/"><span>Evaluation Dashboard</span></a></li><li class="level-2"><a class="final" href="/evaluation/metricchoose/"><span>Choosing Evaluation Metrics</span></a></li><li class="level-2"><a class="final" hre
f="/evaluation/metricbuild/"><span>Building Evaluation Metrics</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>System Architecture</span></a><ul><li class="level-2"><a class="final" href="/system/"><span>Architecture Overview</span></a></li><li class="level-2"><a class="final" href="/system/anotherdatastore/"><span>Using Another Data Store</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Engine Template Gallery</span></a><ul><li class="level-2"><a class="final" href="http://templates.prediction.io"><span>Browse</span></a></li><li class="level-2"><a class="final" href="/community/submit-template/"><span>Submit your Engine as a Template</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Demo Tutorials</span></a><ul><li class="level-2"><a class="final" href="/demo/tapster/"><span>Comics Recommendation Demo</span></a></li><li class="level-2"><a class="final" href="/demo/community/"><span>Co
mmunity Contributed Demo</span></a></li><li class="level-2"><a class="final" href="/demo/textclassification/"><span>Text Classification Engine Tutorial</span></a></li></ul></li><li class="level-1"><a class="expandible" href="/community/"><span>Getting Involved</span></a><ul><li class="level-2"><a class="final" href="/community/contribute-code/"><span>Contribute Code</span></a></li><li class="level-2"><a class="final" href="/community/contribute-documentation/"><span>Contribute Documentation</span></a></li><li class="level-2"><a class="final" href="/community/contribute-sdk/"><span>Contribute a SDK</span></a></li><li class="level-2"><a class="final" href="/community/contribute-webhook/"><span>Contribute a Webhook</span></a></li><li class="level-2"><a class="final" href="/community/projects/"><span>Community Projects</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Getting Help</span></a><ul><li class="level-2"><a class="final" href="/resources/faq/"><
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<div class="row"><div class="col-md-9 col-sm-11 col-xs-11"><div class="hidden-md hidden-lg" id="mobile-page-heading-wrapper"><p>PredictionIO Docs</p><h4>Installing Apache PredictionIO (incubating)</h4></div><h4 class="hidden-sm hidden-xs">PredictionIO Docs</h4></div><div class="col-md-3 col-sm-1 col-xs-1 hidden-md hidden-lg"><img id="left-menu-indicator" src="/images/icons/down-arrow-dfe9f7fe.png"/></div><div class="col-md-3 col-sm-12 col-xs-12 swiftype-wrapper"><div class="swiftype"><form class="search-form"><img class="search-box-toggler hidden-xs hidden-sm" src="/images/icons/search-glass-704bd4ff.png"/><div class="search-box"><img src="/images/icons/search-glass-704bd4ff.png"/><input type="text" id="st-search-input" class="st-search-input" placeholder="Search Doc..."/></div><img class="swiftype-row-hider hidden-md hidden-lg" src="/images/icons/drawer-toggle-active-fcbef12a.png"/></form></div></div><div class="mobile-left-menu-toggler hidden-md hidden-lg"></div></div></div></div>
<div id="page" class="container-fluid"><div class="row"><div id="left-menu-wrapper" class="col-md-3"><nav id="nav-main"><ul><li class="level-1"><a class="expandible" href="/"><span>Apache PredictionIO (incubating) Documentation</span></a><ul><li class="level-2"><a class="final" href="/"><span>Welcome to Apache PredictionIO (incubating)</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Getting Started</span></a><ul><li class="level-2"><a class="final" href="/start/"><span>A Quick Intro</span></a></li><li class="level-2"><a class="final active" href="/install/"><span>Installing Apache PredictionIO (incubating)</span></a></li><li class="level-2"><a class="final" href="/start/download/"><span>Downloading an Engine Template</span></a></li><li class="level-2"><a class="final" href="/start/deploy/"><span>Deploying Your First Engine</span></a></li><li class="level-2"><a class="final" href="/start/customize/"><span>Customizing the Engine</span></a></li></ul></
li><li class="level-1"><a class="expandible" href="#"><span>Integrating with Your App</span></a><ul><li class="level-2"><a class="final" href="/appintegration/"><span>App Integration Overview</span></a></li><li class="level-2"><a class="expandible" href="/sdk/"><span>List of SDKs</span></a><ul><li class="level-3"><a class="final" href="/sdk/java/"><span>Java & Android SDK</span></a></li><li class="level-3"><a class="final" href="/sdk/php/"><span>PHP SDK</span></a></li><li class="level-3"><a class="final" href="/sdk/python/"><span>Python SDK</span></a></li><li class="level-3"><a class="final" href="/sdk/ruby/"><span>Ruby SDK</span></a></li><li class="level-3"><a class="final" href="/sdk/community/"><span>Community Powered SDKs</span></a></li></ul></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Deploying an Engine</span></a><ul><li class="level-2"><a class="final" href="/deploy/"><span>Deploying as a Web Service</span></a></li><li class="level-2"><a class="fina
l" href="/cli/#engine-commands"><span>Engine Command-line Interface</span></a></li><li class="level-2"><a class="final" href="/deploy/engineparams/"><span>Setting Engine Parameters</span></a></li><li class="level-2"><a class="final" href="/deploy/enginevariants/"><span>Deploying Multiple Engine Variants</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Customizing an Engine</span></a><ul><li class="level-2"><a class="final" href="/customize/"><span>Learning DASE</span></a></li><li class="level-2"><a class="final" href="/customize/dase/"><span>Implement DASE</span></a></li><li class="level-2"><a class="final" href="/customize/troubleshooting/"><span>Troubleshooting Engine Development</span></a></li><li class="level-2"><a class="final" href="/api/current/#package"><span>Engine Scala APIs</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Collecting and Analyzing Data</span></a><ul><li class="level-2"><a class="final" href=
"/datacollection/"><span>Event Server Overview</span></a></li><li class="level-2"><a class="final" href="/cli/#event-server-commands"><span>Event Server Command-line Interface</span></a></li><li class="level-2"><a class="final" href="/datacollection/eventapi/"><span>Collecting Data with REST/SDKs</span></a></li><li class="level-2"><a class="final" href="/datacollection/eventmodel/"><span>Events Modeling</span></a></li><li class="level-2"><a class="final" href="/datacollection/webhooks/"><span>Unifying Multichannel Data with Webhooks</span></a></li><li class="level-2"><a class="final" href="/datacollection/channel/"><span>Channel</span></a></li><li class="level-2"><a class="final" href="/datacollection/batchimport/"><span>Importing Data in Batch</span></a></li><li class="level-2"><a class="final" href="/datacollection/analytics/"><span>Using Analytics Tools</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Choosing an Algorithm(s)</span></a><ul><li cla
ss="level-2"><a class="final" href="/algorithm/"><span>Built-in Algorithm Libraries</span></a></li><li class="level-2"><a class="final" href="/algorithm/switch/"><span>Switching to Another Algorithm</span></a></li><li class="level-2"><a class="final" href="/algorithm/multiple/"><span>Combining Multiple Algorithms</span></a></li><li class="level-2"><a class="final" href="/algorithm/custom/"><span>Adding Your Own Algorithms</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>ML Tuning and Evaluation</span></a><ul><li class="level-2"><a class="final" href="/evaluation/"><span>Overview</span></a></li><li class="level-2"><a class="final" href="/evaluation/paramtuning/"><span>Hyperparameter Tuning</span></a></li><li class="level-2"><a class="final" href="/evaluation/evaluationdashboard/"><span>Evaluation Dashboard</span></a></li><li class="level-2"><a class="final" href="/evaluation/metricchoose/"><span>Choosing Evaluation Metrics</span></a></li><li class="le
vel-2"><a class="final" href="/evaluation/metricbuild/"><span>Building Evaluation Metrics</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>System Architecture</span></a><ul><li class="level-2"><a class="final" href="/system/"><span>Architecture Overview</span></a></li><li class="level-2"><a class="final" href="/system/anotherdatastore/"><span>Using Another Data Store</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Engine Template Gallery</span></a><ul><li class="level-2"><a class="final" href="http://templates.prediction.io"><span>Browse</span></a></li><li class="level-2"><a class="final" href="/community/submit-template/"><span>Submit your Engine as a Template</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Demo Tutorials</span></a><ul><li class="level-2"><a class="final" href="/demo/tapster/"><span>Comics Recommendation Demo</span></a></li><li class="level-2"><a class="final" href=
"/demo/community/"><span>Community Contributed Demo</span></a></li><li class="level-2"><a class="final" href="/demo/textclassification/"><span>Text Classification Engine Tutorial</span></a></li></ul></li><li class="level-1"><a class="expandible" href="/community/"><span>Getting Involved</span></a><ul><li class="level-2"><a class="final" href="/community/contribute-code/"><span>Contribute Code</span></a></li><li class="level-2"><a class="final" href="/community/contribute-documentation/"><span>Contribute Documentation</span></a></li><li class="level-2"><a class="final" href="/community/contribute-sdk/"><span>Contribute a SDK</span></a></li><li class="level-2"><a class="final" href="/community/contribute-webhook/"><span>Contribute a Webhook</span></a></li><li class="level-2"><a class="final" href="/community/projects/"><span>Community Projects</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Getting Help</span></a><ul><li class="level-2"><a class="fina
l" href="/resources/faq/"><span>FAQs</span></a></li><li class="level-2"><a class="final" href="/support/"><span>Community Support</span></a></li><li class="level-2"><a class="final" href="/support/#enterprise-support"><span>Enterprise Support</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Resources</span></a><ul><li class="level-2"><a class="final" href="/resources/intellij/"><span>Developing Engines with IntelliJ IDEA</span></a></li><li class="level-2"><a class="final" href="/resources/upgrade/"><span>Upgrade Instructions</span></a></li><li class="level-2"><a class="final" href="/resources/glossary/"><span>Glossary</span></a></li></ul></li></ul></nav></div><div class="col-md-9 col-sm-12"><div class="content-header hidden-md hidden-lg"><div id="breadcrumbs" class="hidden-sm hidden xs"><ul><li><a href="#">Getting Started</a><span class="spacer">></span></li><li><span class="last">Installing Apache PredictionIO (incubating)</span></li></ul></div><
div id="page-title"><h1>Installing Apache PredictionIO (incubating)</h1></div></div><div id="table-of-content-wrapper"><h5>On this page</h5><aside id="table-of-contents"><ul> <li> <a href="#method-1-quick-install">Method 1: Quick Install</a> </li> <li> <a href="#method-2-manual-install">Method 2: Manual Install</a> </li> <li> <a href="#method-3-terminal-com">Method 3: Terminal.com</a> </li> </ul> </aside><hr/><a id="edit-page-link" href="https://github.com/apache/incubator-predictionio/tree/livedoc/docs/manual/source/install/index.html.md.erb"><img src="/images/icons/edit-pencil-d6c1bb3d.png"/>Edit this page</a></div><div class="content-header hidden-sm hidden-xs"><div id="breadcrumbs" class="hidden-sm hidden xs"><ul><li><a href="#">Getting Started</a><span class="spacer">></span></li><li><span class="last">Installing Apache PredictionIO (incubating)</span></li></ul></div><div id="page-title"><h1>Installing Apache PredictionIO (incubating)</h1></div></div><div class="content"><h2
id='method-1:-quick-install' class='header-anchors'>Method 1: Quick Install</h2><p>On Linux / Mac OS X, Apache PredictionIO (incubating) can now be installed with a single command:</p><div class="highlight shell"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1</pre></td><td class="code"><pre><span class="gp">$ </span>bash -c <span class="s2">"</span><span class="k">$(</span>curl -s https://raw.githubusercontent.com/apache/incubator-predictionio/master/bin/install.sh<span class="k">)</span><span class="s2">"</span>
+</pre></td></tr></tbody></table> </div> <p>The above script will complete the installation for you.</p><p>You can proceed to <a href="/start/download">Choosing an Engine Template</a>, or continue the QuickStart guide of the Engine template if you have already chosen one.</p> <h2 id='method-2:-manual-install' class='header-anchors'>Method 2: Manual Install</h2><h3 id='prerequisites' class='header-anchors'>Prerequisites</h3><p>It is <strong>very important</strong> to meet the minimum version of the following technologies that power Apache PredictionIO (incubating).</p> <ul> <li>Apache Hadoop 2.4.0 (optional, required only if YARN and HDFS are needed)</li> <li>Apache Spark 1.3.0 for Hadoop 2.4</li> <li>Java SE Development Kit 7</li> </ul> <p>and one of the following sets:</p> <ul> <li>PostgreSQL 9.1</li> </ul> <p>or</p> <ul> <li>MySQL 5.1</li> </ul> <p>or</p> <ul> <li>Apache HBase 0.98.6</li> <li>Elasticsearch 1.4.0</li> </ul> <p>If you are running on a single machine, we recommend a m
inimum of 2GB memory.</p><div class="alert-message info"><p>If you are using Linux, Apache Spark local mode, which is the default operation mode without further configuration, may not work. In that case, configure your Apache Spark to run in <a href="http://spark.apache.org/docs/latest/spark-standalone.html">standalone cluster mode</a>.</p></div><h3 id='installing-apache-predictionio-(incubating)' class='header-anchors'>Installing Apache PredictionIO (incubating)</h3><p>Apache PredictionIO (incubating) runs on a Java virtual machine, so it runs on most platforms. Choose your platform below:</p> <ul> <li><a href="/install/install-linux/">Installing Apache PredictionIO (incubating) on Linux / Mac OS X</a></li> <li><a href="/install/install-sourcecode/">Installing Apache PredictionIO (incubating) from Source Code</a></li> <li><a href="/install/install-vagrant/">Installing Apache PredictionIO (incubating) with Vagrant (VirtualBox)</a></li> <li><a href="https://www.terminal.com/snapshot/
f444bfb7538dfc596485374f56167ec6f79cbc16f793f013ad120067070eb81a">Installing Apache PredictionIO (incubating) with Terminal.com Snap</a></li> </ul> <p>You may also use one of the community-contributed packages to install Apache PredictionIO (incubating):</p> <ul> <li><a href="/community/projects/#docker-installation-for-predictionio">Installing Apache PredictionIO (incubating) with Docker</a></li> </ul> <div class="alert-message warning"><p><strong>0.8.2 contains schema changes from the previous versions, if you have installed the previous versions, you may need to clear both HBase and Elasticsearch. See more <a href="/resources/upgrade/">here</a>.</strong></p></div><h2 id='method-3:-terminal.com' class='header-anchors'>Method 3: Terminal.com</h2><p>Public snaps are available on our Terminal.com <a href="https://www.terminal.com/user/predictionio">page</a>.</p><p>Instance type <strong>must be</strong> set to <em>medium</em> or higher for Apache PredictionIO (incubating) to function
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<div class="row"><div class="col-md-9 col-sm-11 col-xs-11"><div class="hidden-md hidden-lg" id="mobile-page-heading-wrapper"><p>PredictionIO Docs</p><h4>Installing Apache PredictionIO (incubating) on Linux / Mac OS X</h4></div><h4 class="hidden-sm hidden-xs">PredictionIO Docs</h4></div><div class="col-md-3 col-sm-1 col-xs-1 hidden-md hidden-lg"><img id="left-menu-indicator" src="/images/icons/down-arrow-dfe9f7fe.png"/></div><div class="col-md-3 col-sm-12 col-xs-12 swiftype-wrapper"><div class="swiftype"><form class="search-form"><img class="search-box-toggler hidden-xs hidden-sm" src="/images/icons/search-glass-704bd4ff.png"/><div class="search-box"><img src="/images/icons/search-glass-704bd4ff.png"/><input type="text" id="st-search-input" class="st-search-input" placeholder="Search Doc..."/></div><img class="swiftype-row-hider hidden-md hidden-lg" src="/images/icons/drawer-toggle-active-fcbef12a.png"/></form></div></div><div class="mobile-left-menu-toggler hidden-md hidden-lg"></di
v></div></div></div><div id="page" class="container-fluid"><div class="row"><div id="left-menu-wrapper" class="col-md-3"><nav id="nav-main"><ul><li class="level-1"><a class="expandible" href="/"><span>Apache PredictionIO (incubating) Documentation</span></a><ul><li class="level-2"><a class="final" href="/"><span>Welcome to Apache PredictionIO (incubating)</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Getting Started</span></a><ul><li class="level-2"><a class="final" href="/start/"><span>A Quick Intro</span></a></li><li class="level-2"><a class="final" href="/install/"><span>Installing Apache PredictionIO (incubating)</span></a></li><li class="level-2"><a class="final" href="/start/download/"><span>Downloading an Engine Template</span></a></li><li class="level-2"><a class="final" href="/start/deploy/"><span>Deploying Your First Engine</span></a></li><li class="level-2"><a class="final" href="/start/customize/"><span>Customizing the Engine</span></a
></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Integrating with Your App</span></a><ul><li class="level-2"><a class="final" href="/appintegration/"><span>App Integration Overview</span></a></li><li class="level-2"><a class="expandible" href="/sdk/"><span>List of SDKs</span></a><ul><li class="level-3"><a class="final" href="/sdk/java/"><span>Java & Android SDK</span></a></li><li class="level-3"><a class="final" href="/sdk/php/"><span>PHP SDK</span></a></li><li class="level-3"><a class="final" href="/sdk/python/"><span>Python SDK</span></a></li><li class="level-3"><a class="final" href="/sdk/ruby/"><span>Ruby SDK</span></a></li><li class="level-3"><a class="final" href="/sdk/community/"><span>Community Powered SDKs</span></a></li></ul></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Deploying an Engine</span></a><ul><li class="level-2"><a class="final" href="/deploy/"><span>Deploying as a Web Service</span></a></li><li class="level-2"><
a class="final" href="/cli/#engine-commands"><span>Engine Command-line Interface</span></a></li><li class="level-2"><a class="final" href="/deploy/engineparams/"><span>Setting Engine Parameters</span></a></li><li class="level-2"><a class="final" href="/deploy/enginevariants/"><span>Deploying Multiple Engine Variants</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Customizing an Engine</span></a><ul><li class="level-2"><a class="final" href="/customize/"><span>Learning DASE</span></a></li><li class="level-2"><a class="final" href="/customize/dase/"><span>Implement DASE</span></a></li><li class="level-2"><a class="final" href="/customize/troubleshooting/"><span>Troubleshooting Engine Development</span></a></li><li class="level-2"><a class="final" href="/api/current/#package"><span>Engine Scala APIs</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Collecting and Analyzing Data</span></a><ul><li class="level-2"><a class=
"final" href="/datacollection/"><span>Event Server Overview</span></a></li><li class="level-2"><a class="final" href="/cli/#event-server-commands"><span>Event Server Command-line Interface</span></a></li><li class="level-2"><a class="final" href="/datacollection/eventapi/"><span>Collecting Data with REST/SDKs</span></a></li><li class="level-2"><a class="final" href="/datacollection/eventmodel/"><span>Events Modeling</span></a></li><li class="level-2"><a class="final" href="/datacollection/webhooks/"><span>Unifying Multichannel Data with Webhooks</span></a></li><li class="level-2"><a class="final" href="/datacollection/channel/"><span>Channel</span></a></li><li class="level-2"><a class="final" href="/datacollection/batchimport/"><span>Importing Data in Batch</span></a></li><li class="level-2"><a class="final" href="/datacollection/analytics/"><span>Using Analytics Tools</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Choosing an Algorithm(s)</span></
a><ul><li class="level-2"><a class="final" href="/algorithm/"><span>Built-in Algorithm Libraries</span></a></li><li class="level-2"><a class="final" href="/algorithm/switch/"><span>Switching to Another Algorithm</span></a></li><li class="level-2"><a class="final" href="/algorithm/multiple/"><span>Combining Multiple Algorithms</span></a></li><li class="level-2"><a class="final" href="/algorithm/custom/"><span>Adding Your Own Algorithms</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>ML Tuning and Evaluation</span></a><ul><li class="level-2"><a class="final" href="/evaluation/"><span>Overview</span></a></li><li class="level-2"><a class="final" href="/evaluation/paramtuning/"><span>Hyperparameter Tuning</span></a></li><li class="level-2"><a class="final" href="/evaluation/evaluationdashboard/"><span>Evaluation Dashboard</span></a></li><li class="level-2"><a class="final" href="/evaluation/metricchoose/"><span>Choosing Evaluation Metrics</span></a></li>
<li class="level-2"><a class="final" href="/evaluation/metricbuild/"><span>Building Evaluation Metrics</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>System Architecture</span></a><ul><li class="level-2"><a class="final" href="/system/"><span>Architecture Overview</span></a></li><li class="level-2"><a class="final" href="/system/anotherdatastore/"><span>Using Another Data Store</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Engine Template Gallery</span></a><ul><li class="level-2"><a class="final" href="http://templates.prediction.io"><span>Browse</span></a></li><li class="level-2"><a class="final" href="/community/submit-template/"><span>Submit your Engine as a Template</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Demo Tutorials</span></a><ul><li class="level-2"><a class="final" href="/demo/tapster/"><span>Comics Recommendation Demo</span></a></li><li class="level-2"><a class=
"final" href="/demo/community/"><span>Community Contributed Demo</span></a></li><li class="level-2"><a class="final" href="/demo/textclassification/"><span>Text Classification Engine Tutorial</span></a></li></ul></li><li class="level-1"><a class="expandible" href="/community/"><span>Getting Involved</span></a><ul><li class="level-2"><a class="final" href="/community/contribute-code/"><span>Contribute Code</span></a></li><li class="level-2"><a class="final" href="/community/contribute-documentation/"><span>Contribute Documentation</span></a></li><li class="level-2"><a class="final" href="/community/contribute-sdk/"><span>Contribute a SDK</span></a></li><li class="level-2"><a class="final" href="/community/contribute-webhook/"><span>Contribute a Webhook</span></a></li><li class="level-2"><a class="final" href="/community/projects/"><span>Community Projects</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Getting Help</span></a><ul><li class="level-2"><
a class="final" href="/resources/faq/"><span>FAQs</span></a></li><li class="level-2"><a class="final" href="/support/"><span>Community Support</span></a></li><li class="level-2"><a class="final" href="/support/#enterprise-support"><span>Enterprise Support</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Resources</span></a><ul><li class="level-2"><a class="final" href="/resources/intellij/"><span>Developing Engines with IntelliJ IDEA</span></a></li><li class="level-2"><a class="final" href="/resources/upgrade/"><span>Upgrade Instructions</span></a></li><li class="level-2"><a class="final" href="/resources/glossary/"><span>Glossary</span></a></li></ul></li></ul></nav></div><div class="col-md-9 col-sm-12"><div class="content-header hidden-md hidden-lg"><div id="page-title"><h1>Installing Apache PredictionIO (incubating) on Linux / Mac OS X</h1></div></div><div id="table-of-content-wrapper"><h5>On this page</h5><aside id="table-of-contents"><ul> <li> <a
href="#method-1-quick-install">Method 1: Quick Install</a> </li> <li> <a href="#method-2-manual-install">Method 2: Manual Install</a> </li> </ul> </aside><hr/><a id="edit-page-link" href="https://github.com/apache/incubator-predictionio/tree/livedoc/docs/manual/source/install/install-linux.html.md.erb"><img src="/images/icons/edit-pencil-d6c1bb3d.png"/>Edit this page</a></div><div class="content-header hidden-sm hidden-xs"><div id="page-title"><h1>Installing Apache PredictionIO (incubating) on Linux / Mac OS X</h1></div></div><div class="content"><h2 id='method-1:-quick-install' class='header-anchors'>Method 1: Quick Install</h2><p>On Linux / Mac OS X, Apache PredictionIO (incubating) can now be installed with a single command:</p><div class="highlight shell"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1</pre></td><td class="code"><pre><span class="gp">$ </span>bash -c <span class="s2">"</span><span class="k">$(</s
pan>curl -s https://raw.githubusercontent.com/apache/incubator-predictionio/master/bin/install.sh<span class="k">)</span><span class="s2">"</span>
+</pre></td></tr></tbody></table> </div> <p>The above script will complete the installation for you.</p><p>You can proceed to <a href="/start/download">Choosing an Engine Template</a>, or continue the QuickStart guide of the Engine template if you have already chosen one.</p> <h2 id='method-2:-manual-install' class='header-anchors'>Method 2: Manual Install</h2><p>If you do not want to use the Quick Install script, you can follow the steps below to setup Apache PredictionIO (incubating) and its dependencies. In these instructions we will assume you are in your home directory. Wherever you see <code>/home/abc</code>, replace it with your own home directory.</p><h3 id='java' class='header-anchors'>Java</h3><p>Ensure you have an appropriate Java version installed. For example:</p><div class="highlight shell"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1
+2
+3
+4</pre></td><td class="code"><pre><span class="gp">$ </span>java -version
+java version <span class="s2">"1.8.0_40"</span>
+Java<span class="o">(</span>TM<span class="o">)</span> SE Runtime Environment <span class="o">(</span>build 1.8.0_40-b25<span class="o">)</span>
+Java HotSpot<span class="o">(</span>TM<span class="o">)</span> 64-Bit Server VM <span class="o">(</span>build 25.40-b25, mixed mode<span class="o">)</span>
+</pre></td></tr></tbody></table> </div> <h3 id='download-apache-predictionio-(incubating)' class='header-anchors'>Download Apache PredictionIO (incubating)</h3><p>Download Apache PredictionIO (incubating) and extract it.</p><div class="highlight shell"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1
+2
+3
+4
+5</pre></td><td class="code"><pre><span class="gp">$ </span><span class="nb">cd</span>
+<span class="gp">$ </span><span class="nb">pwd</span>
+/home/abc
+<span class="gp">$ </span>wget http://download.prediction.io/PredictionIO-0.9.6.tar.gz
+<span class="gp">$ </span>tar zxvf PredictionIO-0.9.6.tar.gz
+</pre></td></tr></tbody></table> </div> <div class="alert-message note"><p>Download instructions above apply to previous non-Apache releases only. Once we have made an Apache release, new instructions will be provided.</p></div><h3 id='installing-dependencies' class='header-anchors'>Installing Dependencies</h3><p>Let us install dependencies inside a subdirectory of the Apache PredictionIO (incubating) installation. By following this convention, you can use PredictionIO's default configuration as is.</p><div class="highlight shell"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1</pre></td><td class="code"><pre><span class="gp">$ </span>mkdir PredictionIO-0.9.6/vendors
+</pre></td></tr></tbody></table> </div> <h4 id='spark-setup' class='header-anchors'>Spark Setup</h4><p><a href="http://spark.apache.org">Apache Spark</a> is the default processing engine for PredictionIO. Download and extract it.</p><div class="highlight shell"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1
+2</pre></td><td class="code"><pre><span class="gp">$ </span>wget http://d3kbcqa49mib13.cloudfront.net/spark-1.5.1-bin-hadoop2.6.tgz
+<span class="gp">$ </span>tar zxvfC spark-1.5.1-bin-hadoop2.6.tgz PredictionIO-0.9.6/vendors
+</pre></td></tr></tbody></table> </div> <div class="alert-message info"><p>If you decide to install Apache Spark to another location, you must edit <code>PredictionIO-0.9.6/conf/pio-env.sh</code> and change the <code>SPARK_HOME</code> variable to point to your own Apache Spark installation.</p></div><h4 id='elasticsearch-setup' class='header-anchors'>Elasticsearch Setup</h4><div class="alert-message warning"><p>You may skip this section if you are using PostgreSQL or MySQL.</p></div><p><a href="http://www.elasticsearch.org/">Elasticsearch</a> is the default metadata store for PredictionIO. Download and extract it.</p><div class="highlight shell"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1
+2</pre></td><td class="code"><pre><span class="gp">$ </span>wget https://download.elasticsearch.org/elasticsearch/elasticsearch/elasticsearch-1.4.4.tar.gz
+<span class="gp">$ </span>tar zxvfC elasticsearch-1.4.4.tar.gz PredictionIO-0.9.6/vendors
+</pre></td></tr></tbody></table> </div> <div class="alert-message info"><p>If you decide to install Elasticsearch to another location, you must edit <code>PredictionIO-0.9.6/conf/pio-env.sh</code> and change the <code>PIO_STORAGE_SOURCES_ELASTICSEARCH_HOME</code> variable to point to your own Elasticsearch installation.</p></div><div class="alert-message info"><p>If you are using a shared network, change the <code>network.host</code> line in <code>PredictionIO-0.9.6/vendors/elasticsearch-1.4.4/config/elasticsearch.yml</code> to <code>network.host: 127.0.0.1</code> because by default, Elasticsearch looks for other machines on the network upon setup and you may run into weird errors if there are other machines that is also running Elasticsearch.</p></div><p>If you are not using the default setting at <code>localhost</code>, you may change the following in <code>PredictionIO-0.9.6/conf/pio-env.sh</code> to fit your setup.</p><div class="highlight shell"><table style="border-spacing: 0"
><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1
+2
+3</pre></td><td class="code"><pre><span class="nv">PIO_STORAGE_SOURCES_ELASTICSEARCH_TYPE</span><span class="o">=</span>elasticsearch
+<span class="nv">PIO_STORAGE_SOURCES_ELASTICSEARCH_HOSTS</span><span class="o">=</span>localhost
+<span class="nv">PIO_STORAGE_SOURCES_ELASTICSEARCH_PORTS</span><span class="o">=</span>9300
+</pre></td></tr></tbody></table> </div> <h4 id='hbase-setup<a-class="anchor"-name="hbase"> </a>' class='header-anchors' >HBase Setup<a class="anchor" name="hbase"> </a></h4><div class="alert-message warning"><p>You may skip this section if you are using PostgreSQL or MySQL.</p></div><p><a href="http://hbase.apache.org">HBase</a> is the default event data store for PredictionIO. Download and extract it.</p><div class="highlight shell"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1
+2</pre></td><td class="code"><pre><span class="gp">$ </span>wget http://archive.apache.org/dist/hbase/hbase-1.0.0/hbase-1.0.0-bin.tar.gz
+<span class="gp">$ </span>tar zxvfC hbase-1.0.0-bin.tar.gz PredictionIO-0.9.6/vendors
+</pre></td></tr></tbody></table> </div> <div class="alert-message info"><p>If you decide to install HBase to another location, you must edit <code>PredictionIO-0.9.6/conf/pio-env.sh</code> and change the <code>PIO_STORAGE_SOURCES_HBASE_HOME</code> variable to point to your own HBase installation.</p></div><p>You will need to at least add a minimal configuration to HBase to start it in standalone mode. Details can be found <a href="http://hbase.apache.org/book/quickstart.html">here</a>. Here, we are showing a sample minimal configuration.</p><div class="alert-message info"><p>For production deployment, run a fully distributed HBase configuration.</p></div><p>Edit <code>PredictionIO-0.9.6/vendors/hbase-1.0.0/conf/hbase-site.xml</code>.</p><div class="highlight shell"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1
+2
+3
+4
+5
+6
+7
+8
+9
+10</pre></td><td class="code"><pre><configuration>
+ <property>
+ <name>hbase.rootdir</name>
+ <value>file:///home/abc/PredictionIO-0.9.6/vendors/hbase-1.0.0/data</value>
+ </property>
+ <property>
+ <name>hbase.zookeeper.property.dataDir</name>
+ <value>/home/abc/PredictionIO-0.9.6/vendors/hbase-1.0.0/zookeeper</value>
+ </property>
+</configuration>
+</pre></td></tr></tbody></table> </div> <div class="alert-message info"><p>HBase will create <code>hbase.rootdir</code> automatically to store its data.</p></div><p>Edit <code>PredictionIO-0.9.6/vendors/hbase-1.0.0/conf/hbase-env.sh</code> to set <code>JAVA_HOME</code> for the cluster. For example:</p><div class="highlight shell"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1</pre></td><td class="code"><pre><span class="nb">export </span><span class="nv">JAVA_HOME</span><span class="o">=</span>/usr/lib/jvm/java-8-oracle/jre
+</pre></td></tr></tbody></table> </div> <p>For Mac users, use this instead (change <code>1.8</code> to <code>1.7</code> if you have Java 7 installed):</p><div class="highlight shell"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1</pre></td><td class="code"><pre><span class="nb">export </span><span class="nv">JAVA_HOME</span><span class="o">=</span><span class="sb">`</span>/usr/libexec/java_home -v 1.8<span class="sb">`</span>
+</pre></td></tr></tbody></table> </div> <p>In addition, you must set your environment variable <code>JAVA_HOME</code>. For example, in <code>/home/abc/.bashrc</code> add the following line:</p><div class="highlight shell"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1</pre></td><td class="code"><pre><span class="nb">export </span><span class="nv">JAVA_HOME</span><span class="o">=</span>/usr/lib/jvm/java-8-oracle
+</pre></td></tr></tbody></table> </div> <h3 id='start-predictionio-and-dependent-services' class='header-anchors'>Start PredictionIO and Dependent Services</h3><div class="alert-message warning"><p>If you are using PostgreSQL or MySQL, skip <code>pio-start-all</code> and <code>pio-stop-all</code>, and do <code>PredictionIO-0.9.6/bin/pio eventserver &</code> instead.</p></div><p>Simply do <code>PredictionIO-0.9.6/bin/pio-start-all</code> and you should see something similar to the following:</p><div class="highlight shell"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1
+2
+3
+4
+5
+6
+7</pre></td><td class="code"><pre><span class="gp">$ </span>PredictionIO-0.9.6/bin/pio-start-all
+Starting Elasticsearch...
+Starting HBase...
+starting master, logging to /home/abc/PredictionIO-0.9.6/vendors/hbase-1.0.0/bin/../logs/hbase-abc-master-yourhost.local.out
+Waiting 10 seconds <span class="k">for </span>HBase to fully initialize...
+Starting PredictionIO Event Server...
+<span class="err">$</span>
+</pre></td></tr></tbody></table> </div> <p>You may use <code>jps</code> to verify that you have everything started:</p><div class="highlight shell"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1
+2
+3
+4
+5
+6</pre></td><td class="code"><pre><span class="gp">$ </span>jps -l
+15344 org.apache.hadoop.hbase.master.HMaster
+15409 io.prediction.tools.console.Console
+15256 org.elasticsearch.bootstrap.Elasticsearch
+15469 sun.tools.jps.Jps
+<span class="err">$</span>
+</pre></td></tr></tbody></table> </div> <p>A running setup will have these up and running:</p> <ul> <li>io.prediction.tools.console.Console</li> <li>org.apache.hadoop.hbase.master.HMaster</li> <li>org.elasticsearch.bootstrap.Elasticsearch</li> </ul> <p>At any time, you can run <code>PredictionIO-0.9.6/bin/pio status</code> to check the status of the dependencies.</p><p>Now you have installed everything you need!</p><p>You can proceed to <a href="/start/download">Choosing an Engine Template</a>, or continue the QuickStart guide of the Engine template if you have already chosen one.</p> </div></div></div></div><footer><div class="container"><div class="seperator"></div><div class="row"><div class="col-md-4 col-md-push-8 col-xs-12"><div class="subscription-form-wrapper"><h4>Subscribe to our Newsletter</h4><form class="ajax-form" id="subscribe-form" method="POST" action="https://script.google.com/macros/s/AKfycbwhzeKCQJjQ52eVAqNT_vcklH07OITUO7wzOMDXvK6EGAWgaZgF/exec"><input class="requi
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+fbq('track', "PageView");</script><script src="//use.typekit.net/mut4mjx.js"></script><script>try{Typekit.load();}catch(e){}</script></head><body><div id="global"><header><div class="container" id="header-wrapper"><div class="row"><div class="col-sm-12"><div id="logo-wrapper"><span id="drawer-toggle"></span><a href="#"></a><a href="http://prediction.io/"><img alt="PredictionIO" id="logo" src="/images/logos/logo-ee2b9bb3.png"/></a></div><div id="menu-wrapper"><div id="header-nav-options-wrapper"><ul><li><a href="/">Install & Doc</a></li> <li><a href="/support">Support</a></li> </ul></div><div id="pill-wrapper"><a class="pill left" href="//templates.prediction.io/">TEMPLATES</a> <a class="pill right" href="//github.com/PredictionIO/PredictionIO/">OPEN SOURCE</a></div></div><img class="mobile-search-bar-toggler hidden-md hidden-lg" src="/images/icons/search-glass-704bd4ff.png"/></div></div></div></header><div id="search-bar-row-wrapper"><div class="container-fluid" id="search-bar-row">
<div class="row"><div class="col-md-9 col-sm-11 col-xs-11"><div class="hidden-md hidden-lg" id="mobile-page-heading-wrapper"><p>PredictionIO Docs</p><h4>Level 3</h4></div><h4 class="hidden-sm hidden-xs">PredictionIO Docs</h4></div><div class="col-md-3 col-sm-1 col-xs-1 hidden-md hidden-lg"><img id="left-menu-indicator" src="/images/icons/down-arrow-dfe9f7fe.png"/></div><div class="col-md-3 col-sm-12 col-xs-12 swiftype-wrapper"><div class="swiftype"><form class="search-form"><img class="search-box-toggler hidden-xs hidden-sm" src="/images/icons/search-glass-704bd4ff.png"/><div class="search-box"><img src="/images/icons/search-glass-704bd4ff.png"/><input type="text" id="st-search-input" class="st-search-input" placeholder="Search Doc..."/></div><img class="swiftype-row-hider hidden-md hidden-lg" src="/images/icons/drawer-toggle-active-fcbef12a.png"/></form></div></div><div class="mobile-left-menu-toggler hidden-md hidden-lg"></div></div></div></div><div id="page" class="container-flui
d"><div class="row"><div id="left-menu-wrapper" class="col-md-3"><nav id="nav-main"><ul><li class="level-1"><a class="expandible" href="/"><span>Apache PredictionIO (incubating) Documentation</span></a><ul><li class="level-2"><a class="final" href="/"><span>Welcome to Apache PredictionIO (incubating)</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Getting Started</span></a><ul><li class="level-2"><a class="final" href="/start/"><span>A Quick Intro</span></a></li><li class="level-2"><a class="final" href="/install/"><span>Installing Apache PredictionIO (incubating)</span></a></li><li class="level-2"><a class="final" href="/start/download/"><span>Downloading an Engine Template</span></a></li><li class="level-2"><a class="final" href="/start/deploy/"><span>Deploying Your First Engine</span></a></li><li class="level-2"><a class="final" href="/start/customize/"><span>Customizing the Engine</span></a></li></ul></li><li class="level-1"><a class="expandible
" href="#"><span>Integrating with Your App</span></a><ul><li class="level-2"><a class="final" href="/appintegration/"><span>App Integration Overview</span></a></li><li class="level-2"><a class="expandible" href="/sdk/"><span>List of SDKs</span></a><ul><li class="level-3"><a class="final" href="/sdk/java/"><span>Java & Android SDK</span></a></li><li class="level-3"><a class="final" href="/sdk/php/"><span>PHP SDK</span></a></li><li class="level-3"><a class="final" href="/sdk/python/"><span>Python SDK</span></a></li><li class="level-3"><a class="final" href="/sdk/ruby/"><span>Ruby SDK</span></a></li><li class="level-3"><a class="final" href="/sdk/community/"><span>Community Powered SDKs</span></a></li></ul></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Deploying an Engine</span></a><ul><li class="level-2"><a class="final" href="/deploy/"><span>Deploying as a Web Service</span></a></li><li class="level-2"><a class="final" href="/cli/#engine-commands"><span>Engin
e Command-line Interface</span></a></li><li class="level-2"><a class="final" href="/deploy/engineparams/"><span>Setting Engine Parameters</span></a></li><li class="level-2"><a class="final" href="/deploy/enginevariants/"><span>Deploying Multiple Engine Variants</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Customizing an Engine</span></a><ul><li class="level-2"><a class="final" href="/customize/"><span>Learning DASE</span></a></li><li class="level-2"><a class="final" href="/customize/dase/"><span>Implement DASE</span></a></li><li class="level-2"><a class="final" href="/customize/troubleshooting/"><span>Troubleshooting Engine Development</span></a></li><li class="level-2"><a class="final" href="/api/current/#package"><span>Engine Scala APIs</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Collecting and Analyzing Data</span></a><ul><li class="level-2"><a class="final" href="/datacollection/"><span>Event Server Overv
iew</span></a></li><li class="level-2"><a class="final" href="/cli/#event-server-commands"><span>Event Server Command-line Interface</span></a></li><li class="level-2"><a class="final" href="/datacollection/eventapi/"><span>Collecting Data with REST/SDKs</span></a></li><li class="level-2"><a class="final" href="/datacollection/eventmodel/"><span>Events Modeling</span></a></li><li class="level-2"><a class="final" href="/datacollection/webhooks/"><span>Unifying Multichannel Data with Webhooks</span></a></li><li class="level-2"><a class="final" href="/datacollection/channel/"><span>Channel</span></a></li><li class="level-2"><a class="final" href="/datacollection/batchimport/"><span>Importing Data in Batch</span></a></li><li class="level-2"><a class="final" href="/datacollection/analytics/"><span>Using Analytics Tools</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Choosing an Algorithm(s)</span></a><ul><li class="level-2"><a class="final" href="/algori
thm/"><span>Built-in Algorithm Libraries</span></a></li><li class="level-2"><a class="final" href="/algorithm/switch/"><span>Switching to Another Algorithm</span></a></li><li class="level-2"><a class="final" href="/algorithm/multiple/"><span>Combining Multiple Algorithms</span></a></li><li class="level-2"><a class="final" href="/algorithm/custom/"><span>Adding Your Own Algorithms</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>ML Tuning and Evaluation</span></a><ul><li class="level-2"><a class="final" href="/evaluation/"><span>Overview</span></a></li><li class="level-2"><a class="final" href="/evaluation/paramtuning/"><span>Hyperparameter Tuning</span></a></li><li class="level-2"><a class="final" href="/evaluation/evaluationdashboard/"><span>Evaluation Dashboard</span></a></li><li class="level-2"><a class="final" href="/evaluation/metricchoose/"><span>Choosing Evaluation Metrics</span></a></li><li class="level-2"><a class="final" href="/evaluation/m
etricbuild/"><span>Building Evaluation Metrics</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>System Architecture</span></a><ul><li class="level-2"><a class="final" href="/system/"><span>Architecture Overview</span></a></li><li class="level-2"><a class="final" href="/system/anotherdatastore/"><span>Using Another Data Store</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Engine Template Gallery</span></a><ul><li class="level-2"><a class="final" href="http://templates.prediction.io"><span>Browse</span></a></li><li class="level-2"><a class="final" href="/community/submit-template/"><span>Submit your Engine as a Template</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Demo Tutorials</span></a><ul><li class="level-2"><a class="final" href="/demo/tapster/"><span>Comics Recommendation Demo</span></a></li><li class="level-2"><a class="final" href="/demo/community/"><span>Community Contribu
ted Demo</span></a></li><li class="level-2"><a class="final" href="/demo/textclassification/"><span>Text Classification Engine Tutorial</span></a></li></ul></li><li class="level-1"><a class="expandible" href="/community/"><span>Getting Involved</span></a><ul><li class="level-2"><a class="final" href="/community/contribute-code/"><span>Contribute Code</span></a></li><li class="level-2"><a class="final" href="/community/contribute-documentation/"><span>Contribute Documentation</span></a></li><li class="level-2"><a class="final" href="/community/contribute-sdk/"><span>Contribute a SDK</span></a></li><li class="level-2"><a class="final" href="/community/contribute-webhook/"><span>Contribute a Webhook</span></a></li><li class="level-2"><a class="final" href="/community/projects/"><span>Community Projects</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Getting Help</span></a><ul><li class="level-2"><a class="final" href="/resources/faq/"><span>FAQs</span>
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<div class="row"><div class="col-md-9 col-sm-11 col-xs-11"><div class="hidden-md hidden-lg" id="mobile-page-heading-wrapper"><p>PredictionIO Docs</p><h4>Level 4.1</h4></div><h4 class="hidden-sm hidden-xs">PredictionIO Docs</h4></div><div class="col-md-3 col-sm-1 col-xs-1 hidden-md hidden-lg"><img id="left-menu-indicator" src="/images/icons/down-arrow-dfe9f7fe.png"/></div><div class="col-md-3 col-sm-12 col-xs-12 swiftype-wrapper"><div class="swiftype"><form class="search-form"><img class="search-box-toggler hidden-xs hidden-sm" src="/images/icons/search-glass-704bd4ff.png"/><div class="search-box"><img src="/images/icons/search-glass-704bd4ff.png"/><input type="text" id="st-search-input" class="st-search-input" placeholder="Search Doc..."/></div><img class="swiftype-row-hider hidden-md hidden-lg" src="/images/icons/drawer-toggle-active-fcbef12a.png"/></form></div></div><div class="mobile-left-menu-toggler hidden-md hidden-lg"></div></div></div></div><div id="page" class="container-fl
uid"><div class="row"><div id="left-menu-wrapper" class="col-md-3"><nav id="nav-main"><ul><li class="level-1"><a class="expandible" href="/"><span>Apache PredictionIO (incubating) Documentation</span></a><ul><li class="level-2"><a class="final" href="/"><span>Welcome to Apache PredictionIO (incubating)</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Getting Started</span></a><ul><li class="level-2"><a class="final" href="/start/"><span>A Quick Intro</span></a></li><li class="level-2"><a class="final" href="/install/"><span>Installing Apache PredictionIO (incubating)</span></a></li><li class="level-2"><a class="final" href="/start/download/"><span>Downloading an Engine Template</span></a></li><li class="level-2"><a class="final" href="/start/deploy/"><span>Deploying Your First Engine</span></a></li><li class="level-2"><a class="final" href="/start/customize/"><span>Customizing the Engine</span></a></li></ul></li><li class="level-1"><a class="expandib
le" href="#"><span>Integrating with Your App</span></a><ul><li class="level-2"><a class="final" href="/appintegration/"><span>App Integration Overview</span></a></li><li class="level-2"><a class="expandible" href="/sdk/"><span>List of SDKs</span></a><ul><li class="level-3"><a class="final" href="/sdk/java/"><span>Java & Android SDK</span></a></li><li class="level-3"><a class="final" href="/sdk/php/"><span>PHP SDK</span></a></li><li class="level-3"><a class="final" href="/sdk/python/"><span>Python SDK</span></a></li><li class="level-3"><a class="final" href="/sdk/ruby/"><span>Ruby SDK</span></a></li><li class="level-3"><a class="final" href="/sdk/community/"><span>Community Powered SDKs</span></a></li></ul></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Deploying an Engine</span></a><ul><li class="level-2"><a class="final" href="/deploy/"><span>Deploying as a Web Service</span></a></li><li class="level-2"><a class="final" href="/cli/#engine-commands"><span>Eng
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rview</span></a></li><li class="level-2"><a class="final" href="/cli/#event-server-commands"><span>Event Server Command-line Interface</span></a></li><li class="level-2"><a class="final" href="/datacollection/eventapi/"><span>Collecting Data with REST/SDKs</span></a></li><li class="level-2"><a class="final" href="/datacollection/eventmodel/"><span>Events Modeling</span></a></li><li class="level-2"><a class="final" href="/datacollection/webhooks/"><span>Unifying Multichannel Data with Webhooks</span></a></li><li class="level-2"><a class="final" href="/datacollection/channel/"><span>Channel</span></a></li><li class="level-2"><a class="final" href="/datacollection/batchimport/"><span>Importing Data in Batch</span></a></li><li class="level-2"><a class="final" href="/datacollection/analytics/"><span>Using Analytics Tools</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Choosing an Algorithm(s)</span></a><ul><li class="level-2"><a class="final" href="/algo
rithm/"><span>Built-in Algorithm Libraries</span></a></li><li class="level-2"><a class="final" href="/algorithm/switch/"><span>Switching to Another Algorithm</span></a></li><li class="level-2"><a class="final" href="/algorithm/multiple/"><span>Combining Multiple Algorithms</span></a></li><li class="level-2"><a class="final" href="/algorithm/custom/"><span>Adding Your Own Algorithms</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>ML Tuning and Evaluation</span></a><ul><li class="level-2"><a class="final" href="/evaluation/"><span>Overview</span></a></li><li class="level-2"><a class="final" href="/evaluation/paramtuning/"><span>Hyperparameter Tuning</span></a></li><li class="level-2"><a class="final" href="/evaluation/evaluationdashboard/"><span>Evaluation Dashboard</span></a></li><li class="level-2"><a class="final" href="/evaluation/metricchoose/"><span>Choosing Evaluation Metrics</span></a></li><li class="level-2"><a class="final" href="/evaluation
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n></a></li><li class="level-2"><a class="final" href="/support/"><span>Community Support</span></a></li><li class="level-2"><a class="final" href="/support/#enterprise-support"><span>Enterprise Support</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Resources</span></a><ul><li class="level-2"><a class="final" href="/resources/intellij/"><span>Developing Engines with IntelliJ IDEA</span></a></li><li class="level-2"><a class="final" href="/resources/upgrade/"><span>Upgrade Instructions</span></a></li><li class="level-2"><a class="final" href="/resources/glossary/"><span>Glossary</span></a></li></ul></li></ul></nav></div><div class="col-md-9 col-sm-12"><div class="content-header hidden-md hidden-lg"><div id="page-title"><h1>Level 4.1</h1></div></div><div id="table-of-content-wrapper"><h5>On this page</h5><aside id="table-of-contents"><ul> <li> <a href="#level-4-1">Level 4.1</a> </li> </ul> </aside><hr/><a id="edit-page-link" href="https://github.com/ap
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uid"><div class="row"><div id="left-menu-wrapper" class="col-md-3"><nav id="nav-main"><ul><li class="level-1"><a class="expandible" href="/"><span>Apache PredictionIO (incubating) Documentation</span></a><ul><li class="level-2"><a class="final" href="/"><span>Welcome to Apache PredictionIO (incubating)</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Getting Started</span></a><ul><li class="level-2"><a class="final" href="/start/"><span>A Quick Intro</span></a></li><li class="level-2"><a class="final" href="/install/"><span>Installing Apache PredictionIO (incubating)</span></a></li><li class="level-2"><a class="final" href="/start/download/"><span>Downloading an Engine Template</span></a></li><li class="level-2"><a class="final" href="/start/deploy/"><span>Deploying Your First Engine</span></a></li><li class="level-2"><a class="final" href="/start/customize/"><span>Customizing the Engine</span></a></li></ul></li><li class="level-1"><a class="expandib
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rithm/"><span>Built-in Algorithm Libraries</span></a></li><li class="level-2"><a class="final" href="/algorithm/switch/"><span>Switching to Another Algorithm</span></a></li><li class="level-2"><a class="final" href="/algorithm/multiple/"><span>Combining Multiple Algorithms</span></a></li><li class="level-2"><a class="final" href="/algorithm/custom/"><span>Adding Your Own Algorithms</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>ML Tuning and Evaluation</span></a><ul><li class="level-2"><a class="final" href="/evaluation/"><span>Overview</span></a></li><li class="level-2"><a class="final" href="/evaluation/paramtuning/"><span>Hyperparameter Tuning</span></a></li><li class="level-2"><a class="final" href="/evaluation/evaluationdashboard/"><span>Evaluation Dashboard</span></a></li><li class="level-2"><a class="final" href="/evaluation/metricchoose/"><span>Choosing Evaluation Metrics</span></a></li><li class="level-2"><a class="final" href="/evaluation
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<div class="row"><div class="col-md-9 col-sm-11 col-xs-11"><div class="hidden-md hidden-lg" id="mobile-page-heading-wrapper"><p>PredictionIO Docs</p><h4>Level 4.3</h4></div><h4 class="hidden-sm hidden-xs">PredictionIO Docs</h4></div><div class="col-md-3 col-sm-1 col-xs-1 hidden-md hidden-lg"><img id="left-menu-indicator" src="/images/icons/down-arrow-dfe9f7fe.png"/></div><div class="col-md-3 col-sm-12 col-xs-12 swiftype-wrapper"><div class="swiftype"><form class="search-form"><img class="search-box-toggler hidden-xs hidden-sm" src="/images/icons/search-glass-704bd4ff.png"/><div class="search-box"><img src="/images/icons/search-glass-704bd4ff.png"/><input type="text" id="st-search-input" class="st-search-input" placeholder="Search Doc..."/></div><img class="swiftype-row-hider hidden-md hidden-lg" src="/images/icons/drawer-toggle-active-fcbef12a.png"/></form></div></div><div class="mobile-left-menu-toggler hidden-md hidden-lg"></div></div></div></div><div id="page" class="container-fl
uid"><div class="row"><div id="left-menu-wrapper" class="col-md-3"><nav id="nav-main"><ul><li class="level-1"><a class="expandible" href="/"><span>Apache PredictionIO (incubating) Documentation</span></a><ul><li class="level-2"><a class="final" href="/"><span>Welcome to Apache PredictionIO (incubating)</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Getting Started</span></a><ul><li class="level-2"><a class="final" href="/start/"><span>A Quick Intro</span></a></li><li class="level-2"><a class="final" href="/install/"><span>Installing Apache PredictionIO (incubating)</span></a></li><li class="level-2"><a class="final" href="/start/download/"><span>Downloading an Engine Template</span></a></li><li class="level-2"><a class="final" href="/start/deploy/"><span>Deploying Your First Engine</span></a></li><li class="level-2"><a class="final" href="/start/customize/"><span>Customizing the Engine</span></a></li></ul></li><li class="level-1"><a class="expandib
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rithm/"><span>Built-in Algorithm Libraries</span></a></li><li class="level-2"><a class="final" href="/algorithm/switch/"><span>Switching to Another Algorithm</span></a></li><li class="level-2"><a class="final" href="/algorithm/multiple/"><span>Combining Multiple Algorithms</span></a></li><li class="level-2"><a class="final" href="/algorithm/custom/"><span>Adding Your Own Algorithms</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>ML Tuning and Evaluation</span></a><ul><li class="level-2"><a class="final" href="/evaluation/"><span>Overview</span></a></li><li class="level-2"><a class="final" href="/evaluation/paramtuning/"><span>Hyperparameter Tuning</span></a></li><li class="level-2"><a class="final" href="/evaluation/evaluationdashboard/"><span>Evaluation Dashboard</span></a></li><li class="level-2"><a class="final" href="/evaluation/metricchoose/"><span>Choosing Evaluation Metrics</span></a></li><li class="level-2"><a class="final" href="/evaluation
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pan>FAQs</span></a></li><li class="level-2"><a class="final" href="/support/"><span>Community Support</span></a></li><li class="level-2"><a class="final" href="/support/#enterprise-support"><span>Enterprise Support</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Resources</span></a><ul><li class="level-2"><a class="final" href="/resources/intellij/"><span>Developing Engines with IntelliJ IDEA</span></a></li><li class="level-2"><a class="final" href="/resources/upgrade/"><span>Upgrade Instructions</span></a></li><li class="level-2"><a class="final" href="/resources/glossary/"><span>Glossary</span></a></li></ul></li></ul></nav></div><div class="col-md-9 col-sm-12"><div class="content-header hidden-md hidden-lg"><div id="breadcrumbs" class="hidden-sm hidden xs"><ul><li><a href="#">Collecting and Analyzing Data</a><span class="spacer">></span></li><li><span class="last">Events Modeling</span></li></ul></div><div id="page-title"><h1>Events Modeling</h
1></div></div><div id="table-of-content-wrapper"><h5>On this page</h5><aside id="table-of-contents"><ul> <li> <a href="#1-generic-events-performed-by-an-entity">1. Generic events performed by an entity</a> </li> <li> <a href="#2-special-events-for-recording-changes-of-an-entity-s-properties">2. Special events for recording changes of an entity's properties</a> </li> <li> <a href="#3-batch-events-to-the-eventserver">3. Batch Events to the EventServer</a> </li> </ul> </aside><hr/><a id="edit-page-link" href="https://github.com/apache/incubator-predictionio/tree/livedoc/docs/manual/source/datacollection/eventmodel.html.md.erb"><img src="/images/icons/edit-pencil-d6c1bb3d.png"/>Edit this page</a></div><div class="content-header hidden-sm hidden-xs"><div id="breadcrumbs" class="hidden-sm hidden xs"><ul><li><a href="#">Collecting and Analyzing Data</a><span class="spacer">></span></li><li><span class="last">Events Modeling</span></li></ul></div><div id="page-title"><h1>Events Modeling<
/h1></div></div><div class="content"><p>This section explains how to model your application data as events.</p><p><strong>Entity</strong>: it's the real world object involved in the events. The entity may perform the events, or interact with other entity (which became <code>targetEntity</code> in an event).</p><p>For example, your application may have users and some items which the user can interact with. Then you can model them as two entity types: <strong>user</strong> and <strong>item</strong> and the entityId can uniquely identify the entity within each entityType (e.g. user with ID 1, item with ID 1).</p><p>An entity may peform some events (e.g user 1 does something), and entity may have properties associated with it (e.g. user may have gender, age, email etc). Hence, <strong>events</strong> involve <strong>entities</strong> and there are two types of events, respectively:</p> <ol> <li>Generic events performed by an entity.</li> <li>Special events for recording changes of a
n entity's properties</li> <li>Batch events</li> </ol> <p>They are explained in details below.</p><h2 id='1.-generic-events-performed-by-an-entity' class='header-anchors'>1. Generic events performed by an entity</h2><p>Whenever the entity performs an action, you can describe such event as <code>entity "verb" targetEntity with "some extra information"</code>. The <em>"targetEntity"</em> and <em>"some extra information"</em> can be optional. The <em>"verb"</em> can be used as the name of the <em>"event"</em>. The <em>"some extra information"</em> can be recorded as <code>properties</code> of the event.</p><p>The following are some simple examples:</p> <ul> <li>user-1 signs-up</li> </ul> <div class="highlight json"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1
+2
+3
+4
+5</pre></td><td class="code"><pre><span class="p">{</span><span class="w">
+ </span><span class="s2">"event"</span><span class="w"> </span><span class="p">:</span><span class="w"> </span><span class="s2">"sign-up"</span><span class="p">,</span><span class="w">
+ </span><span class="s2">"entityType"</span><span class="w"> </span><span class="p">:</span><span class="w"> </span><span class="s2">"user"</span><span class="p">,</span><span class="w">
+ </span><span class="s2">"entityId"</span><span class="w"> </span><span class="p">:</span><span class="w"> </span><span class="s2">"1"</span><span class="w">
+</span><span class="p">}</span><span class="w">
+</span></pre></td></tr></tbody></table> </div> <ul> <li>user-1 views item-1 <em>(with targetEntity)</em></li> </ul> <div class="highlight json"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1
+2
+3
+4
+5
+6
+7</pre></td><td class="code"><pre><span class="p">{</span><span class="w">
+ </span><span class="s2">"event"</span><span class="w"> </span><span class="p">:</span><span class="w"> </span><span class="s2">"view"</span><span class="p">,</span><span class="w">
+ </span><span class="s2">"entityType"</span><span class="w"> </span><span class="p">:</span><span class="w"> </span><span class="s2">"user"</span><span class="p">,</span><span class="w">
+ </span><span class="s2">"entityId"</span><span class="w"> </span><span class="p">:</span><span class="w"> </span><span class="s2">"1"</span><span class="p">,</span><span class="w">
+ </span><span class="s2">"targetEntityType"</span><span class="w"> </span><span class="p">:</span><span class="w"> </span><span class="s2">"item"</span><span class="p">,</span><span class="w">
+ </span><span class="s2">"targetEntityId"</span><span class="w"> </span><span class="p">:</span><span class="w"> </span><span class="s2">"1"</span><span class="w">
+</span><span class="p">}</span><span class="w">
+</span></pre></td></tr></tbody></table> </div> <ul> <li>user-1 rates item-1 with rating of 4 stars <em>(with targetEntity and properties)</em></li> </ul> <div class="highlight json"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1
+2
+3
+4
+5
+6
+7
+8
+9
+10</pre></td><td class="code"><pre><span class="p">{</span><span class="w">
+ </span><span class="s2">"event"</span><span class="w"> </span><span class="p">:</span><span class="w"> </span><span class="s2">"rate"</span><span class="p">,</span><span class="w">
+ </span><span class="s2">"entityType"</span><span class="w"> </span><span class="p">:</span><span class="w"> </span><span class="s2">"user"</span><span class="p">,</span><span class="w">
+ </span><span class="s2">"entityId"</span><span class="w"> </span><span class="p">:</span><span class="w"> </span><span class="s2">"1"</span><span class="p">,</span><span class="w">
+ </span><span class="s2">"targetEntityType"</span><span class="w"> </span><span class="p">:</span><span class="w"> </span><span class="s2">"item"</span><span class="p">,</span><span class="w">
+ </span><span class="s2">"targetEntityId"</span><span class="w"> </span><span class="p">:</span><span class="w"> </span><span class="s2">"1"</span><span class="p">,</span><span class="w">
+ </span><span class="s2">"properties"</span><span class="w"> </span><span class="p">:</span><span class="w"> </span><span class="p">{</span><span class="w">
+ </span><span class="s2">"rating"</span><span class="w"> </span><span class="p">:</span><span class="w"> </span><span class="mi">4</span><span class="w">
+ </span><span class="p">}</span><span class="w">
+</span><span class="p">}</span><span class="w">
+</span></pre></td></tr></tbody></table> </div> <h2 id='2.-special-events-for-recording-changes-of-an-entity's-properties' class='header-anchors'>2. Special events for recording changes of an entity's properties</h2><p>The generic events described above are used to record general actions performed by the entity. However, an entity may have properties (or attributes) associated with it. Morever, the properties of the entity may change over time (for example, user may have new address, item may have new categories). In order to record such changes of an entity's properties. Special events <code>$set</code> , <code>$unset</code> and <code>$delete</code> are introduced.</p><p>The following special events are reserved for updating entities and their properties:</p> <ul> <li> <code>"$set"</code> event: Set properties of an entity (also implicitly create the entity). To change properties of entity, you simply set the corresponding properties with value again. The <code
>$set</code> events should be created only when: <ul> <li> The entity is <em>first</em> created (or re-create after <code>$delete</code> event), or</li> <li> Set the entity's existing or new properties to new values (For example, user updates his email, user adds a phone number, item has a updated categories)</li> </ul></li> <li> <code>"$unset"</code> event: Unset properties of an entity. It means treating the specified properties as not existing anymore. Note that the field <code>properties</code> cannot be empty for <code>$unset</code> event.</li> <li> <code>"$delete"</code> event: delete the entity.</li> </ul> <p>There is no <code>targetEntityId</code> for these special events.</p><p>For example, setting entity <code>user-1</code>'s properties <code>birthday</code> and <code>address</code>:</p><div class="highlight json"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1
+2
+3
+4
+5
+6
+7
+8
+9</pre></td><td class="code"><pre><span class="p">{</span><span class="w">
+ </span><span class="s2">"event"</span><span class="w"> </span><span class="p">:</span><span class="w"> </span><span class="s2">"$set"</span><span class="p">,</span><span class="w">
+ </span><span class="s2">"entityType"</span><span class="w"> </span><span class="p">:</span><span class="w"> </span><span class="s2">"user"</span><span class="p">,</span><span class="w">
+ </span><span class="s2">"entityId"</span><span class="w"> </span><span class="p">:</span><span class="w"> </span><span class="s2">"1"</span><span class="p">,</span><span class="w">
+ </span><span class="s2">"properties"</span><span class="w"> </span><span class="p">:</span><span class="w"> </span><span class="p">{</span><span class="w">
+ </span><span class="s2">"birthday"</span><span class="w"> </span><span class="p">:</span><span class="w"> </span><span class="s2">"1984-10-11"</span><span class="p">,</span><span class="w">
+ </span><span class="s2">"address"</span><span class="w"> </span><span class="p">:</span><span class="w"> </span><span class="s2">"1234 Street, San Francisco, CA 94107"</span><span class="w">
+ </span><span class="p">}</span><span class="w">
+</span><span class="p">}</span><span class="w">
+</span></pre></td></tr></tbody></table> </div> <p><strong>Note</strong> that the properties values of the entity will be aggregated based on these special events and the eventTime. The state of the entity is different depending on the time you are looking at the data. In engine's DataSource, you can use <a href="https://docs.prediction.io/api/current/#io.prediction.data.store.PEventStore$">PEventStore.aggregateProperties() API</a> to retrieve the state of entity's properties (based on time).</p><div class="alert-message note"><p>Although it doesn't hurt to import duplicated special events for an entity (exactly same properties) into event server (it just means that the entity changes to the same state as before and new duplicated event provides no new information about the user), it could waste storage space.</p></div><p>To demonstrate the concept of these special events, we are going to import a sequence of events and see how it affects the retrieved entitiy's prope
rties.</p><p>Assuming you have created the App (named "MyTestApp") for testing and Event Server is started.</p><h4 id='event-1' class='header-anchors'>Event 1</h4><p>For example, on <code>2014-09-09T...</code>, a user with ID "2" is newly added in your application. Also, this user has properties a = 3 and b = 4. To record such event, we can create a <code>$set</code> event for the user.</p><p>for convenience, assign the ACCESS_KEY of your test app to the shell variable <code>ACCESS_KEY</code> and run following curl command to import the event:</p><div class="highlight shell"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1
+2
+3
+4
+5
+6
+7
+8
+9
+10
+11
+12
+13
+14</pre></td><td class="code"><pre><span class="gp">$ </span><span class="nv">ACCESS_KEY</span><span class="o">=</span><span class="s2">"<YOUR_ACCESS_KEY>"</span>
+
+<span class="gp">$ </span>curl -i -X POST http://localhost:7070/events.json?accessKey<span class="o">=</span><span class="nv">$ACCESS_KEY</span> <span class="se">\</span>
+-H <span class="s2">"Content-Type: application/json"</span> <span class="se">\</span>
+-d <span class="s1">'{
+ "event" : "$set",
+ "entityType" : "user",
+ "entityId" : "2",
+ "properties" : {
+ "a" : 3,
+ "b" : 4
+ },
+ "eventTime" : "2014-09-09T16:17:42.937-08:00"
+}'</span>
+</pre></td></tr></tbody></table> </div> <p>You should see something like the following, meaning the events are imported successfully.</p><div class="highlight shell"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1
+2
+3
+4
+5
+6
+7</pre></td><td class="code"><pre>HTTP/1.1 201 Created
+Server: spray-can/1.3.2
+Date: Tue, 02 Jun 2015 23:13:58 GMT
+Content-Type: application/json; <span class="nv">charset</span><span class="o">=</span>UTF-8
+Content-Length: 57
+
+<span class="o">{</span><span class="s2">"eventId"</span>:<span class="s2">"PVjOIP6AJ5PgsiGQW6pgswAAAUhc7EwZpCfSj5bS5yg"</span><span class="o">}</span>a
+</pre></td></tr></tbody></table> </div> <p>After this eventTime, user-2 is created and has properties of a = 3 and b = 4.</p><h4 id='event-2' class='header-anchors'>Event 2</h4><p>Then, on <code>2014-09-10T...</code>, let's say the user has updated the properties b = 5 and c = 6. To record such propertiy change, create another <code>$set</code> event. Run the following command:</p><div class="highlight shell"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1
+2
+3
+4
+5
+6
+7
+8
+9
+10
+11
+12</pre></td><td class="code"><pre><span class="gp">$ </span>curl -i -X POST http://localhost:7070/events.json?accessKey<span class="o">=</span><span class="nv">$ACCESS_KEY</span> <span class="se">\</span>
+-H <span class="s2">"Content-Type: application/json"</span> <span class="se">\</span>
+-d <span class="s1">'{
+ "event" : "$set",
+ "entityType" : "user",
+ "entityId" : "2",
+ "properties" : {
+ "b" : 5,
+ "c" : 6
+ },
+ "eventTime" : "2014-09-10T13:12:04.937-08:00"
+}'</span>
+</pre></td></tr></tbody></table> </div> <p>After this eventTime, user-2 has properties of a = 3, b = 5 and c = 6. Note that property <code>b</code> is updated with latest value.</p><h4 id='event-3' class='header-anchors'>Event 3</h4><p>Then, let's say on <code>2014-09-11T...</code>, the user's properties 'b' is removed for some reasons. To record such event, create <code>$unset</code> event for user-2 with properties b:</p><div class="highlight shell"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1
+2
+3
+4
+5
+6
+7
+8
+9
+10
+11</pre></td><td class="code"><pre><span class="gp">$ </span>curl -i -X POST http://localhost:7070/events.json?accessKey<span class="o">=</span><span class="nv">$ACCESS_KEY</span> <span class="se">\</span>
+-H <span class="s2">"Content-Type: application/json"</span> <span class="se">\</span>
+-d <span class="s1">'{
+ "event" : "$unset",
+ "entityType" : "user",
+ "entityId" : "2",
+ "properties" : {
+ "b" : null
+ },
+ "eventTime" : "2014-09-11T14:17:42.456-08:00"
+}'</span>
+</pre></td></tr></tbody></table> </div> <p>After this eventTime, user-2 has properties of a = 3, and c = 6. Note that property <code>b</code> is removed.</p><h4 id='event-4' class='header-anchors'>Event 4</h4><p>Then, on <code>2014-09-12T...</code>, the user is removed from the application data. To record such event, create <code>$delete</code> event:</p><div class="highlight shell"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1
+2
+3
+4
+5
+6
+7
+8</pre></td><td class="code"><pre><span class="gp">$ </span>curl -i -X POST http://localhost:7070/events.json?accessKey<span class="o">=</span><span class="nv">$ACCESS_KEY</span> <span class="se">\</span>
+-H <span class="s2">"Content-Type: application/json"</span> <span class="se">\</span>
+-d <span class="s1">'{
+ "event" : "$delete",
+ "entityType" : "user",
+ "entityId" : "2",
+ "eventTime" : "2014-09-12T16:13:41.452-08:00"
+}'</span>
+</pre></td></tr></tbody></table> </div> <p>After this eventTime, user-2 is removed.</p><h4 id='event-5' class='header-anchors'>Event 5</h4><p>Then, on <code>2014-09-13T...</code>, let's say we want to add back the user-2 into the application again for some reasons. To record such event, create <code>$set</code> event for user-2 with empty properties:</p><div class="highlight shell"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1
+2
+3
+4
+5
+6
+7
+8</pre></td><td class="code"><pre><span class="gp">$ </span>curl -i -X POST http://localhost:7070/events.json?accessKey<span class="o">=</span><span class="nv">$ACCESS_KEY</span> <span class="se">\</span>
+-H <span class="s2">"Content-Type: application/json"</span> <span class="se">\</span>
+-d <span class="s1">'{
+ "event" : "$set",
+ "entityType" : "user",
+ "entityId" : "2",
+ "eventTime" : "2014-09-13T16:17:42.143-08:00"
+}'</span>
+</pre></td></tr></tbody></table> </div> <p>After this eventTime, user-2 is created again with empty properties.</p><p>Note that all above events are recorded in Event Store. Let's query Event Server and see if these events are imported.</p><p>Go to following URL with your browser:</p><p><code>http://localhost:7070/events.json?accessKey=<YOUR_ACCESS_KEY></code></p><p>or run the following command in terminal:</p><div class="highlight shell"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1</pre></td><td class="code"><pre><span class="gp">$ </span>curl -i -X GET <span class="s2">"http://localhost:7070/events.json?accessKey=</span><span class="nv">$ACCESS_KEY</span><span class="s2">"</span>
+</pre></td></tr></tbody></table> </div> <div class="alert-message note"><p>Note that you should quote the entire URL by using single or double quotes when you run the curl command.</p></div><p>You should see all events being created for this user-2.</p><p>Now, let's retrieve the user-2's properties using the <a href="https://docs.prediction.io/api/current/#io.prediction.data.store.PEventStore$">PEventStore API</a>.</p><p>First, start <code>pio-shell</code> by running:</p><div class="highlight shell"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1</pre></td><td class="code"><pre><span class="gp">$ </span>pio-shell --with-spark
+</pre></td></tr></tbody></table> </div> <p>You should see the following output and shell prompt:</p><div class="highlight shell"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1
+2
+3
+4
+5
+6</pre></td><td class="code"><pre>15/06/02 16:01:54 INFO SparkILoop: Created spark context..
+Spark context available as sc.
+15/06/02 16:01:54 INFO SparkILoop: Created sql context <span class="o">(</span>with Hive support<span class="o">)</span>..
+SQL context available as sqlContext.
+
+scala>
+</pre></td></tr></tbody></table> </div> <p>Run the following code in PIO shell (Replace <code>"MyTestApp"</code> with your app name):</p><div class="highlight scala"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1
+2
+3</pre></td><td class="code"><pre><span class="n">scala</span><span class="o">></span> <span class="k">val</span> <span class="n">appName</span><span class="o">=</span><span class="s">"MyTestApp"</span>
+<span class="n">scala</span><span class="o">></span> <span class="k">import</span> <span class="nn">io.prediction.data.store.PEventStore</span>
+<span class="n">scala</span><span class="o">></span> <span class="nc">PEventStore</span><span class="o">.</span><span class="n">aggregateProperties</span><span class="o">(</span><span class="n">appName</span><span class="k">=</span><span class="n">appName</span><span class="o">,</span> <span class="n">entityType</span><span class="o">=</span><span class="s">"user"</span><span class="o">)(</span><span class="n">sc</span><span class="o">).</span><span class="n">collect</span><span class="o">()</span>
+</pre></td></tr></tbody></table> </div> <p>This command is using PEventStore to aggregate the user properties as a Map of user Id and the PropertyMap. <code>collect()</code> will return the data as array. You should see the following output at the end, which indicates there is user id 2 with empty properties because that's the state of user 2 with all imported events taken into account.</p><div class="highlight shell"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1
+2</pre></td><td class="code"><pre>res0: Array[<span class="o">(</span>String, io.prediction.data.storage.PropertyMap<span class="o">)]</span> <span class="o">=</span>
+Array<span class="o">((</span>2,PropertyMap<span class="o">(</span>Map<span class="o">()</span>, 2014-09-09T16:17:42.937-08:00, 2014-09-13T16:17:42.143-08:00<span class="o">)))</span>
+</pre></td></tr></tbody></table> </div> <p>Let's say we want to retrieve the state of user 2 properties with only events 1 and event 2 imported. To do that, we can specify the untilTime (aggregate the user properties with events up to the specified time) in the API.</p><p>Run the following in the pio-shell. the untilTime is set to DateTime(2014, 9, 11, 0, 0) which is the time right before event 3.</p><div class="highlight shell"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1
+2</pre></td><td class="code"><pre><span class="gp">scala> </span>import org.joda.time.DateTime
+<span class="gp">scala> </span>PEventStore.aggregateProperties<span class="o">(</span><span class="nv">appName</span><span class="o">=</span>appName, <span class="nv">entityType</span><span class="o">=</span><span class="s2">"user"</span>, <span class="nv">untilTime</span><span class="o">=</span>Some<span class="o">(</span>new DateTime<span class="o">(</span>2014, 9, 11, 0, 0<span class="o">)))(</span>sc<span class="o">)</span>.collect<span class="o">()</span>
+</pre></td></tr></tbody></table> </div> <p>You should see the following ouptut and the aggregated properties matches what we expected as described earlier (right befor event 3): user-2 has properties of a = 3, b = 5 and c = 6.</p><div class="highlight shell"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1
+2</pre></td><td class="code"><pre>res2: Array[<span class="o">(</span>String, io.prediction.data.storage.PropertyMap<span class="o">)]</span> <span class="o">=</span>
+Array<span class="o">((</span>2,PropertyMap<span class="o">(</span>Map<span class="o">(</span>b -> JInt<span class="o">(</span>5<span class="o">)</span>, a -> JInt<span class="o">(</span>3<span class="o">)</span>, c -> JInt<span class="o">(</span>6<span class="o">))</span>, 2014-09-09T16:17:42.937-08:00, 2014-09-10T13:12:04.937-08:00<span class="o">))</span>
+</pre></td></tr></tbody></table> </div> <p>As you have seen in the example above, the state of user-2 is different depending on the available events or the time you are looking at the data. Recording events in logging fashioned allows us to re-construct the state the entity according to the time.</p><h2 id='3.-batch-events-to-the-eventserver' class='header-anchors'>3. Batch Events to the EventServer</h2><p>Using a different REST address on the usual EventServer port, as of PredictionIO 0.9.5 you can send batches of up to 50 events as a time. The format is as described above but the JSON payload is packaged as an array of Event objects.</p><p><strong>Response:</strong></p> <ul> <li>Status: <ul> <li>200 on success if we can return an array data in the response even when some events fail (e.g. because of ill-format). Client needs to check individual dictionary to verify all events were successfully created.</li> <li>400 otherwise. Perhaps exceeded 50 events?</li> </ul></li> <li>Data: a
n array of dictionaries each of which contains either following keys <ul> <li>\u201cstatus\u201d: 201 if the event was successfully created; otherwise, 400.</li> <li>"eventID": the value is the eventID if the event is successfully created and</li> <li>"message": the error message string if any error occurs during creation</li> </ul></li> </ul> <p>The order in the response array is corresponding to the order of the request array. However, the events might be imported in any order.</p><h3 id='sample-request:' class='header-anchors'>Sample Request:</h3><div class="highlight shell"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1
+2
+3
+4
+5
+6
+7
+8
+9
+10
+11
+12
+13
+14
+15
+16
+17
+18
+19
+20
+21
+22
+23
+24</pre></td><td class="code"><pre>curl -i -X POST http://localhost:7070/batch/events.json?accessKey<span class="o">=</span>...
+-H <span class="s2">"Content-Type: application/json"</span> -d \u2018 <span class="se">\</span>
+<span class="o">[</span>
+ <span class="o">{</span>
+ <span class="s2">"event"</span>: <span class="s2">"</span><span class="nv">$create</span><span class="s2">"</span>,
+ <span class="s2">"entityType"</span>: <span class="s2">"user"</span>,
+ <span class="s2">"entityId"</span>: <span class="s2">"uid"</span>,
+ <span class="s2">"properties"</span>: <span class="o">{</span>
+ ...
+ <span class="o">}</span>
+ <span class="o">}</span>,
+ <span class="o">{</span>
+ <span class="s2">"event"</span>: <span class="s2">"like"</span>,
+ <span class="s2">"entityType"</span>: <span class="s2">"user"</span>,
+ <span class="s2">"entityId"</span>: <span class="s2">"uid"</span>,
+ <span class="s2">"targetEntityType"</span>: <span class="s2">"item"</span>,
+ <span class="s2">"targetEntityId"</span>: <span class="s2">"iid"</span>,
+ <span class="s2">"properties"</span>: <span class="o">{</span>
+ ...
+ <span class="o">}</span>
+ <span class="s2">"eventTime"</span>: <span class="s2">"2004-12-13T21:39:45.618-07:00"</span>
+ <span class="o">}</span>,
+ ...
+<span class="o">]</span>\u2018
+</pre></td></tr></tbody></table> </div> <h3 id='sample-response:' class='header-anchors'>Sample Response:</h3><div class="highlight shell"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1
+2
+3
+4
+5
+6
+7
+8
+9
+10
+11
+12
+13
+14
+15
+16
+17
+18
+19
+20
+21
+22</pre></td><td class="code"><pre>HTTP/1.1 200 Successful
+Server: spray-can/1.2.1
+Date: Wed, 10 Sep 2014 22:51:33 GMT
+Content-Type: application/json; <span class="nv">charset</span><span class="o">=</span>UTF-8
+Content-Length: 41
+<span class="o">[</span>
+ <span class="o">{</span><span class="s2">"eventId"</span>:<span class="s2">"AAAABAAAAQDP3-jSlTMGVu0waj8"</span><span class="o">}</span>,
+ <span class="o">{</span>
+ <span class="s2">"status"</span>: 201,
+ <span class="s2">"eventId"</span>: <span class="s2">"AAAABAAAAQDP3-jSlTMGVu0waj8"</span>
+ <span class="o">}</span>,
+ <span class="o">{</span>
+ <span class="s2">"status"</span>: 201,
+ <span class="s2">"eventId"</span>:<span class="s2">"AAAABAAAAQDP3-jSlTMGVu0waj9"</span>
+ <span class="o">}</span>,
+ \u2026
+ <span class="o">{</span>
+ <span class="s2">"status"</span>: 400,
+ <span class="s2">"message"</span>:<span class="s2">"Required entityType is missing\u201d
+ },
+ \u2026
+]
+</span></pre></td></tr></tbody></table> </div> <p>Notice that each subrequest receives a status responce. The limit of 50 events per batch requests is in line with Facebook, Mixpanel, SegmentIO and other event syncs that accept batches.</p></div></div></div></div><footer><div class="container"><div class="seperator"></div><div class="row"><div class="col-md-4 col-md-push-8 col-xs-12"><div class="subscription-form-wrapper"><h4>Subscribe to our Newsletter</h4><form class="ajax-form" id="subscribe-form" method="POST" action="https://script.google.com/macros/s/AKfycbwhzeKCQJjQ52eVAqNT_vcklH07OITUO7wzOMDXvK6EGAWgaZgF/exec"><input class="required underlined-input" type="email" placeholder="Your email address" name="subscription_email" id="subscription_email"/><input class="pill-button" value="SUBSCRIBE" type="submit" data-state-normal="SUBSCRIBE" data-state-sucess="SUBSCRIBED!" data-state-loading="SENDING..." onclick="t($('#subscription_email').val());"/><p class="result"></p></form></div
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<div class="row"><div class="col-md-9 col-sm-11 col-xs-11"><div class="hidden-md hidden-lg" id="mobile-page-heading-wrapper"><p>PredictionIO Docs</p><h4>Event Server Overview</h4></div><h4 class="hidden-sm hidden-xs">PredictionIO Docs</h4></div><div class="col-md-3 col-sm-1 col-xs-1 hidden-md hidden-lg"><img id="left-menu-indicator" src="/images/icons/down-arrow-dfe9f7fe.png"/></div><div class="col-md-3 col-sm-12 col-xs-12 swiftype-wrapper"><div class="swiftype"><form class="search-form"><img class="search-box-toggler hidden-xs hidden-sm" src="/images/icons/search-glass-704bd4ff.png"/><div class="search-box"><img src="/images/icons/search-glass-704bd4ff.png"/><input type="text" id="st-search-input" class="st-search-input" placeholder="Search Doc..."/></div><img class="swiftype-row-hider hidden-md hidden-lg" src="/images/icons/drawer-toggle-active-fcbef12a.png"/></form></div></div><div class="mobile-left-menu-toggler hidden-md hidden-lg"></div></div></div></div><div id="page" class="
container-fluid"><div class="row"><div id="left-menu-wrapper" class="col-md-3"><nav id="nav-main"><ul><li class="level-1"><a class="expandible" href="/"><span>Apache PredictionIO (incubating) Documentation</span></a><ul><li class="level-2"><a class="final" href="/"><span>Welcome to Apache PredictionIO (incubating)</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Getting Started</span></a><ul><li class="level-2"><a class="final" href="/start/"><span>A Quick Intro</span></a></li><li class="level-2"><a class="final" href="/install/"><span>Installing Apache PredictionIO (incubating)</span></a></li><li class="level-2"><a class="final" href="/start/download/"><span>Downloading an Engine Template</span></a></li><li class="level-2"><a class="final" href="/start/deploy/"><span>Deploying Your First Engine</span></a></li><li class="level-2"><a class="final" href="/start/customize/"><span>Customizing the Engine</span></a></li></ul></li><li class="level-1"><a cla
ss="expandible" href="#"><span>Integrating with Your App</span></a><ul><li class="level-2"><a class="final" href="/appintegration/"><span>App Integration Overview</span></a></li><li class="level-2"><a class="expandible" href="/sdk/"><span>List of SDKs</span></a><ul><li class="level-3"><a class="final" href="/sdk/java/"><span>Java & Android SDK</span></a></li><li class="level-3"><a class="final" href="/sdk/php/"><span>PHP SDK</span></a></li><li class="level-3"><a class="final" href="/sdk/python/"><span>Python SDK</span></a></li><li class="level-3"><a class="final" href="/sdk/ruby/"><span>Ruby SDK</span></a></li><li class="level-3"><a class="final" href="/sdk/community/"><span>Community Powered SDKs</span></a></li></ul></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Deploying an Engine</span></a><ul><li class="level-2"><a class="final" href="/deploy/"><span>Deploying as a Web Service</span></a></li><li class="level-2"><a class="final" href="/cli/#engine-command
s"><span>Engine Command-line Interface</span></a></li><li class="level-2"><a class="final" href="/deploy/engineparams/"><span>Setting Engine Parameters</span></a></li><li class="level-2"><a class="final" href="/deploy/enginevariants/"><span>Deploying Multiple Engine Variants</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Customizing an Engine</span></a><ul><li class="level-2"><a class="final" href="/customize/"><span>Learning DASE</span></a></li><li class="level-2"><a class="final" href="/customize/dase/"><span>Implement DASE</span></a></li><li class="level-2"><a class="final" href="/customize/troubleshooting/"><span>Troubleshooting Engine Development</span></a></li><li class="level-2"><a class="final" href="/api/current/#package"><span>Engine Scala APIs</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Collecting and Analyzing Data</span></a><ul><li class="level-2"><a class="final active" href="/datacollection/"><sp
an>Event Server Overview</span></a></li><li class="level-2"><a class="final" href="/cli/#event-server-commands"><span>Event Server Command-line Interface</span></a></li><li class="level-2"><a class="final" href="/datacollection/eventapi/"><span>Collecting Data with REST/SDKs</span></a></li><li class="level-2"><a class="final" href="/datacollection/eventmodel/"><span>Events Modeling</span></a></li><li class="level-2"><a class="final" href="/datacollection/webhooks/"><span>Unifying Multichannel Data with Webhooks</span></a></li><li class="level-2"><a class="final" href="/datacollection/channel/"><span>Channel</span></a></li><li class="level-2"><a class="final" href="/datacollection/batchimport/"><span>Importing Data in Batch</span></a></li><li class="level-2"><a class="final" href="/datacollection/analytics/"><span>Using Analytics Tools</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Choosing an Algorithm(s)</span></a><ul><li class="level-2"><a class=
"final" href="/algorithm/"><span>Built-in Algorithm Libraries</span></a></li><li class="level-2"><a class="final" href="/algorithm/switch/"><span>Switching to Another Algorithm</span></a></li><li class="level-2"><a class="final" href="/algorithm/multiple/"><span>Combining Multiple Algorithms</span></a></li><li class="level-2"><a class="final" href="/algorithm/custom/"><span>Adding Your Own Algorithms</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>ML Tuning and Evaluation</span></a><ul><li class="level-2"><a class="final" href="/evaluation/"><span>Overview</span></a></li><li class="level-2"><a class="final" href="/evaluation/paramtuning/"><span>Hyperparameter Tuning</span></a></li><li class="level-2"><a class="final" href="/evaluation/evaluationdashboard/"><span>Evaluation Dashboard</span></a></li><li class="level-2"><a class="final" href="/evaluation/metricchoose/"><span>Choosing Evaluation Metrics</span></a></li><li class="level-2"><a class="final
" href="/evaluation/metricbuild/"><span>Building Evaluation Metrics</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>System Architecture</span></a><ul><li class="level-2"><a class="final" href="/system/"><span>Architecture Overview</span></a></li><li class="level-2"><a class="final" href="/system/anotherdatastore/"><span>Using Another Data Store</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Engine Template Gallery</span></a><ul><li class="level-2"><a class="final" href="http://templates.prediction.io"><span>Browse</span></a></li><li class="level-2"><a class="final" href="/community/submit-template/"><span>Submit your Engine as a Template</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Demo Tutorials</span></a><ul><li class="level-2"><a class="final" href="/demo/tapster/"><span>Comics Recommendation Demo</span></a></li><li class="level-2"><a class="final" href="/demo/community/"><sp
an>Community Contributed Demo</span></a></li><li class="level-2"><a class="final" href="/demo/textclassification/"><span>Text Classification Engine Tutorial</span></a></li></ul></li><li class="level-1"><a class="expandible" href="/community/"><span>Getting Involved</span></a><ul><li class="level-2"><a class="final" href="/community/contribute-code/"><span>Contribute Code</span></a></li><li class="level-2"><a class="final" href="/community/contribute-documentation/"><span>Contribute Documentation</span></a></li><li class="level-2"><a class="final" href="/community/contribute-sdk/"><span>Contribute a SDK</span></a></li><li class="level-2"><a class="final" href="/community/contribute-webhook/"><span>Contribute a Webhook</span></a></li><li class="level-2"><a class="final" href="/community/projects/"><span>Community Projects</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Getting Help</span></a><ul><li class="level-2"><a class="final" href="/resources/fa
q/"><span>FAQs</span></a></li><li class="level-2"><a class="final" href="/support/"><span>Community Support</span></a></li><li class="level-2"><a class="final" href="/support/#enterprise-support"><span>Enterprise Support</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Resources</span></a><ul><li class="level-2"><a class="final" href="/resources/intellij/"><span>Developing Engines with IntelliJ IDEA</span></a></li><li class="level-2"><a class="final" href="/resources/upgrade/"><span>Upgrade Instructions</span></a></li><li class="level-2"><a class="final" href="/resources/glossary/"><span>Glossary</span></a></li></ul></li></ul></nav></div><div class="col-md-9 col-sm-12"><div class="content-header hidden-md hidden-lg"><div id="breadcrumbs" class="hidden-sm hidden xs"><ul><li><a href="#">Collecting and Analyzing Data</a><span class="spacer">></span></li><li><span class="last">Event Server Overview</span></li></ul></div><div id="page-title"><h1>Event
Server Overview</h1></div></div><div id="table-of-content-wrapper"><h5>On this page</h5><aside id="table-of-contents"><ul> <li> <a href="#what-data-should-i-collect">What data should I collect?</a> </li> </ul> </aside><hr/><a id="edit-page-link" href="https://github.com/apache/incubator-predictionio/tree/livedoc/docs/manual/source/datacollection/index.html.md"><img src="/images/icons/edit-pencil-d6c1bb3d.png"/>Edit this page</a></div><div class="content-header hidden-sm hidden-xs"><div id="breadcrumbs" class="hidden-sm hidden xs"><ul><li><a href="#">Collecting and Analyzing Data</a><span class="spacer">></span></li><li><span class="last">Event Server Overview</span></li></ul></div><div id="page-title"><h1>Event Server Overview</h1></div></div><div class="content"><p>Apache PredictionIO (incubating) offers an Event Server that collects data in an event-based style via a RESTful API. By default, Event Server uses Apache HBase as data store.</p><p><img alt="EventServer Highlight" sr
c="/images/eventserver-overview-b4b841d1.png"/></p><h2 id='what-data-should-i-collect?' class='header-anchors'>What data should I collect?</h2><p>The Event Server can collect and store arbitrary events. At the beginning of your project, it is recommended to collect as much data as you can. Later on, you can exclude data that are not relevant to your predictive model in Data Preparator.</p><h3 id='recommendation-engine' class='header-anchors'>Recommendation Engine</h3><p>With Collaborative Filtering based Recommendation Engine, a common pattern is</p><div class="highlight shell"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1</pre></td><td class="code"><pre>user -- action -- item
+</pre></td></tr></tbody></table> </div> <p>where users and items have properties associated with them.</p><p>For example, for personalized book recommendation, some events to collect would be</p> <ul> <li>User 1 purchased product X</li> <li>User 2 viewed product Y</li> <li>User 1 added product Z in the cart</li> </ul> <p>User properties can be gender, age, location, etc. Item properties can be genre, author, and other attributes that may be related to the the user's preference.</p><p>Data collection varies quite a bit based on your application and your prediction goal. We are happy to <a href="mailto:support@prediction.io">assist you with your questions</a>.</p></div></div></div></div><footer><div class="container"><div class="seperator"></div><div class="row"><div class="col-md-4 col-md-push-8 col-xs-12"><div class="subscription-form-wrapper"><h4>Subscribe to our Newsletter</h4><form class="ajax-form" id="subscribe-form" method="POST" action="https://script.google.com/macros/s/
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<div class="row"><div class="col-md-9 col-sm-11 col-xs-11"><div class="hidden-md hidden-lg" id="mobile-page-heading-wrapper"><p>PredictionIO Docs</p><h4>Ruby SDK</h4></div><h4 class="hidden-sm hidden-xs">PredictionIO Docs</h4></div><div class="col-md-3 col-sm-1 col-xs-1 hidden-md hidden-lg"><img id="left-menu-indicator" src="/images/icons/down-arrow-dfe9f7fe.png"/></div><div class="col-md-3 col-sm-12 col-xs-12 swiftype-wrapper"><div class="swiftype"><form class="search-form"><img class="search-box-toggler hidden-xs hidden-sm" src="/images/icons/search-glass-704bd4ff.png"/><div class="search-box"><img src="/images/icons/search-glass-704bd4ff.png"/><input type="text" id="st-search-input" class="st-search-input" placeholder="Search Doc..."/></div><img class="swiftype-row-hider hidden-md hidden-lg" src="/images/icons/drawer-toggle-active-fcbef12a.png"/></form></div></div><div class="mobile-left-menu-toggler hidden-md hidden-lg"></div></div></div></div><div id="page" class="container-flu
id"><div class="row"><div id="left-menu-wrapper" class="col-md-3"><nav id="nav-main"><ul><li class="level-1"><a class="expandible" href="/"><span>Apache PredictionIO (incubating) Documentation</span></a><ul><li class="level-2"><a class="final" href="/"><span>Welcome to Apache PredictionIO (incubating)</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Getting Started</span></a><ul><li class="level-2"><a class="final" href="/start/"><span>A Quick Intro</span></a></li><li class="level-2"><a class="final" href="/install/"><span>Installing Apache PredictionIO (incubating)</span></a></li><li class="level-2"><a class="final" href="/start/download/"><span>Downloading an Engine Template</span></a></li><li class="level-2"><a class="final" href="/start/deploy/"><span>Deploying Your First Engine</span></a></li><li class="level-2"><a class="final" href="/start/customize/"><span>Customizing the Engine</span></a></li></ul></li><li class="level-1"><a class="expandibl
e" href="#"><span>Integrating with Your App</span></a><ul><li class="level-2"><a class="final" href="/appintegration/"><span>App Integration Overview</span></a></li><li class="level-2"><a class="expandible" href="/sdk/"><span>List of SDKs</span></a><ul><li class="level-3"><a class="final" href="/sdk/java/"><span>Java & Android SDK</span></a></li><li class="level-3"><a class="final" href="/sdk/php/"><span>PHP SDK</span></a></li><li class="level-3"><a class="final" href="/sdk/python/"><span>Python SDK</span></a></li><li class="level-3"><a class="final active" href="/sdk/ruby/"><span>Ruby SDK</span></a></li><li class="level-3"><a class="final" href="/sdk/community/"><span>Community Powered SDKs</span></a></li></ul></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Deploying an Engine</span></a><ul><li class="level-2"><a class="final" href="/deploy/"><span>Deploying as a Web Service</span></a></li><li class="level-2"><a class="final" href="/cli/#engine-commands"><sp
an>Engine Command-line Interface</span></a></li><li class="level-2"><a class="final" href="/deploy/engineparams/"><span>Setting Engine Parameters</span></a></li><li class="level-2"><a class="final" href="/deploy/enginevariants/"><span>Deploying Multiple Engine Variants</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Customizing an Engine</span></a><ul><li class="level-2"><a class="final" href="/customize/"><span>Learning DASE</span></a></li><li class="level-2"><a class="final" href="/customize/dase/"><span>Implement DASE</span></a></li><li class="level-2"><a class="final" href="/customize/troubleshooting/"><span>Troubleshooting Engine Development</span></a></li><li class="level-2"><a class="final" href="/api/current/#package"><span>Engine Scala APIs</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Collecting and Analyzing Data</span></a><ul><li class="level-2"><a class="final" href="/datacollection/"><span>Event Serv
er Overview</span></a></li><li class="level-2"><a class="final" href="/cli/#event-server-commands"><span>Event Server Command-line Interface</span></a></li><li class="level-2"><a class="final" href="/datacollection/eventapi/"><span>Collecting Data with REST/SDKs</span></a></li><li class="level-2"><a class="final" href="/datacollection/eventmodel/"><span>Events Modeling</span></a></li><li class="level-2"><a class="final" href="/datacollection/webhooks/"><span>Unifying Multichannel Data with Webhooks</span></a></li><li class="level-2"><a class="final" href="/datacollection/channel/"><span>Channel</span></a></li><li class="level-2"><a class="final" href="/datacollection/batchimport/"><span>Importing Data in Batch</span></a></li><li class="level-2"><a class="final" href="/datacollection/analytics/"><span>Using Analytics Tools</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Choosing an Algorithm(s)</span></a><ul><li class="level-2"><a class="final" href=
"/algorithm/"><span>Built-in Algorithm Libraries</span></a></li><li class="level-2"><a class="final" href="/algorithm/switch/"><span>Switching to Another Algorithm</span></a></li><li class="level-2"><a class="final" href="/algorithm/multiple/"><span>Combining Multiple Algorithms</span></a></li><li class="level-2"><a class="final" href="/algorithm/custom/"><span>Adding Your Own Algorithms</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>ML Tuning and Evaluation</span></a><ul><li class="level-2"><a class="final" href="/evaluation/"><span>Overview</span></a></li><li class="level-2"><a class="final" href="/evaluation/paramtuning/"><span>Hyperparameter Tuning</span></a></li><li class="level-2"><a class="final" href="/evaluation/evaluationdashboard/"><span>Evaluation Dashboard</span></a></li><li class="level-2"><a class="final" href="/evaluation/metricchoose/"><span>Choosing Evaluation Metrics</span></a></li><li class="level-2"><a class="final" href="/eval
uation/metricbuild/"><span>Building Evaluation Metrics</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>System Architecture</span></a><ul><li class="level-2"><a class="final" href="/system/"><span>Architecture Overview</span></a></li><li class="level-2"><a class="final" href="/system/anotherdatastore/"><span>Using Another Data Store</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Engine Template Gallery</span></a><ul><li class="level-2"><a class="final" href="http://templates.prediction.io"><span>Browse</span></a></li><li class="level-2"><a class="final" href="/community/submit-template/"><span>Submit your Engine as a Template</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Demo Tutorials</span></a><ul><li class="level-2"><a class="final" href="/demo/tapster/"><span>Comics Recommendation Demo</span></a></li><li class="level-2"><a class="final" href="/demo/community/"><span>Community
Contributed Demo</span></a></li><li class="level-2"><a class="final" href="/demo/textclassification/"><span>Text Classification Engine Tutorial</span></a></li></ul></li><li class="level-1"><a class="expandible" href="/community/"><span>Getting Involved</span></a><ul><li class="level-2"><a class="final" href="/community/contribute-code/"><span>Contribute Code</span></a></li><li class="level-2"><a class="final" href="/community/contribute-documentation/"><span>Contribute Documentation</span></a></li><li class="level-2"><a class="final" href="/community/contribute-sdk/"><span>Contribute a SDK</span></a></li><li class="level-2"><a class="final" href="/community/contribute-webhook/"><span>Contribute a Webhook</span></a></li><li class="level-2"><a class="final" href="/community/projects/"><span>Community Projects</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Getting Help</span></a><ul><li class="level-2"><a class="final" href="/resources/faq/"><span>FAQ
s</span></a></li><li class="level-2"><a class="final" href="/support/"><span>Community Support</span></a></li><li class="level-2"><a class="final" href="/support/#enterprise-support"><span>Enterprise Support</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Resources</span></a><ul><li class="level-2"><a class="final" href="/resources/intellij/"><span>Developing Engines with IntelliJ IDEA</span></a></li><li class="level-2"><a class="final" href="/resources/upgrade/"><span>Upgrade Instructions</span></a></li><li class="level-2"><a class="final" href="/resources/glossary/"><span>Glossary</span></a></li></ul></li></ul></nav></div><div class="col-md-9 col-sm-12"><div class="content-header hidden-md hidden-lg"><div id="breadcrumbs" class="hidden-sm hidden xs"><ul><li><a href="#">Integrating with Your App</a><span class="spacer">></span></li><li><a href="/sdk/">List of SDKs</a><span class="spacer">></span></li><li><span class="last">Ruby SDK</span></li
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er-fluid"><div class="row"><div id="left-menu-wrapper" class="col-md-3"><nav id="nav-main"><ul><li class="level-1"><a class="expandible" href="/"><span>Apache PredictionIO (incubating) Documentation</span></a><ul><li class="level-2"><a class="final" href="/"><span>Welcome to Apache PredictionIO (incubating)</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Getting Started</span></a><ul><li class="level-2"><a class="final" href="/start/"><span>A Quick Intro</span></a></li><li class="level-2"><a class="final" href="/install/"><span>Installing Apache PredictionIO (incubating)</span></a></li><li class="level-2"><a class="final" href="/start/download/"><span>Downloading an Engine Template</span></a></li><li class="level-2"><a class="final" href="/start/deploy/"><span>Deploying Your First Engine</span></a></li><li class="level-2"><a class="final" href="/start/customize/"><span>Customizing the Engine</span></a></li></ul></li><li class="level-1"><a class="exp
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r Overview</span></a></li><li class="level-2"><a class="final" href="/cli/#event-server-commands"><span>Event Server Command-line Interface</span></a></li><li class="level-2"><a class="final" href="/datacollection/eventapi/"><span>Collecting Data with REST/SDKs</span></a></li><li class="level-2"><a class="final" href="/datacollection/eventmodel/"><span>Events Modeling</span></a></li><li class="level-2"><a class="final" href="/datacollection/webhooks/"><span>Unifying Multichannel Data with Webhooks</span></a></li><li class="level-2"><a class="final" href="/datacollection/channel/"><span>Channel</span></a></li><li class="level-2"><a class="final" href="/datacollection/batchimport/"><span>Importing Data in Batch</span></a></li><li class="level-2"><a class="final" href="/datacollection/analytics/"><span>Using Analytics Tools</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Choosing an Algorithm(s)</span></a><ul><li class="level-2"><a class="final" href="
/algorithm/"><span>Built-in Algorithm Libraries</span></a></li><li class="level-2"><a class="final" href="/algorithm/switch/"><span>Switching to Another Algorithm</span></a></li><li class="level-2"><a class="final" href="/algorithm/multiple/"><span>Combining Multiple Algorithms</span></a></li><li class="level-2"><a class="final" href="/algorithm/custom/"><span>Adding Your Own Algorithms</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>ML Tuning and Evaluation</span></a><ul><li class="level-2"><a class="final" href="/evaluation/"><span>Overview</span></a></li><li class="level-2"><a class="final" href="/evaluation/paramtuning/"><span>Hyperparameter Tuning</span></a></li><li class="level-2"><a class="final" href="/evaluation/evaluationdashboard/"><span>Evaluation Dashboard</span></a></li><li class="level-2"><a class="final" href="/evaluation/metricchoose/"><span>Choosing Evaluation Metrics</span></a></li><li class="level-2"><a class="final" href="/evalu
ation/metricbuild/"><span>Building Evaluation Metrics</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>System Architecture</span></a><ul><li class="level-2"><a class="final" href="/system/"><span>Architecture Overview</span></a></li><li class="level-2"><a class="final" href="/system/anotherdatastore/"><span>Using Another Data Store</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Engine Template Gallery</span></a><ul><li class="level-2"><a class="final" href="http://templates.prediction.io"><span>Browse</span></a></li><li class="level-2"><a class="final" href="/community/submit-template/"><span>Submit your Engine as a Template</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Demo Tutorials</span></a><ul><li class="level-2"><a class="final" href="/demo/tapster/"><span>Comics Recommendation Demo</span></a></li><li class="level-2"><a class="final" href="/demo/community/"><span>Community C
ontributed Demo</span></a></li><li class="level-2"><a class="final" href="/demo/textclassification/"><span>Text Classification Engine Tutorial</span></a></li></ul></li><li class="level-1"><a class="expandible" href="/community/"><span>Getting Involved</span></a><ul><li class="level-2"><a class="final" href="/community/contribute-code/"><span>Contribute Code</span></a></li><li class="level-2"><a class="final" href="/community/contribute-documentation/"><span>Contribute Documentation</span></a></li><li class="level-2"><a class="final" href="/community/contribute-sdk/"><span>Contribute a SDK</span></a></li><li class="level-2"><a class="final" href="/community/contribute-webhook/"><span>Contribute a Webhook</span></a></li><li class="level-2"><a class="final" href="/community/projects/"><span>Community Projects</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Getting Help</span></a><ul><li class="level-2"><a class="final" href="/resources/faq/"><span>FAQs
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[31/51] [partial] incubator-predictionio-site git commit: Initial doc
site
Posted by do...@apache.org.
http://git-wip-us.apache.org/repos/asf/incubator-predictionio-site/blob/92a45fa4/images/logos/downloads/banner-light-background-b6ba095f.svg
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diff --git a/images/logos/downloads/banner-light-background-b6ba095f.svg b/images/logos/downloads/banner-light-background-b6ba095f.svg
new file mode 100644
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--- /dev/null
+++ b/images/logos/downloads/banner-light-background-b6ba095f.svg
@@ -0,0 +1,48 @@
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http://git-wip-us.apache.org/repos/asf/incubator-predictionio-site/blob/92a45fa4/images/logos/downloads/frog-light-background-1ae5ccaf.svg
----------------------------------------------------------------------
diff --git a/images/logos/downloads/frog-light-background-1ae5ccaf.svg b/images/logos/downloads/frog-light-background-1ae5ccaf.svg
new file mode 100644
index 0000000..14817cb
--- /dev/null
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+ <!-- Generator: Sketch 3.3 (11970) - http://www.bohemiancoding.com/sketch -->
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+<!DOCTYPE html><html><head><title>Text Classification Engine Tutorial</title><meta charset="utf-8"/><meta content="IE=edge,chrome=1" http-equiv="X-UA-Compatible"/><meta name="viewport" content="width=device-width, initial-scale=1.0"/><meta class="swiftype" name="title" data-type="string" content="Text Classification Engine Tutorial"/><link rel="canonical" href="https://docs.prediction.io/demo/textclassification/"/><link href="/images/favicon/normal-b330020a.png" rel="shortcut icon"/><link href="/images/favicon/apple-c0febcf2.png" rel="apple-touch-icon"/><link href="//fonts.googleapis.com/css?family=Open+Sans:300italic,400italic,600italic,700italic,800italic,400,300,600,700,800" rel="stylesheet"/><link href="//maxcdn.bootstrapcdn.com/font-awesome/4.2.0/css/font-awesome.min.css" rel="stylesheet"/><link href="/stylesheets/application-3598c7d7.css" rel="stylesheet" type="text/css"/><!--[if lt IE 9]><script src="//cdnjs.cloudflare.com/ajax/libs/html5shiv/3.7.2/html5shiv.min.js"></script>
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+fbq('track', "PageView");</script><script src="//use.typekit.net/mut4mjx.js"></script><script>try{Typekit.load();}catch(e){}</script></head><body><div id="global"><header><div class="container" id="header-wrapper"><div class="row"><div class="col-sm-12"><div id="logo-wrapper"><span id="drawer-toggle"></span><a href="#"></a><a href="http://prediction.io/"><img alt="PredictionIO" id="logo" src="/images/logos/logo-ee2b9bb3.png"/></a></div><div id="menu-wrapper"><div id="header-nav-options-wrapper"><ul><li><a href="/">Install & Doc</a></li> <li><a href="/support">Support</a></li> </ul></div><div id="pill-wrapper"><a class="pill left" href="//templates.prediction.io/">TEMPLATES</a> <a class="pill right" href="//github.com/PredictionIO/PredictionIO/">OPEN SOURCE</a></div></div><img class="mobile-search-bar-toggler hidden-md hidden-lg" src="/images/icons/search-glass-704bd4ff.png"/></div></div></div></header><div id="search-bar-row-wrapper"><div class="container-fluid" id="search-bar-row">
<div class="row"><div class="col-md-9 col-sm-11 col-xs-11"><div class="hidden-md hidden-lg" id="mobile-page-heading-wrapper"><p>PredictionIO Docs</p><h4>Text Classification Engine Tutorial</h4></div><h4 class="hidden-sm hidden-xs">PredictionIO Docs</h4></div><div class="col-md-3 col-sm-1 col-xs-1 hidden-md hidden-lg"><img id="left-menu-indicator" src="/images/icons/down-arrow-dfe9f7fe.png"/></div><div class="col-md-3 col-sm-12 col-xs-12 swiftype-wrapper"><div class="swiftype"><form class="search-form"><img class="search-box-toggler hidden-xs hidden-sm" src="/images/icons/search-glass-704bd4ff.png"/><div class="search-box"><img src="/images/icons/search-glass-704bd4ff.png"/><input type="text" id="st-search-input" class="st-search-input" placeholder="Search Doc..."/></div><img class="swiftype-row-hider hidden-md hidden-lg" src="/images/icons/drawer-toggle-active-fcbef12a.png"/></form></div></div><div class="mobile-left-menu-toggler hidden-md hidden-lg"></div></div></div></div><div id=
"page" class="container-fluid"><div class="row"><div id="left-menu-wrapper" class="col-md-3"><nav id="nav-main"><ul><li class="level-1"><a class="expandible" href="/"><span>Apache PredictionIO (incubating) Documentation</span></a><ul><li class="level-2"><a class="final" href="/"><span>Welcome to Apache PredictionIO (incubating)</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Getting Started</span></a><ul><li class="level-2"><a class="final" href="/start/"><span>A Quick Intro</span></a></li><li class="level-2"><a class="final" href="/install/"><span>Installing Apache PredictionIO (incubating)</span></a></li><li class="level-2"><a class="final" href="/start/download/"><span>Downloading an Engine Template</span></a></li><li class="level-2"><a class="final" href="/start/deploy/"><span>Deploying Your First Engine</span></a></li><li class="level-2"><a class="final" href="/start/customize/"><span>Customizing the Engine</span></a></li></ul></li><li class="l
evel-1"><a class="expandible" href="#"><span>Integrating with Your App</span></a><ul><li class="level-2"><a class="final" href="/appintegration/"><span>App Integration Overview</span></a></li><li class="level-2"><a class="expandible" href="/sdk/"><span>List of SDKs</span></a><ul><li class="level-3"><a class="final" href="/sdk/java/"><span>Java & Android SDK</span></a></li><li class="level-3"><a class="final" href="/sdk/php/"><span>PHP SDK</span></a></li><li class="level-3"><a class="final" href="/sdk/python/"><span>Python SDK</span></a></li><li class="level-3"><a class="final" href="/sdk/ruby/"><span>Ruby SDK</span></a></li><li class="level-3"><a class="final" href="/sdk/community/"><span>Community Powered SDKs</span></a></li></ul></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Deploying an Engine</span></a><ul><li class="level-2"><a class="final" href="/deploy/"><span>Deploying as a Web Service</span></a></li><li class="level-2"><a class="final" href="/cli/#
engine-commands"><span>Engine Command-line Interface</span></a></li><li class="level-2"><a class="final" href="/deploy/engineparams/"><span>Setting Engine Parameters</span></a></li><li class="level-2"><a class="final" href="/deploy/enginevariants/"><span>Deploying Multiple Engine Variants</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Customizing an Engine</span></a><ul><li class="level-2"><a class="final" href="/customize/"><span>Learning DASE</span></a></li><li class="level-2"><a class="final" href="/customize/dase/"><span>Implement DASE</span></a></li><li class="level-2"><a class="final" href="/customize/troubleshooting/"><span>Troubleshooting Engine Development</span></a></li><li class="level-2"><a class="final" href="/api/current/#package"><span>Engine Scala APIs</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Collecting and Analyzing Data</span></a><ul><li class="level-2"><a class="final" href="/datacollectio
n/"><span>Event Server Overview</span></a></li><li class="level-2"><a class="final" href="/cli/#event-server-commands"><span>Event Server Command-line Interface</span></a></li><li class="level-2"><a class="final" href="/datacollection/eventapi/"><span>Collecting Data with REST/SDKs</span></a></li><li class="level-2"><a class="final" href="/datacollection/eventmodel/"><span>Events Modeling</span></a></li><li class="level-2"><a class="final" href="/datacollection/webhooks/"><span>Unifying Multichannel Data with Webhooks</span></a></li><li class="level-2"><a class="final" href="/datacollection/channel/"><span>Channel</span></a></li><li class="level-2"><a class="final" href="/datacollection/batchimport/"><span>Importing Data in Batch</span></a></li><li class="level-2"><a class="final" href="/datacollection/analytics/"><span>Using Analytics Tools</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Choosing an Algorithm(s)</span></a><ul><li class="level-2"><a
class="final" href="/algorithm/"><span>Built-in Algorithm Libraries</span></a></li><li class="level-2"><a class="final" href="/algorithm/switch/"><span>Switching to Another Algorithm</span></a></li><li class="level-2"><a class="final" href="/algorithm/multiple/"><span>Combining Multiple Algorithms</span></a></li><li class="level-2"><a class="final" href="/algorithm/custom/"><span>Adding Your Own Algorithms</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>ML Tuning and Evaluation</span></a><ul><li class="level-2"><a class="final" href="/evaluation/"><span>Overview</span></a></li><li class="level-2"><a class="final" href="/evaluation/paramtuning/"><span>Hyperparameter Tuning</span></a></li><li class="level-2"><a class="final" href="/evaluation/evaluationdashboard/"><span>Evaluation Dashboard</span></a></li><li class="level-2"><a class="final" href="/evaluation/metricchoose/"><span>Choosing Evaluation Metrics</span></a></li><li class="level-2"><a class
="final" href="/evaluation/metricbuild/"><span>Building Evaluation Metrics</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>System Architecture</span></a><ul><li class="level-2"><a class="final" href="/system/"><span>Architecture Overview</span></a></li><li class="level-2"><a class="final" href="/system/anotherdatastore/"><span>Using Another Data Store</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Engine Template Gallery</span></a><ul><li class="level-2"><a class="final" href="http://templates.prediction.io"><span>Browse</span></a></li><li class="level-2"><a class="final" href="/community/submit-template/"><span>Submit your Engine as a Template</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Demo Tutorials</span></a><ul><li class="level-2"><a class="final" href="/demo/tapster/"><span>Comics Recommendation Demo</span></a></li><li class="level-2"><a class="final" href="/demo/communit
y/"><span>Community Contributed Demo</span></a></li><li class="level-2"><a class="final active" href="/demo/textclassification/"><span>Text Classification Engine Tutorial</span></a></li></ul></li><li class="level-1"><a class="expandible" href="/community/"><span>Getting Involved</span></a><ul><li class="level-2"><a class="final" href="/community/contribute-code/"><span>Contribute Code</span></a></li><li class="level-2"><a class="final" href="/community/contribute-documentation/"><span>Contribute Documentation</span></a></li><li class="level-2"><a class="final" href="/community/contribute-sdk/"><span>Contribute a SDK</span></a></li><li class="level-2"><a class="final" href="/community/contribute-webhook/"><span>Contribute a Webhook</span></a></li><li class="level-2"><a class="final" href="/community/projects/"><span>Community Projects</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Getting Help</span></a><ul><li class="level-2"><a class="final" href=
"/resources/faq/"><span>FAQs</span></a></li><li class="level-2"><a class="final" href="/support/"><span>Community Support</span></a></li><li class="level-2"><a class="final" href="/support/#enterprise-support"><span>Enterprise Support</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Resources</span></a><ul><li class="level-2"><a class="final" href="/resources/intellij/"><span>Developing Engines with IntelliJ IDEA</span></a></li><li class="level-2"><a class="final" href="/resources/upgrade/"><span>Upgrade Instructions</span></a></li><li class="level-2"><a class="final" href="/resources/glossary/"><span>Glossary</span></a></li></ul></li></ul></nav></div><div class="col-md-9 col-sm-12"><div class="content-header hidden-md hidden-lg"><div id="breadcrumbs" class="hidden-sm hidden xs"><ul><li><a href="#">Demo Tutorials</a><span class="spacer">></span></li><li><span class="last">Text Classification Engine Tutorial</span></li></ul></div><div id="page-titl
e"><h1>Text Classification Engine Tutorial</h1></div></div><div id="table-of-content-wrapper"><h5>On this page</h5><aside id="table-of-contents"><ul> <li> <a href="#introduction">Introduction</a> </li> <li> <a href="#prerequisites">Prerequisites</a> </li> <li> <a href="#engine-overview">Engine Overview</a> </li> <li> <a href="#quick-start">Quick Start</a> </li> </ul> </li> <li> <a href="#detailed-explanation-of-dase">Detailed Explanation of DASE</a> <ul> <li> <a href="#importing-data">Importing Data</a> </li> <li> <a href="#data-source-reading-event-data">Data Source: Reading Event Data</a> </li> <li> <a href="#preparator-data-processing-with-dase">Preparator : Data Processing With DASE</a> </li> <li> <a href="#algorithm-component">Algorithm Component</a> </li> <li> <a href="#serving-delivering-the-final-prediction">Serving: Delivering the Final Prediction</a> </li> <li> <a href="#evaluation-model-assessment-and-selection">Evaluation: Model Assessment and Selection</a> </li> <li> <a
href="#engine-deployment">Engine Deployment</a> </li> </ul> </aside><hr/><a id="edit-page-link" href="https://github.com/apache/incubator-predictionio/tree/livedoc/docs/manual/source/demo/textclassification.html.md.erb"><img src="/images/icons/edit-pencil-d6c1bb3d.png"/>Edit this page</a></div><div class="content-header hidden-sm hidden-xs"><div id="breadcrumbs" class="hidden-sm hidden xs"><ul><li><a href="#">Demo Tutorials</a><span class="spacer">></span></li><li><span class="last">Text Classification Engine Tutorial</span></li></ul></div><div id="page-title"><h1>Text Classification Engine Tutorial</h1></div></div><div class="content"><p>(Updated for Text Classification Template version 3.1)</p><h2 id='introduction' class='header-anchors'>Introduction</h2><p>In the real world, there are many applications that collect text as data. For example, spam detectors take email and header content to automatically determine what is or is not spam; applications can gague the general senti
ment in a geographical area by analyzing Twitter data; and news articles can be automatically categorized based solely on the text content.There are a wide array of machine learning models you can use to create, or train, a predictive model to assign an incoming article, or query, to an existing category. Before you can use these techniques you must first transform the text data (in this case the set of news articles) into numeric vectors, or feature vectors, that can be used to train your model.</p><p>The purpose of this tutorial is to illustrate how you can go about doing this using PredictionIO's platform. The advantages of using this platform include: a dynamic engine that responds to queries in real-time; <a href="http://en.wikipedia.org/wiki/Separation_of_concerns">separation of concerns</a>, which offers code re-use and maintainability, and distributed computing capabilities for scalability and efficiency. Moreover, it is easy to incorporate non-trivial data modeling task
s into the DASE architecture allowing Data Scientists to focus on tasks related to modeling. This tutorial will exemplify some of these ideas by guiding you through PredictionIO's [text classification template(<a href="http://templates.prediction.io/PredictionIO/template-scala-parallel-textclassification/">http://templates.prediction.io/PredictionIO/template-scala-parallel-textclassification/</a>).</p><h2 id='prerequisites' class='header-anchors'>Prerequisites</h2><p>Before getting started, please make sure that you have the latest version of Apache PredictionIO (incubating) <a href="http://predictionio.incubator.apache.org/install/">installed</a>. We emphasize here that this is an engine template written in <strong>Scala</strong> and can be more generally thought of as an SBT project containing all the necessary components.</p><p>You should also download the engine template named Text Classification Engine that accompanies this tutorial by cloning the template repository:</p><d
iv class="highlight shell"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1</pre></td><td class="code"><pre>pio template get PredictionIO/template-scala-parallel-textclassification < Your new engine directory >
+</pre></td></tr></tbody></table> </div> <h2 id='engine-overview' class='header-anchors'>Engine Overview</h2><p>The engine follows the DASE architecture which we briefly review here. As a user, you are tasked with collecting data for your web or application, and importing it into PredictionIO's Event Server. Once the data is in the server, it can be read and processed by the engine via the Data Source and Preparation components, respectively. The Algorithm component uses the processed, or prepared, data to train a set of predictive models. Once you have trained these models, you are ready to deploy your engine and respond to real-time queries via the Serving component which combines the results from different fitted models. The Evaluation component is used to compute an appropriate metric to test the performance of a fitted model, as well as aid in the tuning of model hyper parameters.</p><p>This engine template is meant to handle text classification which means you will be worki
ng with text data. This means that a query, or newly observed documents, will be of the form:</p><p><code>{text : String}</code>.</p><p>In the running example, a query would be an incoming news article. Once the engine is deployed it can process the query, and then return a Predicted Result of the form</p><p><code>{category : String, confidence : Double}</code>.</p><p>Here category is the model's class assignment for this new text document (i.e. the best guess for this article's categorization), and confidence, a value between 0 and 1 representing your confidence in the category prediction (0 meaning you have no confidence in the prediction). The Actual Result is of the form</p><p><code>{category : String}</code>.</p><p>This is used in the evaluation stage when estimating the performance of your predictive model (how well does the model predict categories). Please refer to the <a href="https://docs.prediction.io/customize/">following tutorial</a> for a more detailed explanat
ion of how your engine will interact with your web application, as well as an in depth-overview of DASE.</p><h2 id='quick-start' class='header-anchors'>Quick Start</h2><p>This is a quick start guide in case you want to start using the engine right away. Sample email data for spam classification will be used. For more detailed information, read the subsequent sections.</p><h3 id='1.-create-a-new-application.' class='header-anchors'>1. Create a new application.</h3><p>After the application is created, you will be given an access key and application ID for the application.</p><div class="highlight shell"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1</pre></td><td class="code"><pre><span class="gp">$ </span>pio app new MyTextApp
+</pre></td></tr></tbody></table> </div> <h3 id='2.-import-the-tutorial-data.' class='header-anchors'>2. Import the tutorial data.</h3><p>There are three different data sets available, each giving a different use case for this engine. Please refer to the <strong>Data Source: Reading Event Data</strong> section to see how to appropriate modify the <code>DataSource</code> class for use with each respective data set. The default data set is an e-mail spam data set.</p><p>These data sets have already been processed and are ready for <a href="/datacollection/batchimport/">batch import</a>. Replace <code>***</code> with your actual application ID.</p><div class="highlight shell"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1
+2
+3</pre></td><td class="code"><pre><span class="gp">$ </span>pio import --appid <span class="k">***</span> --input data/stopwords.json
+
+<span class="gp">$ </span>pio import --appid <span class="k">***</span> --input data/emails.json
+</pre></td></tr></tbody></table> </div> <h3 id='3.-set-the-engine-parameters-in-the-file-<code>engine.json</code>.' class='header-anchors' >3. Set the engine parameters in the file <code>engine.json</code>.</h3><p>The default settings are shown below. By default, it uses the algorithm name "lr" which is logstic regression. Please see later section for more detailed explanation of engine.json setting.</p><p>Make sure the "appName" is same as the app you created in step1.</p><div class="highlight shell"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1
+2
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+5
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+26</pre></td><td class="code"><pre><span class="o">{</span>
+ <span class="s2">"id"</span>: <span class="s2">"default"</span>,
+ <span class="s2">"description"</span>: <span class="s2">"Default settings"</span>,
+ <span class="s2">"engineFactory"</span>: <span class="s2">"org.template.textclassification.TextClassificationEngine"</span>,
+ <span class="s2">"datasource"</span>: <span class="o">{</span>
+ <span class="s2">"params"</span>: <span class="o">{</span>
+ <span class="s2">"appName"</span>: <span class="s2">"MyTextApp"</span>
+ <span class="o">}</span>
+ <span class="o">}</span>,
+ <span class="s2">"preparator"</span>: <span class="o">{</span>
+ <span class="s2">"params"</span>: <span class="o">{</span>
+ <span class="s2">"nGram"</span>: 1,
+ <span class="s2">"numFeatures"</span>: 500,
+ <span class="s2">"SPPMI"</span>: <span class="nb">false</span>
+ <span class="o">}</span>
+ <span class="o">}</span>,
+ <span class="s2">"algorithms"</span>: <span class="o">[</span>
+ <span class="o">{</span>
+ <span class="s2">"name"</span>: <span class="s2">"lr"</span>,
+ <span class="s2">"params"</span>: <span class="o">{</span>
+ <span class="s2">"regParam"</span>: 0.00000005
+ <span class="o">}</span>
+ <span class="o">}</span>
+ <span class="o">]</span>
+<span class="o">}</span>
+
+</pre></td></tr></tbody></table> </div> <h3 id='4.-build-your-engine.' class='header-anchors'>4. Build your engine.</h3><div class="highlight shell"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1</pre></td><td class="code"><pre><span class="gp">$ </span>pio build --verbose
+</pre></td></tr></tbody></table> </div> <p>This command should take few minutes for the first time; all subsequent builds should be less than a minute. You can also run it without <code>--verbose</code> if you don't want to see all the log messages.</p><p>Upon successful build, you should see a console message similar to the following</p><div class="highlight shell"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1
+2</pre></td><td class="code"><pre><span class="o">[</span>INFO] <span class="o">[</span>RegisterEngine<span class="nv">$]</span> Registering engine 6wxDy2hxLbvaMJra927ahFdQHDIVXeQz 266bae678c570dee58154b2338cef7aa1646e0d3
+<span class="o">[</span>INFO] <span class="o">[</span>Console<span class="nv">$]</span> Your engine is ready <span class="k">for </span>training.
+</pre></td></tr></tbody></table> </div> <h3 id='5.a.-train-your-model-and-deploy.' class='header-anchors'>5.a. Train your model and deploy.</h3><div class="highlight shell"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1</pre></td><td class="code"><pre><span class="gp">$ </span>pio train
+</pre></td></tr></tbody></table> </div> <p>When your engine is trained successfully, you should see a console message similar to the following.</p><div class="highlight shell"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1</pre></td><td class="code"><pre><span class="o">[</span>INFO] <span class="o">[</span>CoreWorkflow<span class="nv">$]</span> Training completed successfully.
+</pre></td></tr></tbody></table> </div> <p>Now your engine is ready to deploy. Run:</p><div class="highlight shell"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1</pre></td><td class="code"><pre><span class="gp">$ </span>pio deploy
+</pre></td></tr></tbody></table> </div> <p>When the engine is deployed successfully and running, you should see a console message similar to the following:</p><div class="highlight shell"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1
+2</pre></td><td class="code"><pre><span class="o">[</span>INFO] <span class="o">[</span>HttpListener] Bound to /0.0.0.0:8000
+<span class="o">[</span>INFO] <span class="o">[</span>MasterActor] Engine is deployed and running. Engine API is live at http://0.0.0.0:8000.
+</pre></td></tr></tbody></table> </div> <p>Now you can send query to the engine. Open another terminal and send the following http request to the deployed engine:</p><div class="highlight shell"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1</pre></td><td class="code"><pre><span class="gp">$ </span>curl -H <span class="s2">"Content-Type: application/json"</span> -d <span class="s1">'{ "text":"I like speed and fast motorcycles." }'</span> http://localhost:8000/queries.json
+</pre></td></tr></tbody></table> </div> <p>you should see following outputs returned by the engine:</p><div class="highlight shell"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1</pre></td><td class="code"><pre><span class="o">{</span><span class="s2">"category"</span>:<span class="s2">"not spam"</span>,<span class="s2">"confidence"</span>:0.852619510921587<span class="o">}</span>
+</pre></td></tr></tbody></table> </div> <p>Try another query:</p><div class="highlight shell"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1</pre></td><td class="code"><pre><span class="gp">$ </span>curl -H <span class="s2">"Content-Type: application/json"</span> -d <span class="s1">'{ "text":"Earn extra cash!" }'</span> http://localhost:8000/queries.json
+</pre></td></tr></tbody></table> </div> <p>you should see following outputs returned by the engine:</p><div class="highlight shell"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1</pre></td><td class="code"><pre><span class="o">{</span><span class="s2">"category"</span>:<span class="s2">"spam"</span>,<span class="s2">"confidence"</span>:0.5268770133242983<span class="o">}</span>
+</pre></td></tr></tbody></table> </div> <h3 id='5.b.evaluate-your-training-model-and-tune-parameters.' class='header-anchors'>5.b.Evaluate your training model and tune parameters.</h3><div class="highlight shell"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1</pre></td><td class="code"><pre><span class="gp">$ </span>pio <span class="nb">eval </span>org.template.textclassification.AccuracyEvaluation org.template.textclassification.EngineParamsList
+</pre></td></tr></tbody></table> </div> <p><strong>Note:</strong> Training and evaluation stages are generally different stages of engine development. Evaluation is there to help you choose the best <a href="/evaluation/paramtuning/">algorithm parameters</a> to use for training an engine that is to be deployed as a web service.</p><p>Depending on your needs, in steps (5.x.) above, you can configure your Spark settings by typing a command of the form:</p><div class="highlight shell"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1</pre></td><td class="code"><pre><span class="gp">$ </span>pio <span class="nb">command </span>command_parameters -- --master url --driver-memory <span class="o">{</span>0<span class="o">}</span>G --executor-memory <span class="o">{</span>1<span class="o">}</span>G --conf spark.akka.framesize<span class="o">={</span>2<span class="o">}</span> --total_executor_cores <span class="o">{</span>3<span
class="o">}</span>
+</pre></td></tr></tbody></table> </div> <p>Only the latter commands are listed as these are some of the more commonly modified values. See the <a href="https://spark.apache.org/docs/latest/spark-standalone.html">Spark documentation</a> and the <a href="http://predictionio.incubator.apache.org/resources/faq/">PredictionIO FAQ's</a> for more information.</p><p><strong>Note:</strong> We recommend you set your driver memory to <code>1G</code> or <code>2G</code> as the data size when dealing with text can be very large.</p><h1 id='detailed-explanation-of-dase' class='header-anchors'>Detailed Explanation of DASE</h1><h2 id='importing-data' class='header-anchors'>Importing Data</h2><p>In the quick start, email spam classification is used. This template can easily be modified for other types text classification.</p><p>If you want to import different sets of data, follow the Quick Start instructions to import data from different files. Make sure that the Data Source is modified according
ly to match the <code>event</code>, <code>entityType</code>, and <code>properties</code> fields set for the specific dataset. The following section explains this in more detail.</p><h2 id='data-source:-reading-event-data' class='header-anchors'>Data Source: Reading Event Data</h2><p>Now that the data has been imported into PredictionIO's Event Server, it needs to be read from storage to be used by the engine. This is precisely what the DataSource engine component is for, which is implemented in the template script <code>DataSource.scala</code>. The class <code>Observation</code> serves as a wrapper for storing the information about a news document needed to train a model. The attribute label refers to the label of the category a document belongs to, and text, stores the actual document content as a string. The class TrainingData is used to store an RDD of Observation objects along with the set of stop words.</p><p>The class <code>DataSourceParams</code> is used to specify the pa
rameters needed to read and prepare the data for processing. This class is initialized with two parameters <code>appName</code> and <code>evalK</code>. The first parameter specifies your application name (i.e. MyTextApp), which is needed so that the DataSource component knows where to pull the event data from. The second parameter is used for model evaluation and specifies the number of folds to use in <a href="http://en.wikipedia.org/wiki/Cross-validation_%28statistics%29">cross-validation</a> when estimating a model performance metric.</p><p>The final and most important ingredient is the DataSource class. This is initialized with its corresponding parameter class, and extends <code>PDataSource</code>. This <strong>must</strong> implement the method <code>readTraining</code> which returns an instance of type TrainingData. This method completely relies on the defined private methods readEventData and readStopWords. Both of these functions read data observations as Event instances, c
reate an RDD containing these events and finally transforms the RDD of events into an object of the appropriate type as seen below:</p><div class="highlight scala"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1
+2
+3
+4
+5
+6
+7
+8
+9
+10
+11
+12
+13
+14
+15
+16
+17
+18
+19
+20
+21
+22
+23
+24
+25
+26
+27
+28
+29
+30
+31
+32
+33
+34
+35</pre></td><td class="code"><pre><span class="o">...</span>
+<span class="k">private</span> <span class="k">def</span> <span class="n">readEventData</span><span class="o">(</span><span class="n">sc</span><span class="k">:</span> <span class="kt">SparkContext</span><span class="o">)</span> <span class="k">:</span> <span class="kt">RDD</span><span class="o">[</span><span class="kt">Observation</span><span class="o">]</span> <span class="k">=</span> <span class="o">{</span>
+ <span class="c1">//Get RDD of Events.
+</span> <span class="nc">PEventStore</span><span class="o">.</span><span class="n">find</span><span class="o">(</span>
+ <span class="n">appName</span> <span class="k">=</span> <span class="n">dsp</span><span class="o">.</span><span class="n">appName</span><span class="o">,</span>
+ <span class="n">entityType</span> <span class="k">=</span> <span class="nc">Some</span><span class="o">(</span><span class="s">"content"</span><span class="o">),</span> <span class="c1">// specify data entity type
+</span> <span class="n">eventNames</span> <span class="k">=</span> <span class="nc">Some</span><span class="o">(</span><span class="nc">List</span><span class="o">(</span><span class="s">"e-mail"</span><span class="o">))</span> <span class="c1">// specify data event name
+</span>
+ <span class="c1">// Convert collected RDD of events to and RDD of Observation
+</span> <span class="c1">// objects.
+</span> <span class="o">)(</span><span class="n">sc</span><span class="o">).</span><span class="n">map</span><span class="o">(</span><span class="n">e</span> <span class="k">=></span> <span class="o">{</span>
+ <span class="k">val</span> <span class="n">label</span> <span class="k">:</span> <span class="kt">String</span> <span class="o">=</span> <span class="n">e</span><span class="o">.</span><span class="n">properties</span><span class="o">.</span><span class="n">get</span><span class="o">[</span><span class="kt">String</span><span class="o">](</span><span class="s">"label"</span><span class="o">)</span>
+ <span class="nc">Observation</span><span class="o">(</span>
+ <span class="k">if</span> <span class="o">(</span><span class="n">label</span> <span class="o">==</span> <span class="s">"spam"</span><span class="o">)</span> <span class="mf">1.0</span> <span class="k">else</span> <span class="mf">0.0</span><span class="o">,</span>
+ <span class="n">e</span><span class="o">.</span><span class="n">properties</span><span class="o">.</span><span class="n">get</span><span class="o">[</span><span class="kt">String</span><span class="o">](</span><span class="s">"text"</span><span class="o">),</span>
+ <span class="n">label</span>
+ <span class="o">)</span>
+ <span class="o">}).</span><span class="n">cache</span>
+ <span class="o">}</span>
+
+ <span class="c1">// Helper function used to store stop words from
+</span> <span class="c1">// event server.
+</span> <span class="k">private</span> <span class="k">def</span> <span class="n">readStopWords</span><span class="o">(</span><span class="n">sc</span> <span class="k">:</span> <span class="kt">SparkContext</span><span class="o">)</span> <span class="k">:</span> <span class="kt">Set</span><span class="o">[</span><span class="kt">String</span><span class="o">]</span> <span class="k">=</span> <span class="o">{</span>
+ <span class="nc">PEventStore</span><span class="o">.</span><span class="n">find</span><span class="o">(</span>
+ <span class="n">appName</span> <span class="k">=</span> <span class="n">dsp</span><span class="o">.</span><span class="n">appName</span><span class="o">,</span>
+ <span class="n">entityType</span> <span class="k">=</span> <span class="nc">Some</span><span class="o">(</span><span class="s">"resource"</span><span class="o">),</span>
+ <span class="n">eventNames</span> <span class="k">=</span> <span class="nc">Some</span><span class="o">(</span><span class="nc">List</span><span class="o">(</span><span class="s">"stopwords"</span><span class="o">))</span>
+
+ <span class="c1">//Convert collected RDD of strings to a string set.
+</span> <span class="o">)(</span><span class="n">sc</span><span class="o">)</span>
+ <span class="o">.</span><span class="n">map</span><span class="o">(</span><span class="n">e</span> <span class="k">=></span> <span class="n">e</span><span class="o">.</span><span class="n">properties</span><span class="o">.</span><span class="n">get</span><span class="o">[</span><span class="kt">String</span><span class="o">](</span><span class="s">"word"</span><span class="o">))</span>
+ <span class="o">.</span><span class="n">collect</span>
+ <span class="o">.</span><span class="n">toSet</span>
+ <span class="o">}</span>
+<span class="o">...</span>
+</pre></td></tr></tbody></table> </div> <p>Note that <code>readEventData</code> and <code>readStopWords</code> use different entity types and event names, but use the same application name. This is because the sample import script imports two different data types, documents and stop words. These field distinctions are required for distinguishing between the two. The method <code>readEval</code> is used to prepare the different cross-validation folds needed for evaluating your model and tuning hyper parameters.</p><p>Now, the default dataset used for training is contained in the file <code>data/emails.json</code> and contains a set of e-mail spam data. If we want to switch over to one of the other data sets we must make sure that the <code>eventNames</code> and <code>entityType</code> fields are changed accordingly.</p><p>In the data/ directory, you will find different sets of data files for different types of text classifcaiton application. The following show one observation from ea
ch of the provided data files:</p> <ul> <li><code>emails.json</code>:</li> </ul> <div class="highlight shell"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1
+2</pre></td><td class="code"><pre><span class="o">{</span><span class="s2">"eventTime"</span>: <span class="s2">"2015-06-08T16:45:00.590+0000"</span>, <span class="s2">"entityId"</span>: 1, <span class="s2">"properties"</span>: <span class="o">{</span><span class="s2">"text"</span>: <span class="s2">"Subject: dobmeos with hgh my energy level has gone up ! stukm</span><span class="se">\n</span><span class="s2">introducing</span><span class="se">\n</span><span class="s2">doctor - formulated</span><span class="se">\n</span><span class="s2">hgh</span><span class="se">\n</span><span class="s2">human growth hormone - also called hgh</span><span class="se">\n</span><span class="s2">is referred to in medical science as the master hormone . it is very plentiful</span><span class="se">\n</span><span class="s2">when we are young , but near the age of twenty - one our bodies begin to produce</span><span class="se">\n</span><span class="s2">less of it . by the time we are forty nearly everyone i
s deficient in hgh ,</span><span class="se">\n</span><span class="s2">and at eighty our production has normally diminished at least 90 - 95 % .</span><span class="se">\n</span><span class="s2">advantages of hgh :</span><span class="se">\n</span><span class="s2">- increased muscle strength</span><span class="se">\n</span><span class="s2">- loss in body fat</span><span class="se">\n</span><span class="s2">- increased bone density</span><span class="se">\n</span><span class="s2">- lower blood pressure</span><span class="se">\n</span><span class="s2">- quickens wound healing</span><span class="se">\n</span><span class="s2">- reduces cellulite</span><span class="se">\n</span><span class="s2">- improved vision</span><span class="se">\n</span><span class="s2">- wrinkle disappearance</span><span class="se">\n</span><span class="s2">- increased skin thickness texture</span><span class="se">\n</span><span class="s2">- increased energy levels</span><span class="se">\n</span><span class="s2">-
improved sleep and emotional stability</span><span class="se">\n</span><span class="s2">- improved memory and mental alertness</span><span class="se">\n</span><span class="s2">- increased sexual potency</span><span class="se">\n</span><span class="s2">- resistance to common illness</span><span class="se">\n</span><span class="s2">- strengthened heart muscle</span><span class="se">\n</span><span class="s2">- controlled cholesterol</span><span class="se">\n</span><span class="s2">- controlled mood swings</span><span class="se">\n</span><span class="s2">- new hair growth and color restore</span><span class="se">\n</span><span class="s2">read</span><span class="se">\n</span><span class="s2">more at this website</span><span class="se">\n</span><span class="s2">unsubscribe</span><span class="se">\n</span><span class="s2">"</span>, <span class="s2">"label"</span>: <span class="s2">"spam"</span><span class="o">}</span>, <span class="s2">"event"</span>: <span class="s2">"e-mail"</span>, <spa
n class="s2">"entityType"</span>: <span class="s2">"content"</span><span class="o">}</span>
+
+</pre></td></tr></tbody></table> </div> <ul> <li><code>20newsgroups.json</code>:</li> </ul> <div class="highlight shell"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1</pre></td><td class="code"><pre><span class="o">{</span><span class="s2">"entityType"</span>: <span class="s2">"source"</span>, <span class="s2">"eventTime"</span>: <span class="s2">"2015-06-08T18:01:55.003+0000"</span>, <span class="s2">"event"</span>: <span class="s2">"documents"</span>, <span class="s2">"entityId"</span>: 1, <span class="s2">"properties"</span>: <span class="o">{</span><span class="s2">"category"</span>: <span class="s2">"sci.crypt"</span>, <span class="s2">"text"</span>: <span class="s2">"From: rj@ri.cadre.com (Rob deFriesse)</span><span class="se">\n</span><span class="s2">Subject: Can DES code be shipped to Canada?</span><span class="se">\n</span><span class="s2">Article-I.D.: fripp.1993Apr22.125402.27561</span><span class="se">\
n</span><span class="s2">Reply-To: rj@ri.cadre.com</span><span class="se">\n</span><span class="s2">Organization: Cadre Technologies Inc.</span><span class="se">\n</span><span class="s2">Lines: 13</span><span class="se">\n</span><span class="s2">Nntp-Posting-Host: 192.9.200.19</span><span class="se">\n\n</span><span class="s2">Someone in Canada asked me to send him some public domain DES file</span><span class="se">\n</span><span class="s2">encryption code I have. Is it legal for me to send it?</span><span class="se">\n\n</span><span class="s2">Thanx.</span><span class="se">\n</span><span class="s2">--</span><span class="se">\n</span><span class="s2">Eschew Obfuscation</span><span class="se">\n\n</span><span class="s2">Rob deFriesse Mail: rj@ri.cadre.com</span><span class="se">\n</span><span class="s2">Cadre Technologies Inc. Phone: (401) 351-5950</span><span class="se">\n</span><span class="s2">222 Richmond St. Fax: (401) 351-7380</
span><span class="se">\n</span><span class="s2">Providence, RI 02903</span><span class="se">\n\n</span><span class="s2">I don't speak for my employer.</span><span class="se">\n</span><span class="s2">"</span>, <span class="s2">"label"</span>: 11.0<span class="o">}}</span>
+</pre></td></tr></tbody></table> </div> <ul> <li><code>sentimentanalysis.json</code>:</li> </ul> <div class="highlight shell"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1</pre></td><td class="code"><pre><span class="o">{</span><span class="s2">"eventTime"</span>: <span class="s2">"2015-06-08T16:58:14.278+0000"</span>, <span class="s2">"entityId"</span>: 23714, <span class="s2">"entityType"</span>: <span class="s2">"source"</span>, <span class="s2">"properties"</span>: <span class="o">{</span><span class="s2">"phrase"</span>: <span class="s2">"Tosca 's intoxicating ardor"</span>, <span class="s2">"sentiment"</span>: 3<span class="o">}</span>, <span class="s2">"event"</span>: <span class="s2">"phrases"</span><span class="o">}</span>
+</pre></td></tr></tbody></table> </div> <p>Now, note that the <code>entityType</code>, <code>event</code>, and <code>properties</code> fields for the <code>20newsgroups.json</code> dataset differ from the default <code>emails.json</code> set. Default DataSource implementation is to read from <code>email.json</code> data set. If you want to use others such as newsgroups data set, the engine's Data Source component must be modified accordingly. To do this, you need only modify the method <code>readEventData</code> as follows:</p><h3 id='modify-datasource-to-read-<code>20newsgroups.json</code>' class='header-anchors' >Modify DataSource to Read <code>20newsgroups.json</code></h3><div class="highlight scala"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1
+2
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+10
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+18</pre></td><td class="code"><pre><span class="k">private</span> <span class="k">def</span> <span class="n">readEventData</span><span class="o">(</span><span class="n">sc</span><span class="k">:</span> <span class="kt">SparkContext</span><span class="o">)</span> <span class="k">:</span> <span class="kt">RDD</span><span class="o">[</span><span class="kt">Observation</span><span class="o">]</span> <span class="k">=</span> <span class="o">{</span>
+ <span class="c1">//Get RDD of Events.
+</span> <span class="nc">PEventStore</span><span class="o">.</span><span class="n">find</span><span class="o">(</span>
+ <span class="n">appName</span> <span class="k">=</span> <span class="n">dsp</span><span class="o">.</span><span class="n">appName</span><span class="o">,</span>
+ <span class="n">entityType</span> <span class="k">=</span> <span class="nc">Some</span><span class="o">(</span><span class="s">"source"</span><span class="o">),</span> <span class="c1">// specify data entity type
+</span> <span class="n">eventNames</span> <span class="k">=</span> <span class="nc">Some</span><span class="o">(</span><span class="nc">List</span><span class="o">(</span><span class="s">"documents"</span><span class="o">))</span> <span class="c1">// specify data event name
+</span>
+ <span class="c1">// Convert collected RDD of events to and RDD of Observation
+</span> <span class="c1">// objects.
+</span> <span class="o">)(</span><span class="n">sc</span><span class="o">).</span><span class="n">map</span><span class="o">(</span><span class="n">e</span> <span class="k">=></span> <span class="o">{</span>
+
+ <span class="nc">Observation</span><span class="o">(</span>
+ <span class="n">e</span><span class="o">.</span><span class="n">properties</span><span class="o">.</span><span class="n">get</span><span class="o">[</span><span class="kt">Double</span><span class="o">](</span><span class="s">"label"</span><span class="o">),</span>
+ <span class="n">e</span><span class="o">.</span><span class="n">properties</span><span class="o">.</span><span class="n">get</span><span class="o">[</span><span class="kt">String</span><span class="o">](</span><span class="s">"text"</span><span class="o">),</span>
+ <span class="n">e</span><span class="o">.</span><span class="n">properties</span><span class="o">.</span><span class="n">get</span><span class="o">[</span><span class="kt">String</span><span class="o">](</span><span class="s">"category"</span><span class="o">)</span>
+ <span class="o">)</span>
+ <span class="o">}).</span><span class="n">cache</span>
+ <span class="o">}</span>
+</pre></td></tr></tbody></table> </div> <h3 id='modify-datasource-to-read-<code>sentimentanalysis.json</code>' class='header-anchors' >Modify DataSource to Read <code>sentimentanalysis.json</code></h3><div class="highlight scala"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1
+2
+3
+4
+5
+6
+7
+8
+9
+10
+11
+12
+13
+14
+15
+16
+17
+18
+19</pre></td><td class="code"><pre><span class="k">private</span> <span class="k">def</span> <span class="n">readEventData</span><span class="o">(</span><span class="n">sc</span><span class="k">:</span> <span class="kt">SparkContext</span><span class="o">)</span> <span class="k">:</span> <span class="kt">RDD</span><span class="o">[</span><span class="kt">Observation</span><span class="o">]</span> <span class="k">=</span> <span class="o">{</span>
+ <span class="c1">//Get RDD of Events.
+</span> <span class="nc">PEventStore</span><span class="o">.</span><span class="n">find</span><span class="o">(</span>
+ <span class="n">appName</span> <span class="k">=</span> <span class="n">dsp</span><span class="o">.</span><span class="n">appName</span><span class="o">,</span>
+ <span class="n">entityType</span> <span class="k">=</span> <span class="nc">Some</span><span class="o">(</span><span class="s">"source"</span><span class="o">),</span> <span class="c1">// specify data entity type
+</span> <span class="n">eventNames</span> <span class="k">=</span> <span class="nc">Some</span><span class="o">(</span><span class="nc">List</span><span class="o">(</span><span class="s">"phrases"</span><span class="o">))</span> <span class="c1">// specify data event name
+</span>
+ <span class="c1">// Convert collected RDD of events to and RDD of Observation
+</span> <span class="c1">// objects.
+</span> <span class="o">)(</span><span class="n">sc</span><span class="o">).</span><span class="n">map</span><span class="o">(</span><span class="n">e</span> <span class="k">=></span> <span class="o">{</span>
+ <span class="k">val</span> <span class="n">label</span> <span class="k">=</span> <span class="n">e</span><span class="o">.</span><span class="n">properties</span><span class="o">.</span><span class="n">get</span><span class="o">[</span><span class="kt">Double</span><span class="o">](</span><span class="s">"sentiment"</span><span class="o">)</span>
+
+ <span class="nc">Observation</span><span class="o">(</span>
+ <span class="n">label</span><span class="o">,</span>
+ <span class="n">e</span><span class="o">.</span><span class="n">properties</span><span class="o">.</span><span class="n">get</span><span class="o">[</span><span class="kt">String</span><span class="o">](</span><span class="s">"phrase"</span><span class="o">),</span>
+ <span class="n">label</span><span class="o">.</span><span class="n">toString</span>
+ <span class="o">)</span>
+ <span class="o">}).</span><span class="n">cache</span>
+ <span class="o">}</span>
+</pre></td></tr></tbody></table> </div> <p>Note that <code>event</code> field in the json file refers to the <code>eventNames</code> field in the <code>readEventData</code> method. When using this engine with a custom data set, you need to make sure that the respective json fields match with the corresponding fields in the DataSource component. We have included a data sanity check with this engine component that lets you know if your data is actually being read in. If you have 0 observations being read, you should see the following output when your training process performs the Training Data sanity check:</p><p><code>Data set is empty, make sure event fields match imported data.</code></p><p>This data sanity check is a PredictionIO feature available for your <code>TrainingData</code> and <code>PreparedData</code> classes. The following code block demonstrates how the sanity check is implemented:</p><div class="highlight scala"><table style="border-spacing: 0"><tbody><tr><td class="g
utter gl" style="text-align: right"><pre class="lineno">1
+2
+3
+4
+5
+6
+7
+8
+9
+10
+11
+12
+13
+14
+15
+16
+17
+18
+19
+20
+21
+22
+23
+24
+25
+26
+27</pre></td><td class="code"><pre><span class="k">class</span> <span class="nc">TrainingData</span><span class="o">(</span>
+ <span class="k">val</span> <span class="n">data</span> <span class="k">:</span> <span class="kt">RDD</span><span class="o">[</span><span class="kt">Observation</span><span class="o">],</span>
+ <span class="k">val</span> <span class="n">stopWords</span> <span class="k">:</span> <span class="kt">Set</span><span class="o">[</span><span class="kt">String</span><span class="o">]</span>
+<span class="o">)</span> <span class="k">extends</span> <span class="nc">Serializable</span> <span class="k">with</span> <span class="nc">SanityCheck</span> <span class="o">{</span>
+
+ <span class="c1">// Sanity check to make sure your data is being fed in correctly.
+</span>
+ <span class="k">def</span> <span class="n">sanityCheck</span> <span class="o">{</span>
+ <span class="k">try</span> <span class="o">{</span>
+ <span class="k">val</span> <span class="n">obs</span> <span class="k">:</span> <span class="kt">Array</span><span class="o">[</span><span class="kt">Double</span><span class="o">]</span> <span class="k">=</span> <span class="n">data</span><span class="o">.</span><span class="n">takeSample</span><span class="o">(</span><span class="kc">false</span><span class="o">,</span> <span class="mi">5</span><span class="o">).</span><span class="n">map</span><span class="o">(</span><span class="k">_</span><span class="o">.</span><span class="n">label</span><span class="o">)</span>
+
+ <span class="n">println</span><span class="o">()</span>
+ <span class="o">(</span><span class="mi">0</span> <span class="n">until</span> <span class="mi">5</span><span class="o">).</span><span class="n">foreach</span><span class="o">(</span>
+ <span class="n">k</span> <span class="k">=></span> <span class="n">println</span><span class="o">(</span><span class="s">"Observation "</span> <span class="o">+</span> <span class="o">(</span><span class="n">k</span> <span class="o">+</span> <span class="mi">1</span><span class="o">)</span> <span class="o">+</span><span class="s">" label: "</span> <span class="o">+</span> <span class="n">obs</span><span class="o">(</span><span class="n">k</span><span class="o">))</span>
+ <span class="o">)</span>
+ <span class="n">println</span><span class="o">()</span>
+ <span class="o">}</span> <span class="k">catch</span> <span class="o">{</span>
+ <span class="k">case</span> <span class="o">(</span><span class="n">e</span> <span class="k">:</span> <span class="kt">ArrayIndexOutOfBoundsException</span><span class="o">)</span> <span class="k">=></span> <span class="o">{</span>
+ <span class="n">println</span><span class="o">()</span>
+ <span class="n">println</span><span class="o">(</span><span class="s">"Data set is empty, make sure event fields match imported data."</span><span class="o">)</span>
+ <span class="n">println</span><span class="o">()</span>
+ <span class="o">}</span>
+ <span class="o">}</span>
+
+ <span class="o">}</span>
+
+<span class="o">}</span>
+</pre></td></tr></tbody></table> </div> <h2 id='preparator-:-data-processing-with-dase' class='header-anchors'>Preparator : Data Processing With DASE</h2><p>Recall that the Preparator stage is used for doing any prior data processing needed to fit a predictive model. In line with the separation of concerns, the Data Model implementation, PreparedData, is built to do the heavy lifting needed for this data processing. The Preparator must simply implement the prepare method which outputs an object of type PreparedData. This requires you to specify two n-gram window components, and two inverse i.d.f. window components (these terms will be defined in the following section). Therefore a custom class of parameters for the Preparator component, PreparatorParams, must be incorporated. The code defining the full Preparator component is given below:</p><div class="highlight scala"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1
+2
+3
+4
+5
+6
+7
+8
+9
+10
+11
+12
+13
+14
+15
+16
+17
+18
+19
+20
+21
+22</pre></td><td class="code"><pre><span class="c1">// 1. Initialize Preparator parameters. Recall that for our data
+// representation we are only required to input the n-gram window
+// components.
+</span>
+<span class="k">case</span> <span class="k">class</span> <span class="nc">PreparatorParams</span><span class="o">(</span>
+ <span class="n">nGram</span><span class="k">:</span> <span class="kt">Int</span><span class="o">,</span>
+ <span class="n">numFeatures</span><span class="k">:</span> <span class="kt">Int</span> <span class="o">=</span> <span class="mi">5000</span><span class="o">,</span>
+ <span class="nc">SPPMI</span><span class="k">:</span> <span class="kt">Boolean</span>
+<span class="o">)</span> <span class="k">extends</span> <span class="nc">Params</span>
+
+
+
+<span class="c1">// 2. Initialize your Preparator class.
+</span>
+<span class="k">class</span> <span class="nc">Preparator</span><span class="o">(</span><span class="n">pp</span><span class="k">:</span> <span class="kt">PreparatorParams</span><span class="o">)</span> <span class="k">extends</span> <span class="nc">PPreparator</span><span class="o">[</span><span class="kt">TrainingData</span>, <span class="kt">PreparedData</span><span class="o">]</span> <span class="o">{</span>
+
+ <span class="c1">// Prepare your training data.
+</span> <span class="k">def</span> <span class="n">prepare</span><span class="o">(</span><span class="n">sc</span> <span class="k">:</span> <span class="kt">SparkContext</span><span class="o">,</span> <span class="n">td</span><span class="k">:</span> <span class="kt">TrainingData</span><span class="o">)</span><span class="k">:</span> <span class="kt">PreparedData</span> <span class="o">=</span> <span class="o">{</span>
+ <span class="k">new</span> <span class="nc">PreparedData</span><span class="o">(</span><span class="n">td</span><span class="o">,</span> <span class="n">pp</span><span class="o">.</span><span class="n">nGram</span><span class="o">)</span>
+ <span class="o">}</span>
+<span class="o">}</span>
+
+</pre></td></tr></tbody></table> </div> <p>The simplicity of this stage implementation truly exemplifies one of the benefits of using the PredictionIO platform. For developers, it is easy to incorporate different classes and tools into the DASE framework so that the process of creating an engine is greatly simplified which helps increase your productivity. For data scientists, the load of implementation details you need to worry about is minimized so that you can focus on what is important to you: training a good predictive model.</p><p>The following subsection explains the class PreparedData, which actually handles the transformation of text documents to feature vectors.</p><h3 id='prepareddata:-text-vectorization-and-feature-reduction' class='header-anchors'>PreparedData: Text Vectorization and Feature Reduction</h3><p>The Scala class PreparedData which takes the parameters td, nGram, where td is an object of class TrainingData. The other parameter specifies the n-gram parametriza
tion which will be described shortly.</p><p>It will be easier to explain the preparation process with an example, so consider the document \(d\):</p><p><code>"Hello, my name is Marco."</code></p><p>The first thing you need to do is break up \(d\) into an array of "allowed tokens." You can think of a token as a terminating sequence of characters that exist in a document (think of a word in a sentence). For example, the list of tokens that appear in \(d\) is:</p><div class="highlight scala"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1</pre></td><td class="code"><pre><span class="k">val</span> <span class="n">A</span> <span class="k">=</span> <span class="nc">Array</span><span class="o">(</span><span class="s">"Hello"</span><span class="o">,</span> <span class="s">","</span><span class="o">,</span> <span class="s">"my"</span><span class="o">,</span> <span class="s">"name"</span><span class="o">,</
span> <span class="s">"is"</span><span class="o">,</span> <span class="s">"Marco"</span><span class="o">,</span> <span class="s">"."</span><span class="o">)</span>
+</pre></td></tr></tbody></table> </div> <p>Recall that a set of stop words was also imported in the previous sections. This set of stop words contains all the words (or tokens) that you do not want to include once documents are tokenized. Those tokens that appear in \(d\) and are not contained in the set of stop words will be called allowed tokens. So, if the set of stop words is <code>{"my", "is"}</code>, then the list of allowed tokens appearing in \(d\) is:</p><div class="highlight scala"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1</pre></td><td class="code"><pre><span class="k">val</span> <span class="n">A</span> <span class="k">=</span> <span class="nc">Array</span><span class="o">(</span><span class="s">"Hello"</span><span class="o">,</span> <span class="s">","</span><span class="o">,</span> <span class="s">"name"</span><span class="o">,</span> <span class="s">"Marco"</span><span class="
o">,</span> <span class="s">"."</span><span class="o">)</span>
+</pre></td></tr></tbody></table> </div> <p>The next step in the data representation is to take the array of allowed tokens and extract a set of n-grams and a corresponding value indicating the number of times a given n-gram appears. The set of n-grams for n equal to 1 and 2 in the running example is the set of elements of the form <code>[A(</code>\(i\)<code>)]</code> and <code>[A(</code>\(j\)<code>), A(</code>\(j + 1\)<code>)]</code>, respectively. In the general case, the set of n-grams extracted from an array of allowed tokens <code>A</code> will be of the form <code>[A(</code>\(i\)<code>), A(</code>\(i + 1\)<code>), ..., A(</code>\(i + n - 1\)<code>)]</code> for \(i = 0, 1, 2, ...,\) <code>A.size</code> \(- n\). You can set <code>n</code> with the <code>nGram</code> parameter option in your <code>PreparatorParams</code>.</p><p>We use MLLib's <code>HashingTF</code> class to implement the conversion from text to term frequency vectors, and can be seen in the following method of
the class <code>PreparedData</code>:</p><div class="highlight scala"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1
+2
+3
+4
+5
+6
+7
+8
+9
+10
+11
+12
+13
+14
+15
+16
+17
+18</pre></td><td class="code"><pre><span class="o">...</span>
+ <span class="c1">// 1. Hashing function: Text -> term frequency vector.
+</span>
+ <span class="k">private</span> <span class="k">val</span> <span class="n">hasher</span> <span class="k">=</span> <span class="k">new</span> <span class="nc">HashingTF</span><span class="o">()</span>
+
+ <span class="k">private</span> <span class="k">def</span> <span class="n">hashTF</span> <span class="o">(</span><span class="n">text</span> <span class="k">:</span> <span class="kt">String</span><span class="o">)</span> <span class="k">:</span> <span class="kt">Vector</span> <span class="o">=</span> <span class="o">{</span>
+ <span class="k">val</span> <span class="n">newList</span> <span class="k">:</span> <span class="kt">Array</span><span class="o">[</span><span class="kt">String</span><span class="o">]</span> <span class="k">=</span> <span class="n">text</span><span class="o">.</span><span class="n">split</span><span class="o">(</span><span class="s">" "</span><span class="o">)</span>
+ <span class="o">.</span><span class="n">sliding</span><span class="o">(</span><span class="n">nGram</span><span class="o">)</span>
+ <span class="o">.</span><span class="n">map</span><span class="o">(</span><span class="k">_</span><span class="o">.</span><span class="n">mkString</span><span class="o">)</span>
+ <span class="o">.</span><span class="n">toArray</span>
+
+ <span class="n">hasher</span><span class="o">.</span><span class="n">transform</span><span class="o">(</span><span class="n">newList</span><span class="o">)</span>
+ <span class="o">}</span>
+
+ <span class="c1">// 2. Term frequency vector -> t.f.-i.d.f. vector.
+</span>
+ <span class="k">val</span> <span class="n">idf</span> <span class="k">:</span> <span class="kt">IDFModel</span> <span class="o">=</span> <span class="k">new</span> <span class="nc">IDF</span><span class="o">().</span><span class="n">fit</span><span class="o">(</span><span class="n">td</span><span class="o">.</span><span class="n">data</span><span class="o">.</span><span class="n">map</span><span class="o">(</span><span class="n">e</span> <span class="k">=></span> <span class="n">hashTF</span><span class="o">(</span><span class="n">e</span><span class="o">.</span><span class="n">text</span><span class="o">)))</span>
+<span class="o">...</span>
+</pre></td></tr></tbody></table> </div> <p>The next step is, once all of the observations have been hashed, to collect all n-grams and compute their corresponding <a href="http://en.wikipedia.org/wiki/Tf%E2%80%93idf">t.f.-i.d.f. value</a>. The t.f.-i.d.f. transformation is defined for n-grams, and helps to give less weight to those n-grams that appear with high frequency across all documents, and vice versa. This helps to leverage the predictive power of those words that appear rarely, but can make a big difference in the categorization of a given text document. This is implemented using MLLib's <code>IDF</code> and <code>IDFModel</code> classes:</p><div class="highlight scala"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1
+2
+3</pre></td><td class="code"><pre><span class="c1">// 2. Term frequency vector -> t.f.-i.d.f. vector.
+</span>
+ <span class="k">val</span> <span class="n">idf</span> <span class="k">:</span> <span class="kt">IDFModel</span> <span class="o">=</span> <span class="k">new</span> <span class="nc">IDF</span><span class="o">().</span><span class="n">fit</span><span class="o">(</span><span class="n">td</span><span class="o">.</span><span class="n">data</span><span class="o">.</span><span class="n">map</span><span class="o">(</span><span class="n">e</span> <span class="k">=></span> <span class="n">hashTF</span><span class="o">(</span><span class="n">e</span><span class="o">.</span><span class="n">text</span><span class="o">)))</span>
+</pre></td></tr></tbody></table> </div> <p>The last two functions that will be mentioned are the methods you will actually use for the data transformation. The method transform takes a document and outputs a sparse vector (MLLib implementation). The transformData method simply transforms the TrainingData input (a corpus of documents) into a set of vectors that can now be used for training. The method transform is used both to transform the training data and future queries.</p><div class="highlight scala"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1
+2
+3
+4
+5
+6
+7
+8
+9
+10
+11
+12
+13
+14</pre></td><td class="code"><pre><span class="o">...</span>
+<span class="c1">// 3. Document Transformer: text => tf-idf vector.
+</span>
+ <span class="k">def</span> <span class="n">transform</span><span class="o">(</span><span class="n">text</span> <span class="k">:</span> <span class="kt">String</span><span class="o">)</span><span class="k">:</span> <span class="kt">Vector</span> <span class="o">=</span> <span class="o">{</span>
+ <span class="c1">// Map(n-gram -> document tf)
+</span> <span class="n">idf</span><span class="o">.</span><span class="n">transform</span><span class="o">(</span><span class="n">hashTF</span><span class="o">(</span><span class="n">text</span><span class="o">))</span>
+ <span class="o">}</span>
+
+
+ <span class="c1">// 4. Data Transformer: RDD[documents] => RDD[LabeledPoints]
+</span>
+ <span class="k">val</span> <span class="n">transformedData</span><span class="k">:</span> <span class="kt">RDD</span><span class="o">[(</span><span class="kt">LabeledPoint</span><span class="o">)]</span> <span class="k">=</span> <span class="o">{</span>
+ <span class="n">td</span><span class="o">.</span><span class="n">data</span><span class="o">.</span><span class="n">map</span><span class="o">(</span><span class="n">e</span> <span class="k">=></span> <span class="nc">LabeledPoint</span><span class="o">(</span><span class="n">e</span><span class="o">.</span><span class="n">label</span><span class="o">,</span> <span class="n">transform</span><span class="o">(</span><span class="n">e</span><span class="o">.</span><span class="n">text</span><span class="o">)))</span>
+ <span class="o">}</span>
+</pre></td></tr></tbody></table> </div> <p>The last and final object implemented in this class simply creates a Map with keys being class labels and values, the corresponding category.</p><div class="highlight scala"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1
+2</pre></td><td class="code"><pre> <span class="c1">// 5. Finally extract category map, associating label to category.
+</span> <span class="k">val</span> <span class="n">categoryMap</span> <span class="k">=</span> <span class="n">td</span><span class="o">.</span><span class="n">data</span><span class="o">.</span><span class="n">map</span><span class="o">(</span><span class="n">e</span> <span class="k">=></span> <span class="o">(</span><span class="n">e</span><span class="o">.</span><span class="n">label</span><span class="o">,</span> <span class="n">e</span><span class="o">.</span><span class="n">category</span><span class="o">)).</span><span class="n">collectAsMap</span>
+</pre></td></tr></tbody></table> </div> <h2 id='algorithm-component' class='header-anchors'>Algorithm Component</h2><p>The algorithm components in this engine, <code>NBAlgorithm</code> and <code>LRAlgorithm</code>, actually follows a very general form. Firstly, a parameter class must again be initialized to feed in the corresponding Algorithm model parameters. For example, NBAlgorithm incorporates NBAlgorithmParams which holds the appropriate additive smoothing parameter lambda for the Naive Bayes model.</p><p>The main class of interest in this component is the class that extends <a href="https://docs.prediction.io/api/current/#io.prediction.controller.P2LAlgorithm">P2LAlgorithm</a>. This class must implement a method named train which will output your predictive model (as a concrete object, this will be implemented via a Scala class). It must also implement a predict method that transforms a query to an appropriate feature vector, and uses this to predict with the fitted model. The
vectorization function is implemented by a PreparedData object, and the categorization (prediction) is handled by an instance of the NBModel implementation. Again, this demonstrates the facility with which different models can be incorporated into PredictionIO's DASE architecture.</p><p>The model class itself will be discussed in the following section, however, turn your attention to the TextManipulationEngine object defined in the script <code>Engine.scala</code>. You can see here that the engine is initialized by specifying the DataSource, Preparator, and Serving classes, as well as a Map of algorithm names to Algorithm classes. This tells the engine which algorithms to run. In practice, you can have as many statistical learning models as you'd like, you simply have to implement a new algorithm component to do this. However, this general design form will persist, and the main meat of the work should be in the implementation of your model class.</p><p>The following subsect
ion will go over our Naive Bayes implementation in NBModel.</p><h3 id='naive-bayes-classification' class='header-anchors'>Naive Bayes Classification</h3><p>This Training Model class only uses the Multinomial Naive Bayes <a href="https://spark.apache.org/docs/latest/mllib-naive-bayes.html">implementation</a> found in the Spark MLLib library. However, recall that the predicted results required in the specifications listed in the overview are of the form:</p><p><code>{category: String, confidence: Double}</code>.</p><p>The confidence value should really be interpreted as the probability that a document belongs to a category given its vectorized form. Note that MLLib's Naive Bayes model has the class members pi (\(\pi\)), and theta (\(\theta\)). \(\pi\) is a vector of log prior class probabilities, which shows your prior beliefs regarding the probability that an arbitrary document belongs in a category. \(\theta\) is a C \(\times\) D matrix, where C is the number of classes, and D,
the number of features, giving the log probabilities that parametrize the Multinomial likelihood model assumed for each class. The multinomial model is easiest to think about as a problem of randomly throwing balls into bins, where the ball lands in each bin with a certain probability. The model treats each n-gram as a bin, and the corresponding t.f.-i.d.f. value as the number of balls thrown into it. The likelihood is the probability of observing a (vectorized) document given that it comes from a particular class.</p><p>Now, letting \(\mathbf{x}\) be a vectorized text document, then it can be shown that the vector</p><p>$$ \frac{\exp\left(\pi + \theta\mathbf{x}\right)}{\left|\left|\exp\left(\pi + \theta\mathbf{x}\right)\right|\right|} $$</p><p>is a vector with C components that represent the posterior class membership probabilities for the document given \(\mathbf{x}\). That is, the update belief regarding what category this document belongs to after observing its vectorized form.
This is the motivation behind defining the class NBModel which uses Spark MLLib's NaiveBayesModel, but implements a separate prediction method.</p><p>The private methods innerProduct and getScores are implemented to do the matrix computation above.</p><div class="highlight scala"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1
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+ <span class="c1">// 2. Set up linear algebra framework.
+</span>
+ <span class="k">private</span> <span class="k">def</span> <span class="n">innerProduct</span> <span class="o">(</span><span class="n">x</span> <span class="k">:</span> <span class="kt">Array</span><span class="o">[</span><span class="kt">Double</span><span class="o">],</span> <span class="n">y</span> <span class="k">:</span> <span class="kt">Array</span><span class="o">[</span><span class="kt">Double</span><span class="o">])</span> <span class="k">:</span> <span class="kt">Double</span> <span class="o">=</span> <span class="o">{</span>
+ <span class="n">x</span><span class="o">.</span><span class="n">zip</span><span class="o">(</span><span class="n">y</span><span class="o">).</span><span class="n">map</span><span class="o">(</span><span class="n">e</span> <span class="k">=></span> <span class="n">e</span><span class="o">.</span><span class="n">_1</span> <span class="o">*</span> <span class="n">e</span><span class="o">.</span><span class="n">_2</span><span class="o">).</span><span class="n">sum</span>
+ <span class="o">}</span>
+
+ <span class="k">val</span> <span class="n">normalize</span> <span class="k">=</span> <span class="o">(</span><span class="n">u</span><span class="k">:</span> <span class="kt">Array</span><span class="o">[</span><span class="kt">Double</span><span class="o">])</span> <span class="k">=></span> <span class="o">{</span>
+ <span class="k">val</span> <span class="n">uSum</span> <span class="k">=</span> <span class="n">u</span><span class="o">.</span><span class="n">sum</span>
+
+ <span class="n">u</span><span class="o">.</span><span class="n">map</span><span class="o">(</span><span class="n">e</span> <span class="k">=></span> <span class="n">e</span> <span class="o">/</span> <span class="n">uSum</span><span class="o">)</span>
+ <span class="o">}</span>
+
+
+
+ <span class="c1">// 3. Given a document string, return a vector of corresponding
+</span> <span class="c1">// class membership probabilities.
+</span>
+ <span class="k">private</span> <span class="k">def</span> <span class="n">getScores</span><span class="o">(</span><span class="n">doc</span><span class="k">:</span> <span class="kt">String</span><span class="o">)</span><span class="k">:</span> <span class="kt">Array</span><span class="o">[</span><span class="kt">Double</span><span class="o">]</span> <span class="k">=</span> <span class="o">{</span>
+ <span class="c1">// Helper function used to normalize probability scores.
+</span> <span class="c1">// Returns an object of type Array[Double]
+</span>
+ <span class="c1">// Vectorize query,
+</span> <span class="k">val</span> <span class="n">x</span><span class="k">:</span> <span class="kt">Vector</span> <span class="o">=</span> <span class="n">pd</span><span class="o">.</span><span class="n">transform</span><span class="o">(</span><span class="n">doc</span><span class="o">)</span>
+
+ <span class="n">normalize</span><span class="o">(</span>
+ <span class="n">nb</span><span class="o">.</span><span class="n">pi</span>
+ <span class="o">.</span><span class="n">zip</span><span class="o">(</span><span class="n">nb</span><span class="o">.</span><span class="n">theta</span><span class="o">)</span>
+ <span class="o">.</span><span class="n">map</span><span class="o">(</span>
+ <span class="n">e</span> <span class="k">=></span> <span class="n">exp</span><span class="o">(</span><span class="n">innerProduct</span><span class="o">(</span><span class="n">e</span><span class="o">.</span><span class="n">_2</span><span class="o">,</span> <span class="n">x</span><span class="o">.</span><span class="n">toArray</span><span class="o">)</span> <span class="o">+</span> <span class="n">e</span><span class="o">.</span><span class="n">_1</span><span class="o">))</span>
+ <span class="o">)</span>
+ <span class="o">}</span>
+<span class="o">...</span>
+</pre></td></tr></tbody></table> </div> <p>Once you have a vector of class probabilities, you can classify the text document to the category with highest posterior probability, and, finally, return both the category as well as the probability of belonging to that category (i.e. the confidence in the prediction) given the observed data. This is implemented in the method predict.</p><div class="highlight scala"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1
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+9</pre></td><td class="code"><pre><span class="o">...</span>
+ <span class="c1">// 4. Implement predict method for our model using
+</span> <span class="c1">// the prediction rule given in tutorial.
+</span>
+ <span class="k">def</span> <span class="n">predict</span><span class="o">(</span><span class="n">doc</span> <span class="k">:</span> <span class="kt">String</span><span class="o">)</span> <span class="k">:</span> <span class="kt">PredictedResult</span> <span class="o">=</span> <span class="o">{</span>
+ <span class="k">val</span> <span class="n">x</span><span class="k">:</span> <span class="kt">Array</span><span class="o">[</span><span class="kt">Double</span><span class="o">]</span> <span class="k">=</span> <span class="n">getScores</span><span class="o">(</span><span class="n">doc</span><span class="o">)</span>
+ <span class="k">val</span> <span class="n">y</span><span class="k">:</span> <span class="o">(</span><span class="kt">Double</span><span class="o">,</span> <span class="kt">Double</span><span class="o">)</span> <span class="k">=</span> <span class="o">(</span><span class="n">nb</span><span class="o">.</span><span class="n">labels</span> <span class="n">zip</span> <span class="n">x</span><span class="o">).</span><span class="n">maxBy</span><span class="o">(</span><span class="k">_</span><span class="o">.</span><span class="n">_2</span><span class="o">)</span>
+ <span class="k">new</span> <span class="nc">PredictedResult</span><span class="o">(</span><span class="n">pd</span><span class="o">.</span><span class="n">categoryMap</span><span class="o">.</span><span class="n">getOrElse</span><span class="o">(</span><span class="n">y</span><span class="o">.</span><span class="n">_1</span><span class="o">,</span> <span class="s">""</span><span class="o">),</span> <span class="n">y</span><span class="o">.</span><span class="n">_2</span><span class="o">)</span>
+ <span class="o">}</span>
+</pre></td></tr></tbody></table> </div> <h3 id='logistic-regression-classification' class='header-anchors'>Logistic Regression Classification</h3><p>To use the alternative multinomial logistic regression algorithm change your <code>engine.json</code> as follows:</p><div class="highlight json"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1
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+ </span><span class="s2">"id"</span><span class="p">:</span><span class="w"> </span><span class="s2">"default"</span><span class="p">,</span><span class="w">
+ </span><span class="s2">"description"</span><span class="p">:</span><span class="w"> </span><span class="s2">"Default settings"</span><span class="p">,</span><span class="w">
+ </span><span class="s2">"engineFactory"</span><span class="p">:</span><span class="w"> </span><span class="s2">"org.template.textclassification.TextClassificationEngine"</span><span class="p">,</span><span class="w">
+ </span><span class="s2">"datasource"</span><span class="p">:</span><span class="w"> </span><span class="p">{</span><span class="w">
+ </span><span class="s2">"params"</span><span class="p">:</span><span class="w"> </span><span class="p">{</span><span class="w">
+ </span><span class="s2">"appName"</span><span class="p">:</span><span class="w"> </span><span class="s2">"MyTextApp"</span><span class="w">
+ </span><span class="p">}</span><span class="w">
+ </span><span class="p">},</span><span class="w">
+ </span><span class="s2">"preparator"</span><span class="p">:</span><span class="w"> </span><span class="p">{</span><span class="w">
+ </span><span class="s2">"params"</span><span class="p">:</span><span class="w"> </span><span class="p">{</span><span class="w">
+ </span><span class="s2">"nGram"</span><span class="p">:</span><span class="w"> </span><span class="mi">2</span><span class="w">
+ </span><span class="p">}</span><span class="w">
+ </span><span class="p">},</span><span class="w">
+ </span><span class="s2">"algorithms"</span><span class="p">:</span><span class="w"> </span><span class="p">[</span><span class="w">
+ </span><span class="p">{</span><span class="w">
+ </span><span class="s2">"name"</span><span class="p">:</span><span class="w"> </span><span class="s2">"regParam"</span><span class="p">,</span><span class="w">
+ </span><span class="s2">"params"</span><span class="p">:</span><span class="w"> </span><span class="p">{</span><span class="w">
+ </span><span class="s2">"regParam"</span><span class="p">:</span><span class="w"> </span><span class="mf">0.1</span><span class="w">
+ </span><span class="p">}</span><span class="w">
+ </span><span class="p">}</span><span class="w">
+ </span><span class="p">]</span><span class="w">
+</span><span class="p">}</span><span class="w">
+</span></pre></td></tr></tbody></table> </div> <h2 id='serving:-delivering-the-final-prediction' class='header-anchors'>Serving: Delivering the Final Prediction</h2><p>The serving component is the final stage in the engine, and in a sense, the most important. This is the final stage in which you combine the results obtained from the different models you choose to run. The Serving class extends the <a href="https://docs.prediction.io/api/current/#io.prediction.controller.LServing">LServing</a> class which must implement a method called serve. This takes a query and an associated sequence of predicted results, which contains the predicted results from the different algorithms that are implemented in your engine, and combines the results to yield a final prediction. It is this final prediction that you will receive after sending a query.</p><p>For example, you could choose to slightly modify the implementation to return class probabilities coming from a mixture of model estimates for c
lass probabilities, or any other technique you could conceive for combining your results. The default engine setting has this set to yield the label from the model predicting with greater confidence.</p><h2 id='evaluation:-model-assessment-and-selection' class='header-anchors'>Evaluation: Model Assessment and Selection</h2><p> A predictive model needs to be evaluated to see how it will generalize to future observations. PredictionIO uses cross-validation to perform model performance metric estimates needed to assess your particular choice of model. The script <code>Evaluation.scala</code> available with the engine template exemplifies what a usual evaluator setup will look like. First, you must define an appropriate metric. In the engine template, since the topic is text classification, the default metric implemented is category accuracy.</p><p> Second you must define an evaluation object (i.e. extends the class <a href="https://docs.prediction.io/api/current/#io.prediction.controll
er.Evaluation">Evaluation</a>). Here, you must specify the actual engine and metric components that are to be used for the evaluation. In the engine template, the specified engine is the TextManipulationEngine object, and metric, Accuracy. Lastly, you must specify the parameter values that you want to test in the cross validation. You see in the following block of code:</p><div class="highlight scala"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1
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+
+ <span class="c1">// Set data source and preparator parameters.
+</span> <span class="k">private</span><span class="o">[</span><span class="kt">this</span><span class="o">]</span> <span class="k">val</span> <span class="n">baseEP</span> <span class="k">=</span> <span class="nc">EngineParams</span><span class="o">(</span>
+ <span class="n">dataSourceParams</span> <span class="k">=</span> <span class="nc">DataSourceParams</span><span class="o">(</span><span class="n">appName</span> <span class="k">=</span> <span class="s">"marco-MyTextApp"</span><span class="o">,</span>
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+ add DataSource exch get
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+ add
+ }for
+ end
+}bd
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+{
+ 2 copy lt
+ {exch pop}{pop}ifelse
+}bd
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+{
+ /Coords load aload pop
+ 3 index 3 index translate
+
+ 3 -1 roll sub
+ 3 1 roll exch
+ sub
+ 2 copy
+ dup mul exch dup mul add sqrt
+ dup
+ scale
+ atan
+
+ rotate
+
+ /Function load setupFunEval
+
+
+ clippath {pathbbox}stopped {0 0 0 0}if newpath
+ /ymax xs
+ /xmax xs
+ /ymin xs
+ /xmin xs
+ currentdict/Extend known
+ {
+ /Extend load 0 get
+ {
+ 0/Function load FunEval sc
+ xmin ymin xmin abs ymax ymin sub rectfill
+ }if
+ }if
+
+ /Nsteps/Function load/Size get 0 get 1 sub store
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+ gsave
+ /di ymax ymin sub store
+ /Function load
+
+ 0 1 Nsteps
+ {
+ 1 index FunEval sc
+ 0 ymin dx di rectfill
+ dx 0 translate
+ }for
+ pop
+ grestore
+ currentdict/Extend known
+ {
+ /Extend load 1 get
+ {
+ Nsteps/Function load FunEval sc
+ 1 ymin xmax 1 sub abs ymax ymin sub rectfill
+ }if
+ }if
+}bd
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+ 4 copy
+
+ dup 0 gt{
+ 0 exch a1 a0 arc
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+ pop 0 moveto
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+ dup 0 gt{
+ 0 exch a0 a1 arcn
+ }{
+ pop 0 lineto
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+
+ fill
+
+ dup 0 gt{
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+ }{
+ pop 0 moveto
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+ dup 0 gt{
+ 0 exch a1 a0 arcn
+ }{
+ pop 0 lineto
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+
+ fill
+}bd
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+{
+
+ xmin dup mul ymin dup mul add sqrt
+ xmax dup mul ymin dup mul add sqrt
+ xmin dup mul ymax dup mul add sqrt
+ xmax dup mul ymax dup mul add sqrt
+ max max max
+}bd
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+ /Coords load aload pop
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+ 3 -1 roll 5 -1 roll sub
+ 2 copy dup mul exch dup mul add sqrt
+ /dx xs
+ 2 copy 0 ne exch 0 ne or
+ {
+
+ exch atan rotate
+ }{
+ pop pop
+ }ifelse
+
+ /r2 xs
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+ /Function load
+ dup/Size get 0 get 1 sub
+ /Nsteps xs
+ setupFunEval
+
+
+
+
+
+ dx r2 add r1 lt{
+
+ 0
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+ {
+ 1
+ }{
+ r1 r2 eq
+ {
+ 2
+ }{
+ 3
+ }ifelse
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+ clippath {pathbbox}stopped {0 0 0 0}if
+ newpath
+ /ymax xs
+ /xmax xs
+ /ymin xs
+ /xmin xs
+
+ dx dup mul r2 r1 sub dup mul sub dup 0 gt
+ {
+ sqrt r2 r1 sub atan
+ /a0 exch 180 exch sub store
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+ }{
+ pop
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+ /Extend load 0 get r1 0 gt and
+ {
+ 0/Function load FunEval sc
+
+
+
+
+ {
+ {
+ dx 0 r1 360 0 arcn
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+
+
+
+
+ 0 r1 xmin abs r1 add neg r1 shp
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+
+ r2 r1 gt{
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+ 0 r1
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+
+
+
+ 0 r1 calcmaxs
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+ r2 add dx mul dx r1 r2 sub sub div
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+ /Function load
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+
+ d0 0 r0 a1 a0 arc
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+
+
+ d0 0 r0 a0 a1 arc
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+ fill
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+
+ /d0 d0 di add store
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+
+ currentdict/Extend known
+ {
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+ {
+ Nsteps/Function load FunEval sc
+
+
+
+
+ {
+ {
+ dx 0 r2 0 360 arc fill
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+ dx 0 r2 360 0 arcn
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+ eofill
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+
+ xmax abs r1 add r1 dx r1 shp
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+
+ r2 r1 gt{
+
+
+
+ calcmaxs dup
+
+ r1 add dx mul dx r2 r1 sub sub div
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+
+ r1 neg r2 r1 sub div dx mul
+ 0
+ dx
+ r2
+ shp
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+ }
+ sh3tp get exec
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+}bd
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+ gsave
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+ 3 -1 roll exch sub
+ exch rectclip
+ }if
+ 2 eq
+ {sh2}{sh3}ifelse
+ grestore
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+
+ pop
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+ }ifelse
+ end
+}bd
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+%%Trailer
+%%EOF
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[12/51] [partial] incubator-predictionio-site git commit: Initial doc
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+<!DOCTYPE html><html><head><title>PredictionIO - A Quick Intro</title><meta charset="utf-8"/><meta content="IE=edge,chrome=1" http-equiv="X-UA-Compatible"/><meta name="viewport" content="width=device-width, initial-scale=1.0"/><meta class="swiftype" name="title" data-type="string" content="PredictionIO - A Quick Intro"/><link rel="canonical" href="https://docs.prediction.io/start/"/><link href="/images/favicon/normal-b330020a.png" rel="shortcut icon"/><link href="/images/favicon/apple-c0febcf2.png" rel="apple-touch-icon"/><link href="//fonts.googleapis.com/css?family=Open+Sans:300italic,400italic,600italic,700italic,800italic,400,300,600,700,800" rel="stylesheet"/><link href="//maxcdn.bootstrapcdn.com/font-awesome/4.2.0/css/font-awesome.min.css" rel="stylesheet"/><link href="/stylesheets/application-3598c7d7.css" rel="stylesheet" type="text/css"/><!--[if lt IE 9]><script src="//cdnjs.cloudflare.com/ajax/libs/html5shiv/3.7.2/html5shiv.min.js"></script><![endif]--><script src="//cdn.m
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+fbq('track', "PageView");</script><script src="//use.typekit.net/mut4mjx.js"></script><script>try{Typekit.load();}catch(e){}</script></head><body><div id="global"><header><div class="container" id="header-wrapper"><div class="row"><div class="col-sm-12"><div id="logo-wrapper"><span id="drawer-toggle"></span><a href="#"></a><a href="http://prediction.io/"><img alt="PredictionIO" id="logo" src="/images/logos/logo-ee2b9bb3.png"/></a></div><div id="menu-wrapper"><div id="header-nav-options-wrapper"><ul><li><a href="/">Install & Doc</a></li> <li><a href="/support">Support</a></li> </ul></div><div id="pill-wrapper"><a class="pill left" href="//templates.prediction.io/">TEMPLATES</a> <a class="pill right" href="//github.com/PredictionIO/PredictionIO/">OPEN SOURCE</a></div></div><img class="mobile-search-bar-toggler hidden-md hidden-lg" src="/images/icons/search-glass-704bd4ff.png"/></div></div></div></header><div id="search-bar-row-wrapper"><div class="container-fluid" id="search-bar-row">
<div class="row"><div class="col-md-9 col-sm-11 col-xs-11"><div class="hidden-md hidden-lg" id="mobile-page-heading-wrapper"><p>PredictionIO Docs</p><h4>A Quick Intro</h4></div><h4 class="hidden-sm hidden-xs">PredictionIO Docs</h4></div><div class="col-md-3 col-sm-1 col-xs-1 hidden-md hidden-lg"><img id="left-menu-indicator" src="/images/icons/down-arrow-dfe9f7fe.png"/></div><div class="col-md-3 col-sm-12 col-xs-12 swiftype-wrapper"><div class="swiftype"><form class="search-form"><img class="search-box-toggler hidden-xs hidden-sm" src="/images/icons/search-glass-704bd4ff.png"/><div class="search-box"><img src="/images/icons/search-glass-704bd4ff.png"/><input type="text" id="st-search-input" class="st-search-input" placeholder="Search Doc..."/></div><img class="swiftype-row-hider hidden-md hidden-lg" src="/images/icons/drawer-toggle-active-fcbef12a.png"/></form></div></div><div class="mobile-left-menu-toggler hidden-md hidden-lg"></div></div></div></div><div id="page" class="containe
r-fluid"><div class="row"><div id="left-menu-wrapper" class="col-md-3"><nav id="nav-main"><ul><li class="level-1"><a class="expandible" href="/"><span>Apache PredictionIO (incubating) Documentation</span></a><ul><li class="level-2"><a class="final" href="/"><span>Welcome to Apache PredictionIO (incubating)</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Getting Started</span></a><ul><li class="level-2"><a class="final active" href="/start/"><span>A Quick Intro</span></a></li><li class="level-2"><a class="final" href="/install/"><span>Installing Apache PredictionIO (incubating)</span></a></li><li class="level-2"><a class="final" href="/start/download/"><span>Downloading an Engine Template</span></a></li><li class="level-2"><a class="final" href="/start/deploy/"><span>Deploying Your First Engine</span></a></li><li class="level-2"><a class="final" href="/start/customize/"><span>Customizing the Engine</span></a></li></ul></li><li class="level-1"><a clas
s="expandible" href="#"><span>Integrating with Your App</span></a><ul><li class="level-2"><a class="final" href="/appintegration/"><span>App Integration Overview</span></a></li><li class="level-2"><a class="expandible" href="/sdk/"><span>List of SDKs</span></a><ul><li class="level-3"><a class="final" href="/sdk/java/"><span>Java & Android SDK</span></a></li><li class="level-3"><a class="final" href="/sdk/php/"><span>PHP SDK</span></a></li><li class="level-3"><a class="final" href="/sdk/python/"><span>Python SDK</span></a></li><li class="level-3"><a class="final" href="/sdk/ruby/"><span>Ruby SDK</span></a></li><li class="level-3"><a class="final" href="/sdk/community/"><span>Community Powered SDKs</span></a></li></ul></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Deploying an Engine</span></a><ul><li class="level-2"><a class="final" href="/deploy/"><span>Deploying as a Web Service</span></a></li><li class="level-2"><a class="final" href="/cli/#engine-commands
"><span>Engine Command-line Interface</span></a></li><li class="level-2"><a class="final" href="/deploy/engineparams/"><span>Setting Engine Parameters</span></a></li><li class="level-2"><a class="final" href="/deploy/enginevariants/"><span>Deploying Multiple Engine Variants</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Customizing an Engine</span></a><ul><li class="level-2"><a class="final" href="/customize/"><span>Learning DASE</span></a></li><li class="level-2"><a class="final" href="/customize/dase/"><span>Implement DASE</span></a></li><li class="level-2"><a class="final" href="/customize/troubleshooting/"><span>Troubleshooting Engine Development</span></a></li><li class="level-2"><a class="final" href="/api/current/#package"><span>Engine Scala APIs</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Collecting and Analyzing Data</span></a><ul><li class="level-2"><a class="final" href="/datacollection/"><span>Event
Server Overview</span></a></li><li class="level-2"><a class="final" href="/cli/#event-server-commands"><span>Event Server Command-line Interface</span></a></li><li class="level-2"><a class="final" href="/datacollection/eventapi/"><span>Collecting Data with REST/SDKs</span></a></li><li class="level-2"><a class="final" href="/datacollection/eventmodel/"><span>Events Modeling</span></a></li><li class="level-2"><a class="final" href="/datacollection/webhooks/"><span>Unifying Multichannel Data with Webhooks</span></a></li><li class="level-2"><a class="final" href="/datacollection/channel/"><span>Channel</span></a></li><li class="level-2"><a class="final" href="/datacollection/batchimport/"><span>Importing Data in Batch</span></a></li><li class="level-2"><a class="final" href="/datacollection/analytics/"><span>Using Analytics Tools</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Choosing an Algorithm(s)</span></a><ul><li class="level-2"><a class="final"
href="/algorithm/"><span>Built-in Algorithm Libraries</span></a></li><li class="level-2"><a class="final" href="/algorithm/switch/"><span>Switching to Another Algorithm</span></a></li><li class="level-2"><a class="final" href="/algorithm/multiple/"><span>Combining Multiple Algorithms</span></a></li><li class="level-2"><a class="final" href="/algorithm/custom/"><span>Adding Your Own Algorithms</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>ML Tuning and Evaluation</span></a><ul><li class="level-2"><a class="final" href="/evaluation/"><span>Overview</span></a></li><li class="level-2"><a class="final" href="/evaluation/paramtuning/"><span>Hyperparameter Tuning</span></a></li><li class="level-2"><a class="final" href="/evaluation/evaluationdashboard/"><span>Evaluation Dashboard</span></a></li><li class="level-2"><a class="final" href="/evaluation/metricchoose/"><span>Choosing Evaluation Metrics</span></a></li><li class="level-2"><a class="final" href="
/evaluation/metricbuild/"><span>Building Evaluation Metrics</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>System Architecture</span></a><ul><li class="level-2"><a class="final" href="/system/"><span>Architecture Overview</span></a></li><li class="level-2"><a class="final" href="/system/anotherdatastore/"><span>Using Another Data Store</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Engine Template Gallery</span></a><ul><li class="level-2"><a class="final" href="http://templates.prediction.io"><span>Browse</span></a></li><li class="level-2"><a class="final" href="/community/submit-template/"><span>Submit your Engine as a Template</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Demo Tutorials</span></a><ul><li class="level-2"><a class="final" href="/demo/tapster/"><span>Comics Recommendation Demo</span></a></li><li class="level-2"><a class="final" href="/demo/community/"><span>Commu
nity Contributed Demo</span></a></li><li class="level-2"><a class="final" href="/demo/textclassification/"><span>Text Classification Engine Tutorial</span></a></li></ul></li><li class="level-1"><a class="expandible" href="/community/"><span>Getting Involved</span></a><ul><li class="level-2"><a class="final" href="/community/contribute-code/"><span>Contribute Code</span></a></li><li class="level-2"><a class="final" href="/community/contribute-documentation/"><span>Contribute Documentation</span></a></li><li class="level-2"><a class="final" href="/community/contribute-sdk/"><span>Contribute a SDK</span></a></li><li class="level-2"><a class="final" href="/community/contribute-webhook/"><span>Contribute a Webhook</span></a></li><li class="level-2"><a class="final" href="/community/projects/"><span>Community Projects</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Getting Help</span></a><ul><li class="level-2"><a class="final" href="/resources/faq/"><spa
n>FAQs</span></a></li><li class="level-2"><a class="final" href="/support/"><span>Community Support</span></a></li><li class="level-2"><a class="final" href="/support/#enterprise-support"><span>Enterprise Support</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Resources</span></a><ul><li class="level-2"><a class="final" href="/resources/intellij/"><span>Developing Engines with IntelliJ IDEA</span></a></li><li class="level-2"><a class="final" href="/resources/upgrade/"><span>Upgrade Instructions</span></a></li><li class="level-2"><a class="final" href="/resources/glossary/"><span>Glossary</span></a></li></ul></li></ul></nav></div><div class="col-md-9 col-sm-12"><div class="content-header hidden-md hidden-lg"><div id="breadcrumbs" class="hidden-sm hidden xs"><ul><li><a href="#">Getting Started</a><span class="spacer">></span></li><li><span class="last">A Quick Intro</span></li></ul></div><div id="page-title"><h1>PredictionIO - A Quick Intro</h1></d
iv></div><div id="table-of-content-wrapper"><h5>On this page</h5><aside id="table-of-contents"><ul> <li> <a href="#overview">Overview</a> </li> <li> <a href="#event-server">Event Server</a> </li> <li> <a href="#engine">Engine</a> </li> </ul> </aside><hr/><a id="edit-page-link" href="https://github.com/apache/incubator-predictionio/tree/livedoc/docs/manual/source/start/index.html.md"><img src="/images/icons/edit-pencil-d6c1bb3d.png"/>Edit this page</a></div><div class="content-header hidden-sm hidden-xs"><div id="breadcrumbs" class="hidden-sm hidden xs"><ul><li><a href="#">Getting Started</a><span class="spacer">></span></li><li><span class="last">A Quick Intro</span></li></ul></div><div id="page-title"><h1>PredictionIO - A Quick Intro</h1></div></div><div class="content"><h2 id='overview' class='header-anchors'>Overview</h2><p>PredictionIO consist of the following components:</p> <ul> <li><strong>PredictionIO platform</strong> - our open source machine learning stack for building
, evaluating and deploying engines with machine learning algorithms.</li> <li><strong>Event Server</strong> - our open source machine learning analytics layer for unifying events from multiple platforms</li> <li><strong>Template Gallery</strong> - the place for you to download engine templates for different type of machine learning applications</li> </ul> <p><img alt="PredictionIO Overview" src="/images/overview-multiengines-b703caac.png"/></p><h2 id='event-server' class='header-anchors'>Event Server</h2><p>In a common scenario, PredictionIO's <strong>Event Server</strong> continuously collects data from your application. A PredictionIO <strong>engine</strong> then builds predictive model(s) with one or more algorithms using the data. After it is deployed as a web service, it listens to queries from your application and respond with predicted results in real-time.</p><p><img alt="PredictionIO Single Engine Overview" src="/images/overview-singleengine-0a99200d.png"/></p><p><a hre
f="/datacollection/">Event Server</a> collects data from your application, in real-time or in batch. It can also unify data that are related to your application from multiple platforms. After data is collected, it mainly serves two purposes:</p> <ol> <li>Provide data to Engine(s) for model training and evaluation</li> <li>Offer a unified view for data analysis</li> </ol> <p>Like a database server, Event Server can host multiple applications. Data are separated for each application by a unique <em>app_name</em>.</p><p>Once Event Server is launched, you can send data to a specific <em>app_name</em>, identified by an Access Key, through its <a href="/datacollection/eventapi/">Event API</a> with HTTP requests or with <a href="/sdk/">one of the SDKs</a>.</p><p>In some special case, you may want your engine to read data from another datastore instead of Event Server. It can be achieved by <a href="#">making some modifications</a>.</p><h2 id='engine' class='header-anchors'>Engine</h2><p>En
gine is responsible for making prediction. It contains one or more machine learning algorithms. An engine reads training data and build predictive model(s). It is then deployed as a web service. A deployed engine responds to prediction queries from your application through REST API in real-time.</p><p>PredictionIO's <a href="http://templates.prediction.io/">template gallery</a> offers Engine Templates for all kinds of machine learning tasks. You can easily create one or more engines from these templates .</p><p>The components of a template, namely <strong>Data Source</strong>, <strong>Data Preparator</strong>, <strong>Algorithm(s)</strong>, and <strong>Serving</strong>, are all <a href="/start/customize/">customizable</a> for your specific needs.</p></div></div></div></div><footer><div class="container"><div class="seperator"></div><div class="row"><div class="col-md-4 col-md-push-8 col-xs-12"><div class="subscription-form-wrapper"><h4>Subscribe to our Newsletter</h4><form class
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<div class="row"><div class="col-md-9 col-sm-11 col-xs-11"><div class="hidden-md hidden-lg" id="mobile-page-heading-wrapper"><p>PredictionIO Docs</p><h4>Customizing the Engine</h4></div><h4 class="hidden-sm hidden-xs">PredictionIO Docs</h4></div><div class="col-md-3 col-sm-1 col-xs-1 hidden-md hidden-lg"><img id="left-menu-indicator" src="/images/icons/down-arrow-dfe9f7fe.png"/></div><div class="col-md-3 col-sm-12 col-xs-12 swiftype-wrapper"><div class="swiftype"><form class="search-form"><img class="search-box-toggler hidden-xs hidden-sm" src="/images/icons/search-glass-704bd4ff.png"/><div class="search-box"><img src="/images/icons/search-glass-704bd4ff.png"/><input type="text" id="st-search-input" class="st-search-input" placeholder="Search Doc..."/></div><img class="swiftype-row-hider hidden-md hidden-lg" src="/images/icons/drawer-toggle-active-fcbef12a.png"/></form></div></div><div class="mobile-left-menu-toggler hidden-md hidden-lg"></div></div></div></div><div id="page" class=
"container-fluid"><div class="row"><div id="left-menu-wrapper" class="col-md-3"><nav id="nav-main"><ul><li class="level-1"><a class="expandible" href="/"><span>Apache PredictionIO (incubating) Documentation</span></a><ul><li class="level-2"><a class="final" href="/"><span>Welcome to Apache PredictionIO (incubating)</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Getting Started</span></a><ul><li class="level-2"><a class="final" href="/start/"><span>A Quick Intro</span></a></li><li class="level-2"><a class="final" href="/install/"><span>Installing Apache PredictionIO (incubating)</span></a></li><li class="level-2"><a class="final" href="/start/download/"><span>Downloading an Engine Template</span></a></li><li class="level-2"><a class="final" href="/start/deploy/"><span>Deploying Your First Engine</span></a></li><li class="level-2"><a class="final active" href="/start/customize/"><span>Customizing the Engine</span></a></li></ul></li><li class="level-1
"><a class="expandible" href="#"><span>Integrating with Your App</span></a><ul><li class="level-2"><a class="final" href="/appintegration/"><span>App Integration Overview</span></a></li><li class="level-2"><a class="expandible" href="/sdk/"><span>List of SDKs</span></a><ul><li class="level-3"><a class="final" href="/sdk/java/"><span>Java & Android SDK</span></a></li><li class="level-3"><a class="final" href="/sdk/php/"><span>PHP SDK</span></a></li><li class="level-3"><a class="final" href="/sdk/python/"><span>Python SDK</span></a></li><li class="level-3"><a class="final" href="/sdk/ruby/"><span>Ruby SDK</span></a></li><li class="level-3"><a class="final" href="/sdk/community/"><span>Community Powered SDKs</span></a></li></ul></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Deploying an Engine</span></a><ul><li class="level-2"><a class="final" href="/deploy/"><span>Deploying as a Web Service</span></a></li><li class="level-2"><a class="final" href="/cli/#engine
-commands"><span>Engine Command-line Interface</span></a></li><li class="level-2"><a class="final" href="/deploy/engineparams/"><span>Setting Engine Parameters</span></a></li><li class="level-2"><a class="final" href="/deploy/enginevariants/"><span>Deploying Multiple Engine Variants</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Customizing an Engine</span></a><ul><li class="level-2"><a class="final" href="/customize/"><span>Learning DASE</span></a></li><li class="level-2"><a class="final" href="/customize/dase/"><span>Implement DASE</span></a></li><li class="level-2"><a class="final" href="/customize/troubleshooting/"><span>Troubleshooting Engine Development</span></a></li><li class="level-2"><a class="final" href="/api/current/#package"><span>Engine Scala APIs</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Collecting and Analyzing Data</span></a><ul><li class="level-2"><a class="final" href="/datacollection/"><s
pan>Event Server Overview</span></a></li><li class="level-2"><a class="final" href="/cli/#event-server-commands"><span>Event Server Command-line Interface</span></a></li><li class="level-2"><a class="final" href="/datacollection/eventapi/"><span>Collecting Data with REST/SDKs</span></a></li><li class="level-2"><a class="final" href="/datacollection/eventmodel/"><span>Events Modeling</span></a></li><li class="level-2"><a class="final" href="/datacollection/webhooks/"><span>Unifying Multichannel Data with Webhooks</span></a></li><li class="level-2"><a class="final" href="/datacollection/channel/"><span>Channel</span></a></li><li class="level-2"><a class="final" href="/datacollection/batchimport/"><span>Importing Data in Batch</span></a></li><li class="level-2"><a class="final" href="/datacollection/analytics/"><span>Using Analytics Tools</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Choosing an Algorithm(s)</span></a><ul><li class="level-2"><a class
="final" href="/algorithm/"><span>Built-in Algorithm Libraries</span></a></li><li class="level-2"><a class="final" href="/algorithm/switch/"><span>Switching to Another Algorithm</span></a></li><li class="level-2"><a class="final" href="/algorithm/multiple/"><span>Combining Multiple Algorithms</span></a></li><li class="level-2"><a class="final" href="/algorithm/custom/"><span>Adding Your Own Algorithms</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>ML Tuning and Evaluation</span></a><ul><li class="level-2"><a class="final" href="/evaluation/"><span>Overview</span></a></li><li class="level-2"><a class="final" href="/evaluation/paramtuning/"><span>Hyperparameter Tuning</span></a></li><li class="level-2"><a class="final" href="/evaluation/evaluationdashboard/"><span>Evaluation Dashboard</span></a></li><li class="level-2"><a class="final" href="/evaluation/metricchoose/"><span>Choosing Evaluation Metrics</span></a></li><li class="level-2"><a class="fina
l" href="/evaluation/metricbuild/"><span>Building Evaluation Metrics</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>System Architecture</span></a><ul><li class="level-2"><a class="final" href="/system/"><span>Architecture Overview</span></a></li><li class="level-2"><a class="final" href="/system/anotherdatastore/"><span>Using Another Data Store</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Engine Template Gallery</span></a><ul><li class="level-2"><a class="final" href="http://templates.prediction.io"><span>Browse</span></a></li><li class="level-2"><a class="final" href="/community/submit-template/"><span>Submit your Engine as a Template</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Demo Tutorials</span></a><ul><li class="level-2"><a class="final" href="/demo/tapster/"><span>Comics Recommendation Demo</span></a></li><li class="level-2"><a class="final" href="/demo/community/"><s
pan>Community Contributed Demo</span></a></li><li class="level-2"><a class="final" href="/demo/textclassification/"><span>Text Classification Engine Tutorial</span></a></li></ul></li><li class="level-1"><a class="expandible" href="/community/"><span>Getting Involved</span></a><ul><li class="level-2"><a class="final" href="/community/contribute-code/"><span>Contribute Code</span></a></li><li class="level-2"><a class="final" href="/community/contribute-documentation/"><span>Contribute Documentation</span></a></li><li class="level-2"><a class="final" href="/community/contribute-sdk/"><span>Contribute a SDK</span></a></li><li class="level-2"><a class="final" href="/community/contribute-webhook/"><span>Contribute a Webhook</span></a></li><li class="level-2"><a class="final" href="/community/projects/"><span>Community Projects</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Getting Help</span></a><ul><li class="level-2"><a class="final" href="/resources/f
aq/"><span>FAQs</span></a></li><li class="level-2"><a class="final" href="/support/"><span>Community Support</span></a></li><li class="level-2"><a class="final" href="/support/#enterprise-support"><span>Enterprise Support</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Resources</span></a><ul><li class="level-2"><a class="final" href="/resources/intellij/"><span>Developing Engines with IntelliJ IDEA</span></a></li><li class="level-2"><a class="final" href="/resources/upgrade/"><span>Upgrade Instructions</span></a></li><li class="level-2"><a class="final" href="/resources/glossary/"><span>Glossary</span></a></li></ul></li></ul></nav></div><div class="col-md-9 col-sm-12"><div class="content-header hidden-md hidden-lg"><div id="breadcrumbs" class="hidden-sm hidden xs"><ul><li><a href="#">Getting Started</a><span class="spacer">></span></li><li><span class="last">Customizing the Engine</span></li></ul></div><div id="page-title"><h1>Customizing an Eng
ine</h1></div></div><div id="table-of-content-wrapper"><a id="edit-page-link" href="https://github.com/apache/incubator-predictionio/tree/livedoc/docs/manual/source/start/customize.html.md"><img src="/images/icons/edit-pencil-d6c1bb3d.png"/>Edit this page</a></div><div class="content-header hidden-sm hidden-xs"><div id="breadcrumbs" class="hidden-sm hidden xs"><ul><li><a href="#">Getting Started</a><span class="spacer">></span></li><li><span class="last">Customizing the Engine</span></li></ul></div><div id="page-title"><h1>Customizing an Engine</h1></div></div><div class="content"><p>When you download an engine template, it comes with the source code. All engine templates follow the same DASE architecture and they are designed to be customizable.</p><p>You may want to customize an engine for many reasons, for example: </p> <ul> <li>Use another algorithm, or multiple of them</li> <li>Read data from a different, or existing, data store</li> <li>Read different types of training data
</li> <li>Transform data with another approach</li> <li>Add new evaluation measures</li> <li>Add custom business logics</li> </ul> <p>To learn more about DASE, please read "<a href="/customize/">Learning DASE</a>".</p><p>After you have finished modifying the code, you can re-build and deploy the engine again with:</p><div class="highlight shell"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1</pre></td><td class="code"><pre><span class="gp">$ </span>pio build; pio train; pio deploy
+</pre></td></tr></tbody></table> </div> </div></div></div></div><footer><div class="container"><div class="seperator"></div><div class="row"><div class="col-md-4 col-md-push-8 col-xs-12"><div class="subscription-form-wrapper"><h4>Subscribe to our Newsletter</h4><form class="ajax-form" id="subscribe-form" method="POST" action="https://script.google.com/macros/s/AKfycbwhzeKCQJjQ52eVAqNT_vcklH07OITUO7wzOMDXvK6EGAWgaZgF/exec"><input class="required underlined-input" type="email" placeholder="Your email address" name="subscription_email" id="subscription_email"/><input class="pill-button" value="SUBSCRIBE" type="submit" data-state-normal="SUBSCRIBE" data-state-sucess="SUBSCRIBED!" data-state-loading="SENDING..." onclick="t($('#subscription_email').val());"/><p class="result"></p></form></div></div><div class="col-md-2 col-md-pull-4 col-xs-6 footer-link-column"><div class="footer-link-column-row"><h4>Community</h4><ul><li><a href="//docs.prediction.io/install/" target="blank">Download</a>
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<div class="row"><div class="col-md-9 col-sm-11 col-xs-11"><div class="hidden-md hidden-lg" id="mobile-page-heading-wrapper"><p>PredictionIO Docs</p><h4>Deploying Your First Engine</h4></div><h4 class="hidden-sm hidden-xs">PredictionIO Docs</h4></div><div class="col-md-3 col-sm-1 col-xs-1 hidden-md hidden-lg"><img id="left-menu-indicator" src="/images/icons/down-arrow-dfe9f7fe.png"/></div><div class="col-md-3 col-sm-12 col-xs-12 swiftype-wrapper"><div class="swiftype"><form class="search-form"><img class="search-box-toggler hidden-xs hidden-sm" src="/images/icons/search-glass-704bd4ff.png"/><div class="search-box"><img src="/images/icons/search-glass-704bd4ff.png"/><input type="text" id="st-search-input" class="st-search-input" placeholder="Search Doc..."/></div><img class="swiftype-row-hider hidden-md hidden-lg" src="/images/icons/drawer-toggle-active-fcbef12a.png"/></form></div></div><div class="mobile-left-menu-toggler hidden-md hidden-lg"></div></div></div></div><div id="page" c
lass="container-fluid"><div class="row"><div id="left-menu-wrapper" class="col-md-3"><nav id="nav-main"><ul><li class="level-1"><a class="expandible" href="/"><span>Apache PredictionIO (incubating) Documentation</span></a><ul><li class="level-2"><a class="final" href="/"><span>Welcome to Apache PredictionIO (incubating)</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Getting Started</span></a><ul><li class="level-2"><a class="final" href="/start/"><span>A Quick Intro</span></a></li><li class="level-2"><a class="final" href="/install/"><span>Installing Apache PredictionIO (incubating)</span></a></li><li class="level-2"><a class="final" href="/start/download/"><span>Downloading an Engine Template</span></a></li><li class="level-2"><a class="final active" href="/start/deploy/"><span>Deploying Your First Engine</span></a></li><li class="level-2"><a class="final" href="/start/customize/"><span>Customizing the Engine</span></a></li></ul></li><li class="le
vel-1"><a class="expandible" href="#"><span>Integrating with Your App</span></a><ul><li class="level-2"><a class="final" href="/appintegration/"><span>App Integration Overview</span></a></li><li class="level-2"><a class="expandible" href="/sdk/"><span>List of SDKs</span></a><ul><li class="level-3"><a class="final" href="/sdk/java/"><span>Java & Android SDK</span></a></li><li class="level-3"><a class="final" href="/sdk/php/"><span>PHP SDK</span></a></li><li class="level-3"><a class="final" href="/sdk/python/"><span>Python SDK</span></a></li><li class="level-3"><a class="final" href="/sdk/ruby/"><span>Ruby SDK</span></a></li><li class="level-3"><a class="final" href="/sdk/community/"><span>Community Powered SDKs</span></a></li></ul></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Deploying an Engine</span></a><ul><li class="level-2"><a class="final" href="/deploy/"><span>Deploying as a Web Service</span></a></li><li class="level-2"><a class="final" href="/cli/#e
ngine-commands"><span>Engine Command-line Interface</span></a></li><li class="level-2"><a class="final" href="/deploy/engineparams/"><span>Setting Engine Parameters</span></a></li><li class="level-2"><a class="final" href="/deploy/enginevariants/"><span>Deploying Multiple Engine Variants</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Customizing an Engine</span></a><ul><li class="level-2"><a class="final" href="/customize/"><span>Learning DASE</span></a></li><li class="level-2"><a class="final" href="/customize/dase/"><span>Implement DASE</span></a></li><li class="level-2"><a class="final" href="/customize/troubleshooting/"><span>Troubleshooting Engine Development</span></a></li><li class="level-2"><a class="final" href="/api/current/#package"><span>Engine Scala APIs</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Collecting and Analyzing Data</span></a><ul><li class="level-2"><a class="final" href="/datacollection
/"><span>Event Server Overview</span></a></li><li class="level-2"><a class="final" href="/cli/#event-server-commands"><span>Event Server Command-line Interface</span></a></li><li class="level-2"><a class="final" href="/datacollection/eventapi/"><span>Collecting Data with REST/SDKs</span></a></li><li class="level-2"><a class="final" href="/datacollection/eventmodel/"><span>Events Modeling</span></a></li><li class="level-2"><a class="final" href="/datacollection/webhooks/"><span>Unifying Multichannel Data with Webhooks</span></a></li><li class="level-2"><a class="final" href="/datacollection/channel/"><span>Channel</span></a></li><li class="level-2"><a class="final" href="/datacollection/batchimport/"><span>Importing Data in Batch</span></a></li><li class="level-2"><a class="final" href="/datacollection/analytics/"><span>Using Analytics Tools</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Choosing an Algorithm(s)</span></a><ul><li class="level-2"><a
class="final" href="/algorithm/"><span>Built-in Algorithm Libraries</span></a></li><li class="level-2"><a class="final" href="/algorithm/switch/"><span>Switching to Another Algorithm</span></a></li><li class="level-2"><a class="final" href="/algorithm/multiple/"><span>Combining Multiple Algorithms</span></a></li><li class="level-2"><a class="final" href="/algorithm/custom/"><span>Adding Your Own Algorithms</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>ML Tuning and Evaluation</span></a><ul><li class="level-2"><a class="final" href="/evaluation/"><span>Overview</span></a></li><li class="level-2"><a class="final" href="/evaluation/paramtuning/"><span>Hyperparameter Tuning</span></a></li><li class="level-2"><a class="final" href="/evaluation/evaluationdashboard/"><span>Evaluation Dashboard</span></a></li><li class="level-2"><a class="final" href="/evaluation/metricchoose/"><span>Choosing Evaluation Metrics</span></a></li><li class="level-2"><a class=
"final" href="/evaluation/metricbuild/"><span>Building Evaluation Metrics</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>System Architecture</span></a><ul><li class="level-2"><a class="final" href="/system/"><span>Architecture Overview</span></a></li><li class="level-2"><a class="final" href="/system/anotherdatastore/"><span>Using Another Data Store</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Engine Template Gallery</span></a><ul><li class="level-2"><a class="final" href="http://templates.prediction.io"><span>Browse</span></a></li><li class="level-2"><a class="final" href="/community/submit-template/"><span>Submit your Engine as a Template</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Demo Tutorials</span></a><ul><li class="level-2"><a class="final" href="/demo/tapster/"><span>Comics Recommendation Demo</span></a></li><li class="level-2"><a class="final" href="/demo/community
/"><span>Community Contributed Demo</span></a></li><li class="level-2"><a class="final" href="/demo/textclassification/"><span>Text Classification Engine Tutorial</span></a></li></ul></li><li class="level-1"><a class="expandible" href="/community/"><span>Getting Involved</span></a><ul><li class="level-2"><a class="final" href="/community/contribute-code/"><span>Contribute Code</span></a></li><li class="level-2"><a class="final" href="/community/contribute-documentation/"><span>Contribute Documentation</span></a></li><li class="level-2"><a class="final" href="/community/contribute-sdk/"><span>Contribute a SDK</span></a></li><li class="level-2"><a class="final" href="/community/contribute-webhook/"><span>Contribute a Webhook</span></a></li><li class="level-2"><a class="final" href="/community/projects/"><span>Community Projects</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Getting Help</span></a><ul><li class="level-2"><a class="final" href="/resour
ces/faq/"><span>FAQs</span></a></li><li class="level-2"><a class="final" href="/support/"><span>Community Support</span></a></li><li class="level-2"><a class="final" href="/support/#enterprise-support"><span>Enterprise Support</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Resources</span></a><ul><li class="level-2"><a class="final" href="/resources/intellij/"><span>Developing Engines with IntelliJ IDEA</span></a></li><li class="level-2"><a class="final" href="/resources/upgrade/"><span>Upgrade Instructions</span></a></li><li class="level-2"><a class="final" href="/resources/glossary/"><span>Glossary</span></a></li></ul></li></ul></nav></div><div class="col-md-9 col-sm-12"><div class="content-header hidden-md hidden-lg"><div id="breadcrumbs" class="hidden-sm hidden xs"><ul><li><a href="#">Getting Started</a><span class="spacer">></span></li><li><span class="last">Deploying Your First Engine</span></li></ul></div><div id="page-title"><h1>Deployin
g your first Engine</h1></div></div><div id="table-of-content-wrapper"><a id="edit-page-link" href="https://github.com/apache/incubator-predictionio/tree/livedoc/docs/manual/source/start/deploy.html.md.erb"><img src="/images/icons/edit-pencil-d6c1bb3d.png"/>Edit this page</a></div><div class="content-header hidden-sm hidden-xs"><div id="breadcrumbs" class="hidden-sm hidden xs"><ul><li><a href="#">Getting Started</a><span class="spacer">></span></li><li><span class="last">Deploying Your First Engine</span></li></ul></div><div id="page-title"><h1>Deploying your first Engine</h1></div></div><div class="content"><p>Once you have created an engine from a template, it is time to deploy it as a web service. One or more of your applications can then send real-time prediction queries to it.</p><p>It takes 6 simple steps to deploy and use an engine:</p> <ol> <li>Install and Run PredictionIO</li> <li>Create an Engine by downloading an Engine Template</li> <li>Generate an App ID and Access K
ey, if you are integrating PredictionIO with a new application</li> <li>Collecting Data</li> <li>Deploy the Engine as a Service</li> <li>Use the Engine</li> </ol> <p>The <a href="/templates/recommendation/quickstart/">QuickStart</a> of the basic Recommendation template is a great step-by-step guide especially if you are new to PredictionIO.</p><p>Of course, you may also browse the QuickStart of other engine templates in the template gallery.</p></div></div></div></div><footer><div class="container"><div class="seperator"></div><div class="row"><div class="col-md-4 col-md-push-8 col-xs-12"><div class="subscription-form-wrapper"><h4>Subscribe to our Newsletter</h4><form class="ajax-form" id="subscribe-form" method="POST" action="https://script.google.com/macros/s/AKfycbwhzeKCQJjQ52eVAqNT_vcklH07OITUO7wzOMDXvK6EGAWgaZgF/exec"><input class="required underlined-input" type="email" placeholder="Your email address" name="subscription_email" id="subscription_email"/><input class="pill-butto
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+fbq('track', "PageView");</script><script src="//use.typekit.net/mut4mjx.js"></script><script>try{Typekit.load();}catch(e){}</script></head><body><div id="global"><header><div class="container" id="header-wrapper"><div class="row"><div class="col-sm-12"><div id="logo-wrapper"><span id="drawer-toggle"></span><a href="#"></a><a href="http://prediction.io/"><img alt="PredictionIO" id="logo" src="/images/logos/logo-ee2b9bb3.png"/></a></div><div id="menu-wrapper"><div id="header-nav-options-wrapper"><ul><li><a href="/">Install & Doc</a></li> <li><a href="/support">Support</a></li> </ul></div><div id="pill-wrapper"><a class="pill left" href="//templates.prediction.io/">TEMPLATES</a> <a class="pill right" href="//github.com/PredictionIO/PredictionIO/">OPEN SOURCE</a></div></div><img class="mobile-search-bar-toggler hidden-md hidden-lg" src="/images/icons/search-glass-704bd4ff.png"/></div></div></div></header><div id="search-bar-row-wrapper"><div class="container-fluid" id="search-bar-row">
<div class="row"><div class="col-md-9 col-sm-11 col-xs-11"><div class="hidden-md hidden-lg" id="mobile-page-heading-wrapper"><p>PredictionIO Docs</p><h4>Downloading an Engine Template</h4></div><h4 class="hidden-sm hidden-xs">PredictionIO Docs</h4></div><div class="col-md-3 col-sm-1 col-xs-1 hidden-md hidden-lg"><img id="left-menu-indicator" src="/images/icons/down-arrow-dfe9f7fe.png"/></div><div class="col-md-3 col-sm-12 col-xs-12 swiftype-wrapper"><div class="swiftype"><form class="search-form"><img class="search-box-toggler hidden-xs hidden-sm" src="/images/icons/search-glass-704bd4ff.png"/><div class="search-box"><img src="/images/icons/search-glass-704bd4ff.png"/><input type="text" id="st-search-input" class="st-search-input" placeholder="Search Doc..."/></div><img class="swiftype-row-hider hidden-md hidden-lg" src="/images/icons/drawer-toggle-active-fcbef12a.png"/></form></div></div><div class="mobile-left-menu-toggler hidden-md hidden-lg"></div></div></div></div><div id="page
" class="container-fluid"><div class="row"><div id="left-menu-wrapper" class="col-md-3"><nav id="nav-main"><ul><li class="level-1"><a class="expandible" href="/"><span>Apache PredictionIO (incubating) Documentation</span></a><ul><li class="level-2"><a class="final" href="/"><span>Welcome to Apache PredictionIO (incubating)</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Getting Started</span></a><ul><li class="level-2"><a class="final" href="/start/"><span>A Quick Intro</span></a></li><li class="level-2"><a class="final" href="/install/"><span>Installing Apache PredictionIO (incubating)</span></a></li><li class="level-2"><a class="final active" href="/start/download/"><span>Downloading an Engine Template</span></a></li><li class="level-2"><a class="final" href="/start/deploy/"><span>Deploying Your First Engine</span></a></li><li class="level-2"><a class="final" href="/start/customize/"><span>Customizing the Engine</span></a></li></ul></li><li class=
"level-1"><a class="expandible" href="#"><span>Integrating with Your App</span></a><ul><li class="level-2"><a class="final" href="/appintegration/"><span>App Integration Overview</span></a></li><li class="level-2"><a class="expandible" href="/sdk/"><span>List of SDKs</span></a><ul><li class="level-3"><a class="final" href="/sdk/java/"><span>Java & Android SDK</span></a></li><li class="level-3"><a class="final" href="/sdk/php/"><span>PHP SDK</span></a></li><li class="level-3"><a class="final" href="/sdk/python/"><span>Python SDK</span></a></li><li class="level-3"><a class="final" href="/sdk/ruby/"><span>Ruby SDK</span></a></li><li class="level-3"><a class="final" href="/sdk/community/"><span>Community Powered SDKs</span></a></li></ul></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Deploying an Engine</span></a><ul><li class="level-2"><a class="final" href="/deploy/"><span>Deploying as a Web Service</span></a></li><li class="level-2"><a class="final" href="/cli
/#engine-commands"><span>Engine Command-line Interface</span></a></li><li class="level-2"><a class="final" href="/deploy/engineparams/"><span>Setting Engine Parameters</span></a></li><li class="level-2"><a class="final" href="/deploy/enginevariants/"><span>Deploying Multiple Engine Variants</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Customizing an Engine</span></a><ul><li class="level-2"><a class="final" href="/customize/"><span>Learning DASE</span></a></li><li class="level-2"><a class="final" href="/customize/dase/"><span>Implement DASE</span></a></li><li class="level-2"><a class="final" href="/customize/troubleshooting/"><span>Troubleshooting Engine Development</span></a></li><li class="level-2"><a class="final" href="/api/current/#package"><span>Engine Scala APIs</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Collecting and Analyzing Data</span></a><ul><li class="level-2"><a class="final" href="/datacollect
ion/"><span>Event Server Overview</span></a></li><li class="level-2"><a class="final" href="/cli/#event-server-commands"><span>Event Server Command-line Interface</span></a></li><li class="level-2"><a class="final" href="/datacollection/eventapi/"><span>Collecting Data with REST/SDKs</span></a></li><li class="level-2"><a class="final" href="/datacollection/eventmodel/"><span>Events Modeling</span></a></li><li class="level-2"><a class="final" href="/datacollection/webhooks/"><span>Unifying Multichannel Data with Webhooks</span></a></li><li class="level-2"><a class="final" href="/datacollection/channel/"><span>Channel</span></a></li><li class="level-2"><a class="final" href="/datacollection/batchimport/"><span>Importing Data in Batch</span></a></li><li class="level-2"><a class="final" href="/datacollection/analytics/"><span>Using Analytics Tools</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Choosing an Algorithm(s)</span></a><ul><li class="level-2">
<a class="final" href="/algorithm/"><span>Built-in Algorithm Libraries</span></a></li><li class="level-2"><a class="final" href="/algorithm/switch/"><span>Switching to Another Algorithm</span></a></li><li class="level-2"><a class="final" href="/algorithm/multiple/"><span>Combining Multiple Algorithms</span></a></li><li class="level-2"><a class="final" href="/algorithm/custom/"><span>Adding Your Own Algorithms</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>ML Tuning and Evaluation</span></a><ul><li class="level-2"><a class="final" href="/evaluation/"><span>Overview</span></a></li><li class="level-2"><a class="final" href="/evaluation/paramtuning/"><span>Hyperparameter Tuning</span></a></li><li class="level-2"><a class="final" href="/evaluation/evaluationdashboard/"><span>Evaluation Dashboard</span></a></li><li class="level-2"><a class="final" href="/evaluation/metricchoose/"><span>Choosing Evaluation Metrics</span></a></li><li class="level-2"><a cla
ss="final" href="/evaluation/metricbuild/"><span>Building Evaluation Metrics</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>System Architecture</span></a><ul><li class="level-2"><a class="final" href="/system/"><span>Architecture Overview</span></a></li><li class="level-2"><a class="final" href="/system/anotherdatastore/"><span>Using Another Data Store</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Engine Template Gallery</span></a><ul><li class="level-2"><a class="final" href="http://templates.prediction.io"><span>Browse</span></a></li><li class="level-2"><a class="final" href="/community/submit-template/"><span>Submit your Engine as a Template</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Demo Tutorials</span></a><ul><li class="level-2"><a class="final" href="/demo/tapster/"><span>Comics Recommendation Demo</span></a></li><li class="level-2"><a class="final" href="/demo/commun
ity/"><span>Community Contributed Demo</span></a></li><li class="level-2"><a class="final" href="/demo/textclassification/"><span>Text Classification Engine Tutorial</span></a></li></ul></li><li class="level-1"><a class="expandible" href="/community/"><span>Getting Involved</span></a><ul><li class="level-2"><a class="final" href="/community/contribute-code/"><span>Contribute Code</span></a></li><li class="level-2"><a class="final" href="/community/contribute-documentation/"><span>Contribute Documentation</span></a></li><li class="level-2"><a class="final" href="/community/contribute-sdk/"><span>Contribute a SDK</span></a></li><li class="level-2"><a class="final" href="/community/contribute-webhook/"><span>Contribute a Webhook</span></a></li><li class="level-2"><a class="final" href="/community/projects/"><span>Community Projects</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Getting Help</span></a><ul><li class="level-2"><a class="final" href="/res
ources/faq/"><span>FAQs</span></a></li><li class="level-2"><a class="final" href="/support/"><span>Community Support</span></a></li><li class="level-2"><a class="final" href="/support/#enterprise-support"><span>Enterprise Support</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Resources</span></a><ul><li class="level-2"><a class="final" href="/resources/intellij/"><span>Developing Engines with IntelliJ IDEA</span></a></li><li class="level-2"><a class="final" href="/resources/upgrade/"><span>Upgrade Instructions</span></a></li><li class="level-2"><a class="final" href="/resources/glossary/"><span>Glossary</span></a></li></ul></li></ul></nav></div><div class="col-md-9 col-sm-12"><div class="content-header hidden-md hidden-lg"><div id="breadcrumbs" class="hidden-sm hidden xs"><ul><li><a href="#">Getting Started</a><span class="spacer">></span></li><li><span class="last">Downloading an Engine Template</span></li></ul></div><div id="page-title"><h1>Do
wnloading an Engine Template</h1></div></div><div id="table-of-content-wrapper"><a id="edit-page-link" href="https://github.com/apache/incubator-predictionio/tree/livedoc/docs/manual/source/start/download.html.md"><img src="/images/icons/edit-pencil-d6c1bb3d.png"/>Edit this page</a></div><div class="content-header hidden-sm hidden-xs"><div id="breadcrumbs" class="hidden-sm hidden xs"><ul><li><a href="#">Getting Started</a><span class="spacer">></span></li><li><span class="last">Downloading an Engine Template</span></li></ul></div><div id="page-title"><h1>Downloading an Engine Template</h1></div></div><div class="content"><p>The first step to create a new engine is to browse <a href="http://templates.prediction.io/">PredictionIO template gallery</a> where you could find Engine Templates for all kinds of machine learning tasks. Choose an engine template that matches your use case the best. You can further customize the engine later if you like.</p><p>To download a template, run:</p
><div class="highlight shell"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1</pre></td><td class="code"><pre><span class="gp">$ </span>pio template get <template-repo-path> <your-new-engine-directory>
+</pre></td></tr></tbody></table> </div> <p>You will find the <code><template-repo-path></code> of the chosen the template in the <a href="http://templates.prediction.io/">PredictionIO template gallery</a>.</p><div class="alert-message note"><p><code>pio</code> is a command available in the <code>bin/</code> of the installed PredictionIO directory. You may add the installed Prediction's bin/ directory path to you environment PATH.</p></div><p>Please browse the <a href="http://templates.prediction.io/">PredictionIO template gallery</a> to choose an engine template.</p></div></div></div></div><footer><div class="container"><div class="seperator"></div><div class="row"><div class="col-md-4 col-md-push-8 col-xs-12"><div class="subscription-form-wrapper"><h4>Subscribe to our Newsletter</h4><form class="ajax-form" id="subscribe-form" method="POST" action="https://script.google.com/macros/s/AKfycbwhzeKCQJjQ52eVAqNT_vcklH07OITUO7wzOMDXvK6EGAWgaZgF/exec"><input class="required under
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[51/51] [partial] incubator-predictionio-site git commit: Initial doc
site
Posted by do...@apache.org.
Initial doc site
Project: http://git-wip-us.apache.org/repos/asf/incubator-predictionio-site/repo
Commit: http://git-wip-us.apache.org/repos/asf/incubator-predictionio-site/commit/92a45fa4
Tree: http://git-wip-us.apache.org/repos/asf/incubator-predictionio-site/tree/92a45fa4
Diff: http://git-wip-us.apache.org/repos/asf/incubator-predictionio-site/diff/92a45fa4
Branch: refs/heads/master
Commit: 92a45fa4747e017164c449d54af274c8e81d38f2
Parents:
Author: Donald Szeto <ds...@salesforce.com>
Authored: Wed Jul 20 12:09:13 2016 -0700
Committer: Donald Szeto <ds...@salesforce.com>
Committed: Wed Jul 20 12:09:13 2016 -0700
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inal" href="/algorithm/"><span>Built-in Algorithm Libraries</span></a></li><li class="level-2"><a class="final" href="/algorithm/switch/"><span>Switching to Another Algorithm</span></a></li><li class="level-2"><a class="final" href="/algorithm/multiple/"><span>Combining Multiple Algorithms</span></a></li><li class="level-2"><a class="final active" href="/algorithm/custom/"><span>Adding Your Own Algorithms</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>ML Tuning and Evaluation</span></a><ul><li class="level-2"><a class="final" href="/evaluation/"><span>Overview</span></a></li><li class="level-2"><a class="final" href="/evaluation/paramtuning/"><span>Hyperparameter Tuning</span></a></li><li class="level-2"><a class="final" href="/evaluation/evaluationdashboard/"><span>Evaluation Dashboard</span></a></li><li class="level-2"><a class="final" href="/evaluation/metricchoose/"><span>Choosing Evaluation Metrics</span></a></li><li class="level-2"><a class="
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<div class="row"><div class="col-md-9 col-sm-11 col-xs-11"><div class="hidden-md hidden-lg" id="mobile-page-heading-wrapper"><p>PredictionIO Docs</p><h4>Tabs</h4></div><h4 class="hidden-sm hidden-xs">PredictionIO Docs</h4></div><div class="col-md-3 col-sm-1 col-xs-1 hidden-md hidden-lg"><img id="left-menu-indicator" src="/images/icons/down-arrow-dfe9f7fe.png"/></div><div class="col-md-3 col-sm-12 col-xs-12 swiftype-wrapper"><div class="swiftype"><form class="search-form"><img class="search-box-toggler hidden-xs hidden-sm" src="/images/icons/search-glass-704bd4ff.png"/><div class="search-box"><img src="/images/icons/search-glass-704bd4ff.png"/><input type="text" id="st-search-input" class="st-search-input" placeholder="Search Doc..."/></div><img class="swiftype-row-hider hidden-md hidden-lg" src="/images/icons/drawer-toggle-active-fcbef12a.png"/></form></div></div><div class="mobile-left-menu-toggler hidden-md hidden-lg"></div></div></div></div><div id="page" class="container-fluid">
<div class="row"><div id="left-menu-wrapper" class="col-md-3"><nav id="nav-main"><ul><li class="level-1"><a class="expandible" href="/"><span>Apache PredictionIO (incubating) Documentation</span></a><ul><li class="level-2"><a class="final" href="/"><span>Welcome to Apache PredictionIO (incubating)</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Getting Started</span></a><ul><li class="level-2"><a class="final" href="/start/"><span>A Quick Intro</span></a></li><li class="level-2"><a class="final" href="/install/"><span>Installing Apache PredictionIO (incubating)</span></a></li><li class="level-2"><a class="final" href="/start/download/"><span>Downloading an Engine Template</span></a></li><li class="level-2"><a class="final" href="/start/deploy/"><span>Deploying Your First Engine</span></a></li><li class="level-2"><a class="final" href="/start/customize/"><span>Customizing the Engine</span></a></li></ul></li><li class="level-1"><a class="expandible" h
ref="#"><span>Integrating with Your App</span></a><ul><li class="level-2"><a class="final" href="/appintegration/"><span>App Integration Overview</span></a></li><li class="level-2"><a class="expandible" href="/sdk/"><span>List of SDKs</span></a><ul><li class="level-3"><a class="final" href="/sdk/java/"><span>Java & Android SDK</span></a></li><li class="level-3"><a class="final" href="/sdk/php/"><span>PHP SDK</span></a></li><li class="level-3"><a class="final" href="/sdk/python/"><span>Python SDK</span></a></li><li class="level-3"><a class="final" href="/sdk/ruby/"><span>Ruby SDK</span></a></li><li class="level-3"><a class="final" href="/sdk/community/"><span>Community Powered SDKs</span></a></li></ul></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Deploying an Engine</span></a><ul><li class="level-2"><a class="final" href="/deploy/"><span>Deploying as a Web Service</span></a></li><li class="level-2"><a class="final" href="/cli/#engine-commands"><span>Engine C
ommand-line Interface</span></a></li><li class="level-2"><a class="final" href="/deploy/engineparams/"><span>Setting Engine Parameters</span></a></li><li class="level-2"><a class="final" href="/deploy/enginevariants/"><span>Deploying Multiple Engine Variants</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Customizing an Engine</span></a><ul><li class="level-2"><a class="final" href="/customize/"><span>Learning DASE</span></a></li><li class="level-2"><a class="final" href="/customize/dase/"><span>Implement DASE</span></a></li><li class="level-2"><a class="final" href="/customize/troubleshooting/"><span>Troubleshooting Engine Development</span></a></li><li class="level-2"><a class="final" href="/api/current/#package"><span>Engine Scala APIs</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Collecting and Analyzing Data</span></a><ul><li class="level-2"><a class="final" href="/datacollection/"><span>Event Server Overview
</span></a></li><li class="level-2"><a class="final" href="/cli/#event-server-commands"><span>Event Server Command-line Interface</span></a></li><li class="level-2"><a class="final" href="/datacollection/eventapi/"><span>Collecting Data with REST/SDKs</span></a></li><li class="level-2"><a class="final" href="/datacollection/eventmodel/"><span>Events Modeling</span></a></li><li class="level-2"><a class="final" href="/datacollection/webhooks/"><span>Unifying Multichannel Data with Webhooks</span></a></li><li class="level-2"><a class="final" href="/datacollection/channel/"><span>Channel</span></a></li><li class="level-2"><a class="final" href="/datacollection/batchimport/"><span>Importing Data in Batch</span></a></li><li class="level-2"><a class="final" href="/datacollection/analytics/"><span>Using Analytics Tools</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Choosing an Algorithm(s)</span></a><ul><li class="level-2"><a class="final" href="/algorithm
/"><span>Built-in Algorithm Libraries</span></a></li><li class="level-2"><a class="final" href="/algorithm/switch/"><span>Switching to Another Algorithm</span></a></li><li class="level-2"><a class="final" href="/algorithm/multiple/"><span>Combining Multiple Algorithms</span></a></li><li class="level-2"><a class="final" href="/algorithm/custom/"><span>Adding Your Own Algorithms</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>ML Tuning and Evaluation</span></a><ul><li class="level-2"><a class="final" href="/evaluation/"><span>Overview</span></a></li><li class="level-2"><a class="final" href="/evaluation/paramtuning/"><span>Hyperparameter Tuning</span></a></li><li class="level-2"><a class="final" href="/evaluation/evaluationdashboard/"><span>Evaluation Dashboard</span></a></li><li class="level-2"><a class="final" href="/evaluation/metricchoose/"><span>Choosing Evaluation Metrics</span></a></li><li class="level-2"><a class="final" href="/evaluation/metr
icbuild/"><span>Building Evaluation Metrics</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>System Architecture</span></a><ul><li class="level-2"><a class="final" href="/system/"><span>Architecture Overview</span></a></li><li class="level-2"><a class="final" href="/system/anotherdatastore/"><span>Using Another Data Store</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Engine Template Gallery</span></a><ul><li class="level-2"><a class="final" href="http://templates.prediction.io"><span>Browse</span></a></li><li class="level-2"><a class="final" href="/community/submit-template/"><span>Submit your Engine as a Template</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Demo Tutorials</span></a><ul><li class="level-2"><a class="final" href="/demo/tapster/"><span>Comics Recommendation Demo</span></a></li><li class="level-2"><a class="final" href="/demo/community/"><span>Community Contributed
Demo</span></a></li><li class="level-2"><a class="final" href="/demo/textclassification/"><span>Text Classification Engine Tutorial</span></a></li></ul></li><li class="level-1"><a class="expandible" href="/community/"><span>Getting Involved</span></a><ul><li class="level-2"><a class="final" href="/community/contribute-code/"><span>Contribute Code</span></a></li><li class="level-2"><a class="final" href="/community/contribute-documentation/"><span>Contribute Documentation</span></a></li><li class="level-2"><a class="final" href="/community/contribute-sdk/"><span>Contribute a SDK</span></a></li><li class="level-2"><a class="final" href="/community/contribute-webhook/"><span>Contribute a Webhook</span></a></li><li class="level-2"><a class="final" href="/community/projects/"><span>Community Projects</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Getting Help</span></a><ul><li class="level-2"><a class="final" href="/resources/faq/"><span>FAQs</span></a
></li><li class="level-2"><a class="final" href="/support/"><span>Community Support</span></a></li><li class="level-2"><a class="final" href="/support/#enterprise-support"><span>Enterprise Support</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Resources</span></a><ul><li class="level-2"><a class="final" href="/resources/intellij/"><span>Developing Engines with IntelliJ IDEA</span></a></li><li class="level-2"><a class="final" href="/resources/upgrade/"><span>Upgrade Instructions</span></a></li><li class="level-2"><a class="final" href="/resources/glossary/"><span>Glossary</span></a></li></ul></li></ul></nav></div><div class="col-md-9 col-sm-12"><div class="content-header hidden-md hidden-lg"><div id="page-title"><h1>Tabs</h1></div></div><div id="table-of-content-wrapper"><h5>On this page</h5><aside id="table-of-contents"><ul> <li> <a href="#test-syncing">Test Syncing</a> </li> </ul> </aside><hr/><a id="edit-page-link" href="https://github.com/apache
/incubator-predictionio/tree/livedoc/docs/manual/source/samples/tabs.html.md"><img src="/images/icons/edit-pencil-d6c1bb3d.png"/>Edit this page</a></div><div class="content-header hidden-sm hidden-xs"><div id="page-title"><h1>Tabs</h1></div></div><div class="content"><p>This page is used to test the tabs plugin based on <a href="https://github.com/vdw/Tabslet">Tabslet</a>.</p><div class="tabs"> <ul class="control"> <li data-lang="ruby"><a href="#tab-8ffed2ff-84ee-4573-8760-78dd307a7fb0">Ruby</a></li> <li data-lang=""><a href="#tab-1c01baa0-347f-4437-a4a8-90e088131ad7">Plain</a></li> <li data-lang="html"><a href="#tab-4c2d1839-2ab5-4115-b7e8-8f51559b07c1">HTML</a></li> <li data-lang=""><a href="#tab-d7bd4700-b759-4cbb-99b2-dc863014283f">Test</a></li> </ul> <div data-tab="Ruby" data-lang="ruby" id="tab-8ffed2ff-84ee-4573-8760-78dd307a7fb0"> <div class="highlight ruby"> <table style="border-spacing: 0"><tbody><tr> <td class="gutter gl" style="text-align: right"><pre class="lineno">1
+2
+3
+4
+5
+6</pre></td> <td class="code"><pre><span class="c1"># This is a ruby file.</span>
+<span class="k">class</span> <span class="nc">MyClass</span>
+ <span class="k">def</span> <span class="nf">foo</span>
+ <span class="s1">'bar'</span>
+ <span class="k">end</span>
+<span class="k">end</span>
+</pre></td> </tr></tbody></table> </div> </div> <div data-tab="Plain" id="tab-1c01baa0-347f-4437-a4a8-90e088131ad7"> This is a test of **markdown** inside a tab! <div class="highlight shell"> <table style="border-spacing: 0"><tbody><tr> <td class="gutter gl" style="text-align: right"><pre class="lineno">1
+2</pre></td> <td class="code"><pre>// This tab does not have the data-lang attribute <span class="nb">set</span>!
+<span class="gp">$ </span><span class="nb">cd </span>path/to/your/file
+</pre></td> </tr></tbody></table> </div> </div> <div data-tab="HTML" data-lang="html" id="tab-4c2d1839-2ab5-4115-b7e8-8f51559b07c1"> <div class="highlight html"> <table style="border-spacing: 0"><tbody><tr> <td class="gutter gl" style="text-align: right"><pre class="lineno">1</pre></td> <td class="code"><pre><span class="nt"><p></span>Yes you can still use HTML in code blocks!<span class="nt"></p></span>
+</pre></td> </tr></tbody></table> </div> </div> <div data-tab="Test" id="tab-d7bd4700-b759-4cbb-99b2-dc863014283f"> <div class="highlight php"> <table style="border-spacing: 0"><tbody><tr> <td class="gutter gl" style="text-align: right"><pre class="lineno">1
+2
+3
+4
+5
+6
+7
+8</pre></td> <td class="code"><pre>Test 0 <span class="err"><</span>>
+Test 1 >
+Test 3 <span class="nt"><
+Test</span> <span class="na">4</span> <span class="nt">><
+Test</span> <span class="na">5 =</span><span class="err">>
+</span><span class="s">Test</span> <span class="na">6</span> <span class="err"><=</span>
+<span class="na">Test</span> <span class="na">7</span> <span class="err"><</span><span class="nt">></span>
+<span class="nt"><p><b></span>Test<span class="nt"></b></p></span>
+</pre></td> </tr></tbody></table> </div> </div> </div> <h2 id='test-syncing' class='header-anchors'>Test Syncing</h2><p>Here we show a similar set of tabs to test language syncing:</p><div class="tabs"> <ul class="control"> <li data-lang="ruby"><a href="#tab-c122425b-41bd-4e71-8485-4093a4650d2d">Ruby</a></li> <li data-lang=""><a href="#tab-61b899ff-87a7-4df2-9c6c-f505fa970bec">Plain</a></li> <li data-lang="html"><a href="#tab-6450d99c-04d0-4ebc-b578-ab903f8e163d">HTML</a></li> <li data-lang="python"><a href="#tab-ae480f30-ed8b-44de-ad38-dbe69af160a8">Python</a></li> </ul> <div data-tab="Ruby" data-lang="ruby" id="tab-c122425b-41bd-4e71-8485-4093a4650d2d"> <div class="highlight ruby"> <table style="border-spacing: 0"><tbody><tr> <td class="gutter gl" style="text-align: right"><pre class="lineno">1
+2
+3
+4
+5
+6</pre></td> <td class="code"><pre><span class="c1"># This is a ruby file.</span>
+<span class="k">class</span> <span class="nc">MyClass</span>
+ <span class="k">def</span> <span class="nf">foo</span>
+ <span class="s1">'bar'</span>
+ <span class="k">end</span>
+<span class="k">end</span>
+</pre></td> </tr></tbody></table> </div> </div> <div data-tab="Plain" id="tab-61b899ff-87a7-4df2-9c6c-f505fa970bec"> This is a test of **markdown** inside a tab! <div class="highlight shell"> <table style="border-spacing: 0"><tbody><tr> <td class="gutter gl" style="text-align: right"><pre class="lineno">1
+2</pre></td> <td class="code"><pre>// This tab does not have the data-lang attribute <span class="nb">set</span>!
+<span class="gp">$ </span><span class="nb">cd </span>path/to/your/file
+</pre></td> </tr></tbody></table> </div> </div> <div data-tab="HTML" data-lang="html" id="tab-6450d99c-04d0-4ebc-b578-ab903f8e163d"> <p>This HTML is <b>hard coded</b>.</p> </div> <div data-tab="Python" data-lang="python" id="tab-ae480f30-ed8b-44de-ad38-dbe69af160a8"> <div class="highlight python"> <table style="border-spacing: 0"><tbody><tr> <td class="gutter gl" style="text-align: right"><pre class="lineno">1</pre></td> <td class="code"><pre><span class="c"># The other group does not have a Python tab.</span>
+</pre></td> </tr></tbody></table> </div> </div> </div> <div class="tabs"> <ul class="control"> <li data-lang="java"><a href="#tab-01e0034c-8916-469d-9161-497057a532aa">Java</a></li> <li data-lang="html"><a href="#tab-e04c3abe-a30b-4c23-b338-5baaa09ec190">HTML</a></li> </ul> <div data-tab="Java" data-lang="java" id="tab-01e0034c-8916-469d-9161-497057a532aa"> <div class="highlight plaintext"> <table style="border-spacing: 0"><tbody><tr> <td class="gutter gl" style="text-align: right"><pre class="lineno">1</pre></td> <td class="code"><pre>// Java code..
+</pre></td> </tr></tbody></table> </div> </div> <div data-tab="HTML" data-lang="html" id="tab-e04c3abe-a30b-4c23-b338-5baaa09ec190"> This includes **bold** with Markdown. </div> </div> </div></div></div></div><footer><div class="container"><div class="seperator"></div><div class="row"><div class="col-md-4 col-md-push-8 col-xs-12"><div class="subscription-form-wrapper"><h4>Subscribe to our Newsletter</h4><form class="ajax-form" id="subscribe-form" method="POST" action="https://script.google.com/macros/s/AKfycbwhzeKCQJjQ52eVAqNT_vcklH07OITUO7wzOMDXvK6EGAWgaZgF/exec"><input class="required underlined-input" type="email" placeholder="Your email address" name="subscription_email" id="subscription_email"/><input class="pill-button" value="SUBSCRIBE" type="submit" data-state-normal="SUBSCRIBE" data-state-sucess="SUBSCRIBED!" data-state-loading="SENDING..." onclick="t($('#subscription_email').val());"/><p class="result"></p></form></div></div><div class="col-md-2 col-md-pull-4 col-xs-6 foot
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ass="expandible" href="#"><span>Integrating with Your App</span></a><ul><li class="level-2"><a class="final" href="/appintegration/"><span>App Integration Overview</span></a></li><li class="level-2"><a class="expandible" href="/sdk/"><span>List of SDKs</span></a><ul><li class="level-3"><a class="final" href="/sdk/java/"><span>Java & Android SDK</span></a></li><li class="level-3"><a class="final" href="/sdk/php/"><span>PHP SDK</span></a></li><li class="level-3"><a class="final" href="/sdk/python/"><span>Python SDK</span></a></li><li class="level-3"><a class="final" href="/sdk/ruby/"><span>Ruby SDK</span></a></li><li class="level-3"><a class="final active" href="/sdk/community/"><span>Community Powered SDKs</span></a></li></ul></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Deploying an Engine</span></a><ul><li class="level-2"><a class="final" href="/deploy/"><span>Deploying as a Web Service</span></a></li><li class="level-2"><a class="final" href="/cli/#engine
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pan>Event Server Overview</span></a></li><li class="level-2"><a class="final" href="/cli/#event-server-commands"><span>Event Server Command-line Interface</span></a></li><li class="level-2"><a class="final" href="/datacollection/eventapi/"><span>Collecting Data with REST/SDKs</span></a></li><li class="level-2"><a class="final" href="/datacollection/eventmodel/"><span>Events Modeling</span></a></li><li class="level-2"><a class="final" href="/datacollection/webhooks/"><span>Unifying Multichannel Data with Webhooks</span></a></li><li class="level-2"><a class="final" href="/datacollection/channel/"><span>Channel</span></a></li><li class="level-2"><a class="final" href="/datacollection/batchimport/"><span>Importing Data in Batch</span></a></li><li class="level-2"><a class="final" href="/datacollection/analytics/"><span>Using Analytics Tools</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Choosing an Algorithm(s)</span></a><ul><li class="level-2"><a class
="final" href="/algorithm/"><span>Built-in Algorithm Libraries</span></a></li><li class="level-2"><a class="final" href="/algorithm/switch/"><span>Switching to Another Algorithm</span></a></li><li class="level-2"><a class="final" href="/algorithm/multiple/"><span>Combining Multiple Algorithms</span></a></li><li class="level-2"><a class="final" href="/algorithm/custom/"><span>Adding Your Own Algorithms</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>ML Tuning and Evaluation</span></a><ul><li class="level-2"><a class="final" href="/evaluation/"><span>Overview</span></a></li><li class="level-2"><a class="final" href="/evaluation/paramtuning/"><span>Hyperparameter Tuning</span></a></li><li class="level-2"><a class="final" href="/evaluation/evaluationdashboard/"><span>Evaluation Dashboard</span></a></li><li class="level-2"><a class="final" href="/evaluation/metricchoose/"><span>Choosing Evaluation Metrics</span></a></li><li class="level-2"><a class="fina
l" href="/evaluation/metricbuild/"><span>Building Evaluation Metrics</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>System Architecture</span></a><ul><li class="level-2"><a class="final" href="/system/"><span>Architecture Overview</span></a></li><li class="level-2"><a class="final" href="/system/anotherdatastore/"><span>Using Another Data Store</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Engine Template Gallery</span></a><ul><li class="level-2"><a class="final" href="http://templates.prediction.io"><span>Browse</span></a></li><li class="level-2"><a class="final" href="/community/submit-template/"><span>Submit your Engine as a Template</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Demo Tutorials</span></a><ul><li class="level-2"><a class="final" href="/demo/tapster/"><span>Comics Recommendation Demo</span></a></li><li class="level-2"><a class="final" href="/demo/community/"><s
pan>Community Contributed Demo</span></a></li><li class="level-2"><a class="final" href="/demo/textclassification/"><span>Text Classification Engine Tutorial</span></a></li></ul></li><li class="level-1"><a class="expandible" href="/community/"><span>Getting Involved</span></a><ul><li class="level-2"><a class="final" href="/community/contribute-code/"><span>Contribute Code</span></a></li><li class="level-2"><a class="final" href="/community/contribute-documentation/"><span>Contribute Documentation</span></a></li><li class="level-2"><a class="final" href="/community/contribute-sdk/"><span>Contribute a SDK</span></a></li><li class="level-2"><a class="final" href="/community/contribute-webhook/"><span>Contribute a Webhook</span></a></li><li class="level-2"><a class="final" href="/community/projects/"><span>Community Projects</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Getting Help</span></a><ul><li class="level-2"><a class="final" href="/resources/f
aq/"><span>FAQs</span></a></li><li class="level-2"><a class="final" href="/support/"><span>Community Support</span></a></li><li class="level-2"><a class="final" href="/support/#enterprise-support"><span>Enterprise Support</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Resources</span></a><ul><li class="level-2"><a class="final" href="/resources/intellij/"><span>Developing Engines with IntelliJ IDEA</span></a></li><li class="level-2"><a class="final" href="/resources/upgrade/"><span>Upgrade Instructions</span></a></li><li class="level-2"><a class="final" href="/resources/glossary/"><span>Glossary</span></a></li></ul></li></ul></nav></div><div class="col-md-9 col-sm-12"><div class="content-header hidden-md hidden-lg"><div id="breadcrumbs" class="hidden-sm hidden xs"><ul><li><a href="#">Integrating with Your App</a><span class="spacer">></span></li><li><a href="/sdk/">List of SDKs</a><span class="spacer">></span></li><li><span class="last">Commu
nity Powered SDKs</span></li></ul></div><div id="page-title"><h1>Community Powered SDKs</h1></div></div><div id="table-of-content-wrapper"><h5>On this page</h5><aside id="table-of-contents"><ul> <li> <a href="#node-js-sdk-for-predictionio">Node.js SDK for PredictionIO</a> </li> <li> <a href="#c-net-sdk-for-predictionio">C#/.NET SDK for PredictionIO</a> </li> <li> <a href="#net-sdk-for-predictionio">.NET SDK for PredictionIO</a> </li> <li> <a href="#lavarel-wrapper-for-predictionio">Lavarel Wrapper for PredictionIO</a> </li> <li> <a href="#swift-sdk-for-predictionio">Swift SDK for PredictionIO</a> </li> </ul> </aside><hr/><a id="edit-page-link" href="https://github.com/apache/incubator-predictionio/tree/livedoc/docs/manual/source/sdk/community.html.md"><img src="/images/icons/edit-pencil-d6c1bb3d.png"/>Edit this page</a></div><div class="content-header hidden-sm hidden-xs"><div id="breadcrumbs" class="hidden-sm hidden xs"><ul><li><a href="#">Integrating with Your App</a><span class="
spacer">></span></li><li><a href="/sdk/">List of SDKs</a><span class="spacer">></span></li><li><span class="last">Community Powered SDKs</span></li></ul></div><div id="page-title"><h1>Community Powered SDKs</h1></div></div><div class="content"><p><a href="/community/contribute-sdk">SDK contribution</a> is always welcomed!</p><h2 id='node.js-sdk-for-predictionio' class='header-anchors'>Node.js SDK for PredictionIO</h2><p>URL: <a href="https://github.com/asafyish/predictionio-driver">https://github.com/asafyish/predictionio-driver</a> and <a href="https://www.npmjs.org/package/predictionio-driver">https://www.npmjs.org/package/predictionio-driver</a></p><p>Node.js PredictionIO 0.8+ client supporting both callback syntax and promise syntax.</p> <ul> <li><p>Core Author: Asaf Yishai</p></li> <li><p>Status: It works with PredictionIO v0.8 - Under active development</p></li> </ul> <h2 id='c#/.net-sdk-for-predictionio' class='header-anchors'>C#/.NET SDK for PredictionIO</h2><p>URL: <a
href="https://github.com/orbyone/Sensible.PredictionIO.NET">https://github.com/orbyone/Sensible.PredictionIO.NET</a></p><p>C#/.NET library for PredictionIO 0.9.4, supporting both synchronous and asynchronous calls, for item recommendation and item ranking algorithms. Loosely based on the PredictionIO Java SDK API.</p> <ul> <li><p>Core Author: Themos Piperakis</p></li> <li><p>Status: It works with PredictionIO v0.9.4 - Under active development</p></li> </ul> <h2 id='.net-sdk-for-predictionio' class='header-anchors'>.NET SDK for PredictionIO</h2><p>URL: <a href="https://github.com/ibrahimozgon/PredictionIO-.Net-SDK">https://github.com/ibrahimozgon/PredictionIO-.Net-SDK</a></p><p>.NET SDK for PredictionIO</p> <ul> <li><p>Core Author: Ibrahim �zg�n</p></li> <li><p>Status: It works with PredictionIO v0.9 - Under active development</p></li> </ul> <h2 id='lavarel-wrapper-for-predictionio' class='header-anchors'>Lavarel Wrapper for PredictionIO</h2><p>URL: <a href="https://github.com/mic
hael-hopkins/PredictionIO-Laravel-Wrapper">https://github.com/michael-hopkins/PredictionIO-Laravel-Wrapper</a> and <a href="https://packagist.org/packages/hopkins/predictionio-laravel-wrapper">https://packagist.org/packages/hopkins/predictionio-laravel-wrapper</a></p><p>A Laravel wrapper for PredictionIO v0.8.</p> <ul> <li><p>Core Author: Bruno Cabral & Michael Hopkins</p></li> <li><p>Status: It works with PredictionIO v0.8 - Under active development</p></li> </ul> <h2 id='swift-sdk-for-predictionio' class='header-anchors'>Swift SDK for PredictionIO</h2><p>URL: <a href="https://github.com/minhtule/PredictionIO-Swift-SDK">https://github.com/minhtule/PredictionIO-Swift-SDK</a></p><p>A convenient API written in Swift, supporting iOS 7+/ OS X 10.9+ and Xcode 6.1.</p> <ul> <li><p>Core Author: Minh-Tu Le</p></li> <li><p>Status: It works with PredictionIO v0.8.3 and above - Under active development</p></li> </ul> </div></div></div></div><footer><div class="container"><div class="sepera
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+fbq('track', "PageView");</script><script src="//use.typekit.net/mut4mjx.js"></script><script>try{Typekit.load();}catch(e){}</script></head><body><div id="global"><header><div class="container" id="header-wrapper"><div class="row"><div class="col-sm-12"><div id="logo-wrapper"><span id="drawer-toggle"></span><a href="#"></a><a href="http://prediction.io/"><img alt="PredictionIO" id="logo" src="/images/logos/logo-ee2b9bb3.png"/></a></div><div id="menu-wrapper"><div id="header-nav-options-wrapper"><ul><li><a href="/">Install & Doc</a></li> <li><a href="/support">Support</a></li> </ul></div><div id="pill-wrapper"><a class="pill left" href="//templates.prediction.io/">TEMPLATES</a> <a class="pill right" href="//github.com/PredictionIO/PredictionIO/">OPEN SOURCE</a></div></div><img class="mobile-search-bar-toggler hidden-md hidden-lg" src="/images/icons/search-glass-704bd4ff.png"/></div></div></div></header><div id="search-bar-row-wrapper"><div class="container-fluid" id="search-bar-row">
<div class="row"><div class="col-md-9 col-sm-11 col-xs-11"><div class="hidden-md hidden-lg" id="mobile-page-heading-wrapper"><p>PredictionIO Docs</p><h4>List of SDKs</h4></div><h4 class="hidden-sm hidden-xs">PredictionIO Docs</h4></div><div class="col-md-3 col-sm-1 col-xs-1 hidden-md hidden-lg"><img id="left-menu-indicator" src="/images/icons/down-arrow-dfe9f7fe.png"/></div><div class="col-md-3 col-sm-12 col-xs-12 swiftype-wrapper"><div class="swiftype"><form class="search-form"><img class="search-box-toggler hidden-xs hidden-sm" src="/images/icons/search-glass-704bd4ff.png"/><div class="search-box"><img src="/images/icons/search-glass-704bd4ff.png"/><input type="text" id="st-search-input" class="st-search-input" placeholder="Search Doc..."/></div><img class="swiftype-row-hider hidden-md hidden-lg" src="/images/icons/drawer-toggle-active-fcbef12a.png"/></form></div></div><div class="mobile-left-menu-toggler hidden-md hidden-lg"></div></div></div></div><div id="page" class="container
-fluid"><div class="row"><div id="left-menu-wrapper" class="col-md-3"><nav id="nav-main"><ul><li class="level-1"><a class="expandible" href="/"><span>Apache PredictionIO (incubating) Documentation</span></a><ul><li class="level-2"><a class="final" href="/"><span>Welcome to Apache PredictionIO (incubating)</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Getting Started</span></a><ul><li class="level-2"><a class="final" href="/start/"><span>A Quick Intro</span></a></li><li class="level-2"><a class="final" href="/install/"><span>Installing Apache PredictionIO (incubating)</span></a></li><li class="level-2"><a class="final" href="/start/download/"><span>Downloading an Engine Template</span></a></li><li class="level-2"><a class="final" href="/start/deploy/"><span>Deploying Your First Engine</span></a></li><li class="level-2"><a class="final" href="/start/customize/"><span>Customizing the Engine</span></a></li></ul></li><li class="level-1"><a class="expan
dible" href="#"><span>Integrating with Your App</span></a><ul><li class="level-2"><a class="final" href="/appintegration/"><span>App Integration Overview</span></a></li><li class="level-2"><a class="expandible active" href="/sdk/"><span>List of SDKs</span></a><ul><li class="level-3"><a class="final" href="/sdk/java/"><span>Java & Android SDK</span></a></li><li class="level-3"><a class="final" href="/sdk/php/"><span>PHP SDK</span></a></li><li class="level-3"><a class="final" href="/sdk/python/"><span>Python SDK</span></a></li><li class="level-3"><a class="final" href="/sdk/ruby/"><span>Ruby SDK</span></a></li><li class="level-3"><a class="final" href="/sdk/community/"><span>Community Powered SDKs</span></a></li></ul></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Deploying an Engine</span></a><ul><li class="level-2"><a class="final" href="/deploy/"><span>Deploying as a Web Service</span></a></li><li class="level-2"><a class="final" href="/cli/#engine-commands"
><span>Engine Command-line Interface</span></a></li><li class="level-2"><a class="final" href="/deploy/engineparams/"><span>Setting Engine Parameters</span></a></li><li class="level-2"><a class="final" href="/deploy/enginevariants/"><span>Deploying Multiple Engine Variants</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Customizing an Engine</span></a><ul><li class="level-2"><a class="final" href="/customize/"><span>Learning DASE</span></a></li><li class="level-2"><a class="final" href="/customize/dase/"><span>Implement DASE</span></a></li><li class="level-2"><a class="final" href="/customize/troubleshooting/"><span>Troubleshooting Engine Development</span></a></li><li class="level-2"><a class="final" href="/api/current/#package"><span>Engine Scala APIs</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Collecting and Analyzing Data</span></a><ul><li class="level-2"><a class="final" href="/datacollection/"><span>Event
Server Overview</span></a></li><li class="level-2"><a class="final" href="/cli/#event-server-commands"><span>Event Server Command-line Interface</span></a></li><li class="level-2"><a class="final" href="/datacollection/eventapi/"><span>Collecting Data with REST/SDKs</span></a></li><li class="level-2"><a class="final" href="/datacollection/eventmodel/"><span>Events Modeling</span></a></li><li class="level-2"><a class="final" href="/datacollection/webhooks/"><span>Unifying Multichannel Data with Webhooks</span></a></li><li class="level-2"><a class="final" href="/datacollection/channel/"><span>Channel</span></a></li><li class="level-2"><a class="final" href="/datacollection/batchimport/"><span>Importing Data in Batch</span></a></li><li class="level-2"><a class="final" href="/datacollection/analytics/"><span>Using Analytics Tools</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Choosing an Algorithm(s)</span></a><ul><li class="level-2"><a class="final" h
ref="/algorithm/"><span>Built-in Algorithm Libraries</span></a></li><li class="level-2"><a class="final" href="/algorithm/switch/"><span>Switching to Another Algorithm</span></a></li><li class="level-2"><a class="final" href="/algorithm/multiple/"><span>Combining Multiple Algorithms</span></a></li><li class="level-2"><a class="final" href="/algorithm/custom/"><span>Adding Your Own Algorithms</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>ML Tuning and Evaluation</span></a><ul><li class="level-2"><a class="final" href="/evaluation/"><span>Overview</span></a></li><li class="level-2"><a class="final" href="/evaluation/paramtuning/"><span>Hyperparameter Tuning</span></a></li><li class="level-2"><a class="final" href="/evaluation/evaluationdashboard/"><span>Evaluation Dashboard</span></a></li><li class="level-2"><a class="final" href="/evaluation/metricchoose/"><span>Choosing Evaluation Metrics</span></a></li><li class="level-2"><a class="final" href="/
evaluation/metricbuild/"><span>Building Evaluation Metrics</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>System Architecture</span></a><ul><li class="level-2"><a class="final" href="/system/"><span>Architecture Overview</span></a></li><li class="level-2"><a class="final" href="/system/anotherdatastore/"><span>Using Another Data Store</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Engine Template Gallery</span></a><ul><li class="level-2"><a class="final" href="http://templates.prediction.io"><span>Browse</span></a></li><li class="level-2"><a class="final" href="/community/submit-template/"><span>Submit your Engine as a Template</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Demo Tutorials</span></a><ul><li class="level-2"><a class="final" href="/demo/tapster/"><span>Comics Recommendation Demo</span></a></li><li class="level-2"><a class="final" href="/demo/community/"><span>Commun
ity Contributed Demo</span></a></li><li class="level-2"><a class="final" href="/demo/textclassification/"><span>Text Classification Engine Tutorial</span></a></li></ul></li><li class="level-1"><a class="expandible" href="/community/"><span>Getting Involved</span></a><ul><li class="level-2"><a class="final" href="/community/contribute-code/"><span>Contribute Code</span></a></li><li class="level-2"><a class="final" href="/community/contribute-documentation/"><span>Contribute Documentation</span></a></li><li class="level-2"><a class="final" href="/community/contribute-sdk/"><span>Contribute a SDK</span></a></li><li class="level-2"><a class="final" href="/community/contribute-webhook/"><span>Contribute a Webhook</span></a></li><li class="level-2"><a class="final" href="/community/projects/"><span>Community Projects</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Getting Help</span></a><ul><li class="level-2"><a class="final" href="/resources/faq/"><span
>FAQs</span></a></li><li class="level-2"><a class="final" href="/support/"><span>Community Support</span></a></li><li class="level-2"><a class="final" href="/support/#enterprise-support"><span>Enterprise Support</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Resources</span></a><ul><li class="level-2"><a class="final" href="/resources/intellij/"><span>Developing Engines with IntelliJ IDEA</span></a></li><li class="level-2"><a class="final" href="/resources/upgrade/"><span>Upgrade Instructions</span></a></li><li class="level-2"><a class="final" href="/resources/glossary/"><span>Glossary</span></a></li></ul></li></ul></nav></div><div class="col-md-9 col-sm-12"><div class="content-header hidden-md hidden-lg"><div id="breadcrumbs" class="hidden-sm hidden xs"><ul><li><a href="#">Integrating with Your App</a><span class="spacer">></span></li><li><span class="last">List of SDKs</span></li></ul></div><div id="page-title"><h1>List of PredictionIO SDKs</h
1></div></div><div id="table-of-content-wrapper"><h5>On this page</h5><aside id="table-of-contents"><ul> <li> <a href="#officially-supported-sdks">Officially Supported SDKs</a> </li> <li> <a href="#community-powered-sdks">Community Powered SDKs</a> </li> </ul> </aside><hr/><a id="edit-page-link" href="https://github.com/apache/incubator-predictionio/tree/livedoc/docs/manual/source/sdk/index.html.md"><img src="/images/icons/edit-pencil-d6c1bb3d.png"/>Edit this page</a></div><div class="content-header hidden-sm hidden-xs"><div id="breadcrumbs" class="hidden-sm hidden xs"><ul><li><a href="#">Integrating with Your App</a><span class="spacer">></span></li><li><span class="last">List of SDKs</span></li></ul></div><div id="page-title"><h1>List of PredictionIO SDKs</h1></div></div><div class="content"><h2 id='officially-supported-sdks' class='header-anchors'>Officially Supported SDKs</h2> <ul> <li><a href="/sdk/java/">Java & Android SDK</a></li> <li><a href="/sdk/php/">PHP SDK</a></l
i> <li><a href="/sdk/python/">Python SDK</a></li> <li><a href="/sdk/ruby/">Ruby SDK</a></li> </ul> <h2 id='community-powered-sdks' class='header-anchors'>Community Powered SDKs</h2><p>See the full list <a href="/sdk/community/">here</a>.</p></div></div></div></div><footer><div class="container"><div class="seperator"></div><div class="row"><div class="col-md-4 col-md-push-8 col-xs-12"><div class="subscription-form-wrapper"><h4>Subscribe to our Newsletter</h4><form class="ajax-form" id="subscribe-form" method="POST" action="https://script.google.com/macros/s/AKfycbwhzeKCQJjQ52eVAqNT_vcklH07OITUO7wzOMDXvK6EGAWgaZgF/exec"><input class="required underlined-input" type="email" placeholder="Your email address" name="subscription_email" id="subscription_email"/><input class="pill-button" value="SUBSCRIBE" type="submit" data-state-normal="SUBSCRIBE" data-state-sucess="SUBSCRIBED!" data-state-loading="SENDING..." onclick="t($('#subscription_email').val());"/><p class="result"></p></form></di
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Posted by do...@apache.org.
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<div class="row"><div class="col-md-9 col-sm-11 col-xs-11"><div class="hidden-md hidden-lg" id="mobile-page-heading-wrapper"><p>PredictionIO Docs</p><h4>Built-in Algorithm Libraries</h4></div><h4 class="hidden-sm hidden-xs">PredictionIO Docs</h4></div><div class="col-md-3 col-sm-1 col-xs-1 hidden-md hidden-lg"><img id="left-menu-indicator" src="/images/icons/down-arrow-dfe9f7fe.png"/></div><div class="col-md-3 col-sm-12 col-xs-12 swiftype-wrapper"><div class="swiftype"><form class="search-form"><img class="search-box-toggler hidden-xs hidden-sm" src="/images/icons/search-glass-704bd4ff.png"/><div class="search-box"><img src="/images/icons/search-glass-704bd4ff.png"/><input type="text" id="st-search-input" class="st-search-input" placeholder="Search Doc..."/></div><img class="swiftype-row-hider hidden-md hidden-lg" src="/images/icons/drawer-toggle-active-fcbef12a.png"/></form></div></div><div class="mobile-left-menu-toggler hidden-md hidden-lg"></div></div></div></div><div id="page"
class="container-fluid"><div class="row"><div id="left-menu-wrapper" class="col-md-3"><nav id="nav-main"><ul><li class="level-1"><a class="expandible" href="/"><span>Apache PredictionIO (incubating) Documentation</span></a><ul><li class="level-2"><a class="final" href="/"><span>Welcome to Apache PredictionIO (incubating)</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Getting Started</span></a><ul><li class="level-2"><a class="final" href="/start/"><span>A Quick Intro</span></a></li><li class="level-2"><a class="final" href="/install/"><span>Installing Apache PredictionIO (incubating)</span></a></li><li class="level-2"><a class="final" href="/start/download/"><span>Downloading an Engine Template</span></a></li><li class="level-2"><a class="final" href="/start/deploy/"><span>Deploying Your First Engine</span></a></li><li class="level-2"><a class="final" href="/start/customize/"><span>Customizing the Engine</span></a></li></ul></li><li class="level-1"
><a class="expandible" href="#"><span>Integrating with Your App</span></a><ul><li class="level-2"><a class="final" href="/appintegration/"><span>App Integration Overview</span></a></li><li class="level-2"><a class="expandible" href="/sdk/"><span>List of SDKs</span></a><ul><li class="level-3"><a class="final" href="/sdk/java/"><span>Java & Android SDK</span></a></li><li class="level-3"><a class="final" href="/sdk/php/"><span>PHP SDK</span></a></li><li class="level-3"><a class="final" href="/sdk/python/"><span>Python SDK</span></a></li><li class="level-3"><a class="final" href="/sdk/ruby/"><span>Ruby SDK</span></a></li><li class="level-3"><a class="final" href="/sdk/community/"><span>Community Powered SDKs</span></a></li></ul></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Deploying an Engine</span></a><ul><li class="level-2"><a class="final" href="/deploy/"><span>Deploying as a Web Service</span></a></li><li class="level-2"><a class="final" href="/cli/#engine-
commands"><span>Engine Command-line Interface</span></a></li><li class="level-2"><a class="final" href="/deploy/engineparams/"><span>Setting Engine Parameters</span></a></li><li class="level-2"><a class="final" href="/deploy/enginevariants/"><span>Deploying Multiple Engine Variants</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Customizing an Engine</span></a><ul><li class="level-2"><a class="final" href="/customize/"><span>Learning DASE</span></a></li><li class="level-2"><a class="final" href="/customize/dase/"><span>Implement DASE</span></a></li><li class="level-2"><a class="final" href="/customize/troubleshooting/"><span>Troubleshooting Engine Development</span></a></li><li class="level-2"><a class="final" href="/api/current/#package"><span>Engine Scala APIs</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Collecting and Analyzing Data</span></a><ul><li class="level-2"><a class="final" href="/datacollection/"><sp
an>Event Server Overview</span></a></li><li class="level-2"><a class="final" href="/cli/#event-server-commands"><span>Event Server Command-line Interface</span></a></li><li class="level-2"><a class="final" href="/datacollection/eventapi/"><span>Collecting Data with REST/SDKs</span></a></li><li class="level-2"><a class="final" href="/datacollection/eventmodel/"><span>Events Modeling</span></a></li><li class="level-2"><a class="final" href="/datacollection/webhooks/"><span>Unifying Multichannel Data with Webhooks</span></a></li><li class="level-2"><a class="final" href="/datacollection/channel/"><span>Channel</span></a></li><li class="level-2"><a class="final" href="/datacollection/batchimport/"><span>Importing Data in Batch</span></a></li><li class="level-2"><a class="final" href="/datacollection/analytics/"><span>Using Analytics Tools</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Choosing an Algorithm(s)</span></a><ul><li class="level-2"><a class=
"final active" href="/algorithm/"><span>Built-in Algorithm Libraries</span></a></li><li class="level-2"><a class="final" href="/algorithm/switch/"><span>Switching to Another Algorithm</span></a></li><li class="level-2"><a class="final" href="/algorithm/multiple/"><span>Combining Multiple Algorithms</span></a></li><li class="level-2"><a class="final" href="/algorithm/custom/"><span>Adding Your Own Algorithms</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>ML Tuning and Evaluation</span></a><ul><li class="level-2"><a class="final" href="/evaluation/"><span>Overview</span></a></li><li class="level-2"><a class="final" href="/evaluation/paramtuning/"><span>Hyperparameter Tuning</span></a></li><li class="level-2"><a class="final" href="/evaluation/evaluationdashboard/"><span>Evaluation Dashboard</span></a></li><li class="level-2"><a class="final" href="/evaluation/metricchoose/"><span>Choosing Evaluation Metrics</span></a></li><li class="level-2"><a class
="final" href="/evaluation/metricbuild/"><span>Building Evaluation Metrics</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>System Architecture</span></a><ul><li class="level-2"><a class="final" href="/system/"><span>Architecture Overview</span></a></li><li class="level-2"><a class="final" href="/system/anotherdatastore/"><span>Using Another Data Store</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Engine Template Gallery</span></a><ul><li class="level-2"><a class="final" href="http://templates.prediction.io"><span>Browse</span></a></li><li class="level-2"><a class="final" href="/community/submit-template/"><span>Submit your Engine as a Template</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Demo Tutorials</span></a><ul><li class="level-2"><a class="final" href="/demo/tapster/"><span>Comics Recommendation Demo</span></a></li><li class="level-2"><a class="final" href="/demo/communit
y/"><span>Community Contributed Demo</span></a></li><li class="level-2"><a class="final" href="/demo/textclassification/"><span>Text Classification Engine Tutorial</span></a></li></ul></li><li class="level-1"><a class="expandible" href="/community/"><span>Getting Involved</span></a><ul><li class="level-2"><a class="final" href="/community/contribute-code/"><span>Contribute Code</span></a></li><li class="level-2"><a class="final" href="/community/contribute-documentation/"><span>Contribute Documentation</span></a></li><li class="level-2"><a class="final" href="/community/contribute-sdk/"><span>Contribute a SDK</span></a></li><li class="level-2"><a class="final" href="/community/contribute-webhook/"><span>Contribute a Webhook</span></a></li><li class="level-2"><a class="final" href="/community/projects/"><span>Community Projects</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Getting Help</span></a><ul><li class="level-2"><a class="final" href="/resou
rces/faq/"><span>FAQs</span></a></li><li class="level-2"><a class="final" href="/support/"><span>Community Support</span></a></li><li class="level-2"><a class="final" href="/support/#enterprise-support"><span>Enterprise Support</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Resources</span></a><ul><li class="level-2"><a class="final" href="/resources/intellij/"><span>Developing Engines with IntelliJ IDEA</span></a></li><li class="level-2"><a class="final" href="/resources/upgrade/"><span>Upgrade Instructions</span></a></li><li class="level-2"><a class="final" href="/resources/glossary/"><span>Glossary</span></a></li></ul></li></ul></nav></div><div class="col-md-9 col-sm-12"><div class="content-header hidden-md hidden-lg"><div id="breadcrumbs" class="hidden-sm hidden xs"><ul><li><a href="#">Choosing an Algorithm(s)</a><span class="spacer">></span></li><li><span class="last">Built-in Algorithm Libraries</span></li></ul></div><div id="page-title"><
h1>Built-in Algorithm Libraries</h1></div></div><div id="table-of-content-wrapper"><a id="edit-page-link" href="https://github.com/apache/incubator-predictionio/tree/livedoc/docs/manual/source/algorithm/index.html.md"><img src="/images/icons/edit-pencil-d6c1bb3d.png"/>Edit this page</a></div><div class="content-header hidden-sm hidden-xs"><div id="breadcrumbs" class="hidden-sm hidden xs"><ul><li><a href="#">Choosing an Algorithm(s)</a><span class="spacer">></span></li><li><span class="last">Built-in Algorithm Libraries</span></li></ul></div><div id="page-title"><h1>Built-in Algorithm Libraries</h1></div></div><div class="content"><p>An engine can virtually call any algorithm in the Algorithm class. Apache PredictionIO (incubating) currently offers native support to <a href="http://spark.apache.org/docs/latest/mllib-guide.html">Spark MLlib</a> machine learning library. It is being used by some of the engine templates in the <a href="http://templates.prediction.io/">template galler
y</a>.</p><p>More library support will be added soon.</p></div></div></div></div><footer><div class="container"><div class="seperator"></div><div class="row"><div class="col-md-4 col-md-push-8 col-xs-12"><div class="subscription-form-wrapper"><h4>Subscribe to our Newsletter</h4><form class="ajax-form" id="subscribe-form" method="POST" action="https://script.google.com/macros/s/AKfycbwhzeKCQJjQ52eVAqNT_vcklH07OITUO7wzOMDXvK6EGAWgaZgF/exec"><input class="required underlined-input" type="email" placeholder="Your email address" name="subscription_email" id="subscription_email"/><input class="pill-button" value="SUBSCRIBE" type="submit" data-state-normal="SUBSCRIBE" data-state-sucess="SUBSCRIBED!" data-state-loading="SENDING..." onclick="t($('#subscription_email').val());"/><p class="result"></p></form></div></div><div class="col-md-2 col-md-pull-4 col-xs-6 footer-link-column"><div class="footer-link-column-row"><h4>Community</h4><ul><li><a href="//docs.prediction.io/install/" target="bl
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<div class="row"><div class="col-md-9 col-sm-11 col-xs-11"><div class="hidden-md hidden-lg" id="mobile-page-heading-wrapper"><p>PredictionIO Docs</p><h4>Combining Multiple Algorithms</h4></div><h4 class="hidden-sm hidden-xs">PredictionIO Docs</h4></div><div class="col-md-3 col-sm-1 col-xs-1 hidden-md hidden-lg"><img id="left-menu-indicator" src="/images/icons/down-arrow-dfe9f7fe.png"/></div><div class="col-md-3 col-sm-12 col-xs-12 swiftype-wrapper"><div class="swiftype"><form class="search-form"><img class="search-box-toggler hidden-xs hidden-sm" src="/images/icons/search-glass-704bd4ff.png"/><div class="search-box"><img src="/images/icons/search-glass-704bd4ff.png"/><input type="text" id="st-search-input" class="st-search-input" placeholder="Search Doc..."/></div><img class="swiftype-row-hider hidden-md hidden-lg" src="/images/icons/drawer-toggle-active-fcbef12a.png"/></form></div></div><div class="mobile-left-menu-toggler hidden-md hidden-lg"></div></div></div></div><div id="page"
class="container-fluid"><div class="row"><div id="left-menu-wrapper" class="col-md-3"><nav id="nav-main"><ul><li class="level-1"><a class="expandible" href="/"><span>Apache PredictionIO (incubating) Documentation</span></a><ul><li class="level-2"><a class="final" href="/"><span>Welcome to Apache PredictionIO (incubating)</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Getting Started</span></a><ul><li class="level-2"><a class="final" href="/start/"><span>A Quick Intro</span></a></li><li class="level-2"><a class="final" href="/install/"><span>Installing Apache PredictionIO (incubating)</span></a></li><li class="level-2"><a class="final" href="/start/download/"><span>Downloading an Engine Template</span></a></li><li class="level-2"><a class="final" href="/start/deploy/"><span>Deploying Your First Engine</span></a></li><li class="level-2"><a class="final" href="/start/customize/"><span>Customizing the Engine</span></a></li></ul></li><li class="level-1
"><a class="expandible" href="#"><span>Integrating with Your App</span></a><ul><li class="level-2"><a class="final" href="/appintegration/"><span>App Integration Overview</span></a></li><li class="level-2"><a class="expandible" href="/sdk/"><span>List of SDKs</span></a><ul><li class="level-3"><a class="final" href="/sdk/java/"><span>Java & Android SDK</span></a></li><li class="level-3"><a class="final" href="/sdk/php/"><span>PHP SDK</span></a></li><li class="level-3"><a class="final" href="/sdk/python/"><span>Python SDK</span></a></li><li class="level-3"><a class="final" href="/sdk/ruby/"><span>Ruby SDK</span></a></li><li class="level-3"><a class="final" href="/sdk/community/"><span>Community Powered SDKs</span></a></li></ul></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Deploying an Engine</span></a><ul><li class="level-2"><a class="final" href="/deploy/"><span>Deploying as a Web Service</span></a></li><li class="level-2"><a class="final" href="/cli/#engine
-commands"><span>Engine Command-line Interface</span></a></li><li class="level-2"><a class="final" href="/deploy/engineparams/"><span>Setting Engine Parameters</span></a></li><li class="level-2"><a class="final" href="/deploy/enginevariants/"><span>Deploying Multiple Engine Variants</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Customizing an Engine</span></a><ul><li class="level-2"><a class="final" href="/customize/"><span>Learning DASE</span></a></li><li class="level-2"><a class="final" href="/customize/dase/"><span>Implement DASE</span></a></li><li class="level-2"><a class="final" href="/customize/troubleshooting/"><span>Troubleshooting Engine Development</span></a></li><li class="level-2"><a class="final" href="/api/current/#package"><span>Engine Scala APIs</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Collecting and Analyzing Data</span></a><ul><li class="level-2"><a class="final" href="/datacollection/"><s
pan>Event Server Overview</span></a></li><li class="level-2"><a class="final" href="/cli/#event-server-commands"><span>Event Server Command-line Interface</span></a></li><li class="level-2"><a class="final" href="/datacollection/eventapi/"><span>Collecting Data with REST/SDKs</span></a></li><li class="level-2"><a class="final" href="/datacollection/eventmodel/"><span>Events Modeling</span></a></li><li class="level-2"><a class="final" href="/datacollection/webhooks/"><span>Unifying Multichannel Data with Webhooks</span></a></li><li class="level-2"><a class="final" href="/datacollection/channel/"><span>Channel</span></a></li><li class="level-2"><a class="final" href="/datacollection/batchimport/"><span>Importing Data in Batch</span></a></li><li class="level-2"><a class="final" href="/datacollection/analytics/"><span>Using Analytics Tools</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Choosing an Algorithm(s)</span></a><ul><li class="level-2"><a class
="final" href="/algorithm/"><span>Built-in Algorithm Libraries</span></a></li><li class="level-2"><a class="final" href="/algorithm/switch/"><span>Switching to Another Algorithm</span></a></li><li class="level-2"><a class="final active" href="/algorithm/multiple/"><span>Combining Multiple Algorithms</span></a></li><li class="level-2"><a class="final" href="/algorithm/custom/"><span>Adding Your Own Algorithms</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>ML Tuning and Evaluation</span></a><ul><li class="level-2"><a class="final" href="/evaluation/"><span>Overview</span></a></li><li class="level-2"><a class="final" href="/evaluation/paramtuning/"><span>Hyperparameter Tuning</span></a></li><li class="level-2"><a class="final" href="/evaluation/evaluationdashboard/"><span>Evaluation Dashboard</span></a></li><li class="level-2"><a class="final" href="/evaluation/metricchoose/"><span>Choosing Evaluation Metrics</span></a></li><li class="level-2"><a clas
s="final" href="/evaluation/metricbuild/"><span>Building Evaluation Metrics</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>System Architecture</span></a><ul><li class="level-2"><a class="final" href="/system/"><span>Architecture Overview</span></a></li><li class="level-2"><a class="final" href="/system/anotherdatastore/"><span>Using Another Data Store</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Engine Template Gallery</span></a><ul><li class="level-2"><a class="final" href="http://templates.prediction.io"><span>Browse</span></a></li><li class="level-2"><a class="final" href="/community/submit-template/"><span>Submit your Engine as a Template</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Demo Tutorials</span></a><ul><li class="level-2"><a class="final" href="/demo/tapster/"><span>Comics Recommendation Demo</span></a></li><li class="level-2"><a class="final" href="/demo/communi
ty/"><span>Community Contributed Demo</span></a></li><li class="level-2"><a class="final" href="/demo/textclassification/"><span>Text Classification Engine Tutorial</span></a></li></ul></li><li class="level-1"><a class="expandible" href="/community/"><span>Getting Involved</span></a><ul><li class="level-2"><a class="final" href="/community/contribute-code/"><span>Contribute Code</span></a></li><li class="level-2"><a class="final" href="/community/contribute-documentation/"><span>Contribute Documentation</span></a></li><li class="level-2"><a class="final" href="/community/contribute-sdk/"><span>Contribute a SDK</span></a></li><li class="level-2"><a class="final" href="/community/contribute-webhook/"><span>Contribute a Webhook</span></a></li><li class="level-2"><a class="final" href="/community/projects/"><span>Community Projects</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Getting Help</span></a><ul><li class="level-2"><a class="final" href="/reso
urces/faq/"><span>FAQs</span></a></li><li class="level-2"><a class="final" href="/support/"><span>Community Support</span></a></li><li class="level-2"><a class="final" href="/support/#enterprise-support"><span>Enterprise Support</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Resources</span></a><ul><li class="level-2"><a class="final" href="/resources/intellij/"><span>Developing Engines with IntelliJ IDEA</span></a></li><li class="level-2"><a class="final" href="/resources/upgrade/"><span>Upgrade Instructions</span></a></li><li class="level-2"><a class="final" href="/resources/glossary/"><span>Glossary</span></a></li></ul></li></ul></nav></div><div class="col-md-9 col-sm-12"><div class="content-header hidden-md hidden-lg"><div id="breadcrumbs" class="hidden-sm hidden xs"><ul><li><a href="#">Choosing an Algorithm(s)</a><span class="spacer">></span></li><li><span class="last">Combining Multiple Algorithms</span></li></ul></div><div id="page-title"
><h1>Combining Multiple Algorithms</h1></div></div><div id="table-of-content-wrapper"><a id="edit-page-link" href="https://github.com/apache/incubator-predictionio/tree/livedoc/docs/manual/source/algorithm/multiple.html.md"><img src="/images/icons/edit-pencil-d6c1bb3d.png"/>Edit this page</a></div><div class="content-header hidden-sm hidden-xs"><div id="breadcrumbs" class="hidden-sm hidden xs"><ul><li><a href="#">Choosing an Algorithm(s)</a><span class="spacer">></span></li><li><span class="last">Combining Multiple Algorithms</span></li></ul></div><div id="page-title"><h1>Combining Multiple Algorithms</h1></div></div><div class="content"><p>You can use more than one algorithm to build multiple models in an engine. The predicted results can be combined in the Serving class.</p><p>Here are some How-to examples:</p> <ul> <li><a href="/templates/similarproduct/multi-events-multi-algos/">Similar Product template - Multiple Events and Multiple Algorithms</a></li> </ul> </div></div></di
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<div class="row"><div class="col-md-9 col-sm-11 col-xs-11"><div class="hidden-md hidden-lg" id="mobile-page-heading-wrapper"><p>PredictionIO Docs</p><h4>Switching to Another Algorithm</h4></div><h4 class="hidden-sm hidden-xs">PredictionIO Docs</h4></div><div class="col-md-3 col-sm-1 col-xs-1 hidden-md hidden-lg"><img id="left-menu-indicator" src="/images/icons/down-arrow-dfe9f7fe.png"/></div><div class="col-md-3 col-sm-12 col-xs-12 swiftype-wrapper"><div class="swiftype"><form class="search-form"><img class="search-box-toggler hidden-xs hidden-sm" src="/images/icons/search-glass-704bd4ff.png"/><div class="search-box"><img src="/images/icons/search-glass-704bd4ff.png"/><input type="text" id="st-search-input" class="st-search-input" placeholder="Search Doc..."/></div><img class="swiftype-row-hider hidden-md hidden-lg" src="/images/icons/drawer-toggle-active-fcbef12a.png"/></form></div></div><div class="mobile-left-menu-toggler hidden-md hidden-lg"></div></div></div></div><div id="page
" class="container-fluid"><div class="row"><div id="left-menu-wrapper" class="col-md-3"><nav id="nav-main"><ul><li class="level-1"><a class="expandible" href="/"><span>Apache PredictionIO (incubating) Documentation</span></a><ul><li class="level-2"><a class="final" href="/"><span>Welcome to Apache PredictionIO (incubating)</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Getting Started</span></a><ul><li class="level-2"><a class="final" href="/start/"><span>A Quick Intro</span></a></li><li class="level-2"><a class="final" href="/install/"><span>Installing Apache PredictionIO (incubating)</span></a></li><li class="level-2"><a class="final" href="/start/download/"><span>Downloading an Engine Template</span></a></li><li class="level-2"><a class="final" href="/start/deploy/"><span>Deploying Your First Engine</span></a></li><li class="level-2"><a class="final" href="/start/customize/"><span>Customizing the Engine</span></a></li></ul></li><li class="level-
1"><a class="expandible" href="#"><span>Integrating with Your App</span></a><ul><li class="level-2"><a class="final" href="/appintegration/"><span>App Integration Overview</span></a></li><li class="level-2"><a class="expandible" href="/sdk/"><span>List of SDKs</span></a><ul><li class="level-3"><a class="final" href="/sdk/java/"><span>Java & Android SDK</span></a></li><li class="level-3"><a class="final" href="/sdk/php/"><span>PHP SDK</span></a></li><li class="level-3"><a class="final" href="/sdk/python/"><span>Python SDK</span></a></li><li class="level-3"><a class="final" href="/sdk/ruby/"><span>Ruby SDK</span></a></li><li class="level-3"><a class="final" href="/sdk/community/"><span>Community Powered SDKs</span></a></li></ul></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Deploying an Engine</span></a><ul><li class="level-2"><a class="final" href="/deploy/"><span>Deploying as a Web Service</span></a></li><li class="level-2"><a class="final" href="/cli/#engin
e-commands"><span>Engine Command-line Interface</span></a></li><li class="level-2"><a class="final" href="/deploy/engineparams/"><span>Setting Engine Parameters</span></a></li><li class="level-2"><a class="final" href="/deploy/enginevariants/"><span>Deploying Multiple Engine Variants</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Customizing an Engine</span></a><ul><li class="level-2"><a class="final" href="/customize/"><span>Learning DASE</span></a></li><li class="level-2"><a class="final" href="/customize/dase/"><span>Implement DASE</span></a></li><li class="level-2"><a class="final" href="/customize/troubleshooting/"><span>Troubleshooting Engine Development</span></a></li><li class="level-2"><a class="final" href="/api/current/#package"><span>Engine Scala APIs</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Collecting and Analyzing Data</span></a><ul><li class="level-2"><a class="final" href="/datacollection/"><
span>Event Server Overview</span></a></li><li class="level-2"><a class="final" href="/cli/#event-server-commands"><span>Event Server Command-line Interface</span></a></li><li class="level-2"><a class="final" href="/datacollection/eventapi/"><span>Collecting Data with REST/SDKs</span></a></li><li class="level-2"><a class="final" href="/datacollection/eventmodel/"><span>Events Modeling</span></a></li><li class="level-2"><a class="final" href="/datacollection/webhooks/"><span>Unifying Multichannel Data with Webhooks</span></a></li><li class="level-2"><a class="final" href="/datacollection/channel/"><span>Channel</span></a></li><li class="level-2"><a class="final" href="/datacollection/batchimport/"><span>Importing Data in Batch</span></a></li><li class="level-2"><a class="final" href="/datacollection/analytics/"><span>Using Analytics Tools</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Choosing an Algorithm(s)</span></a><ul><li class="level-2"><a clas
s="final" href="/algorithm/"><span>Built-in Algorithm Libraries</span></a></li><li class="level-2"><a class="final active" href="/algorithm/switch/"><span>Switching to Another Algorithm</span></a></li><li class="level-2"><a class="final" href="/algorithm/multiple/"><span>Combining Multiple Algorithms</span></a></li><li class="level-2"><a class="final" href="/algorithm/custom/"><span>Adding Your Own Algorithms</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>ML Tuning and Evaluation</span></a><ul><li class="level-2"><a class="final" href="/evaluation/"><span>Overview</span></a></li><li class="level-2"><a class="final" href="/evaluation/paramtuning/"><span>Hyperparameter Tuning</span></a></li><li class="level-2"><a class="final" href="/evaluation/evaluationdashboard/"><span>Evaluation Dashboard</span></a></li><li class="level-2"><a class="final" href="/evaluation/metricchoose/"><span>Choosing Evaluation Metrics</span></a></li><li class="level-2"><a cla
ss="final" href="/evaluation/metricbuild/"><span>Building Evaluation Metrics</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>System Architecture</span></a><ul><li class="level-2"><a class="final" href="/system/"><span>Architecture Overview</span></a></li><li class="level-2"><a class="final" href="/system/anotherdatastore/"><span>Using Another Data Store</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Engine Template Gallery</span></a><ul><li class="level-2"><a class="final" href="http://templates.prediction.io"><span>Browse</span></a></li><li class="level-2"><a class="final" href="/community/submit-template/"><span>Submit your Engine as a Template</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Demo Tutorials</span></a><ul><li class="level-2"><a class="final" href="/demo/tapster/"><span>Comics Recommendation Demo</span></a></li><li class="level-2"><a class="final" href="/demo/commun
ity/"><span>Community Contributed Demo</span></a></li><li class="level-2"><a class="final" href="/demo/textclassification/"><span>Text Classification Engine Tutorial</span></a></li></ul></li><li class="level-1"><a class="expandible" href="/community/"><span>Getting Involved</span></a><ul><li class="level-2"><a class="final" href="/community/contribute-code/"><span>Contribute Code</span></a></li><li class="level-2"><a class="final" href="/community/contribute-documentation/"><span>Contribute Documentation</span></a></li><li class="level-2"><a class="final" href="/community/contribute-sdk/"><span>Contribute a SDK</span></a></li><li class="level-2"><a class="final" href="/community/contribute-webhook/"><span>Contribute a Webhook</span></a></li><li class="level-2"><a class="final" href="/community/projects/"><span>Community Projects</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Getting Help</span></a><ul><li class="level-2"><a class="final" href="/res
ources/faq/"><span>FAQs</span></a></li><li class="level-2"><a class="final" href="/support/"><span>Community Support</span></a></li><li class="level-2"><a class="final" href="/support/#enterprise-support"><span>Enterprise Support</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Resources</span></a><ul><li class="level-2"><a class="final" href="/resources/intellij/"><span>Developing Engines with IntelliJ IDEA</span></a></li><li class="level-2"><a class="final" href="/resources/upgrade/"><span>Upgrade Instructions</span></a></li><li class="level-2"><a class="final" href="/resources/glossary/"><span>Glossary</span></a></li></ul></li></ul></nav></div><div class="col-md-9 col-sm-12"><div class="content-header hidden-md hidden-lg"><div id="breadcrumbs" class="hidden-sm hidden xs"><ul><li><a href="#">Choosing an Algorithm(s)</a><span class="spacer">></span></li><li><span class="last">Switching to Another Algorithm</span></li></ul></div><div id="page-titl
e"><h1>Switching to Another Algorithm</h1></div></div><div id="table-of-content-wrapper"><a id="edit-page-link" href="https://github.com/apache/incubator-predictionio/tree/livedoc/docs/manual/source/algorithm/switch.html.md"><img src="/images/icons/edit-pencil-d6c1bb3d.png"/>Edit this page</a></div><div class="content-header hidden-sm hidden-xs"><div id="breadcrumbs" class="hidden-sm hidden xs"><ul><li><a href="#">Choosing an Algorithm(s)</a><span class="spacer">></span></li><li><span class="last">Switching to Another Algorithm</span></li></ul></div><div id="page-title"><h1>Switching to Another Algorithm</h1></div></div><div class="content"><p>Every engine template comes with default algorithm(s). To switch to another algorithm, you simply need to modify the Algorithm class.</p><p>Here are some How-to examples:</p> <ul> <li><a href="/templates/classification/add-algorithm/">Classification template - switching from NaiveBayes to Random Forests</a></li> </ul> </div></div></div></di
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<div class="row"><div class="col-md-9 col-sm-11 col-xs-11"><div class="hidden-md hidden-lg" id="mobile-page-heading-wrapper"><p>PredictionIO Docs</p><h4>App Integration Overview</h4></div><h4 class="hidden-sm hidden-xs">PredictionIO Docs</h4></div><div class="col-md-3 col-sm-1 col-xs-1 hidden-md hidden-lg"><img id="left-menu-indicator" src="/images/icons/down-arrow-dfe9f7fe.png"/></div><div class="col-md-3 col-sm-12 col-xs-12 swiftype-wrapper"><div class="swiftype"><form class="search-form"><img class="search-box-toggler hidden-xs hidden-sm" src="/images/icons/search-glass-704bd4ff.png"/><div class="search-box"><img src="/images/icons/search-glass-704bd4ff.png"/><input type="text" id="st-search-input" class="st-search-input" placeholder="Search Doc..."/></div><img class="swiftype-row-hider hidden-md hidden-lg" src="/images/icons/drawer-toggle-active-fcbef12a.png"/></form></div></div><div class="mobile-left-menu-toggler hidden-md hidden-lg"></div></div></div></div><div id="page" clas
s="container-fluid"><div class="row"><div id="left-menu-wrapper" class="col-md-3"><nav id="nav-main"><ul><li class="level-1"><a class="expandible" href="/"><span>Apache PredictionIO (incubating) Documentation</span></a><ul><li class="level-2"><a class="final" href="/"><span>Welcome to Apache PredictionIO (incubating)</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Getting Started</span></a><ul><li class="level-2"><a class="final" href="/start/"><span>A Quick Intro</span></a></li><li class="level-2"><a class="final" href="/install/"><span>Installing Apache PredictionIO (incubating)</span></a></li><li class="level-2"><a class="final" href="/start/download/"><span>Downloading an Engine Template</span></a></li><li class="level-2"><a class="final" href="/start/deploy/"><span>Deploying Your First Engine</span></a></li><li class="level-2"><a class="final" href="/start/customize/"><span>Customizing the Engine</span></a></li></ul></li><li class="level-1"><a
class="expandible" href="#"><span>Integrating with Your App</span></a><ul><li class="level-2"><a class="final active" href="/appintegration/"><span>App Integration Overview</span></a></li><li class="level-2"><a class="expandible" href="/sdk/"><span>List of SDKs</span></a><ul><li class="level-3"><a class="final" href="/sdk/java/"><span>Java & Android SDK</span></a></li><li class="level-3"><a class="final" href="/sdk/php/"><span>PHP SDK</span></a></li><li class="level-3"><a class="final" href="/sdk/python/"><span>Python SDK</span></a></li><li class="level-3"><a class="final" href="/sdk/ruby/"><span>Ruby SDK</span></a></li><li class="level-3"><a class="final" href="/sdk/community/"><span>Community Powered SDKs</span></a></li></ul></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Deploying an Engine</span></a><ul><li class="level-2"><a class="final" href="/deploy/"><span>Deploying as a Web Service</span></a></li><li class="level-2"><a class="final" href="/cli/#engi
ne-commands"><span>Engine Command-line Interface</span></a></li><li class="level-2"><a class="final" href="/deploy/engineparams/"><span>Setting Engine Parameters</span></a></li><li class="level-2"><a class="final" href="/deploy/enginevariants/"><span>Deploying Multiple Engine Variants</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Customizing an Engine</span></a><ul><li class="level-2"><a class="final" href="/customize/"><span>Learning DASE</span></a></li><li class="level-2"><a class="final" href="/customize/dase/"><span>Implement DASE</span></a></li><li class="level-2"><a class="final" href="/customize/troubleshooting/"><span>Troubleshooting Engine Development</span></a></li><li class="level-2"><a class="final" href="/api/current/#package"><span>Engine Scala APIs</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Collecting and Analyzing Data</span></a><ul><li class="level-2"><a class="final" href="/datacollection/">
<span>Event Server Overview</span></a></li><li class="level-2"><a class="final" href="/cli/#event-server-commands"><span>Event Server Command-line Interface</span></a></li><li class="level-2"><a class="final" href="/datacollection/eventapi/"><span>Collecting Data with REST/SDKs</span></a></li><li class="level-2"><a class="final" href="/datacollection/eventmodel/"><span>Events Modeling</span></a></li><li class="level-2"><a class="final" href="/datacollection/webhooks/"><span>Unifying Multichannel Data with Webhooks</span></a></li><li class="level-2"><a class="final" href="/datacollection/channel/"><span>Channel</span></a></li><li class="level-2"><a class="final" href="/datacollection/batchimport/"><span>Importing Data in Batch</span></a></li><li class="level-2"><a class="final" href="/datacollection/analytics/"><span>Using Analytics Tools</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Choosing an Algorithm(s)</span></a><ul><li class="level-2"><a cla
ss="final" href="/algorithm/"><span>Built-in Algorithm Libraries</span></a></li><li class="level-2"><a class="final" href="/algorithm/switch/"><span>Switching to Another Algorithm</span></a></li><li class="level-2"><a class="final" href="/algorithm/multiple/"><span>Combining Multiple Algorithms</span></a></li><li class="level-2"><a class="final" href="/algorithm/custom/"><span>Adding Your Own Algorithms</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>ML Tuning and Evaluation</span></a><ul><li class="level-2"><a class="final" href="/evaluation/"><span>Overview</span></a></li><li class="level-2"><a class="final" href="/evaluation/paramtuning/"><span>Hyperparameter Tuning</span></a></li><li class="level-2"><a class="final" href="/evaluation/evaluationdashboard/"><span>Evaluation Dashboard</span></a></li><li class="level-2"><a class="final" href="/evaluation/metricchoose/"><span>Choosing Evaluation Metrics</span></a></li><li class="level-2"><a class="fi
nal" href="/evaluation/metricbuild/"><span>Building Evaluation Metrics</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>System Architecture</span></a><ul><li class="level-2"><a class="final" href="/system/"><span>Architecture Overview</span></a></li><li class="level-2"><a class="final" href="/system/anotherdatastore/"><span>Using Another Data Store</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Engine Template Gallery</span></a><ul><li class="level-2"><a class="final" href="http://templates.prediction.io"><span>Browse</span></a></li><li class="level-2"><a class="final" href="/community/submit-template/"><span>Submit your Engine as a Template</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Demo Tutorials</span></a><ul><li class="level-2"><a class="final" href="/demo/tapster/"><span>Comics Recommendation Demo</span></a></li><li class="level-2"><a class="final" href="/demo/community/">
<span>Community Contributed Demo</span></a></li><li class="level-2"><a class="final" href="/demo/textclassification/"><span>Text Classification Engine Tutorial</span></a></li></ul></li><li class="level-1"><a class="expandible" href="/community/"><span>Getting Involved</span></a><ul><li class="level-2"><a class="final" href="/community/contribute-code/"><span>Contribute Code</span></a></li><li class="level-2"><a class="final" href="/community/contribute-documentation/"><span>Contribute Documentation</span></a></li><li class="level-2"><a class="final" href="/community/contribute-sdk/"><span>Contribute a SDK</span></a></li><li class="level-2"><a class="final" href="/community/contribute-webhook/"><span>Contribute a Webhook</span></a></li><li class="level-2"><a class="final" href="/community/projects/"><span>Community Projects</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Getting Help</span></a><ul><li class="level-2"><a class="final" href="/resources
/faq/"><span>FAQs</span></a></li><li class="level-2"><a class="final" href="/support/"><span>Community Support</span></a></li><li class="level-2"><a class="final" href="/support/#enterprise-support"><span>Enterprise Support</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Resources</span></a><ul><li class="level-2"><a class="final" href="/resources/intellij/"><span>Developing Engines with IntelliJ IDEA</span></a></li><li class="level-2"><a class="final" href="/resources/upgrade/"><span>Upgrade Instructions</span></a></li><li class="level-2"><a class="final" href="/resources/glossary/"><span>Glossary</span></a></li></ul></li></ul></nav></div><div class="col-md-9 col-sm-12"><div class="content-header hidden-md hidden-lg"><div id="breadcrumbs" class="hidden-sm hidden xs"><ul><li><a href="#">Integrating with Your App</a><span class="spacer">></span></li><li><span class="last">App Integration Overview</span></li></ul></div><div id="page-title"><h1>App
Integration Overview</h1></div></div><div id="table-of-content-wrapper"><h5>On this page</h5><aside id="table-of-contents"><ul> <li> <a href="#sending-event-data">Sending Event Data</a> </li> <li> <a href="#sending-query">Sending Query</a> </li> </ul> </aside><hr/><a id="edit-page-link" href="https://github.com/apache/incubator-predictionio/tree/livedoc/docs/manual/source/appintegration/index.html.md"><img src="/images/icons/edit-pencil-d6c1bb3d.png"/>Edit this page</a></div><div class="content-header hidden-sm hidden-xs"><div id="breadcrumbs" class="hidden-sm hidden xs"><ul><li><a href="#">Integrating with Your App</a><span class="spacer">></span></li><li><span class="last">App Integration Overview</span></li></ul></div><div id="page-title"><h1>App Integration Overview</h1></div></div><div class="content"><p>Apache PredictionIO (incubating) is designed as a machine learning server that integrates with your applications on production environments.</p><p>A web or mobile app normal
ly:</p> <ol> <li> Send event data to Apache PredictionIO (incubating)'s Event Server for model training</li> <li> Send dynamic queries to deployed engine(s) to retrieve predicted results</li> </ol> <p><img alt="Apache PredictionIO (incubating) Single Engine Overview" src="/images/overview-singleengine-0a99200d.png"/></p><h2 id='sending-event-data' class='header-anchors'>Sending Event Data</h2><p>Apache PredictionIO (incubating)'s Event Server receives event data from your application. The data can be used by engines as training data to build preditive models.</p><p>Event Server listens to port 7070 by default. You can change the port with the <a href="/cli/#event-server-commands">--port arg</a> when you launch the Event Server.</p><p>For further information, please read:</p> <ul> <li><a href="/datacollection/">Event Server Overview</a></li> <li><a href="/datacollection/eventapi">Collecting Data with REST/SDKs</a></li> </ul> <h2 id='sending-query' class='header-anchors'>Sendi
ng Query</h2><p>After you deploy an engine as a web service, it will wait for queries from your application and return predicted results in JSON format. An engine listens to port 8000 by default. If you want to deploy multiple engines, you can specific a different port for each of them.</p><p>For further information, please read:</p> <ul> <li><a href="/deploy/">Deploying an Engine as a Web Service</a></li> </ul> </div></div></div></div><footer><div class="container"><div class="seperator"></div><div class="row"><div class="col-md-4 col-md-push-8 col-xs-12"><div class="subscription-form-wrapper"><h4>Subscribe to our Newsletter</h4><form class="ajax-form" id="subscribe-form" method="POST" action="https://script.google.com/macros/s/AKfycbwhzeKCQJjQ52eVAqNT_vcklH07OITUO7wzOMDXvK6EGAWgaZgF/exec"><input class="required underlined-input" type="email" placeholder="Your email address" name="subscription_email" id="subscription_email"/><input class="pill-button" value="SUBSCRIBE" type="submit
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+fbq('track', "PageView");</script><script src="//use.typekit.net/mut4mjx.js"></script><script>try{Typekit.load();}catch(e){}</script></head><body><div id="global"><header><div class="container" id="header-wrapper"><div class="row"><div class="col-sm-12"><div id="logo-wrapper"><span id="drawer-toggle"></span><a href="#"></a><a href="http://prediction.io/"><img alt="PredictionIO" id="logo" src="/images/logos/logo-ee2b9bb3.png"/></a></div><div id="menu-wrapper"><div id="header-nav-options-wrapper"><ul><li><a href="/">Install & Doc</a></li> <li><a href="/support">Support</a></li> </ul></div><div id="pill-wrapper"><a class="pill left" href="//templates.prediction.io/">TEMPLATES</a> <a class="pill right" href="//github.com/PredictionIO/PredictionIO/">OPEN SOURCE</a></div></div><img class="mobile-search-bar-toggler hidden-md hidden-lg" src="/images/icons/search-glass-704bd4ff.png"/></div></div></div></header><div id="search-bar-row-wrapper"><div class="container-fluid" id="search-bar-row">
<div class="row"><div class="col-md-9 col-sm-11 col-xs-11"><div class="hidden-md hidden-lg" id="mobile-page-heading-wrapper"><p>PredictionIO Docs</p><h4>Collecting Data with REST/SDKs</h4></div><h4 class="hidden-sm hidden-xs">PredictionIO Docs</h4></div><div class="col-md-3 col-sm-1 col-xs-1 hidden-md hidden-lg"><img id="left-menu-indicator" src="/images/icons/down-arrow-dfe9f7fe.png"/></div><div class="col-md-3 col-sm-12 col-xs-12 swiftype-wrapper"><div class="swiftype"><form class="search-form"><img class="search-box-toggler hidden-xs hidden-sm" src="/images/icons/search-glass-704bd4ff.png"/><div class="search-box"><img src="/images/icons/search-glass-704bd4ff.png"/><input type="text" id="st-search-input" class="st-search-input" placeholder="Search Doc..."/></div><img class="swiftype-row-hider hidden-md hidden-lg" src="/images/icons/drawer-toggle-active-fcbef12a.png"/></form></div></div><div class="mobile-left-menu-toggler hidden-md hidden-lg"></div></div></div></div><div id="page
" class="container-fluid"><div class="row"><div id="left-menu-wrapper" class="col-md-3"><nav id="nav-main"><ul><li class="level-1"><a class="expandible" href="/"><span>Apache PredictionIO (incubating) Documentation</span></a><ul><li class="level-2"><a class="final" href="/"><span>Welcome to Apache PredictionIO (incubating)</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Getting Started</span></a><ul><li class="level-2"><a class="final" href="/start/"><span>A Quick Intro</span></a></li><li class="level-2"><a class="final" href="/install/"><span>Installing Apache PredictionIO (incubating)</span></a></li><li class="level-2"><a class="final" href="/start/download/"><span>Downloading an Engine Template</span></a></li><li class="level-2"><a class="final" href="/start/deploy/"><span>Deploying Your First Engine</span></a></li><li class="level-2"><a class="final" href="/start/customize/"><span>Customizing the Engine</span></a></li></ul></li><li class="level-
1"><a class="expandible" href="#"><span>Integrating with Your App</span></a><ul><li class="level-2"><a class="final" href="/appintegration/"><span>App Integration Overview</span></a></li><li class="level-2"><a class="expandible" href="/sdk/"><span>List of SDKs</span></a><ul><li class="level-3"><a class="final" href="/sdk/java/"><span>Java & Android SDK</span></a></li><li class="level-3"><a class="final" href="/sdk/php/"><span>PHP SDK</span></a></li><li class="level-3"><a class="final" href="/sdk/python/"><span>Python SDK</span></a></li><li class="level-3"><a class="final" href="/sdk/ruby/"><span>Ruby SDK</span></a></li><li class="level-3"><a class="final" href="/sdk/community/"><span>Community Powered SDKs</span></a></li></ul></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Deploying an Engine</span></a><ul><li class="level-2"><a class="final" href="/deploy/"><span>Deploying as a Web Service</span></a></li><li class="level-2"><a class="final" href="/cli/#engin
e-commands"><span>Engine Command-line Interface</span></a></li><li class="level-2"><a class="final" href="/deploy/engineparams/"><span>Setting Engine Parameters</span></a></li><li class="level-2"><a class="final" href="/deploy/enginevariants/"><span>Deploying Multiple Engine Variants</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Customizing an Engine</span></a><ul><li class="level-2"><a class="final" href="/customize/"><span>Learning DASE</span></a></li><li class="level-2"><a class="final" href="/customize/dase/"><span>Implement DASE</span></a></li><li class="level-2"><a class="final" href="/customize/troubleshooting/"><span>Troubleshooting Engine Development</span></a></li><li class="level-2"><a class="final" href="/api/current/#package"><span>Engine Scala APIs</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Collecting and Analyzing Data</span></a><ul><li class="level-2"><a class="final" href="/datacollection/"><
span>Event Server Overview</span></a></li><li class="level-2"><a class="final" href="/cli/#event-server-commands"><span>Event Server Command-line Interface</span></a></li><li class="level-2"><a class="final active" href="/datacollection/eventapi/"><span>Collecting Data with REST/SDKs</span></a></li><li class="level-2"><a class="final" href="/datacollection/eventmodel/"><span>Events Modeling</span></a></li><li class="level-2"><a class="final" href="/datacollection/webhooks/"><span>Unifying Multichannel Data with Webhooks</span></a></li><li class="level-2"><a class="final" href="/datacollection/channel/"><span>Channel</span></a></li><li class="level-2"><a class="final" href="/datacollection/batchimport/"><span>Importing Data in Batch</span></a></li><li class="level-2"><a class="final" href="/datacollection/analytics/"><span>Using Analytics Tools</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Choosing an Algorithm(s)</span></a><ul><li class="level-2">
<a class="final" href="/algorithm/"><span>Built-in Algorithm Libraries</span></a></li><li class="level-2"><a class="final" href="/algorithm/switch/"><span>Switching to Another Algorithm</span></a></li><li class="level-2"><a class="final" href="/algorithm/multiple/"><span>Combining Multiple Algorithms</span></a></li><li class="level-2"><a class="final" href="/algorithm/custom/"><span>Adding Your Own Algorithms</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>ML Tuning and Evaluation</span></a><ul><li class="level-2"><a class="final" href="/evaluation/"><span>Overview</span></a></li><li class="level-2"><a class="final" href="/evaluation/paramtuning/"><span>Hyperparameter Tuning</span></a></li><li class="level-2"><a class="final" href="/evaluation/evaluationdashboard/"><span>Evaluation Dashboard</span></a></li><li class="level-2"><a class="final" href="/evaluation/metricchoose/"><span>Choosing Evaluation Metrics</span></a></li><li class="level-2"><a cla
ss="final" href="/evaluation/metricbuild/"><span>Building Evaluation Metrics</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>System Architecture</span></a><ul><li class="level-2"><a class="final" href="/system/"><span>Architecture Overview</span></a></li><li class="level-2"><a class="final" href="/system/anotherdatastore/"><span>Using Another Data Store</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Engine Template Gallery</span></a><ul><li class="level-2"><a class="final" href="http://templates.prediction.io"><span>Browse</span></a></li><li class="level-2"><a class="final" href="/community/submit-template/"><span>Submit your Engine as a Template</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Demo Tutorials</span></a><ul><li class="level-2"><a class="final" href="/demo/tapster/"><span>Comics Recommendation Demo</span></a></li><li class="level-2"><a class="final" href="/demo/commun
ity/"><span>Community Contributed Demo</span></a></li><li class="level-2"><a class="final" href="/demo/textclassification/"><span>Text Classification Engine Tutorial</span></a></li></ul></li><li class="level-1"><a class="expandible" href="/community/"><span>Getting Involved</span></a><ul><li class="level-2"><a class="final" href="/community/contribute-code/"><span>Contribute Code</span></a></li><li class="level-2"><a class="final" href="/community/contribute-documentation/"><span>Contribute Documentation</span></a></li><li class="level-2"><a class="final" href="/community/contribute-sdk/"><span>Contribute a SDK</span></a></li><li class="level-2"><a class="final" href="/community/contribute-webhook/"><span>Contribute a Webhook</span></a></li><li class="level-2"><a class="final" href="/community/projects/"><span>Community Projects</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Getting Help</span></a><ul><li class="level-2"><a class="final" href="/res
ources/faq/"><span>FAQs</span></a></li><li class="level-2"><a class="final" href="/support/"><span>Community Support</span></a></li><li class="level-2"><a class="final" href="/support/#enterprise-support"><span>Enterprise Support</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Resources</span></a><ul><li class="level-2"><a class="final" href="/resources/intellij/"><span>Developing Engines with IntelliJ IDEA</span></a></li><li class="level-2"><a class="final" href="/resources/upgrade/"><span>Upgrade Instructions</span></a></li><li class="level-2"><a class="final" href="/resources/glossary/"><span>Glossary</span></a></li></ul></li></ul></nav></div><div class="col-md-9 col-sm-12"><div class="content-header hidden-md hidden-lg"><div id="breadcrumbs" class="hidden-sm hidden xs"><ul><li><a href="#">Collecting and Analyzing Data</a><span class="spacer">></span></li><li><span class="last">Collecting Data with REST/SDKs</span></li></ul></div><div id="page
-title"><h1>Collecting Data through REST/SDKs</h1></div></div><div id="table-of-content-wrapper"><h5>On this page</h5><aside id="table-of-contents"><ul> <li> <a href="#launching-the-event-server">Launching the Event Server</a> </li> <li> <a href="#using-event-api">Using Event API</a> </li> <li> <a href="#note-about-properties">Note About Properties</a> </li> <li> <a href="#debugging-recipes">Debugging Recipes</a> </li> </ul> </aside><hr/><a id="edit-page-link" href="https://github.com/apache/incubator-predictionio/tree/livedoc/docs/manual/source/datacollection/eventapi.html.md"><img src="/images/icons/edit-pencil-d6c1bb3d.png"/>Edit this page</a></div><div class="content-header hidden-sm hidden-xs"><div id="breadcrumbs" class="hidden-sm hidden xs"><ul><li><a href="#">Collecting and Analyzing Data</a><span class="spacer">></span></li><li><span class="last">Collecting Data with REST/SDKs</span></li></ul></div><div id="page-title"><h1>Collecting Data through REST/SDKs</h1></div></di
v><div class="content"><p><strong>Event Server</strong> is designed to collect data into Apache PredictionIO (incubating) in an event-based style. Once the Event Server is launched, your application can send data to it through its <strong>Event API</strong> with HTTP requests or with <code>EventClient</code>s of PredictionIO's SDKs.</p><div class="alert-message info"><p>All Apache PredictionIO (incubating)-compliant engines support accessing the Event Store (i.e. the data store of Event Server) through <a href="http://docs.prediction.io/api/current/index.html#io.prediction.data.storage.package">Apache PredictionIO (incubating)'s Storage API</a>.</p></div><h2 id='launching-the-event-server' class='header-anchors'>Launching the Event Server</h2><div class="alert-message info"><p>Before launching the Event Server, make sure that your event data store backend is properly configured and is running. By default, Apache PredictionIO (incubating) uses Apache HBase, and a quick config
uration can be found <a href="/install/install-linux/#hbase">here</a>. Please allow a minute (usually less than 30 seconds) after HBase is started for its initialization to complete before starting the Event Server.</p></div><p>Everything about Apache PredictionIO (incubating) can be done through the <code>pio</code> command. Please add PIO binary command path to to your <code>PATH</code> first. Assuming PredictionIO is installed at <code>/home/yourname/PredictionIO/</code>, you can run</p><div class="highlight shell"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1</pre></td><td class="code"><pre><span class="gp">$ </span><span class="nv">PATH</span><span class="o">=</span><span class="nv">$PATH</span>:/home/yourname/PredictionIO/bin; <span class="nb">export </span>PATH
+</pre></td></tr></tbody></table> </div> <p>To start the event server, run</p><div class="highlight shell"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1</pre></td><td class="code"><pre><span class="gp">$ </span>pio eventserver
+</pre></td></tr></tbody></table> </div> <div class="alert-message info"><p>By default, the Event Server is bound to 0.0.0.0, which serves global traffic. To tighten security, you may use <code>pio eventserver --ip 127.0.0.1</code> to serve only local traffic.</p></div><h3 id='check-server-status' class='header-anchors'>Check Server Status</h3><div class="highlight shell"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1</pre></td><td class="code"><pre><span class="gp">$ </span>curl -i -X GET http://localhost:7070
+</pre></td></tr></tbody></table> </div> <p>Sample response:</p><div class="highlight shell"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1
+2
+3
+4
+5
+6
+7</pre></td><td class="code"><pre>HTTP/1.1 200 OK
+Server: spray-can/1.2.1
+Date: Wed, 10 Sep 2014 22:37:30 GMT
+Content-Type: application/json; <span class="nv">charset</span><span class="o">=</span>UTF-8
+Content-Length: 18
+
+<span class="o">{</span><span class="s2">"status"</span>:<span class="s2">"alive"</span><span class="o">}</span>
+</pre></td></tr></tbody></table> </div> <h3 id='generating-app-id-and-access-key' class='header-anchors'>Generating App ID and Access Key</h3><p>First, you need to create a new app in the Event Server. You will later send data into it.</p><div class="highlight shell"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1</pre></td><td class="code"><pre><span class="gp">$ </span>pio app new MyTestApp
+</pre></td></tr></tbody></table> </div> <blockquote> <p>You can replace <code>MyTestApp</code> with name of your App.</p></blockquote> <p>Take note of the <em>Access Key</em> and <em>App ID</em> generated. You need the <em>Access Key</em> to use the Event API. You should see something like the following output:</p><div class="highlight shell"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1
+2
+3
+4</pre></td><td class="code"><pre><span class="o">[</span>INFO] <span class="o">[</span>App<span class="nv">$]</span> Created new app:
+<span class="o">[</span>INFO] <span class="o">[</span>App<span class="nv">$]</span> Name: MyTestApp
+<span class="o">[</span>INFO] <span class="o">[</span>App<span class="nv">$]</span> ID: 6
+<span class="o">[</span>INFO] <span class="o">[</span>App<span class="nv">$]</span> Access Key: WPgcXKd42FPQpZHVbVeMyqF4CQJUnXQmIMTHhX3ZUrSzvy1KXJjdFUrslifa9rnB
+</pre></td></tr></tbody></table> </div> <h3 id='creating-your-first-event' class='header-anchors'>Creating Your First Event</h3><p>You may connect to the Event Server with HTTP request or by using one of many <strong>Apache PredictionIO (incubating) SDKs</strong>.</p><p>For example, the following shows how one can create an event involving a single entity. Replace the value of <code>accessKey</code> by the <em>Access Key</em> generated for your App.</p><div class="tabs"> <ul class="control"> <li data-lang="bash"><a href="#tab-48f668a0-58f7-467b-bec4-b95bdf3cbcb7">Raw HTTP</a></li> <li data-lang="php"><a href="#tab-b541c121-6d9a-4b65-887c-2741faa65398">PHP SDK</a></li> <li data-lang="python"><a href="#tab-1fd5a428-364e-4983-a529-d46a8eee03e0">Python SDK</a></li> <li data-lang="ruby"><a href="#tab-e456c0ba-d59e-47db-91c1-c5fed4d87561">Ruby SDK</a></li> <li data-lang="java"><a href="#tab-33d2a0b0-f63b-4e11-b007-a21af081feaa">Java SDK</a></li> </ul> <div data-tab="Raw HTTP" data-lang="b
ash" id="tab-48f668a0-58f7-467b-bec4-b95bdf3cbcb7"> <div class="highlight shell"> <table style="border-spacing: 0"><tbody><tr> <td class="gutter gl" style="text-align: right"><pre class="lineno">1
+2
+3
+4
+5
+6
+7
+8
+9
+10
+11
+12
+13
+14
+15
+16</pre></td> <td class="code"><pre><span class="gp">$ </span>curl -i -X POST http://localhost:7070/events.json?accessKey<span class="o">=</span>WPgcXKd42FPQpZHVbVeMyqF4CQJUnXQmIMTHhX3ZUrSzvy1KXJjdFUrslifa9rnB <span class="se">\</span>
+-H <span class="s2">"Content-Type: application/json"</span> <span class="se">\</span>
+-d <span class="s1">'{
+ "event" : "my_event",
+ "entityType" : "user"
+ "entityId" : "uid",
+ "properties" : {
+ "prop1" : 1,
+ "prop2" : "value2",
+ "prop3" : [1, 2, 3],
+ "prop4" : true,
+ "prop5" : ["a", "b", "c"],
+ "prop6" : 4.56
+ }
+ "eventTime" : "2004-12-13T21:39:45.618-07:00"
+}'</span>
+</pre></td> </tr></tbody></table> </div> </div> <div data-tab="PHP SDK" data-lang="php" id="tab-b541c121-6d9a-4b65-887c-2741faa65398"> <div class="highlight php"> <table style="border-spacing: 0"><tbody><tr> <td class="gutter gl" style="text-align: right"><pre class="lineno">1
+2
+3
+4
+5
+6
+7
+8
+9
+10
+11
+12
+13
+14
+15
+16
+17
+18
+19
+20
+21</pre></td> <td class="code"><pre><span class="cp"><?php</span>
+ <span class="k">require_once</span><span class="p">(</span><span class="s2">"vendor/autoload.php"</span><span class="p">);</span>
+
+ <span class="k">use</span> <span class="nx">predictionio\EventClient</span><span class="p">;</span>
+
+ <span class="nv">$accessKey</span> <span class="o">=</span> <span class="s1">'YOUR_ACCESS_KEY'</span><span class="p">;</span>
+ <span class="nv">$client</span> <span class="o">=</span> <span class="k">new</span> <span class="nx">EventClient</span><span class="p">(</span><span class="nv">$accessKey</span><span class="p">);</span>
+ <span class="nv">$response</span> <span class="o">=</span> <span class="nv">$client</span><span class="o">-></span><span class="na">createEvent</span><span class="p">(</span><span class="k">array</span><span class="p">(</span>
+ <span class="s1">'event'</span> <span class="o">=></span> <span class="s1">'my_event'</span><span class="p">,</span>
+ <span class="s1">'entityType'</span> <span class="o">=></span> <span class="s1">'user'</span><span class="p">,</span>
+ <span class="s1">'entityId'</span> <span class="o">=></span> <span class="s1">'uid'</span><span class="p">,</span>
+ <span class="s1">'properties'</span> <span class="o">=></span> <span class="k">array</span><span class="p">(</span><span class="s1">'prop1'</span> <span class="o">=></span> <span class="mi">1</span><span class="p">,</span>
+ <span class="s1">'prop2'</span> <span class="o">=></span> <span class="s1">'value2'</span><span class="p">,</span>
+ <span class="s1">'prop3'</span> <span class="o">=></span> <span class="k">array</span><span class="p">(</span><span class="mi">1</span><span class="p">,</span><span class="mi">2</span><span class="p">,</span><span class="mi">3</span><span class="p">),</span>
+ <span class="s1">'prop4'</span> <span class="o">=></span> <span class="kc">true</span><span class="p">,</span>
+ <span class="s1">'prop5'</span> <span class="o">=></span> <span class="k">array</span><span class="p">(</span><span class="s1">'a'</span><span class="p">,</span><span class="s1">'b'</span><span class="p">,</span><span class="s1">'c'</span><span class="p">),</span>
+ <span class="s1">'prop6'</span> <span class="o">=></span> <span class="mf">4.56</span>
+ <span class="p">),</span>
+ <span class="s1">'eventTime'</span> <span class="o">=></span> <span class="s1">'2004-12-13T21:39:45.618-07:00'</span>
+ <span class="p">));</span>
+<span class="cp">?></span>
+</pre></td> </tr></tbody></table> </div> </div> <div data-tab="Python SDK" data-lang="python" id="tab-1fd5a428-364e-4983-a529-d46a8eee03e0"> <div class="highlight python"> <table style="border-spacing: 0"><tbody><tr> <td class="gutter gl" style="text-align: right"><pre class="lineno">1
+2
+3
+4
+5
+6
+7
+8
+9
+10
+11
+12
+13
+14
+15
+16
+17
+18
+19
+20
+21
+22</pre></td> <td class="code"><pre><span class="kn">from</span> <span class="nn">predictionio</span> <span class="kn">import</span> <span class="n">EventClient</span>
+<span class="kn">from</span> <span class="nn">datetime</span> <span class="kn">import</span> <span class="n">datetime</span>
+<span class="kn">import</span> <span class="nn">pytz</span>
+<span class="n">client</span> <span class="o">=</span> <span class="n">EventClient</span><span class="p">(</span><span class="s">'YOUR_ACCESS_KEY'</span><span class="p">,</span> <span class="s">"http://localhost:7070"</span><span class="p">)</span>
+
+<span class="n">first_event_properties</span> <span class="o">=</span> <span class="p">{</span>
+ <span class="s">"prop1"</span> <span class="p">:</span> <span class="mi">1</span><span class="p">,</span>
+ <span class="s">"prop2"</span> <span class="p">:</span> <span class="s">"value2"</span><span class="p">,</span>
+ <span class="s">"prop3"</span> <span class="p">:</span> <span class="p">[</span><span class="mi">1</span><span class="p">,</span> <span class="mi">2</span><span class="p">,</span> <span class="mi">3</span><span class="p">],</span>
+ <span class="s">"prop4"</span> <span class="p">:</span> <span class="bp">True</span><span class="p">,</span>
+ <span class="s">"prop5"</span> <span class="p">:</span> <span class="p">[</span><span class="s">"a"</span><span class="p">,</span> <span class="s">"b"</span><span class="p">,</span> <span class="s">"c"</span><span class="p">],</span>
+ <span class="s">"prop6"</span> <span class="p">:</span> <span class="mf">4.56</span> <span class="p">,</span>
+ <span class="p">}</span>
+<span class="n">first_event_time</span> <span class="o">=</span> <span class="n">datetime</span><span class="p">(</span>
+ <span class="mi">2004</span><span class="p">,</span> <span class="mi">12</span><span class="p">,</span> <span class="mi">13</span><span class="p">,</span> <span class="mi">21</span><span class="p">,</span> <span class="mi">39</span><span class="p">,</span> <span class="mi">45</span><span class="p">,</span> <span class="mi">618000</span><span class="p">,</span> <span class="n">pytz</span><span class="o">.</span><span class="n">timezone</span><span class="p">(</span><span class="s">'US/Mountain'</span><span class="p">))</span>
+<span class="n">first_event_response</span> <span class="o">=</span> <span class="n">client</span><span class="o">.</span><span class="n">create_event</span><span class="p">(</span>
+ <span class="n">event</span><span class="o">=</span><span class="s">"my_event"</span><span class="p">,</span>
+ <span class="n">entity_type</span><span class="o">=</span><span class="s">"user"</span><span class="p">,</span>
+ <span class="n">entity_id</span><span class="o">=</span><span class="s">"uid"</span><span class="p">,</span>
+ <span class="n">properties</span><span class="o">=</span><span class="n">first_event_properties</span><span class="p">,</span>
+ <span class="n">event_time</span><span class="o">=</span><span class="n">first_event_time</span><span class="p">,</span>
+<span class="p">)</span>
+</pre></td> </tr></tbody></table> </div> </div> <div data-tab="Ruby SDK" data-lang="ruby" id="tab-e456c0ba-d59e-47db-91c1-c5fed4d87561"> <div class="highlight ruby"> <table style="border-spacing: 0"><tbody><tr> <td class="gutter gl" style="text-align: right"><pre class="lineno">1
+2
+3
+4
+5
+6
+7
+8
+9
+10
+11</pre></td> <td class="code"><pre><span class="nb">require</span> <span class="s1">'predictionio'</span>
+
+<span class="n">event_client</span> <span class="o">=</span> <span class="no">PredictionIO</span><span class="o">::</span><span class="no">EventClient</span><span class="p">.</span><span class="nf">new</span><span class="p">(</span><span class="s1">'YOUR_ACCESS_KEY'</span><span class="p">)</span>
+<span class="n">event_client</span><span class="p">.</span><span class="nf">create_event</span><span class="p">(</span><span class="s1">'my_event'</span><span class="p">,</span> <span class="s1">'user'</span><span class="p">,</span> <span class="s1">'uid'</span><span class="p">,</span>
+ <span class="s1">'eventTime'</span> <span class="o">=></span> <span class="s1">'2004-12-13T21:39:45.618-07:00'</span><span class="p">,</span>
+ <span class="s1">'properties'</span> <span class="o">=></span> <span class="p">{</span> <span class="s1">'prop1'</span> <span class="o">=></span> <span class="mi">1</span><span class="p">,</span>
+ <span class="s1">'prop2'</span> <span class="o">=></span> <span class="s1">'value2'</span><span class="p">,</span>
+ <span class="s1">'prop3'</span> <span class="o">=></span> <span class="p">[</span><span class="mi">1</span><span class="p">,</span> <span class="mi">2</span><span class="p">,</span> <span class="mi">3</span><span class="p">],</span>
+ <span class="s1">'prop4'</span> <span class="o">=></span> <span class="kp">true</span><span class="p">,</span>
+ <span class="s1">'prop5'</span> <span class="o">=></span> <span class="sx">%w(a b c)</span><span class="p">,</span>
+ <span class="s1">'prop6'</span> <span class="o">=></span> <span class="mi">4</span><span class="o">.</span><span class="mi">56</span> <span class="p">})</span>
+</pre></td> </tr></tbody></table> </div> </div> <div data-tab="Java SDK" data-lang="java" id="tab-33d2a0b0-f63b-4e11-b007-a21af081feaa"> <div class="highlight java"> <table style="border-spacing: 0"><tbody><tr> <td class="gutter gl" style="text-align: right"><pre class="lineno">1</pre></td> <td class="code"><pre><span class="o">(</span><span class="n">coming</span> <span class="n">soon</span><span class="o">)</span>
+</pre></td> </tr></tbody></table> </div> </div> </div> <p>For example, the following shows how one can create an event involving two entities (with <code>targetEntity</code>).</p><div class="tabs"> <ul class="control"> <li data-lang="bash"><a href="#tab-7192bd19-b4cd-41ec-94b8-2f09296e0c68">Raw HTTP</a></li> <li data-lang="php"><a href="#tab-9183acf1-0530-4a0e-84d8-83f3f4c42c85">PHP SDK</a></li> <li data-lang="python"><a href="#tab-f545f2c7-cd3e-433b-bd96-8cfcf84c04b2">Python SDK</a></li> <li data-lang="ruby"><a href="#tab-6711b590-8c98-465e-9e08-22b82bb88f56">Ruby SDK</a></li> <li data-lang="java"><a href="#tab-ac909d7b-fc91-45b3-a91d-a51077921720">Java SDK</a></li> </ul> <div data-tab="Raw HTTP" data-lang="bash" id="tab-7192bd19-b4cd-41ec-94b8-2f09296e0c68"> <div class="highlight shell"> <table style="border-spacing: 0"><tbody><tr> <td class="gutter gl" style="text-align: right"><pre class="lineno">1
+2
+3
+4
+5
+6
+7
+8
+9
+10
+11
+12
+13
+14</pre></td> <td class="code"><pre><span class="gp">$ </span>curl -i -X POST http://localhost:7070/events.json?accessKey<span class="o">=</span>WPgcXKd42FPQpZHVbVeMyqF4CQJUnXQmIMTHhX3ZUrSzvy1KXJjdFUrslifa9rnB <span class="se">\</span>
+-H <span class="s2">"Content-Type: application/json"</span> <span class="se">\</span>
+-d <span class="s1">'{
+ "event" : "my_event",
+ "entityType" : "user",
+ "entityId" : "uid",
+ "targetEntityType" : "item",
+ "targetEntityId" : "iid",
+ "properties" : {
+ "someProperty" : "value1",
+ "anotherProperty" : "value2"
+ },
+ "eventTime" : "2004-12-13T21:39:45.618Z"
+}'</span>
+</pre></td> </tr></tbody></table> </div> </div> <div data-tab="PHP SDK" data-lang="php" id="tab-9183acf1-0530-4a0e-84d8-83f3f4c42c85"> <div class="highlight php"> <table style="border-spacing: 0"><tbody><tr> <td class="gutter gl" style="text-align: right"><pre class="lineno">1
+2
+3
+4
+5
+6
+7
+8
+9
+10
+11
+12
+13
+14
+15
+16
+17
+18</pre></td> <td class="code"><pre><span class="cp"><?php</span>
+ <span class="k">require_once</span><span class="p">(</span><span class="s2">"vendor/autoload.php"</span><span class="p">);</span>
+
+ <span class="k">use</span> <span class="nx">predictionio\EventClient</span><span class="p">;</span>
+
+ <span class="nv">$accessKey</span> <span class="o">=</span> <span class="s1">'YOUR_ACCESS_KEY'</span><span class="p">;</span>
+ <span class="nv">$client</span> <span class="o">=</span> <span class="k">new</span> <span class="nx">EventClient</span><span class="p">(</span><span class="nv">$accessKey</span><span class="p">);</span>
+ <span class="nv">$response</span> <span class="o">=</span> <span class="nv">$client</span><span class="o">-></span><span class="na">createEvent</span><span class="p">(</span><span class="k">array</span><span class="p">(</span>
+ <span class="s1">'event'</span> <span class="o">=></span> <span class="s1">'my_event'</span><span class="p">,</span>
+ <span class="s1">'entityType'</span> <span class="o">=></span> <span class="s1">'user'</span><span class="p">,</span>
+ <span class="s1">'entityId'</span> <span class="o">=></span> <span class="s1">'uid'</span><span class="p">,</span>
+ <span class="s1">'targetEntityType'</span> <span class="o">=></span> <span class="s1">'item'</span><span class="p">,</span>
+ <span class="s1">'targetEntityId'</span> <span class="o">=></span> <span class="s1">'iid'</span><span class="p">,</span>
+ <span class="s1">'properties'</span> <span class="o">=></span> <span class="k">array</span><span class="p">(</span><span class="s1">'someProperty'</span><span class="o">=></span><span class="s1">'value1'</span><span class="p">,</span>
+ <span class="s1">'anotherProperty'</span><span class="o">=></span><span class="s1">'value2'</span><span class="p">),</span>
+ <span class="s1">'eventTime'</span> <span class="o">=></span> <span class="s1">'2004-12-13T21:39:45.618Z'</span>
+ <span class="p">));</span>
+<span class="cp">?></span>
+</pre></td> </tr></tbody></table> </div> </div> <div data-tab="Python SDK" data-lang="python" id="tab-f545f2c7-cd3e-433b-bd96-8cfcf84c04b2"> <div class="highlight python"> <table style="border-spacing: 0"><tbody><tr> <td class="gutter gl" style="text-align: right"><pre class="lineno">1
+2
+3
+4
+5
+6
+7
+8
+9
+10
+11
+12
+13</pre></td> <td class="code"><pre><span class="c"># Second Event</span>
+<span class="n">second_event_properties</span> <span class="o">=</span> <span class="p">{</span>
+ <span class="s">"someProperty"</span> <span class="p">:</span> <span class="s">"value1"</span><span class="p">,</span>
+ <span class="s">"anotherProperty"</span> <span class="p">:</span> <span class="s">"value2"</span><span class="p">,</span>
+ <span class="p">}</span>
+<span class="n">second_event_response</span> <span class="o">=</span> <span class="n">client</span><span class="o">.</span><span class="n">create_event</span><span class="p">(</span>
+ <span class="n">event</span><span class="o">=</span><span class="s">"my_event"</span><span class="p">,</span>
+ <span class="n">entity_type</span><span class="o">=</span><span class="s">"user"</span><span class="p">,</span>
+ <span class="n">entity_id</span><span class="o">=</span><span class="s">"uid"</span><span class="p">,</span>
+ <span class="n">target_entity_type</span><span class="o">=</span><span class="s">"item"</span><span class="p">,</span>
+ <span class="n">target_entity_id</span><span class="o">=</span><span class="s">"iid"</span><span class="p">,</span>
+ <span class="n">properties</span><span class="o">=</span><span class="n">second_event_properties</span><span class="p">,</span>
+ <span class="n">event_time</span><span class="o">=</span><span class="n">datetime</span><span class="p">(</span><span class="mi">2014</span><span class="p">,</span> <span class="mi">12</span><span class="p">,</span> <span class="mi">13</span><span class="p">,</span> <span class="mi">21</span><span class="p">,</span> <span class="mi">38</span><span class="p">,</span> <span class="mi">45</span><span class="p">,</span> <span class="mi">618000</span><span class="p">,</span> <span class="n">pytz</span><span class="o">.</span><span class="n">utc</span><span class="p">))</span>
+</pre></td> </tr></tbody></table> </div> </div> <div data-tab="Ruby SDK" data-lang="ruby" id="tab-6711b590-8c98-465e-9e08-22b82bb88f56"> <div class="highlight ruby"> <table style="border-spacing: 0"><tbody><tr> <td class="gutter gl" style="text-align: right"><pre class="lineno">1
+2
+3
+4
+5
+6
+7
+8
+9</pre></td> <td class="code"><pre><span class="nb">require</span> <span class="s1">'predictionio'</span>
+
+<span class="n">event_client</span> <span class="o">=</span> <span class="no">PredictionIO</span><span class="o">::</span><span class="no">EventClient</span><span class="p">.</span><span class="nf">new</span><span class="p">(</span><span class="s1">'YOUR_ACCESS_KEY'</span><span class="p">)</span>
+<span class="n">event_client</span><span class="p">.</span><span class="nf">create_event</span><span class="p">(</span><span class="s1">'my_event'</span><span class="p">,</span> <span class="s1">'user'</span><span class="p">,</span> <span class="s1">'uid'</span><span class="p">,</span>
+ <span class="s1">'targetEntityType'</span> <span class="o">=></span> <span class="s1">'item'</span><span class="p">,</span>
+ <span class="s1">'targetEntityId'</span> <span class="o">=></span> <span class="s1">'iid'</span><span class="p">,</span>
+ <span class="s1">'eventTime'</span> <span class="o">=></span> <span class="s1">'2004-12-13T21:39:45.618Z'</span><span class="p">,</span>
+ <span class="s1">'properties'</span> <span class="o">=></span> <span class="p">{</span> <span class="s1">'someProperty'</span> <span class="o">=></span> <span class="s1">'value1'</span><span class="p">,</span>
+ <span class="s1">'anotherProperty'</span> <span class="o">=></span> <span class="s1">'value2'</span> <span class="p">})</span>
+</pre></td> </tr></tbody></table> </div> </div> <div data-tab="Java SDK" data-lang="java" id="tab-ac909d7b-fc91-45b3-a91d-a51077921720"> <div class="highlight java"> <table style="border-spacing: 0"><tbody><tr> <td class="gutter gl" style="text-align: right"><pre class="lineno">1</pre></td> <td class="code"><pre><span class="o">(</span><span class="n">coming</span> <span class="n">soon</span><span class="o">)</span>
+</pre></td> </tr></tbody></table> </div> </div> </div> <p>Sample response:</p><div class="highlight shell"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1
+2
+3
+4
+5
+6
+7</pre></td><td class="code"><pre>HTTP/1.1 201 Created
+Server: spray-can/1.2.1
+Date: Wed, 10 Sep 2014 22:51:33 GMT
+Content-Type: application/json; <span class="nv">charset</span><span class="o">=</span>UTF-8
+Content-Length: 41
+
+<span class="o">{</span><span class="s2">"eventId"</span>:<span class="s2">"AAAABAAAAQDP3-jSlTMGVu0waj8"</span><span class="o">}</span>
+</pre></td></tr></tbody></table> </div> <h2 id='using-event-api' class='header-anchors'>Using Event API</h2><h3 id='event-creation-api' class='header-anchors'>Event Creation API</h3><p>URL: <code>http://localhost:7070/events.json?accessKey=yourAccessKeyString</code></p><p>Query parameters:</p> <table><thead> <tr> <th style="text-align: left">Field</th> <th style="text-align: left">Type</th> <th style="text-align: left">Description</th> </tr> </thead><tbody> <tr> <td style="text-align: left"><code>accessKey</code></td> <td style="text-align: left">String</td> <td style="text-align: left">The Access Key for your App</td> </tr> </tbody></table> <p>The event creation support many commonly used data. POST request body:</p> <table><thead> <tr> <th style="text-align: left">Field</th> <th style="text-align: left">Type</th> <th style="text-align: left">Description</th> </tr> </thead><tbody> <tr> <td style="text-align: left"><code>event</code></td> <td style="text-align: left">String</td> <td
style="text-align: left">Name of the event.</td> </tr> <tr> <td style="text-align: left"></td> <td style="text-align: left"></td> <td style="text-align: left">(Examples: "sign-up", "rate", "view", "buy").</td> </tr> <tr> <td style="text-align: left"></td> <td style="text-align: left"></td> <td style="text-align: left"><strong>Note</strong>: All event names start with "$" and "pio_" are reserved</td> </tr> <tr> <td style="text-align: left"></td> <td style="text-align: left"></td> <td style="text-align: left">and shouldn't be used as your custom event name (eg. "$set").</td> </tr> <tr> <td style="text-align: left"><code>entityType</code></td> <td style="text-align: left">String</td> <td style="text-align: left">The entity type. It is the namespace of the entityId and</td> </tr> <tr> <td style="text-align: left"></td> <td style="text-align: left"></td> <td style="text-align: left">analogous to the table name of
a relational database. The</td> </tr> <tr> <td style="text-align: left"></td> <td style="text-align: left"></td> <td style="text-align: left">entityId must be unique within same entityType.</td> </tr> <tr> <td style="text-align: left"></td> <td style="text-align: left"></td> <td style="text-align: left"><strong>Note</strong>: All entityType names start with "$" and "pio_" are</td> </tr> <tr> <td style="text-align: left"></td> <td style="text-align: left"></td> <td style="text-align: left">reserved and shouldn't be used.</td> </tr> <tr> <td style="text-align: left"><code>entityId</code></td> <td style="text-align: left">String</td> <td style="text-align: left">The entity ID. <code>entityType-entityId</code> becomes the unique</td> </tr> <tr> <td style="text-align: left"></td> <td style="text-align: left"></td> <td style="text-align: left">identifier of the entity. For example, you may have entityType</td> </tr> <tr> <td style="text-align: left"></td> <td style
="text-align: left"></td> <td style="text-align: left">named <code>user</code>, and different entity IDs, say <code>1</code> and <code>2</code>. In this</td> </tr> <tr> <td style="text-align: left"></td> <td style="text-align: left"></td> <td style="text-align: left">case, <code>user-1</code> and <code>user-2</code> uniquely identifies</td> </tr> <tr> <td style="text-align: left"></td> <td style="text-align: left"></td> <td style="text-align: left">entities.</td> </tr> <tr> <td style="text-align: left"><code>targetEntityType</code></td> <td style="text-align: left">String</td> <td style="text-align: left">(Optional) The target entity type.</td> </tr> <tr> <td style="text-align: left"></td> <td style="text-align: left"></td> <td style="text-align: left"><strong>Note</strong>: All entityType names start with "$" and "pio_"</td> </tr> <tr> <td style="text-align: left"></td> <td style="text-align: left"></td> <td style="text-align: left">are reserved and shouldn'
t be used.</td> </tr> <tr> <td style="text-align: left"><code>targetEntityId</code></td> <td style="text-align: left">String</td> <td style="text-align: left">(Optional) The target entity ID.</td> </tr> <tr> <td style="text-align: left"><code>properties</code></td> <td style="text-align: left">JSON</td> <td style="text-align: left">(Optional) See <strong>Note About Properties</strong> below</td> </tr> <tr> <td style="text-align: left"></td> <td style="text-align: left"></td> <td style="text-align: left"><strong>Note</strong>: All peroperty names start with "$" and "pio_"</td> </tr> <tr> <td style="text-align: left"></td> <td style="text-align: left"></td> <td style="text-align: left">are reserved and shouldn't be used as keys inside <code>properties</code>.</td> </tr> <tr> <td style="text-align: left"><code>eventTime</code></td> <td style="text-align: left">String</td> <td style="text-align: left">(Optional) The time of the event. Although Event Server's<
/td> </tr> <tr> <td style="text-align: left"></td> <td style="text-align: left"></td> <td style="text-align: left">current system time and UTC timezone will be used if this is</td> </tr> <tr> <td style="text-align: left"></td> <td style="text-align: left"></td> <td style="text-align: left">unspecified, it is highly recommended that this time should be</td> </tr> <tr> <td style="text-align: left"></td> <td style="text-align: left"></td> <td style="text-align: left">generated by the client application in order to accurately</td> </tr> <tr> <td style="text-align: left"></td> <td style="text-align: left"></td> <td style="text-align: left">record the time of the event.</td> </tr> <tr> <td style="text-align: left"></td> <td style="text-align: left"></td> <td style="text-align: left">Must be in ISO 8601 format (e.g.</td> </tr> <tr> <td style="text-align: left"></td> <td style="text-align: left"></td> <td style="text-align: left"><code>2004-12-13T21:39:45.618Z</code>, or <code>2014-09-09T16
:17:42.937-08:00</code>).</td> </tr> </tbody></table> <h2 id='note-about-properties' class='header-anchors'>Note About Properties</h2><p>Note that <code>properties</code> can be:</p> <ol> <li>Associated with an <em>generic event</em>: The <code>properties</code> field provide additional information about this event</li> <li>Associated with an <em>entity</em>: The <code>properties</code> field is used to record the changes of an entity's properties with special events <code>$set</code>, <code>$unset</code> and <code>$delete</code>.</li> </ol> <p>Please see the <a href="/datacollection/eventmodel/">Events Modeling</a> for detailed explanation.</p><h2 id='debugging-recipes' class='header-anchors'>Debugging Recipes</h2><div class="alert-message warning"><p>The following API are mainly for development or debugging purpose only. They should not be supported by SDK nor used by real application under normal circumstances and they are subject to changes.</p></div><div class="alert-messag
e info"><p>Instead of using <code>curl</code>, you can also install JSON browser plugins such as <strong>JSONView</strong> to pretty-print the JSON on your browser. With the browser plugin you can make the <code>GET</code> queries below by passing in the URL. Plugins like <strong>Postman - REST Client</strong> provide a more advanced interface for making queries.</p></div><p>The <code>accessKey</code> query parameter is mandatory.</p><p>Replace <code><your_accessKey></code> and <code><your_eventId></code> by a real one in the following:</p><h3 id='get-an-event' class='header-anchors'>Get an Event</h3><div class="highlight shell"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1</pre></td><td class="code"><pre><span class="gp">$ </span>curl -i -X GET http://localhost:7070/events/<your_eventId>.json?accessKey<span class="o">=</span><your_accessKey>
+</pre></td></tr></tbody></table> </div> <h3 id='delete-an-event' class='header-anchors'>Delete an Event</h3><div class="highlight shell"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1</pre></td><td class="code"><pre><span class="gp">$ </span>curl -i -X DELETE http://localhost:7070/events/<your_eventId>.json?accessKey<span class="o">=</span><your_accessKey>
+</pre></td></tr></tbody></table> </div> <h3 id='get-events-of-an-app' class='header-anchors'>Get Events of an App</h3><div class="highlight shell"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1</pre></td><td class="code"><pre><span class="gp">$ </span>curl -i -X GET http://localhost:7070/events.json?accessKey<span class="o">=</span><your_accessKey>
+</pre></td></tr></tbody></table> </div> <div class="alert-message info"><p>By default, it returns at most 20 events. Use the <code>limit</code> parameter to specify how many events returned (see below). Use cautiously!</p></div><p>In addition, the following <em>optional</em> parameters are supported:</p> <ul> <li><code>startTime</code>: time in ISO8601 format. Return events with <code>eventTime >= startTime</code>.</li> <li><code>untilTime</code>: time in ISO8601 format. Return events with <code>eventTime < untilTime</code>.</li> <li><code>entityType</code>: String. The entityType. Return events for this <code>entityType</code> only.</li> <li><code>entityId</code>: String. The entityId. Return events for this <code>entityId</code> only.</li> <li><code>event</code>: String. The event name. Return events with this name only.</li> <li><code>targetEntityType</code>: String. The targetEntityType. Return events for this <code>targetEntityType</code> only.</li> <li><code>targetEntity
Id</code>: String. The targetEntityId. Return events for this <code>targetEntityId</code> only.</li> <li><code>limit</code>: Integer. The number of record events returned. Default is 20. -1 to get all.</li> <li><code>reversed</code>: Boolean. <strong>Must be used with both <code>entityType</code> and <code>entityId</code> specified</strong>, returns events in reversed chronological order. Default is false.</li> </ul> <div class="alert-message warning"><p>If you are using <code>curl</code> with the <code>&</code> symbol, you should quote the entire URL by using single or double quotes.</p></div><div class="alert-message warning"><p>Depending on the size of data, you may encounter timeout when querying with some of the above filters. Event server uses <code>entityType</code> and <code>entityId</code> as the key so any query without both <code>entityType</code> and <code>entityId</code> specified might result in a timeout.</p></div><p>For example, get all events of an app with <cod
e>eventTime >= startTime</code></p><div class="highlight shell"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1</pre></td><td class="code"><pre><span class="gp">$ </span>curl -i -X GET <span class="s2">"http://localhost:7070/events.json?accessKey=<your_accessKey>&startTime=<time in ISO8601 format>"</span>
+</pre></td></tr></tbody></table> </div> <p>For example, get all events of an app with <code>eventTime < untilTime</code>:</p><div class="highlight shell"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1</pre></td><td class="code"><pre><span class="gp">$ </span>curl -i -X GET <span class="s2">"http://localhost:7070/events.json?accessKey=<your_accessKey>&untilTime=<time in ISO8601 format>"</span>
+</pre></td></tr></tbody></table> </div> <p>For example, get all events of an app with <code>eventTime >= startTime</code> and <code>eventTime < untilTime</code>:</p><div class="highlight shell"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1</pre></td><td class="code"><pre><span class="gp">$ </span>curl -i -X GET <span class="s2">"http://localhost:7070/events.json?accessKey=<your_accessKey>&startTime=<time in ISO8601 format>&untilTime=<time in ISO8601 format>"</span>
+</pre></td></tr></tbody></table> </div> <p>For example, get all events of a specific entity with <code>eventTime < untilTime</code>:</p><div class="highlight shell"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1</pre></td><td class="code"><pre><span class="gp">$ </span>curl -i -X GET <span class="s2">"http://localhost:7070/events.json?accessKey=<your_accessKey>&entityType=<your_entityType>&entityId=<your_entityId>&untilTime=<time in ISO801 format>"</span>
+</pre></td></tr></tbody></table> </div> <h3 id='delete-all-events-of-an-app' class='header-anchors'>Delete All Events of an App</h3><p>Please use the following CLI command:</p><div class="highlight shell"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1</pre></td><td class="code"><pre><span class="gp">$ </span>pio app data-delete <your_app_name>
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<div class="row"><div class="col-md-9 col-sm-11 col-xs-11"><div class="hidden-md hidden-lg" id="mobile-page-heading-wrapper"><p>PredictionIO Docs</p><h4>Modeling Workflow and DASE</h4></div><h4 class="hidden-sm hidden-xs">PredictionIO Docs</h4></div><div class="col-md-3 col-sm-1 col-xs-1 hidden-md hidden-lg"><img id="left-menu-indicator" src="/images/icons/down-arrow-dfe9f7fe.png"/></div><div class="col-md-3 col-sm-12 col-xs-12 swiftype-wrapper"><div class="swiftype"><form class="search-form"><img class="search-box-toggler hidden-xs hidden-sm" src="/images/icons/search-glass-704bd4ff.png"/><div class="search-box"><img src="/images/icons/search-glass-704bd4ff.png"/><input type="text" id="st-search-input" class="st-search-input" placeholder="Search Doc..."/></div><img class="swiftype-row-hider hidden-md hidden-lg" src="/images/icons/drawer-toggle-active-fcbef12a.png"/></form></div></div><div class="mobile-left-menu-toggler hidden-md hidden-lg"></div></div></div></div><div id="page" cl
ass="container-fluid"><div class="row"><div id="left-menu-wrapper" class="col-md-3"><nav id="nav-main"><ul><li class="level-1"><a class="expandible" href="/"><span>Apache PredictionIO (incubating) Documentation</span></a><ul><li class="level-2"><a class="final" href="/"><span>Welcome to Apache PredictionIO (incubating)</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Getting Started</span></a><ul><li class="level-2"><a class="final" href="/start/"><span>A Quick Intro</span></a></li><li class="level-2"><a class="final" href="/install/"><span>Installing Apache PredictionIO (incubating)</span></a></li><li class="level-2"><a class="final" href="/start/download/"><span>Downloading an Engine Template</span></a></li><li class="level-2"><a class="final" href="/start/deploy/"><span>Deploying Your First Engine</span></a></li><li class="level-2"><a class="final" href="/start/customize/"><span>Customizing the Engine</span></a></li></ul></li><li class="level-1"><
a class="expandible" href="#"><span>Integrating with Your App</span></a><ul><li class="level-2"><a class="final" href="/appintegration/"><span>App Integration Overview</span></a></li><li class="level-2"><a class="expandible" href="/sdk/"><span>List of SDKs</span></a><ul><li class="level-3"><a class="final" href="/sdk/java/"><span>Java & Android SDK</span></a></li><li class="level-3"><a class="final" href="/sdk/php/"><span>PHP SDK</span></a></li><li class="level-3"><a class="final" href="/sdk/python/"><span>Python SDK</span></a></li><li class="level-3"><a class="final" href="/sdk/ruby/"><span>Ruby SDK</span></a></li><li class="level-3"><a class="final" href="/sdk/community/"><span>Community Powered SDKs</span></a></li></ul></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Deploying an Engine</span></a><ul><li class="level-2"><a class="final" href="/deploy/"><span>Deploying as a Web Service</span></a></li><li class="level-2"><a class="final" href="/cli/#engine-co
mmands"><span>Engine Command-line Interface</span></a></li><li class="level-2"><a class="final" href="/deploy/engineparams/"><span>Setting Engine Parameters</span></a></li><li class="level-2"><a class="final" href="/deploy/enginevariants/"><span>Deploying Multiple Engine Variants</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Customizing an Engine</span></a><ul><li class="level-2"><a class="final" href="/customize/"><span>Learning DASE</span></a></li><li class="level-2"><a class="final" href="/customize/dase/"><span>Implement DASE</span></a></li><li class="level-2"><a class="final" href="/customize/troubleshooting/"><span>Troubleshooting Engine Development</span></a></li><li class="level-2"><a class="final" href="/api/current/#package"><span>Engine Scala APIs</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Collecting and Analyzing Data</span></a><ul><li class="level-2"><a class="final" href="/datacollection/"><span
>Event Server Overview</span></a></li><li class="level-2"><a class="final" href="/cli/#event-server-commands"><span>Event Server Command-line Interface</span></a></li><li class="level-2"><a class="final" href="/datacollection/eventapi/"><span>Collecting Data with REST/SDKs</span></a></li><li class="level-2"><a class="final" href="/datacollection/eventmodel/"><span>Events Modeling</span></a></li><li class="level-2"><a class="final" href="/datacollection/webhooks/"><span>Unifying Multichannel Data with Webhooks</span></a></li><li class="level-2"><a class="final" href="/datacollection/channel/"><span>Channel</span></a></li><li class="level-2"><a class="final" href="/datacollection/batchimport/"><span>Importing Data in Batch</span></a></li><li class="level-2"><a class="final" href="/datacollection/analytics/"><span>Using Analytics Tools</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Choosing an Algorithm(s)</span></a><ul><li class="level-2"><a class="f
inal" href="/algorithm/"><span>Built-in Algorithm Libraries</span></a></li><li class="level-2"><a class="final" href="/algorithm/switch/"><span>Switching to Another Algorithm</span></a></li><li class="level-2"><a class="final" href="/algorithm/multiple/"><span>Combining Multiple Algorithms</span></a></li><li class="level-2"><a class="final" href="/algorithm/custom/"><span>Adding Your Own Algorithms</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>ML Tuning and Evaluation</span></a><ul><li class="level-2"><a class="final" href="/evaluation/"><span>Overview</span></a></li><li class="level-2"><a class="final" href="/evaluation/paramtuning/"><span>Hyperparameter Tuning</span></a></li><li class="level-2"><a class="final" href="/evaluation/evaluationdashboard/"><span>Evaluation Dashboard</span></a></li><li class="level-2"><a class="final" href="/evaluation/metricchoose/"><span>Choosing Evaluation Metrics</span></a></li><li class="level-2"><a class="final"
href="/evaluation/metricbuild/"><span>Building Evaluation Metrics</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>System Architecture</span></a><ul><li class="level-2"><a class="final" href="/system/"><span>Architecture Overview</span></a></li><li class="level-2"><a class="final" href="/system/anotherdatastore/"><span>Using Another Data Store</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Engine Template Gallery</span></a><ul><li class="level-2"><a class="final" href="http://templates.prediction.io"><span>Browse</span></a></li><li class="level-2"><a class="final" href="/community/submit-template/"><span>Submit your Engine as a Template</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Demo Tutorials</span></a><ul><li class="level-2"><a class="final" href="/demo/tapster/"><span>Comics Recommendation Demo</span></a></li><li class="level-2"><a class="final" href="/demo/community/"><span
>Community Contributed Demo</span></a></li><li class="level-2"><a class="final" href="/demo/textclassification/"><span>Text Classification Engine Tutorial</span></a></li></ul></li><li class="level-1"><a class="expandible" href="/community/"><span>Getting Involved</span></a><ul><li class="level-2"><a class="final" href="/community/contribute-code/"><span>Contribute Code</span></a></li><li class="level-2"><a class="final" href="/community/contribute-documentation/"><span>Contribute Documentation</span></a></li><li class="level-2"><a class="final" href="/community/contribute-sdk/"><span>Contribute a SDK</span></a></li><li class="level-2"><a class="final" href="/community/contribute-webhook/"><span>Contribute a Webhook</span></a></li><li class="level-2"><a class="final" href="/community/projects/"><span>Community Projects</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Getting Help</span></a><ul><li class="level-2"><a class="final" href="/resources/faq/
"><span>FAQs</span></a></li><li class="level-2"><a class="final" href="/support/"><span>Community Support</span></a></li><li class="level-2"><a class="final" href="/support/#enterprise-support"><span>Enterprise Support</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Resources</span></a><ul><li class="level-2"><a class="final" href="/resources/intellij/"><span>Developing Engines with IntelliJ IDEA</span></a></li><li class="level-2"><a class="final" href="/resources/upgrade/"><span>Upgrade Instructions</span></a></li><li class="level-2"><a class="final" href="/resources/glossary/"><span>Glossary</span></a></li></ul></li></ul></nav></div><div class="col-md-9 col-sm-12"><div class="content-header hidden-md hidden-lg"><div id="page-title"><h1>Modeling Workflow and DASE</h1></div></div><div id="table-of-content-wrapper"><h5>On this page</h5><aside id="table-of-contents"><ul> <li> <a href="#training-the-model">Training The Model</a> </li> </ul> </aside><hr
/><a id="edit-page-link" href="https://github.com/apache/incubator-predictionio/tree/livedoc/docs/manual/source/machinelearning/modelingworkflow.html.md"><img src="/images/icons/edit-pencil-d6c1bb3d.png"/>Edit this page</a></div><div class="content-header hidden-sm hidden-xs"><div id="page-title"><h1>Modeling Workflow and DASE</h1></div></div><div class="content"><p>In addition to the DASE components, we also introduce the Data Model and Training Model abstractions. The Data Model abstraction refers to the set of Scala classes dealing with the implementation of modeling choices relating to feature <strong>extraction</strong>, <strong>preparation</strong>, and/or <strong>selection</strong>. For this illustration, this only includes the vectorization of text and t.f.-i.d.f. processing which is entirely implemented in the PreparedData class. The Training Model abstraction refers to any set of classes that individually take in a set of feature observations and output a predictive model.
This predictive model is leveraged by the Algorithm component to produce prediction results to queries in real-time. In the engine template, this abstraction is implemented in the NBModel class. <strong>Please note that these are conceptual abstractions that are designed to make engine development easier by decoupling class functionality.</strong> Keeping these abstractions in mind will help you in the future with debugging your code, and also make it easier to incorporate different modeling ideas into your engine. </p><p>The figure below shows a graphical representation of the engine architecture just described, as well as its interactions with your web/app and a provided Event Server:</p><p><img alt="Engine Overview" src="/images/demo/text_classification_template/engine_overview-27e09a89.png"/></p><h2 id='training-the-model' class='header-anchors'>Training The Model</h2><p>This section will guide you through the two Training Model implementations that come with this engine templa
te. Recall that the Training Model abstraction refers to an arbitrary set Scala Class that outputs a predictive model (i.e. implements some method that can be used for prediction). The general problem this engine template is tackling is text classification, so that our Training Model abstraction domain is restricted to implementations producing classifiers. In particular, the classification model that is implemented in this engine template is based on Multinomial Naive Bayes using t.f.-i.d.f. vectorized text. </p></div></div></div></div><footer><div class="container"><div class="seperator"></div><div class="row"><div class="col-md-4 col-md-push-8 col-xs-12"><div class="subscription-form-wrapper"><h4>Subscribe to our Newsletter</h4><form class="ajax-form" id="subscribe-form" method="POST" action="https://script.google.com/macros/s/AKfycbwhzeKCQJjQ52eVAqNT_vcklH07OITUO7wzOMDXvK6EGAWgaZgF/exec"><input class="required underlined-input" type="email" placeholder="Your email address" name=
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<div class="row"><div class="col-md-9 col-sm-11 col-xs-11"><div class="hidden-md hidden-lg" id="mobile-page-heading-wrapper"><p>PredictionIO Docs</p><h4>Deploying with AWS CloudFormation</h4></div><h4 class="hidden-sm hidden-xs">PredictionIO Docs</h4></div><div class="col-md-3 col-sm-1 col-xs-1 hidden-md hidden-lg"><img id="left-menu-indicator" src="/images/icons/down-arrow-dfe9f7fe.png"/></div><div class="col-md-3 col-sm-12 col-xs-12 swiftype-wrapper"><div class="swiftype"><form class="search-form"><img class="search-box-toggler hidden-xs hidden-sm" src="/images/icons/search-glass-704bd4ff.png"/><div class="search-box"><img src="/images/icons/search-glass-704bd4ff.png"/><input type="text" id="st-search-input" class="st-search-input" placeholder="Search Doc..."/></div><img class="swiftype-row-hider hidden-md hidden-lg" src="/images/icons/drawer-toggle-active-fcbef12a.png"/></form></div></div><div class="mobile-left-menu-toggler hidden-md hidden-lg"></div></div></div></div><div id="p
age" class="container-fluid"><div class="row"><div id="left-menu-wrapper" class="col-md-3"><nav id="nav-main"><ul><li class="level-1"><a class="expandible" href="/"><span>Apache PredictionIO (incubating) Documentation</span></a><ul><li class="level-2"><a class="final" href="/"><span>Welcome to Apache PredictionIO (incubating)</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Getting Started</span></a><ul><li class="level-2"><a class="final" href="/start/"><span>A Quick Intro</span></a></li><li class="level-2"><a class="final" href="/install/"><span>Installing Apache PredictionIO (incubating)</span></a></li><li class="level-2"><a class="final" href="/start/download/"><span>Downloading an Engine Template</span></a></li><li class="level-2"><a class="final" href="/start/deploy/"><span>Deploying Your First Engine</span></a></li><li class="level-2"><a class="final" href="/start/customize/"><span>Customizing the Engine</span></a></li></ul></li><li class="lev
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ref="#"><span>Integrating with Your App</span></a><ul><li class="level-2"><a class="final" href="/appintegration/"><span>App Integration Overview</span></a></li><li class="level-2"><a class="expandible" href="/sdk/"><span>List of SDKs</span></a><ul><li class="level-3"><a class="final" href="/sdk/java/"><span>Java & Android SDK</span></a></li><li class="level-3"><a class="final" href="/sdk/php/"><span>PHP SDK</span></a></li><li class="level-3"><a class="final" href="/sdk/python/"><span>Python SDK</span></a></li><li class="level-3"><a class="final" href="/sdk/ruby/"><span>Ruby SDK</span></a></li><li class="level-3"><a class="final" href="/sdk/community/"><span>Community Powered SDKs</span></a></li></ul></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Deploying an Engine</span></a><ul><li class="level-2"><a class="final" href="/deploy/"><span>Deploying as a Web Service</span></a></li><li class="level-2"><a class="final" href="/cli/#engine-commands"><span>Engine C
ommand-line Interface</span></a></li><li class="level-2"><a class="final" href="/deploy/engineparams/"><span>Setting Engine Parameters</span></a></li><li class="level-2"><a class="final" href="/deploy/enginevariants/"><span>Deploying Multiple Engine Variants</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Customizing an Engine</span></a><ul><li class="level-2"><a class="final" href="/customize/"><span>Learning DASE</span></a></li><li class="level-2"><a class="final" href="/customize/dase/"><span>Implement DASE</span></a></li><li class="level-2"><a class="final" href="/customize/troubleshooting/"><span>Troubleshooting Engine Development</span></a></li><li class="level-2"><a class="final" href="/api/current/#package"><span>Engine Scala APIs</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Collecting and Analyzing Data</span></a><ul><li class="level-2"><a class="final" href="/datacollection/"><span>Event Server Overview
</span></a></li><li class="level-2"><a class="final" href="/cli/#event-server-commands"><span>Event Server Command-line Interface</span></a></li><li class="level-2"><a class="final" href="/datacollection/eventapi/"><span>Collecting Data with REST/SDKs</span></a></li><li class="level-2"><a class="final" href="/datacollection/eventmodel/"><span>Events Modeling</span></a></li><li class="level-2"><a class="final" href="/datacollection/webhooks/"><span>Unifying Multichannel Data with Webhooks</span></a></li><li class="level-2"><a class="final" href="/datacollection/channel/"><span>Channel</span></a></li><li class="level-2"><a class="final" href="/datacollection/batchimport/"><span>Importing Data in Batch</span></a></li><li class="level-2"><a class="final" href="/datacollection/analytics/"><span>Using Analytics Tools</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Choosing an Algorithm(s)</span></a><ul><li class="level-2"><a class="final" href="/algorithm
/"><span>Built-in Algorithm Libraries</span></a></li><li class="level-2"><a class="final" href="/algorithm/switch/"><span>Switching to Another Algorithm</span></a></li><li class="level-2"><a class="final" href="/algorithm/multiple/"><span>Combining Multiple Algorithms</span></a></li><li class="level-2"><a class="final" href="/algorithm/custom/"><span>Adding Your Own Algorithms</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>ML Tuning and Evaluation</span></a><ul><li class="level-2"><a class="final" href="/evaluation/"><span>Overview</span></a></li><li class="level-2"><a class="final" href="/evaluation/paramtuning/"><span>Hyperparameter Tuning</span></a></li><li class="level-2"><a class="final" href="/evaluation/evaluationdashboard/"><span>Evaluation Dashboard</span></a></li><li class="level-2"><a class="final" href="/evaluation/metricchoose/"><span>Choosing Evaluation Metrics</span></a></li><li class="level-2"><a class="final" href="/evaluation/metr
icbuild/"><span>Building Evaluation Metrics</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>System Architecture</span></a><ul><li class="level-2"><a class="final" href="/system/"><span>Architecture Overview</span></a></li><li class="level-2"><a class="final" href="/system/anotherdatastore/"><span>Using Another Data Store</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Engine Template Gallery</span></a><ul><li class="level-2"><a class="final" href="http://templates.prediction.io"><span>Browse</span></a></li><li class="level-2"><a class="final" href="/community/submit-template/"><span>Submit your Engine as a Template</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Demo Tutorials</span></a><ul><li class="level-2"><a class="final" href="/demo/tapster/"><span>Comics Recommendation Demo</span></a></li><li class="level-2"><a class="final" href="/demo/community/"><span>Community Contributed
Demo</span></a></li><li class="level-2"><a class="final" href="/demo/textclassification/"><span>Text Classification Engine Tutorial</span></a></li></ul></li><li class="level-1"><a class="expandible" href="/community/"><span>Getting Involved</span></a><ul><li class="level-2"><a class="final" href="/community/contribute-code/"><span>Contribute Code</span></a></li><li class="level-2"><a class="final" href="/community/contribute-documentation/"><span>Contribute Documentation</span></a></li><li class="level-2"><a class="final" href="/community/contribute-sdk/"><span>Contribute a SDK</span></a></li><li class="level-2"><a class="final" href="/community/contribute-webhook/"><span>Contribute a Webhook</span></a></li><li class="level-2"><a class="final" href="/community/projects/"><span>Community Projects</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Getting Help</span></a><ul><li class="level-2"><a class="final active" href="/resources/faq/"><span>FAQs</s
pan></a></li><li class="level-2"><a class="final" href="/support/"><span>Community Support</span></a></li><li class="level-2"><a class="final" href="/support/#enterprise-support"><span>Enterprise Support</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Resources</span></a><ul><li class="level-2"><a class="final" href="/resources/intellij/"><span>Developing Engines with IntelliJ IDEA</span></a></li><li class="level-2"><a class="final" href="/resources/upgrade/"><span>Upgrade Instructions</span></a></li><li class="level-2"><a class="final" href="/resources/glossary/"><span>Glossary</span></a></li></ul></li></ul></nav></div><div class="col-md-9 col-sm-12"><div class="content-header hidden-md hidden-lg"><div id="breadcrumbs" class="hidden-sm hidden xs"><ul><li><a href="#">Getting Help</a><span class="spacer">></span></li><li><span class="last">FAQs</span></li></ul></div><div id="page-title"><h1>Frequently Asked Questions</h1></div></div><div id="table
-of-content-wrapper"><h5>On this page</h5><aside id="table-of-contents"><ul> <li> <a href="#using-predictionio">Using PredictionIO</a> </li> <li> <a href="#problem-with-event-server">Problem with Event Server</a> </li> <li> <a href="#engine-training">Engine Training</a> </li> <li> <a href="#deploy-engine">Deploy Engine</a> </li> <li> <a href="#building-predictionio">Building PredictionIO</a> </li> <li> <a href="#engine-development">Engine Development</a> </li> <li> <a href="#running-hbase">Running HBase</a> </li> </ul> </aside><hr/><a id="edit-page-link" href="https://github.com/apache/incubator-predictionio/tree/livedoc/docs/manual/source/resources/faq.html.md"><img src="/images/icons/edit-pencil-d6c1bb3d.png"/>Edit this page</a></div><div class="content-header hidden-sm hidden-xs"><div id="breadcrumbs" class="hidden-sm hidden xs"><ul><li><a href="#">Getting Help</a><span class="spacer">></span></li><li><span class="last">FAQs</span></li></ul></div><div id="page-title"><h1>Frequ
ently Asked Questions</h1></div></div><div class="content"><h2 id='using-predictionio' class='header-anchors'>Using PredictionIO</h2><h3 id='q:-how-do-i-check-to-see-if-various-dependencies,-such-as-elasticsearch-and-hbase,-are-running?' class='header-anchors'>Q: How do I check to see if various dependencies, such as ElasticSearch and HBase, are running?</h3><p>You can run <code>$ pio status</code> from the terminal and it will return the status of various components that PredictionIO depends on.</p> <ul> <li> You should see the following message if everything is OK:</li> </ul> <div class="highlight shell"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1
+2
+3
+4
+5
+6
+7
+8
+9
+10
+11
+12
+13
+14
+15
+16
+17
+18
+19</pre></td><td class="code"><pre><span class="gp">$ </span>pio status
+PredictionIO
+ Installed at: /home/vagrant/PredictionIO
+ Version: 0.8.6
+
+Apache Spark
+ Installed at: /home/vagrant/PredictionIO/vendors/spark-1.2.0
+ Version: 1.2.0 <span class="o">(</span>meets minimum requirement of 1.2.0<span class="o">)</span>
+
+Storage Backend Connections
+ Verifying Meta Data Backend
+ Verifying Model Data Backend
+ Verifying Event Data Backend
+ Test write Event Store <span class="o">(</span>App Id 0<span class="o">)</span>
+2015-02-03 18:52:38,904 INFO hbase.HBLEvents - The table predictionio_eventdata:events_0 doesn<span class="s1">'t exist yet. Creating now...
+2015-02-03 18:52:39,868 INFO hbase.HBLEvents - Removing table predictionio_eventdata:events_0...
+
+(sleeping 5 seconds for all messages to show up...)
+Your system is all ready to go.
+</span></pre></td></tr></tbody></table> </div> <ul> <li>If you see the following error message, it usually means ElasticSearch is not running properly:</li> </ul> <div class="highlight shell"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1
+2
+3
+4
+5
+6
+7
+8
+9</pre></td><td class="code"><pre> ...
+Storage Backend Connections
+ Verifying Meta Data Backend
+ ...
+Caused by: org.elasticsearch.client.transport.NoNodeAvailableException: None of the configured nodes are available: <span class="o">[]</span>
+ at org.elasticsearch.client.transport.TransportClientNodesService.ensureNodesAreAvailable<span class="o">(</span>TransportClientNodesService.java:298<span class="o">)</span>
+ ...
+
+Unable to connect to all storage backend<span class="o">(</span>s<span class="o">)</span> successfully. Please refer to error message<span class="o">(</span>s<span class="o">)</span> above. Aborting.
+</pre></td></tr></tbody></table> </div> <p>You can check if there is any ElasticSearch process by running 'jps'.</p><p>Please see <strong>How to start elasticsearch</strong> below.</p> <ul> <li>If you see the following error message, it usually means HBase is not running properly:</li> </ul> <div class="highlight shell"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1
+2
+3
+4
+5
+6
+7
+8
+9
+10
+11
+12
+13
+14
+15</pre></td><td class="code"><pre>Storage Backend Connections
+ Verifying Meta Data Backend
+ Verifying Model Data Backend
+ Verifying Event Data Backend
+2015-02-03 18:40:04,810 ERROR zookeeper.RecoverableZooKeeper - ZooKeeper exists failed after 1 attempts
+2015-02-03 18:40:04,812 ERROR zookeeper.ZooKeeperWatcher - hconnection-0x1e4075ce, <span class="nv">quorum</span><span class="o">=</span>localhost:2181, <span class="nv">baseZNode</span><span class="o">=</span>/hbase Received unexpected KeeperException, re-throwing exception
+org.apache.zookeeper.KeeperException<span class="nv">$ConnectionLossException</span>: KeeperErrorCode <span class="o">=</span> ConnectionLoss <span class="k">for</span> /hbase/hbaseid
+...
+2015-02-03 18:40:07,021 ERROR hbase.StorageClient - Failed to connect to HBase. Plase check <span class="k">if </span>HBase is running properly.
+2015-02-03 18:40:07,026 ERROR storage.Storage<span class="nv">$ </span>- Error initializing storage client <span class="k">for </span><span class="nb">source </span>HBASE
+2015-02-03 18:40:07,027 ERROR storage.Storage<span class="nv">$ </span>- Can<span class="s1">'t connect to ZooKeeper
+java.util.NoSuchElementException: None.get
+...
+
+Unable to connect to all storage backend(s) successfully. Please refer to error message(s) above. Aborting.
+</span></pre></td></tr></tbody></table> </div> <p>You can check if there is any HBase-related process by running 'jps'.</p><p>Please see <strong>How to start HBase</strong> below.</p><h3 id='q:-how-to-start-elasticsearch?' class='header-anchors'>Q: How to start ElasticSearch?</h3><p>If you used the <a href="/install/install-linux/#quick-install">install script</a> to install PredictionIO, the ElasticSearch is installed at <code>~/PredictionIO/vendors/elasticsearch-x.y.z/</code> where x.y.z is the version number (currently it's 1.4.4). To start it, run:</p><div class="highlight shell"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1</pre></td><td class="code"><pre><span class="gp">$ </span>~/PredictionIO/vendors/elasticsearch-x.y.z/bin/elasticsearch
+</pre></td></tr></tbody></table> </div> <p>If you didn't use install script, please go to where ElasticSearch is installed to start it.</p><div class="alert-message info"><p>It may take some time (15 seconds or so) for ElasticSearch to become ready after you start it (wait a bit before you run <code>pio status</code> again).</p></div><h3 id='q:-how-to-start-hbase-?' class='header-anchors'>Q: How to start HBase ?</h3><p>If you used the <a href="/install/install-linux/#quick-install">install script</a> to install PredictionIO, the HBase is installed at <code>~/PredictionIO/vendors/hbase-x.y.z/</code> where x.y.z is the version number (currently it's 0.98.6). To start it, run:</p><div class="highlight shell"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1</pre></td><td class="code"><pre><span class="gp">$ </span>~/PredictionIO/vendors/hbase-x.y.z/bin/start-hbase.sh
+</pre></td></tr></tbody></table> </div> <p>If you didn't use install script, please go to where HBase is installed to start it.</p><div class="alert-message info"><p>It may take some time (15 seconds or so) for HBase to become ready after you start it (wait a bit before you run <code>pio status</code> again).</p></div><h2 id='problem-with-event-server' class='header-anchors'>Problem with Event Server</h2><h3 id='q:-how-do-i-increase-the-jvm-heap-size-of-the-event-server?' class='header-anchors'>Q: How do I increase the JVM heap size of the Event Server?</h3><p>Add the <code>JAVA_OPTS</code> environmental variable to supply JVM options, e.g.</p><div class="highlight shell"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1</pre></td><td class="code"><pre><span class="gp">$ </span><span class="nv">JAVA_OPTS</span><span class="o">=</span>-Xmx16g bin/pio eventserver ...
+</pre></td></tr></tbody></table> </div> <h2 id='engine-training' class='header-anchors'>Engine Training</h2><h3 id='q:-how-to-increase-spark-driver-program-and-worker-executor-memory-size?' class='header-anchors'>Q: How to increase Spark driver program and worker executor memory size?</h3><p>In general, the PredictionIO <code>bin/pio</code> scripts wraps around Spark's <code>spark-submit</code> script. You can specify a lot of Spark configurations (i.e. executor memory, cores, master url, etc.) with it. You can supply these as pass-through arguments at the end of <code>bin/pio</code> command.</p><p>If the engine training seems stuck, it's possible that the the executor doesn't have enough memory.</p><p>First, follow <a href="http://spark.apache.org/docs/latest/spark-standalone.html">instruction here</a> to start standalone Spark cluster and get the master URL. If you use the provided quick install script to install PredictionIO, the Spark is installed at <code>Prediction
IO/vendors/spark-1.2.0/</code> where you could run the Spark commands in <code>sbin/</code> as described in the Spark documentation. Then use following train commmand to specify executor memory (default is only 512 MB) and driver memory.</p><p>For example, the follow command set the Spark master to <code>spark://localhost:7077</code> (the default url of standalone cluster), set the driver memory to 16G and set the executor memory to 24G for <code>pio train</code>.</p><div class="highlight shell"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1</pre></td><td class="code"><pre><span class="gp">$ </span>pio train -- --master spark://localhost:7077 --driver-memory 16G --executor-memory 24G
+</pre></td></tr></tbody></table> </div> <h3 id='q:-how-to-resolve-"exception-in-thread-"main"-org.apache.spark.sparkexception:-job-aborted-due-to-stage-failure:-serialized-task-165:35-was-110539813-bytes,-which-exceeds-max-allowed:-spark.akka.framesize-(10485760-bytes)---reserved-(204800-bytes).-consider-increasing-spark.akka.framesize-or-using-broadcast-variables-for-large-values."?' class='header-anchors'>Q: How to resolve "Exception in thread "main" org.apache.spark.SparkException: Job aborted due to stage failure: Serialized task 165:35 was 110539813 bytes, which exceeds max allowed: spark.akka.frameSize (10485760 bytes) - reserved (204800 bytes). Consider increasing spark.akka.frameSize or using broadcast variables for large values."?</h3><p>A likely reason is the local algorithm model is larger than the default frame size. You can specify a larger value as a pass-thru argument to spark-submit when you <code>pio train</code>. The followin
g command increase the frameSize to 1024MB.</p><div class="highlight shell"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1</pre></td><td class="code"><pre><span class="gp">$ </span>pio train -- --conf spark.akka.frameSize<span class="o">=</span>1024
+</pre></td></tr></tbody></table> </div> <h2 id='deploy-engine' class='header-anchors'>Deploy Engine</h2><h3 id='q:-how-to-increase-heap-space-memory-for-"pio-deploy"?' class='header-anchors'>Q: How to increase heap space memory for "pio deploy"?</h3><p>If you see the following error during <code>pio deploy</code>, it means there is not enough heap space memory.</p><div class="highlight shell"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1
+2
+3
+4</pre></td><td class="code"><pre>...
+<span class="o">[</span>ERROR] <span class="o">[</span>LocalFSModels] Java heap space
+<span class="o">[</span>ERROR] <span class="o">[</span>OneForOneStrategy] None.get
+...
+</pre></td></tr></tbody></table> </div> <p>To increase the heap space, specify the "-- --driver-memory " parameter in the command. For example, set the driver memory to 8G when deploy the engine:</p><div class="highlight shell"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1</pre></td><td class="code"><pre><span class="gp">$ </span>pio deploy -- --driver-memory 8G
+</pre></td></tr></tbody></table> </div> <h2 id='building-predictionio' class='header-anchors'>Building PredictionIO</h2><h3 id='q:-how-to-resolve-"error:-could-not-find-or-load-main-class-io.prediction.tools.console"-after-./make_distribution.sh?' class='header-anchors'>Q: How to resolve "Error: Could not find or load main class io.prediction.tools.Console" after ./make_distribution.sh?</h3><div class="highlight shell"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1
+2</pre></td><td class="code"><pre><span class="gp">$ </span>bin/pio app
+Error: Could not find or load main class io.prediction.tools.Console
+</pre></td></tr></tbody></table> </div> <p>When PredictionIO bumps a version, it creates another JAR file with the new version number.</p><p>Delete everything but the latest <code>pio-assembly-<VERSION>.jar</code> in <code>$PIO_HOME/assembly</code> directory. For example:</p><div class="highlight shell"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1
+2
+3
+4
+5
+6
+7
+8
+9</pre></td><td class="code"><pre><span class="gp">PredictionIO$ </span><span class="nb">cd </span>assembly/
+<span class="gp">PredictionIO/assembly$ </span>ls -al
+total 197776
+drwxr-xr-x 2 yipjustin yipjustin 4096 Nov 12 00:08 .
+drwxr-xr-x 17 yipjustin yipjustin 4096 Nov 12 00:09 ..
+-rw-r--r-- 1 yipjustin yipjustin 101184982 Nov 5 06:05 pio-assembly-0.8.1-SNAPSHOT.jar
+-rw-r--r-- 1 yipjustin yipjustin 101324859 Nov 12 00:09 pio-assembly-0.8.2.jar
+
+<span class="gp">PredictionIO/assembly$ </span>rm pio-assembly-0.8.1-SNAPSHOT.jar
+</pre></td></tr></tbody></table> </div> <h3 id='q:-how-to-resolve-".......<a-href="data/compile:compile">error</a>-java.lang.assertionerror:-assertion-failed:-java.lang.autocloseable"-when-./make_distribution.sh?' class='header-anchors' >Q: How to resolve ".......<a href="data/compile:compile">error</a> java.lang.AssertionError: assertion failed: java.lang.AutoCloseable" when ./make_distribution.sh?</h3><p>PredictionIO only support Java 7 or later. Please make sure you have the correct Java version with the command:</p><div class="highlight shell"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1</pre></td><td class="code"><pre><span class="gp">$ </span>javac -version
+</pre></td></tr></tbody></table> </div> <h2 id='engine-development' class='header-anchors'>Engine Development</h2><h3 id='q:-what's-the-difference-between-p--and-l--prefixed-classes-and-functions?' class='header-anchors'>Q: What's the difference between P- and L- prefixed classes and functions?</h3><p>PredictionIO v0.8 is built on the top of Spark, a massively scalable programming framework. A spark algorithm is different from conventional single machine algorithm in a way that spark algorithms use the <a href="http://spark.apache.org/docs/1.0.1/programming-guide.html#resilient-distributed-datasets-rdds">RDD</a> abstraction as its primary data type.</p><p>PredictionIO framework natively support both RDD-based algorithms and traditional single-machine algorithms. For controllers prefixed by "P" (i.e. PJavaDataSource, PJavaAlgorithm), their data include RDD abstraction; For "L" controllers, they are traditional single machine algorithms.</p><h2 id='running-
hbase' class='header-anchors'>Running HBase</h2><h3 id='q:-how-to-resolve-'exception-in-thread-"main"-java.lang.nullpointerexception-at-org.apache.hadoop.net.dns.reversedns(dns.java:92)'?' class='header-anchors'>Q: How to resolve 'Exception in thread "main" java.lang.NullPointerException at org.apache.hadoop.net.DNS.reverseDns(DNS.java:92)'?</h3><p>HBase relies on reverse DNS be set up properly to function. If your network configuration changes (such as working on a laptop with public WiFi hotspots), there could be a chance that reverse DNS does not function properly. You can install a DNS server on your own computer. Some users have reported that using <a href="https://developers.google.com/speed/public-dns/">Google Public DNS</a> would also solve the problem.</p><p>If you have other questions, you can search or post on the <a href="https://groups.google.com/forum/#!forum/predictionio-user">user group</a> or <a href="mailto:support@prediction.io"
>email the core team</a> directly.</p></div></div></div></div><footer><div class="container"><div class="seperator"></div><div class="row"><div class="col-md-4 col-md-push-8 col-xs-12"><div class="subscription-form-wrapper"><h4>Subscribe to our Newsletter</h4><form class="ajax-form" id="subscribe-form" method="POST" action="https://script.google.com/macros/s/AKfycbwhzeKCQJjQ52eVAqNT_vcklH07OITUO7wzOMDXvK6EGAWgaZgF/exec"><input class="required underlined-input" type="email" placeholder="Your email address" name="subscription_email" id="subscription_email"/><input class="pill-button" value="SUBSCRIBE" type="submit" data-state-normal="SUBSCRIBE" data-state-sucess="SUBSCRIBED!" data-state-loading="SENDING..." onclick="t($('#subscription_email').val());"/><p class="result"></p></form></div></div><div class="col-md-2 col-md-pull-4 col-xs-6 footer-link-column"><div class="footer-link-column-row"><h4>Community</h4><ul><li><a href="//docs.prediction.io/install/" target="blank">Download</a></
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<div class="row"><div class="col-md-9 col-sm-11 col-xs-11"><div class="hidden-md hidden-lg" id="mobile-page-heading-wrapper"><p>PredictionIO Docs</p><h4>Evaluation Dashboard</h4></div><h4 class="hidden-sm hidden-xs">PredictionIO Docs</h4></div><div class="col-md-3 col-sm-1 col-xs-1 hidden-md hidden-lg"><img id="left-menu-indicator" src="/images/icons/down-arrow-dfe9f7fe.png"/></div><div class="col-md-3 col-sm-12 col-xs-12 swiftype-wrapper"><div class="swiftype"><form class="search-form"><img class="search-box-toggler hidden-xs hidden-sm" src="/images/icons/search-glass-704bd4ff.png"/><div class="search-box"><img src="/images/icons/search-glass-704bd4ff.png"/><input type="text" id="st-search-input" class="st-search-input" placeholder="Search Doc..."/></div><img class="swiftype-row-hider hidden-md hidden-lg" src="/images/icons/drawer-toggle-active-fcbef12a.png"/></form></div></div><div class="mobile-left-menu-toggler hidden-md hidden-lg"></div></div></div></div><div id="page" class="c
ontainer-fluid"><div class="row"><div id="left-menu-wrapper" class="col-md-3"><nav id="nav-main"><ul><li class="level-1"><a class="expandible" href="/"><span>Apache PredictionIO (incubating) Documentation</span></a><ul><li class="level-2"><a class="final" href="/"><span>Welcome to Apache PredictionIO (incubating)</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Getting Started</span></a><ul><li class="level-2"><a class="final" href="/start/"><span>A Quick Intro</span></a></li><li class="level-2"><a class="final" href="/install/"><span>Installing Apache PredictionIO (incubating)</span></a></li><li class="level-2"><a class="final" href="/start/download/"><span>Downloading an Engine Template</span></a></li><li class="level-2"><a class="final" href="/start/deploy/"><span>Deploying Your First Engine</span></a></li><li class="level-2"><a class="final" href="/start/customize/"><span>Customizing the Engine</span></a></li></ul></li><li class="level-1"><a clas
s="expandible" href="#"><span>Integrating with Your App</span></a><ul><li class="level-2"><a class="final" href="/appintegration/"><span>App Integration Overview</span></a></li><li class="level-2"><a class="expandible" href="/sdk/"><span>List of SDKs</span></a><ul><li class="level-3"><a class="final" href="/sdk/java/"><span>Java & Android SDK</span></a></li><li class="level-3"><a class="final" href="/sdk/php/"><span>PHP SDK</span></a></li><li class="level-3"><a class="final" href="/sdk/python/"><span>Python SDK</span></a></li><li class="level-3"><a class="final" href="/sdk/ruby/"><span>Ruby SDK</span></a></li><li class="level-3"><a class="final" href="/sdk/community/"><span>Community Powered SDKs</span></a></li></ul></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Deploying an Engine</span></a><ul><li class="level-2"><a class="final" href="/deploy/"><span>Deploying as a Web Service</span></a></li><li class="level-2"><a class="final" href="/cli/#engine-commands
"><span>Engine Command-line Interface</span></a></li><li class="level-2"><a class="final" href="/deploy/engineparams/"><span>Setting Engine Parameters</span></a></li><li class="level-2"><a class="final" href="/deploy/enginevariants/"><span>Deploying Multiple Engine Variants</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Customizing an Engine</span></a><ul><li class="level-2"><a class="final" href="/customize/"><span>Learning DASE</span></a></li><li class="level-2"><a class="final" href="/customize/dase/"><span>Implement DASE</span></a></li><li class="level-2"><a class="final" href="/customize/troubleshooting/"><span>Troubleshooting Engine Development</span></a></li><li class="level-2"><a class="final" href="/api/current/#package"><span>Engine Scala APIs</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Collecting and Analyzing Data</span></a><ul><li class="level-2"><a class="final" href="/datacollection/"><span>Event
Server Overview</span></a></li><li class="level-2"><a class="final" href="/cli/#event-server-commands"><span>Event Server Command-line Interface</span></a></li><li class="level-2"><a class="final" href="/datacollection/eventapi/"><span>Collecting Data with REST/SDKs</span></a></li><li class="level-2"><a class="final" href="/datacollection/eventmodel/"><span>Events Modeling</span></a></li><li class="level-2"><a class="final" href="/datacollection/webhooks/"><span>Unifying Multichannel Data with Webhooks</span></a></li><li class="level-2"><a class="final" href="/datacollection/channel/"><span>Channel</span></a></li><li class="level-2"><a class="final" href="/datacollection/batchimport/"><span>Importing Data in Batch</span></a></li><li class="level-2"><a class="final" href="/datacollection/analytics/"><span>Using Analytics Tools</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Choosing an Algorithm(s)</span></a><ul><li class="level-2"><a class="final"
href="/algorithm/"><span>Built-in Algorithm Libraries</span></a></li><li class="level-2"><a class="final" href="/algorithm/switch/"><span>Switching to Another Algorithm</span></a></li><li class="level-2"><a class="final" href="/algorithm/multiple/"><span>Combining Multiple Algorithms</span></a></li><li class="level-2"><a class="final" href="/algorithm/custom/"><span>Adding Your Own Algorithms</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>ML Tuning and Evaluation</span></a><ul><li class="level-2"><a class="final" href="/evaluation/"><span>Overview</span></a></li><li class="level-2"><a class="final" href="/evaluation/paramtuning/"><span>Hyperparameter Tuning</span></a></li><li class="level-2"><a class="final active" href="/evaluation/evaluationdashboard/"><span>Evaluation Dashboard</span></a></li><li class="level-2"><a class="final" href="/evaluation/metricchoose/"><span>Choosing Evaluation Metrics</span></a></li><li class="level-2"><a class="final"
href="/evaluation/metricbuild/"><span>Building Evaluation Metrics</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>System Architecture</span></a><ul><li class="level-2"><a class="final" href="/system/"><span>Architecture Overview</span></a></li><li class="level-2"><a class="final" href="/system/anotherdatastore/"><span>Using Another Data Store</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Engine Template Gallery</span></a><ul><li class="level-2"><a class="final" href="http://templates.prediction.io"><span>Browse</span></a></li><li class="level-2"><a class="final" href="/community/submit-template/"><span>Submit your Engine as a Template</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Demo Tutorials</span></a><ul><li class="level-2"><a class="final" href="/demo/tapster/"><span>Comics Recommendation Demo</span></a></li><li class="level-2"><a class="final" href="/demo/community/"><spa
n>Community Contributed Demo</span></a></li><li class="level-2"><a class="final" href="/demo/textclassification/"><span>Text Classification Engine Tutorial</span></a></li></ul></li><li class="level-1"><a class="expandible" href="/community/"><span>Getting Involved</span></a><ul><li class="level-2"><a class="final" href="/community/contribute-code/"><span>Contribute Code</span></a></li><li class="level-2"><a class="final" href="/community/contribute-documentation/"><span>Contribute Documentation</span></a></li><li class="level-2"><a class="final" href="/community/contribute-sdk/"><span>Contribute a SDK</span></a></li><li class="level-2"><a class="final" href="/community/contribute-webhook/"><span>Contribute a Webhook</span></a></li><li class="level-2"><a class="final" href="/community/projects/"><span>Community Projects</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Getting Help</span></a><ul><li class="level-2"><a class="final" href="/resources/faq
/"><span>FAQs</span></a></li><li class="level-2"><a class="final" href="/support/"><span>Community Support</span></a></li><li class="level-2"><a class="final" href="/support/#enterprise-support"><span>Enterprise Support</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Resources</span></a><ul><li class="level-2"><a class="final" href="/resources/intellij/"><span>Developing Engines with IntelliJ IDEA</span></a></li><li class="level-2"><a class="final" href="/resources/upgrade/"><span>Upgrade Instructions</span></a></li><li class="level-2"><a class="final" href="/resources/glossary/"><span>Glossary</span></a></li></ul></li></ul></nav></div><div class="col-md-9 col-sm-12"><div class="content-header hidden-md hidden-lg"><div id="breadcrumbs" class="hidden-sm hidden xs"><ul><li><a href="#">ML Tuning and Evaluation</a><span class="spacer">></span></li><li><span class="last">Evaluation Dashboard</span></li></ul></div><div id="page-title"><h1>Evaluation Da
shboard</h1></div></div><div id="table-of-content-wrapper"><a id="edit-page-link" href="https://github.com/apache/incubator-predictionio/tree/livedoc/docs/manual/source/evaluation/evaluationdashboard.html.md"><img src="/images/icons/edit-pencil-d6c1bb3d.png"/>Edit this page</a></div><div class="content-header hidden-sm hidden-xs"><div id="breadcrumbs" class="hidden-sm hidden xs"><ul><li><a href="#">ML Tuning and Evaluation</a><span class="spacer">></span></li><li><span class="last">Evaluation Dashboard</span></li></ul></div><div id="page-title"><h1>Evaluation Dashboard</h1></div></div><div class="content"><div class="alert-message warning"><p>This is an experimental development tool, which exposes environment variables and other sensitive information about the PredictionIO application (e.g. storage configs, credentials etc.). It is not recommended to be run in production.</p></div><p>PredictionIO provides a web dashboard which allows you to see previous evaluation and a drill dow
n page about each evaluation. It is particularly useful when we ran multiple <a href="/evaluation/paramtuning/">hyperparameter tunings</a> as we may easily lose track of all the engine variants evaluated.</p><p>We can start the dashboard with the following command:</p><div class="highlight shell"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1</pre></td><td class="code"><pre><span class="gp">$ </span>pio dashboard
+</pre></td></tr></tbody></table> </div> <p>The dashboard lists out all completed evaluations in a reversed chronological order. A high level description of each evaluation can be seen directly from the dashboard. We can also click on the <em>HTML</em> button to see the evaluation drill down page.</p><p><em>Note:</em> The dashboard server has SSL enabled and is authenticated by a key passed as a query string param <code>accessKey</code>. The configuration is in <code>conf/server.conf</code></p></div></div></div></div><footer><div class="container"><div class="seperator"></div><div class="row"><div class="col-md-4 col-md-push-8 col-xs-12"><div class="subscription-form-wrapper"><h4>Subscribe to our Newsletter</h4><form class="ajax-form" id="subscribe-form" method="POST" action="https://script.google.com/macros/s/AKfycbwhzeKCQJjQ52eVAqNT_vcklH07OITUO7wzOMDXvK6EGAWgaZgF/exec"><input class="required underlined-input" type="email" placeholder="Your email address" name="subscription_email"
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id"><div class="row"><div id="left-menu-wrapper" class="col-md-3"><nav id="nav-main"><ul><li class="level-1"><a class="expandible" href="/"><span>Apache PredictionIO (incubating) Documentation</span></a><ul><li class="level-2"><a class="final" href="/"><span>Welcome to Apache PredictionIO (incubating)</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Getting Started</span></a><ul><li class="level-2"><a class="final" href="/start/"><span>A Quick Intro</span></a></li><li class="level-2"><a class="final" href="/install/"><span>Installing Apache PredictionIO (incubating)</span></a></li><li class="level-2"><a class="final" href="/start/download/"><span>Downloading an Engine Template</span></a></li><li class="level-2"><a class="final" href="/start/deploy/"><span>Deploying Your First Engine</span></a></li><li class="level-2"><a class="final" href="/start/customize/"><span>Customizing the Engine</span></a></li></ul></li><li class="level-1"><a class="expandibl
e" href="#"><span>Integrating with Your App</span></a><ul><li class="level-2"><a class="final" href="/appintegration/"><span>App Integration Overview</span></a></li><li class="level-2"><a class="expandible" href="/sdk/"><span>List of SDKs</span></a><ul><li class="level-3"><a class="final" href="/sdk/java/"><span>Java & Android SDK</span></a></li><li class="level-3"><a class="final" href="/sdk/php/"><span>PHP SDK</span></a></li><li class="level-3"><a class="final" href="/sdk/python/"><span>Python SDK</span></a></li><li class="level-3"><a class="final" href="/sdk/ruby/"><span>Ruby SDK</span></a></li><li class="level-3"><a class="final" href="/sdk/community/"><span>Community Powered SDKs</span></a></li></ul></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Deploying an Engine</span></a><ul><li class="level-2"><a class="final" href="/deploy/"><span>Deploying as a Web Service</span></a></li><li class="level-2"><a class="final" href="/cli/#engine-commands"><span>Engi
ne Command-line Interface</span></a></li><li class="level-2"><a class="final" href="/deploy/engineparams/"><span>Setting Engine Parameters</span></a></li><li class="level-2"><a class="final" href="/deploy/enginevariants/"><span>Deploying Multiple Engine Variants</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Customizing an Engine</span></a><ul><li class="level-2"><a class="final" href="/customize/"><span>Learning DASE</span></a></li><li class="level-2"><a class="final" href="/customize/dase/"><span>Implement DASE</span></a></li><li class="level-2"><a class="final" href="/customize/troubleshooting/"><span>Troubleshooting Engine Development</span></a></li><li class="level-2"><a class="final" href="/api/current/#package"><span>Engine Scala APIs</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Collecting and Analyzing Data</span></a><ul><li class="level-2"><a class="final" href="/datacollection/"><span>Event Server Over
view</span></a></li><li class="level-2"><a class="final" href="/cli/#event-server-commands"><span>Event Server Command-line Interface</span></a></li><li class="level-2"><a class="final" href="/datacollection/eventapi/"><span>Collecting Data with REST/SDKs</span></a></li><li class="level-2"><a class="final" href="/datacollection/eventmodel/"><span>Events Modeling</span></a></li><li class="level-2"><a class="final" href="/datacollection/webhooks/"><span>Unifying Multichannel Data with Webhooks</span></a></li><li class="level-2"><a class="final" href="/datacollection/channel/"><span>Channel</span></a></li><li class="level-2"><a class="final" href="/datacollection/batchimport/"><span>Importing Data in Batch</span></a></li><li class="level-2"><a class="final" href="/datacollection/analytics/"><span>Using Analytics Tools</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Choosing an Algorithm(s)</span></a><ul><li class="level-2"><a class="final" href="/algor
ithm/"><span>Built-in Algorithm Libraries</span></a></li><li class="level-2"><a class="final" href="/algorithm/switch/"><span>Switching to Another Algorithm</span></a></li><li class="level-2"><a class="final" href="/algorithm/multiple/"><span>Combining Multiple Algorithms</span></a></li><li class="level-2"><a class="final" href="/algorithm/custom/"><span>Adding Your Own Algorithms</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>ML Tuning and Evaluation</span></a><ul><li class="level-2"><a class="final active" href="/evaluation/"><span>Overview</span></a></li><li class="level-2"><a class="final" href="/evaluation/paramtuning/"><span>Hyperparameter Tuning</span></a></li><li class="level-2"><a class="final" href="/evaluation/evaluationdashboard/"><span>Evaluation Dashboard</span></a></li><li class="level-2"><a class="final" href="/evaluation/metricchoose/"><span>Choosing Evaluation Metrics</span></a></li><li class="level-2"><a class="final" href="/eval
uation/metricbuild/"><span>Building Evaluation Metrics</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>System Architecture</span></a><ul><li class="level-2"><a class="final" href="/system/"><span>Architecture Overview</span></a></li><li class="level-2"><a class="final" href="/system/anotherdatastore/"><span>Using Another Data Store</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Engine Template Gallery</span></a><ul><li class="level-2"><a class="final" href="http://templates.prediction.io"><span>Browse</span></a></li><li class="level-2"><a class="final" href="/community/submit-template/"><span>Submit your Engine as a Template</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Demo Tutorials</span></a><ul><li class="level-2"><a class="final" href="/demo/tapster/"><span>Comics Recommendation Demo</span></a></li><li class="level-2"><a class="final" href="/demo/community/"><span>Community
Contributed Demo</span></a></li><li class="level-2"><a class="final" href="/demo/textclassification/"><span>Text Classification Engine Tutorial</span></a></li></ul></li><li class="level-1"><a class="expandible" href="/community/"><span>Getting Involved</span></a><ul><li class="level-2"><a class="final" href="/community/contribute-code/"><span>Contribute Code</span></a></li><li class="level-2"><a class="final" href="/community/contribute-documentation/"><span>Contribute Documentation</span></a></li><li class="level-2"><a class="final" href="/community/contribute-sdk/"><span>Contribute a SDK</span></a></li><li class="level-2"><a class="final" href="/community/contribute-webhook/"><span>Contribute a Webhook</span></a></li><li class="level-2"><a class="final" href="/community/projects/"><span>Community Projects</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Getting Help</span></a><ul><li class="level-2"><a class="final" href="/resources/faq/"><span>FAQ
s</span></a></li><li class="level-2"><a class="final" href="/support/"><span>Community Support</span></a></li><li class="level-2"><a class="final" href="/support/#enterprise-support"><span>Enterprise Support</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Resources</span></a><ul><li class="level-2"><a class="final" href="/resources/intellij/"><span>Developing Engines with IntelliJ IDEA</span></a></li><li class="level-2"><a class="final" href="/resources/upgrade/"><span>Upgrade Instructions</span></a></li><li class="level-2"><a class="final" href="/resources/glossary/"><span>Glossary</span></a></li></ul></li></ul></nav></div><div class="col-md-9 col-sm-12"><div class="content-header hidden-md hidden-lg"><div id="breadcrumbs" class="hidden-sm hidden xs"><ul><li><a href="#">ML Tuning and Evaluation</a><span class="spacer">></span></li><li><span class="last">Overview</span></li></ul></div><div id="page-title"><h1>ML Tuning and Evaluation</h1></div></
div><div id="table-of-content-wrapper"><a id="edit-page-link" href="https://github.com/apache/incubator-predictionio/tree/livedoc/docs/manual/source/evaluation/index.html.md"><img src="/images/icons/edit-pencil-d6c1bb3d.png"/>Edit this page</a></div><div class="content-header hidden-sm hidden-xs"><div id="breadcrumbs" class="hidden-sm hidden xs"><ul><li><a href="#">ML Tuning and Evaluation</a><span class="spacer">></span></li><li><span class="last">Overview</span></li></ul></div><div id="page-title"><h1>ML Tuning and Evaluation</h1></div></div><div class="content"><p>PredictionIO's evaluation module allows you to streamline the process of testing lots of knobs in engine parameters and deploy the best one out of it using statisically sound cross-validation methods.</p><p>There are two key components:</p><h3 id='engine' class='header-anchors'>Engine</h3><p>It is our evaluation target. During evaluation, in addition to the <em>train</em> and <em>deploy</em> mode we describe in e
arlier sections, the engine also generates a list of testing data points. These data points are a sequence of <em>Query</em> and <em>Actual Result</em> tuples. <em>Queries</em> are sent to the engine and the engine responds with a <em>Predicted Result</em>, in the same way as how the engine serves a query.</p><h3 id='evaluator' class='header-anchors'>Evaluator</h3><p>The evaluator joins the sequence of <em>Query</em>, <em>Predicted Result</em>, and <em>Actual Result</em> together and evaluates the quality of the engine. PredictionIO enables you to implement any metric with just a few lines of code.</p><p><img alt="PredictionIO Evaluation Overview" src="/images/engine-evaluation-4ab1bfeb.png"/></p><p>We will discuss various aspects of evaluation with PredictionIO.</p> <ul> <li><a href="/evaluation/paramtuning/">Hyperparameter Tuning</a> - it is an end-to-end example of using PredictionIO evaluation module to select and deploy the best engine parameter.</li> <li><a href="/evaluation/e
valuationdashboard/">Evaluation Dashboard</a> - it is the dashboard where you can see a detailed breakdown of all previous evaluations.</li> <li><a href="/evaluation/metricchoose/">Choosing Evaluation Metrics</a> - we cover some basic machine learning metrics</li> <li><a href="/evaluation/metricbuild/">Bulding Evaluation Metrics</a> - we illustrate how to implement a custom metric with as few as one line of code (plus some boilerplates).</li> </ul> </div></div></div></div><footer><div class="container"><div class="seperator"></div><div class="row"><div class="col-md-4 col-md-push-8 col-xs-12"><div class="subscription-form-wrapper"><h4>Subscribe to our Newsletter</h4><form class="ajax-form" id="subscribe-form" method="POST" action="https://script.google.com/macros/s/AKfycbwhzeKCQJjQ52eVAqNT_vcklH07OITUO7wzOMDXvK6EGAWgaZgF/exec"><input class="required underlined-input" type="email" placeholder="Your email address" name="subscription_email" id="subscription_email"/><input class="pill-b
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<div class="row"><div class="col-md-9 col-sm-11 col-xs-11"><div class="hidden-md hidden-lg" id="mobile-page-heading-wrapper"><p>PredictionIO Docs</p><h4>Importing Data in Batch</h4></div><h4 class="hidden-sm hidden-xs">PredictionIO Docs</h4></div><div class="col-md-3 col-sm-1 col-xs-1 hidden-md hidden-lg"><img id="left-menu-indicator" src="/images/icons/down-arrow-dfe9f7fe.png"/></div><div class="col-md-3 col-sm-12 col-xs-12 swiftype-wrapper"><div class="swiftype"><form class="search-form"><img class="search-box-toggler hidden-xs hidden-sm" src="/images/icons/search-glass-704bd4ff.png"/><div class="search-box"><img src="/images/icons/search-glass-704bd4ff.png"/><input type="text" id="st-search-input" class="st-search-input" placeholder="Search Doc..."/></div><img class="swiftype-row-hider hidden-md hidden-lg" src="/images/icons/drawer-toggle-active-fcbef12a.png"/></form></div></div><div class="mobile-left-menu-toggler hidden-md hidden-lg"></div></div></div></div><div id="page" class
="container-fluid"><div class="row"><div id="left-menu-wrapper" class="col-md-3"><nav id="nav-main"><ul><li class="level-1"><a class="expandible" href="/"><span>Apache PredictionIO (incubating) Documentation</span></a><ul><li class="level-2"><a class="final" href="/"><span>Welcome to Apache PredictionIO (incubating)</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Getting Started</span></a><ul><li class="level-2"><a class="final" href="/start/"><span>A Quick Intro</span></a></li><li class="level-2"><a class="final" href="/install/"><span>Installing Apache PredictionIO (incubating)</span></a></li><li class="level-2"><a class="final" href="/start/download/"><span>Downloading an Engine Template</span></a></li><li class="level-2"><a class="final" href="/start/deploy/"><span>Deploying Your First Engine</span></a></li><li class="level-2"><a class="final" href="/start/customize/"><span>Customizing the Engine</span></a></li></ul></li><li class="level-1"><a c
lass="expandible" href="#"><span>Integrating with Your App</span></a><ul><li class="level-2"><a class="final" href="/appintegration/"><span>App Integration Overview</span></a></li><li class="level-2"><a class="expandible" href="/sdk/"><span>List of SDKs</span></a><ul><li class="level-3"><a class="final" href="/sdk/java/"><span>Java & Android SDK</span></a></li><li class="level-3"><a class="final" href="/sdk/php/"><span>PHP SDK</span></a></li><li class="level-3"><a class="final" href="/sdk/python/"><span>Python SDK</span></a></li><li class="level-3"><a class="final" href="/sdk/ruby/"><span>Ruby SDK</span></a></li><li class="level-3"><a class="final" href="/sdk/community/"><span>Community Powered SDKs</span></a></li></ul></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Deploying an Engine</span></a><ul><li class="level-2"><a class="final" href="/deploy/"><span>Deploying as a Web Service</span></a></li><li class="level-2"><a class="final" href="/cli/#engine-comma
nds"><span>Engine Command-line Interface</span></a></li><li class="level-2"><a class="final" href="/deploy/engineparams/"><span>Setting Engine Parameters</span></a></li><li class="level-2"><a class="final" href="/deploy/enginevariants/"><span>Deploying Multiple Engine Variants</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Customizing an Engine</span></a><ul><li class="level-2"><a class="final" href="/customize/"><span>Learning DASE</span></a></li><li class="level-2"><a class="final" href="/customize/dase/"><span>Implement DASE</span></a></li><li class="level-2"><a class="final" href="/customize/troubleshooting/"><span>Troubleshooting Engine Development</span></a></li><li class="level-2"><a class="final" href="/api/current/#package"><span>Engine Scala APIs</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Collecting and Analyzing Data</span></a><ul><li class="level-2"><a class="final" href="/datacollection/"><span>Ev
ent Server Overview</span></a></li><li class="level-2"><a class="final" href="/cli/#event-server-commands"><span>Event Server Command-line Interface</span></a></li><li class="level-2"><a class="final" href="/datacollection/eventapi/"><span>Collecting Data with REST/SDKs</span></a></li><li class="level-2"><a class="final" href="/datacollection/eventmodel/"><span>Events Modeling</span></a></li><li class="level-2"><a class="final" href="/datacollection/webhooks/"><span>Unifying Multichannel Data with Webhooks</span></a></li><li class="level-2"><a class="final" href="/datacollection/channel/"><span>Channel</span></a></li><li class="level-2"><a class="final active" href="/datacollection/batchimport/"><span>Importing Data in Batch</span></a></li><li class="level-2"><a class="final" href="/datacollection/analytics/"><span>Using Analytics Tools</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Choosing an Algorithm(s)</span></a><ul><li class="level-2"><a clas
s="final" href="/algorithm/"><span>Built-in Algorithm Libraries</span></a></li><li class="level-2"><a class="final" href="/algorithm/switch/"><span>Switching to Another Algorithm</span></a></li><li class="level-2"><a class="final" href="/algorithm/multiple/"><span>Combining Multiple Algorithms</span></a></li><li class="level-2"><a class="final" href="/algorithm/custom/"><span>Adding Your Own Algorithms</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>ML Tuning and Evaluation</span></a><ul><li class="level-2"><a class="final" href="/evaluation/"><span>Overview</span></a></li><li class="level-2"><a class="final" href="/evaluation/paramtuning/"><span>Hyperparameter Tuning</span></a></li><li class="level-2"><a class="final" href="/evaluation/evaluationdashboard/"><span>Evaluation Dashboard</span></a></li><li class="level-2"><a class="final" href="/evaluation/metricchoose/"><span>Choosing Evaluation Metrics</span></a></li><li class="level-2"><a class="fin
al" href="/evaluation/metricbuild/"><span>Building Evaluation Metrics</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>System Architecture</span></a><ul><li class="level-2"><a class="final" href="/system/"><span>Architecture Overview</span></a></li><li class="level-2"><a class="final" href="/system/anotherdatastore/"><span>Using Another Data Store</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Engine Template Gallery</span></a><ul><li class="level-2"><a class="final" href="http://templates.prediction.io"><span>Browse</span></a></li><li class="level-2"><a class="final" href="/community/submit-template/"><span>Submit your Engine as a Template</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Demo Tutorials</span></a><ul><li class="level-2"><a class="final" href="/demo/tapster/"><span>Comics Recommendation Demo</span></a></li><li class="level-2"><a class="final" href="/demo/community/"><
span>Community Contributed Demo</span></a></li><li class="level-2"><a class="final" href="/demo/textclassification/"><span>Text Classification Engine Tutorial</span></a></li></ul></li><li class="level-1"><a class="expandible" href="/community/"><span>Getting Involved</span></a><ul><li class="level-2"><a class="final" href="/community/contribute-code/"><span>Contribute Code</span></a></li><li class="level-2"><a class="final" href="/community/contribute-documentation/"><span>Contribute Documentation</span></a></li><li class="level-2"><a class="final" href="/community/contribute-sdk/"><span>Contribute a SDK</span></a></li><li class="level-2"><a class="final" href="/community/contribute-webhook/"><span>Contribute a Webhook</span></a></li><li class="level-2"><a class="final" href="/community/projects/"><span>Community Projects</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Getting Help</span></a><ul><li class="level-2"><a class="final" href="/resources/
faq/"><span>FAQs</span></a></li><li class="level-2"><a class="final" href="/support/"><span>Community Support</span></a></li><li class="level-2"><a class="final" href="/support/#enterprise-support"><span>Enterprise Support</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Resources</span></a><ul><li class="level-2"><a class="final" href="/resources/intellij/"><span>Developing Engines with IntelliJ IDEA</span></a></li><li class="level-2"><a class="final" href="/resources/upgrade/"><span>Upgrade Instructions</span></a></li><li class="level-2"><a class="final" href="/resources/glossary/"><span>Glossary</span></a></li></ul></li></ul></nav></div><div class="col-md-9 col-sm-12"><div class="content-header hidden-md hidden-lg"><div id="breadcrumbs" class="hidden-sm hidden xs"><ul><li><a href="#">Collecting and Analyzing Data</a><span class="spacer">></span></li><li><span class="last">Importing Data in Batch</span></li></ul></div><div id="page-title"><h1>Im
porting Data in Batch</h1></div></div><div id="table-of-content-wrapper"><h5>On this page</h5><aside id="table-of-contents"><ul> <li> <a href="#preparing-input-file">Preparing Input File</a> </li> <li> <a href="#use-sdk-to-prepare-batch-input-file">Use SDK to Prepare Batch Input File</a> </li> <li> <a href="#import-events-from-input-file">Import Events from Input File</a> </li> </ul> </aside><hr/><a id="edit-page-link" href="https://github.com/apache/incubator-predictionio/tree/livedoc/docs/manual/source/datacollection/batchimport.html.md"><img src="/images/icons/edit-pencil-d6c1bb3d.png"/>Edit this page</a></div><div class="content-header hidden-sm hidden-xs"><div id="breadcrumbs" class="hidden-sm hidden xs"><ul><li><a href="#">Collecting and Analyzing Data</a><span class="spacer">></span></li><li><span class="last">Importing Data in Batch</span></li></ul></div><div id="page-title"><h1>Importing Data in Batch</h1></div></div><div class="content"><p>If you have a large amount of
data to start with, performing batch import will be much faster than sending every event over an HTTP connection.</p><h2 id='preparing-input-file' class='header-anchors'>Preparing Input File</h2><p>The import tool expects its input to be a file stored either in the local filesystem or on HDFS. Each line of the file should be a JSON object string representing an event. For more information about the format of event JSON object, please refer to <a href="/datacollection/eventapi/#using-event-api">this page</a>.</p><p>Shown below is an example that contains 5 events ready to be imported to the Event Server.</p><div class="highlight json"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1
+2
+3
+4
+5</pre></td><td class="code"><pre><span class="p">{</span><span class="s2">"event"</span><span class="p">:</span><span class="s2">"buy"</span><span class="p">,</span><span class="s2">"entityType"</span><span class="p">:</span><span class="s2">"user"</span><span class="p">,</span><span class="s2">"entityId"</span><span class="p">:</span><span class="s2">"3"</span><span class="p">,</span><span class="s2">"targetEntityType"</span><span class="p">:</span><span class="s2">"item"</span><span class="p">,</span><span class="s2">"targetEntityId"</span><span class="p">:</span><span class="s2">"0"</span><span class="p">,</span><span class="s2">"eventTime"</span><span class="p">:</span><span class="s2">"2014-11-21T01:04:14.716Z"</span><span class="p">}</span><span class="w">
+</span><span class="p">{</span><span class="s2">"event"</span><span class="p">:</span><span class="s2">"buy"</span><span class="p">,</span><span class="s2">"entityType"</span><span class="p">:</span><span class="s2">"user"</span><span class="p">,</span><span class="s2">"entityId"</span><span class="p">:</span><span class="s2">"3"</span><span class="p">,</span><span class="s2">"targetEntityType"</span><span class="p">:</span><span class="s2">"item"</span><span class="p">,</span><span class="s2">"targetEntityId"</span><span class="p">:</span><span class="s2">"1"</span><span class="p">,</span><span class="s2">"eventTime"</span><span class="p">:</span><span class="s2">"2014-11-21T01:04:14.722Z"</span><span class="p">}</span><span class="w">
+</span><span class="p">{</span><span class="s2">"event"</span><span class="p">:</span><span class="s2">"rate"</span><span class="p">,</span><span class="s2">"entityType"</span><span class="p">:</span><span class="s2">"user"</span><span class="p">,</span><span class="s2">"entityId"</span><span class="p">:</span><span class="s2">"3"</span><span class="p">,</span><span class="s2">"targetEntityType"</span><span class="p">:</span><span class="s2">"item"</span><span class="p">,</span><span class="s2">"targetEntityId"</span><span class="p">:</span><span class="s2">"2"</span><span class="p">,</span><span class="s2">"properties"</span><span class="p">:{</span><span class="s2">"rating"</span><span class="p">:</span><span class="mf">1.0</span><span class="p">},</span><span class="s2">"eventTime"</span><span class="p">:</span><span class="s2">"2014-11-21T01:04:14.729Z"</span><span class="p">}</span><span class="w">
+</span><span class="p">{</span><span class="s2">"event"</span><span class="p">:</span><span class="s2">"buy"</span><span class="p">,</span><span class="s2">"entityType"</span><span class="p">:</span><span class="s2">"user"</span><span class="p">,</span><span class="s2">"entityId"</span><span class="p">:</span><span class="s2">"3"</span><span class="p">,</span><span class="s2">"targetEntityType"</span><span class="p">:</span><span class="s2">"item"</span><span class="p">,</span><span class="s2">"targetEntityId"</span><span class="p">:</span><span class="s2">"7"</span><span class="p">,</span><span class="s2">"eventTime"</span><span class="p">:</span><span class="s2">"2014-11-21T01:04:14.735Z"</span><span class="p">}</span><span class="w">
+</span><span class="p">{</span><span class="s2">"event"</span><span class="p">:</span><span class="s2">"buy"</span><span class="p">,</span><span class="s2">"entityType"</span><span class="p">:</span><span class="s2">"user"</span><span class="p">,</span><span class="s2">"entityId"</span><span class="p">:</span><span class="s2">"3"</span><span class="p">,</span><span class="s2">"targetEntityType"</span><span class="p">:</span><span class="s2">"item"</span><span class="p">,</span><span class="s2">"targetEntityId"</span><span class="p">:</span><span class="s2">"8"</span><span class="p">,</span><span class="s2">"eventTime"</span><span class="p">:</span><span class="s2">"2014-11-21T01:04:14.741Z"</span><span class="p">}</span><span class="w">
+</span></pre></td></tr></tbody></table> </div> <div class="alert-message warning"><p>Please make sure your import file does not contain any empty lines. Empty lines will be treated as a null object and will return an error during import.</p></div><h2 id='use-sdk-to-prepare-batch-input-file' class='header-anchors'>Use SDK to Prepare Batch Input File</h2><p>Some of the Apache PredictionIO (incubating) SDKs also provides FileExporter client. You may use them to prepare the JSON file as described above. The FileExporter creates event in the same way as EventClient except that the events are written to a JSON file instead of being sent to EventSever. The written JSON file can then be used by batch import.</p><div class="tabs"> <ul class="control"> <li data-lang="php"><a href="#tab-7b7286ec-61e4-4e86-a18d-a002bf8704dc">PHP SDK</a></li> <li data-lang="python"><a href="#tab-9540712e-10cb-4619-a8ec-4e20d61ec3d9">Python SDK</a></li> <li data-lang="ruby"><a href="#tab-a84d919c-3f49-4eeb-92dc-a
dd2d6e9bcf2">Ruby SDK</a></li> <li data-lang="java"><a href="#tab-9429a9c9-a2a3-4706-a0b3-f13e8e98e8e4">Java SDK</a></li> </ul> <div data-tab="PHP SDK" data-lang="php" id="tab-7b7286ec-61e4-4e86-a18d-a002bf8704dc"> (coming soon) </div> <div data-tab="Python SDK" data-lang="python" id="tab-9540712e-10cb-4619-a8ec-4e20d61ec3d9"> <div class="highlight python"> <table style="border-spacing: 0"><tbody><tr> <td class="gutter gl" style="text-align: right"><pre class="lineno">1
+2
+3
+4
+5
+6
+7
+8
+9
+10
+11
+12
+13
+14
+15
+16
+17
+18
+19
+20
+21
+22
+23
+24
+25
+26</pre></td> <td class="code"><pre><span class="kn">import</span> <span class="nn">predictionio</span>
+<span class="kn">from</span> <span class="nn">datetime</span> <span class="kn">import</span> <span class="n">datetime</span>
+<span class="kn">import</span> <span class="nn">pytz</span>
+
+<span class="c"># Create a FileExporter and specify "my_events.json" as destination file</span>
+<span class="n">exporter</span> <span class="o">=</span> <span class="n">predictionio</span><span class="o">.</span><span class="n">FileExporter</span><span class="p">(</span><span class="n">file_name</span><span class="o">=</span><span class="s">"my_events.json"</span><span class="p">)</span>
+
+<span class="n">event_properties</span> <span class="o">=</span> <span class="p">{</span>
+ <span class="s">"someProperty"</span> <span class="p">:</span> <span class="s">"value1"</span><span class="p">,</span>
+ <span class="s">"anotherProperty"</span> <span class="p">:</span> <span class="s">"value2"</span><span class="p">,</span>
+ <span class="p">}</span>
+<span class="c"># write the events to a file</span>
+<span class="n">event_response</span> <span class="o">=</span> <span class="n">exporter</span><span class="o">.</span><span class="n">create_event</span><span class="p">(</span>
+ <span class="n">event</span><span class="o">=</span><span class="s">"my_event"</span><span class="p">,</span>
+ <span class="n">entity_type</span><span class="o">=</span><span class="s">"user"</span><span class="p">,</span>
+ <span class="n">entity_id</span><span class="o">=</span><span class="s">"uid"</span><span class="p">,</span>
+ <span class="n">target_entity_type</span><span class="o">=</span><span class="s">"item"</span><span class="p">,</span>
+ <span class="n">target_entity_id</span><span class="o">=</span><span class="s">"iid"</span><span class="p">,</span>
+ <span class="n">properties</span><span class="o">=</span><span class="n">event_properties</span><span class="p">,</span>
+ <span class="n">event_time</span><span class="o">=</span><span class="n">datetime</span><span class="p">(</span><span class="mi">2014</span><span class="p">,</span> <span class="mi">12</span><span class="p">,</span> <span class="mi">13</span><span class="p">,</span> <span class="mi">21</span><span class="p">,</span> <span class="mi">38</span><span class="p">,</span> <span class="mi">45</span><span class="p">,</span> <span class="mi">618000</span><span class="p">,</span> <span class="n">pytz</span><span class="o">.</span><span class="n">utc</span><span class="p">))</span>
+
+<span class="c"># ...</span>
+
+<span class="c"># close the FileExporter when finish writing all events</span>
+<span class="n">exporter</span><span class="o">.</span><span class="n">close</span><span class="p">()</span>
+
+</pre></td> </tr></tbody></table> </div> </div> <div data-tab="Ruby SDK" data-lang="ruby" id="tab-a84d919c-3f49-4eeb-92dc-add2d6e9bcf2"> (coming soon) </div> <div data-tab="Java SDK" data-lang="java" id="tab-9429a9c9-a2a3-4706-a0b3-f13e8e98e8e4"> <div class="highlight java"> <table style="border-spacing: 0"><tbody><tr> <td class="gutter gl" style="text-align: right"><pre class="lineno">1</pre></td> <td class="code"><pre><span class="o">(</span><span class="n">coming</span> <span class="n">soon</span><span class="o">)</span>
+</pre></td> </tr></tbody></table> </div> </div> </div> <h2 id='import-events-from-input-file' class='header-anchors'>Import Events from Input File</h2><p>Importing events from a file can be done easily using the command line interface. Assuming that <code>pio</code> be in your search path, your App ID be <code>123</code>, and the input file <code>my_events.json</code> be in your current working directory:</p><div class="highlight shell"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1</pre></td><td class="code"><pre><span class="gp">$ </span>pio import --appid 123 --input my_events.json
+</pre></td></tr></tbody></table> </div> <p>After a brief while, the tool should return to the console without any error. Congratulations! You have successfully imported your events.</p></div></div></div></div><footer><div class="container"><div class="seperator"></div><div class="row"><div class="col-md-4 col-md-push-8 col-xs-12"><div class="subscription-form-wrapper"><h4>Subscribe to our Newsletter</h4><form class="ajax-form" id="subscribe-form" method="POST" action="https://script.google.com/macros/s/AKfycbwhzeKCQJjQ52eVAqNT_vcklH07OITUO7wzOMDXvK6EGAWgaZgF/exec"><input class="required underlined-input" type="email" placeholder="Your email address" name="subscription_email" id="subscription_email"/><input class="pill-button" value="SUBSCRIBE" type="submit" data-state-normal="SUBSCRIBE" data-state-sucess="SUBSCRIBED!" data-state-loading="SENDING..." onclick="t($('#subscription_email').val());"/><p class="result"></p></form></div></div><div class="col-md-2 col-md-pull-4 col-xs-6 foot
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<div class="row"><div class="col-md-9 col-sm-11 col-xs-11"><div class="hidden-md hidden-lg" id="mobile-page-heading-wrapper"><p>PredictionIO Docs</p><h4>Channel</h4></div><h4 class="hidden-sm hidden-xs">PredictionIO Docs</h4></div><div class="col-md-3 col-sm-1 col-xs-1 hidden-md hidden-lg"><img id="left-menu-indicator" src="/images/icons/down-arrow-dfe9f7fe.png"/></div><div class="col-md-3 col-sm-12 col-xs-12 swiftype-wrapper"><div class="swiftype"><form class="search-form"><img class="search-box-toggler hidden-xs hidden-sm" src="/images/icons/search-glass-704bd4ff.png"/><div class="search-box"><img src="/images/icons/search-glass-704bd4ff.png"/><input type="text" id="st-search-input" class="st-search-input" placeholder="Search Doc..."/></div><img class="swiftype-row-hider hidden-md hidden-lg" src="/images/icons/drawer-toggle-active-fcbef12a.png"/></form></div></div><div class="mobile-left-menu-toggler hidden-md hidden-lg"></div></div></div></div><div id="page" class="container-flui
d"><div class="row"><div id="left-menu-wrapper" class="col-md-3"><nav id="nav-main"><ul><li class="level-1"><a class="expandible" href="/"><span>Apache PredictionIO (incubating) Documentation</span></a><ul><li class="level-2"><a class="final" href="/"><span>Welcome to Apache PredictionIO (incubating)</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Getting Started</span></a><ul><li class="level-2"><a class="final" href="/start/"><span>A Quick Intro</span></a></li><li class="level-2"><a class="final" href="/install/"><span>Installing Apache PredictionIO (incubating)</span></a></li><li class="level-2"><a class="final" href="/start/download/"><span>Downloading an Engine Template</span></a></li><li class="level-2"><a class="final" href="/start/deploy/"><span>Deploying Your First Engine</span></a></li><li class="level-2"><a class="final" href="/start/customize/"><span>Customizing the Engine</span></a></li></ul></li><li class="level-1"><a class="expandible
" href="#"><span>Integrating with Your App</span></a><ul><li class="level-2"><a class="final" href="/appintegration/"><span>App Integration Overview</span></a></li><li class="level-2"><a class="expandible" href="/sdk/"><span>List of SDKs</span></a><ul><li class="level-3"><a class="final" href="/sdk/java/"><span>Java & Android SDK</span></a></li><li class="level-3"><a class="final" href="/sdk/php/"><span>PHP SDK</span></a></li><li class="level-3"><a class="final" href="/sdk/python/"><span>Python SDK</span></a></li><li class="level-3"><a class="final" href="/sdk/ruby/"><span>Ruby SDK</span></a></li><li class="level-3"><a class="final" href="/sdk/community/"><span>Community Powered SDKs</span></a></li></ul></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Deploying an Engine</span></a><ul><li class="level-2"><a class="final" href="/deploy/"><span>Deploying as a Web Service</span></a></li><li class="level-2"><a class="final" href="/cli/#engine-commands"><span>Engin
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iew</span></a></li><li class="level-2"><a class="final" href="/cli/#event-server-commands"><span>Event Server Command-line Interface</span></a></li><li class="level-2"><a class="final" href="/datacollection/eventapi/"><span>Collecting Data with REST/SDKs</span></a></li><li class="level-2"><a class="final" href="/datacollection/eventmodel/"><span>Events Modeling</span></a></li><li class="level-2"><a class="final" href="/datacollection/webhooks/"><span>Unifying Multichannel Data with Webhooks</span></a></li><li class="level-2"><a class="final active" href="/datacollection/channel/"><span>Channel</span></a></li><li class="level-2"><a class="final" href="/datacollection/batchimport/"><span>Importing Data in Batch</span></a></li><li class="level-2"><a class="final" href="/datacollection/analytics/"><span>Using Analytics Tools</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Choosing an Algorithm(s)</span></a><ul><li class="level-2"><a class="final" href="
/algorithm/"><span>Built-in Algorithm Libraries</span></a></li><li class="level-2"><a class="final" href="/algorithm/switch/"><span>Switching to Another Algorithm</span></a></li><li class="level-2"><a class="final" href="/algorithm/multiple/"><span>Combining Multiple Algorithms</span></a></li><li class="level-2"><a class="final" href="/algorithm/custom/"><span>Adding Your Own Algorithms</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>ML Tuning and Evaluation</span></a><ul><li class="level-2"><a class="final" href="/evaluation/"><span>Overview</span></a></li><li class="level-2"><a class="final" href="/evaluation/paramtuning/"><span>Hyperparameter Tuning</span></a></li><li class="level-2"><a class="final" href="/evaluation/evaluationdashboard/"><span>Evaluation Dashboard</span></a></li><li class="level-2"><a class="final" href="/evaluation/metricchoose/"><span>Choosing Evaluation Metrics</span></a></li><li class="level-2"><a class="final" href="/evalu
ation/metricbuild/"><span>Building Evaluation Metrics</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>System Architecture</span></a><ul><li class="level-2"><a class="final" href="/system/"><span>Architecture Overview</span></a></li><li class="level-2"><a class="final" href="/system/anotherdatastore/"><span>Using Another Data Store</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Engine Template Gallery</span></a><ul><li class="level-2"><a class="final" href="http://templates.prediction.io"><span>Browse</span></a></li><li class="level-2"><a class="final" href="/community/submit-template/"><span>Submit your Engine as a Template</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Demo Tutorials</span></a><ul><li class="level-2"><a class="final" href="/demo/tapster/"><span>Comics Recommendation Demo</span></a></li><li class="level-2"><a class="final" href="/demo/community/"><span>Community C
ontributed Demo</span></a></li><li class="level-2"><a class="final" href="/demo/textclassification/"><span>Text Classification Engine Tutorial</span></a></li></ul></li><li class="level-1"><a class="expandible" href="/community/"><span>Getting Involved</span></a><ul><li class="level-2"><a class="final" href="/community/contribute-code/"><span>Contribute Code</span></a></li><li class="level-2"><a class="final" href="/community/contribute-documentation/"><span>Contribute Documentation</span></a></li><li class="level-2"><a class="final" href="/community/contribute-sdk/"><span>Contribute a SDK</span></a></li><li class="level-2"><a class="final" href="/community/contribute-webhook/"><span>Contribute a Webhook</span></a></li><li class="level-2"><a class="final" href="/community/projects/"><span>Community Projects</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Getting Help</span></a><ul><li class="level-2"><a class="final" href="/resources/faq/"><span>FAQs
</span></a></li><li class="level-2"><a class="final" href="/support/"><span>Community Support</span></a></li><li class="level-2"><a class="final" href="/support/#enterprise-support"><span>Enterprise Support</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Resources</span></a><ul><li class="level-2"><a class="final" href="/resources/intellij/"><span>Developing Engines with IntelliJ IDEA</span></a></li><li class="level-2"><a class="final" href="/resources/upgrade/"><span>Upgrade Instructions</span></a></li><li class="level-2"><a class="final" href="/resources/glossary/"><span>Glossary</span></a></li></ul></li></ul></nav></div><div class="col-md-9 col-sm-12"><div class="content-header hidden-md hidden-lg"><div id="breadcrumbs" class="hidden-sm hidden xs"><ul><li><a href="#">Collecting and Analyzing Data</a><span class="spacer">></span></li><li><span class="last">Channel</span></li></ul></div><div id="page-title"><h1>Channel</h1></div></div><div id="t
able-of-content-wrapper"><h5>On this page</h5><aside id="table-of-contents"><ul> <li> <a href="#create-a-new-channel">Create a new Channel</a> </li> <li> <a href="#collect-data-through-channel">Collect data through Channel</a> </li> <li> <a href="#delete-a-channel-including-all-imported-data">Delete a Channel (including all imported data)</a> </li> <li> <a href="#delete-the-data-only-of-a-channel">Delete the data-only of a Channel</a> </li> <li> <a href="#accessing-channel-data-in-engine">Accessing Channel Data in Engine</a> </li> </ul> </aside><hr/><a id="edit-page-link" href="https://github.com/apache/incubator-predictionio/tree/livedoc/docs/manual/source/datacollection/channel.html.md.erb"><img src="/images/icons/edit-pencil-d6c1bb3d.png"/>Edit this page</a></div><div class="content-header hidden-sm hidden-xs"><div id="breadcrumbs" class="hidden-sm hidden xs"><ul><li><a href="#">Collecting and Analyzing Data</a><span class="spacer">></span></li><li><span class="last">Channel</
span></li></ul></div><div id="page-title"><h1>Channel</h1></div></div><div class="content"><p>Each App has a default channel (without name) which stores all incoming events. This "default" one is used when channel is not specified.</p><p>You may create additional Channels for the App. Creating multiple Channels is advanced usage. You don't need to create any in order to use Apache PredictionIO (incubating). The Channel is associated with one App only and must have unique name within the same App.</p><p>Creating multiple Channels allows you more easily to identify, manage and use specific event data if you may collect events from different multiple sources (eg. mobile, website, or third-party webhooks service) for the your application.</p><p>(More usage details coming soon...)</p><h2 id='create-a-new-channel' class='header-anchors'>Create a new Channel</h2><p>For example, to create a new channel "myChannel" for app "myApp", run following <code>pio</c
ode> command:</p><div class="highlight shell"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1</pre></td><td class="code"><pre>pio app channel-new myApp myChannel
+</pre></td></tr></tbody></table> </div> <p>you should see something like the following outputs:</p><div class="highlight shell"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1
+2
+3
+4
+5
+6
+7</pre></td><td class="code"><pre><span class="o">[</span>INFO] <span class="o">[</span>App<span class="nv">$]</span> Updated Channel meta-data.
+<span class="o">[</span>INFO] <span class="o">[</span>HBLEvents] The table predictionio_eventdata:events_5_2 doesn<span class="s1">'t exist yet. Creating now...
+[INFO] [App$] Initialized Event Store for the channel: myChannel.
+[INFO] [App$] Created new channel:
+[INFO] [App$] Channel Name: myChannel
+[INFO] [App$] Channel ID: 2
+[INFO] [App$] App ID: 5
+</span></pre></td></tr></tbody></table> </div> <p>Now "myChannel" is created and ready for collecting data.</p><h2 id='collect-data-through-channel' class='header-anchors'>Collect data through Channel</h2><p>The Event API support optional <code>channel</code> query parameter. This allows you to import and query events of the specified channel. When the <code>channel</code> parameter is not specified, the data is collected through the default channel.</p><p>URL: <code>http://localhost:7070/events.json?accessKey=yourAccessKeyString&channel=yourChannelName</code></p><p>Query parameters:</p> <table><thead> <tr> <th style="text-align: left">Field</th> <th style="text-align: left">Type</th> <th style="text-align: left">Description</th> </tr> </thead><tbody> <tr> <td style="text-align: left"><code>accessKey</code></td> <td style="text-align: left">String</td> <td style="text-align: left">The Access Key for your App</td> </tr> <tr> <td style="text-align: left"><code>channel</c
ode></td> <td style="text-align: left">String</td> <td style="text-align: left">The channel name (optional). Specify this to import data to this channel. <strong>NOTE: supported in PIO version >= 0.9.2</strong> only. Channel must be created first.</td> </tr> </tbody></table> <p>For SDK usage, one EventClient should be responsible for collecting data of one specific channel. The channel name is specified when the EventClient object is instantiated.</p><p>For example, the following code import event to "YOUR_CHANNEL" of the corresponding App.</p><div class="tabs"> <ul class="control"> <li data-lang="bash"><a href="#tab-aa76995b-2398-4afb-8a41-ab4568048344">Raw HTTP</a></li> <li data-lang="php"><a href="#tab-d421833b-782e-47b0-9ed4-5992ce24cff3">PHP SDK</a></li> <li data-lang="python"><a href="#tab-7844e8e4-f556-4837-9eb1-679fbdaaeebe">Python SDK</a></li> <li data-lang="ruby"><a href="#tab-229c2ff4-d861-4b36-8ad3-de4ce32d87a6">Ruby SDK</a></li> <li data-lang="java"><a href
="#tab-03fb8998-6e2b-489d-a090-c5aeebb79407">Java SDK</a></li> </ul> <div data-tab="Raw HTTP" data-lang="bash" id="tab-aa76995b-2398-4afb-8a41-ab4568048344"> <div class="highlight shell"> <table style="border-spacing: 0"><tbody><tr> <td class="gutter gl" style="text-align: right"><pre class="lineno">1
+2
+3
+4
+5
+6
+7
+8
+9
+10
+11
+12
+13
+14</pre></td> <td class="code"><pre><span class="gp">$ </span>curl -i -X POST http://localhost:7070/events.json?accessKey<span class="o">=</span>YOUR_ACCESS_KEY&channel<span class="o">=</span>YOUR_CHANNEL <span class="se">\</span>
+-H <span class="s2">"Content-Type: application/json"</span> <span class="se">\</span>
+-d <span class="s1">'{
+ "event" : "my_event",
+ "entityType" : "user",
+ "entityId" : "uid",
+ "targetEntityType" : "item",
+ "targetEntityId" : "iid",
+ "properties" : {
+ "someProperty" : "value1",
+ "anotherProperty" : "value2"
+ },
+ "eventTime" : "2004-12-13T21:39:45.618Z"
+}'</span>
+</pre></td> </tr></tbody></table> </div> </div> <div data-tab="PHP SDK" data-lang="php" id="tab-d421833b-782e-47b0-9ed4-5992ce24cff3"> (TODO: update me) </div> <div data-tab="Python SDK" data-lang="python" id="tab-7844e8e4-f556-4837-9eb1-679fbdaaeebe"> <div class="highlight python"> <table style="border-spacing: 0"><tbody><tr> <td class="gutter gl" style="text-align: right"><pre class="lineno">1
+2
+3
+4
+5
+6
+7
+8
+9
+10
+11
+12
+13
+14
+15
+16
+17
+18
+19
+20
+21</pre></td> <td class="code"><pre><span class="kn">from</span> <span class="nn">predictionio</span> <span class="kn">import</span> <span class="n">EventClient</span>
+<span class="kn">from</span> <span class="nn">datetime</span> <span class="kn">import</span> <span class="n">datetime</span>
+<span class="kn">import</span> <span class="nn">pytz</span>
+
+<span class="c"># Create a EventClient for "YOUR_CHANNEL"</span>
+<span class="n">client</span> <span class="o">=</span> <span class="n">EventClient</span><span class="p">(</span><span class="s">'YOUR_ACCESS_KEY'</span><span class="p">,</span> <span class="s">"http://localhost:7070"</span><span class="p">,</span>
+ <span class="n">channel</span><span class="o">=</span><span class="s">'YOUR_CHANNEL'</span><span class="p">)</span> <span class="c"># default channel if not specified</span>
+
+<span class="n">event_properties</span> <span class="o">=</span> <span class="p">{</span>
+ <span class="s">"someProperty"</span> <span class="p">:</span> <span class="s">"value1"</span><span class="p">,</span>
+ <span class="s">"anotherProperty"</span> <span class="p">:</span> <span class="s">"value2"</span><span class="p">,</span>
+ <span class="p">}</span>
+<span class="n">event_response</span> <span class="o">=</span> <span class="n">client</span><span class="o">.</span><span class="n">create_event</span><span class="p">(</span>
+ <span class="n">event</span><span class="o">=</span><span class="s">"my_event"</span><span class="p">,</span>
+ <span class="n">entity_type</span><span class="o">=</span><span class="s">"user"</span><span class="p">,</span>
+ <span class="n">entity_id</span><span class="o">=</span><span class="s">"uid"</span><span class="p">,</span>
+ <span class="n">target_entity_type</span><span class="o">=</span><span class="s">"item"</span><span class="p">,</span>
+ <span class="n">target_entity_id</span><span class="o">=</span><span class="s">"iid"</span><span class="p">,</span>
+ <span class="n">properties</span><span class="o">=</span><span class="n">event_properties</span><span class="p">,</span>
+ <span class="n">event_time</span><span class="o">=</span><span class="n">datetime</span><span class="p">(</span><span class="mi">2014</span><span class="p">,</span> <span class="mi">12</span><span class="p">,</span> <span class="mi">13</span><span class="p">,</span> <span class="mi">21</span><span class="p">,</span> <span class="mi">38</span><span class="p">,</span> <span class="mi">45</span><span class="p">,</span> <span class="mi">618000</span><span class="p">,</span> <span class="n">pytz</span><span class="o">.</span><span class="n">utc</span><span class="p">))</span>
+
+</pre></td> </tr></tbody></table> </div> </div> <div data-tab="Ruby SDK" data-lang="ruby" id="tab-229c2ff4-d861-4b36-8ad3-de4ce32d87a6"> (TODO: update me) </div> <div data-tab="Java SDK" data-lang="java" id="tab-03fb8998-6e2b-489d-a090-c5aeebb79407"> <div class="highlight java"> <table style="border-spacing: 0"><tbody><tr> <td class="gutter gl" style="text-align: right"><pre class="lineno">1</pre></td> <td class="code"><pre><span class="o">(</span><span class="n">coming</span> <span class="n">soon</span><span class="o">)</span>
+</pre></td> </tr></tbody></table> </div> </div> </div> <p>You can also follow the EventAPI <a href="/datacollection/eventapi/#debugging-recipes">debug receipts</a> to query the events of specific channel by adding the <code>channel</code> query parameter in the URL.</p><h2 id='delete-a-channel-(including-all-imported-data)' class='header-anchors'>Delete a Channel (including all imported data)</h2><div class="highlight shell"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1</pre></td><td class="code"><pre>pio app channel-delete <app name> <channel name>
+</pre></td></tr></tbody></table> </div> <h2 id='delete-the-data-only-of-a-channel' class='header-anchors'>Delete the data-only of a Channel</h2><div class="highlight shell"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1</pre></td><td class="code"><pre>pio app data-delete <app name> --channel <channel name>
+</pre></td></tr></tbody></table> </div> <h2 id='accessing-channel-data-in-engine' class='header-anchors'>Accessing Channel Data in Engine</h2><p>To acccess channel data, simply specify the channel name when use the PEventStore or LEventStore API. Data is read from from the default channel if channelName is not specified.</p><p>For example, read data from default channel:</p><div class="highlight scala"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1
+2
+3
+4
+5
+6
+7
+8</pre></td><td class="code"><pre>
+ <span class="k">val</span> <span class="n">eventsRDD</span><span class="k">:</span> <span class="kt">RDD</span><span class="o">[</span><span class="kt">Event</span><span class="o">]</span> <span class="k">=</span> <span class="nc">PEventStore</span><span class="o">.</span><span class="n">find</span><span class="o">(</span>
+ <span class="n">appName</span> <span class="k">=</span> <span class="n">dsp</span><span class="o">.</span><span class="n">appName</span><span class="o">,</span>
+ <span class="n">entityType</span> <span class="k">=</span> <span class="nc">Some</span><span class="o">(</span><span class="s">"user"</span><span class="o">),</span>
+ <span class="n">eventNames</span> <span class="k">=</span> <span class="nc">Some</span><span class="o">(</span><span class="nc">List</span><span class="o">(</span><span class="s">"rate"</span><span class="o">,</span> <span class="s">"buy"</span><span class="o">)),</span> <span class="c1">// read "rate" and "buy" event
+</span> <span class="c1">// targetEntityType is optional field of an event.
+</span> <span class="n">targetEntityType</span> <span class="k">=</span> <span class="nc">Some</span><span class="o">(</span><span class="nc">Some</span><span class="o">(</span><span class="s">"item"</span><span class="o">)))(</span><span class="n">sc</span><span class="o">)</span>
+
+</pre></td></tr></tbody></table> </div> <p>For examlpe, read data from the channel "CHANNEL_NAME"</p><div class="highlight scala"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1
+2
+3
+4
+5
+6
+7
+8
+9</pre></td><td class="code"><pre>
+ <span class="k">val</span> <span class="n">eventsRDD</span><span class="k">:</span> <span class="kt">RDD</span><span class="o">[</span><span class="kt">Event</span><span class="o">]</span> <span class="k">=</span> <span class="nc">PEventStore</span><span class="o">.</span><span class="n">find</span><span class="o">(</span>
+ <span class="n">appName</span> <span class="k">=</span> <span class="n">dsp</span><span class="o">.</span><span class="n">appName</span><span class="o">,</span>
+ <span class="n">channelName</span> <span class="k">=</span> <span class="nc">Some</span><span class="o">(</span><span class="s">"CHANNEL_NAME"</span><span class="o">),</span> <span class="c1">// ADDED
+</span> <span class="n">entityType</span> <span class="k">=</span> <span class="nc">Some</span><span class="o">(</span><span class="s">"user"</span><span class="o">),</span>
+ <span class="n">eventNames</span> <span class="k">=</span> <span class="nc">Some</span><span class="o">(</span><span class="nc">List</span><span class="o">(</span><span class="s">"rate"</span><span class="o">,</span> <span class="s">"buy"</span><span class="o">)),</span> <span class="c1">// read "rate" and "buy" event
+</span> <span class="c1">// targetEntityType is optional field of an event.
+</span> <span class="n">targetEntityType</span> <span class="k">=</span> <span class="nc">Some</span><span class="o">(</span><span class="nc">Some</span><span class="o">(</span><span class="s">"item"</span><span class="o">)))(</span><span class="n">sc</span><span class="o">)</span>
+
+</pre></td></tr></tbody></table> </div> </div></div></div></div><footer><div class="container"><div class="seperator"></div><div class="row"><div class="col-md-4 col-md-push-8 col-xs-12"><div class="subscription-form-wrapper"><h4>Subscribe to our Newsletter</h4><form class="ajax-form" id="subscribe-form" method="POST" action="https://script.google.com/macros/s/AKfycbwhzeKCQJjQ52eVAqNT_vcklH07OITUO7wzOMDXvK6EGAWgaZgF/exec"><input class="required underlined-input" type="email" placeholder="Your email address" name="subscription_email" id="subscription_email"/><input class="pill-button" value="SUBSCRIBE" type="submit" data-state-normal="SUBSCRIBE" data-state-sucess="SUBSCRIBED!" data-state-loading="SENDING..." onclick="t($('#subscription_email').val());"/><p class="result"></p></form></div></div><div class="col-md-2 col-md-pull-4 col-xs-6 footer-link-column"><div class="footer-link-column-row"><h4>Community</h4><ul><li><a href="//docs.prediction.io/install/" target="blank">Download</a>
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<div class="row"><div class="col-md-9 col-sm-11 col-xs-11"><div class="hidden-md hidden-lg" id="mobile-page-heading-wrapper"><p>PredictionIO Docs</p><h4>Hyperparameter Tuning</h4></div><h4 class="hidden-sm hidden-xs">PredictionIO Docs</h4></div><div class="col-md-3 col-sm-1 col-xs-1 hidden-md hidden-lg"><img id="left-menu-indicator" src="/images/icons/down-arrow-dfe9f7fe.png"/></div><div class="col-md-3 col-sm-12 col-xs-12 swiftype-wrapper"><div class="swiftype"><form class="search-form"><img class="search-box-toggler hidden-xs hidden-sm" src="/images/icons/search-glass-704bd4ff.png"/><div class="search-box"><img src="/images/icons/search-glass-704bd4ff.png"/><input type="text" id="st-search-input" class="st-search-input" placeholder="Search Doc..."/></div><img class="swiftype-row-hider hidden-md hidden-lg" src="/images/icons/drawer-toggle-active-fcbef12a.png"/></form></div></div><div class="mobile-left-menu-toggler hidden-md hidden-lg"></div></div></div></div><div id="page" class="
container-fluid"><div class="row"><div id="left-menu-wrapper" class="col-md-3"><nav id="nav-main"><ul><li class="level-1"><a class="expandible" href="/"><span>Apache PredictionIO (incubating) Documentation</span></a><ul><li class="level-2"><a class="final" href="/"><span>Welcome to Apache PredictionIO (incubating)</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Getting Started</span></a><ul><li class="level-2"><a class="final" href="/start/"><span>A Quick Intro</span></a></li><li class="level-2"><a class="final" href="/install/"><span>Installing Apache PredictionIO (incubating)</span></a></li><li class="level-2"><a class="final" href="/start/download/"><span>Downloading an Engine Template</span></a></li><li class="level-2"><a class="final" href="/start/deploy/"><span>Deploying Your First Engine</span></a></li><li class="level-2"><a class="final" href="/start/customize/"><span>Customizing the Engine</span></a></li></ul></li><li class="level-1"><a cla
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t Server Overview</span></a></li><li class="level-2"><a class="final" href="/cli/#event-server-commands"><span>Event Server Command-line Interface</span></a></li><li class="level-2"><a class="final" href="/datacollection/eventapi/"><span>Collecting Data with REST/SDKs</span></a></li><li class="level-2"><a class="final" href="/datacollection/eventmodel/"><span>Events Modeling</span></a></li><li class="level-2"><a class="final" href="/datacollection/webhooks/"><span>Unifying Multichannel Data with Webhooks</span></a></li><li class="level-2"><a class="final" href="/datacollection/channel/"><span>Channel</span></a></li><li class="level-2"><a class="final" href="/datacollection/batchimport/"><span>Importing Data in Batch</span></a></li><li class="level-2"><a class="final" href="/datacollection/analytics/"><span>Using Analytics Tools</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Choosing an Algorithm(s)</span></a><ul><li class="level-2"><a class="final"
href="/algorithm/"><span>Built-in Algorithm Libraries</span></a></li><li class="level-2"><a class="final" href="/algorithm/switch/"><span>Switching to Another Algorithm</span></a></li><li class="level-2"><a class="final" href="/algorithm/multiple/"><span>Combining Multiple Algorithms</span></a></li><li class="level-2"><a class="final" href="/algorithm/custom/"><span>Adding Your Own Algorithms</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>ML Tuning and Evaluation</span></a><ul><li class="level-2"><a class="final" href="/evaluation/"><span>Overview</span></a></li><li class="level-2"><a class="final active" href="/evaluation/paramtuning/"><span>Hyperparameter Tuning</span></a></li><li class="level-2"><a class="final" href="/evaluation/evaluationdashboard/"><span>Evaluation Dashboard</span></a></li><li class="level-2"><a class="final" href="/evaluation/metricchoose/"><span>Choosing Evaluation Metrics</span></a></li><li class="level-2"><a class="final
" href="/evaluation/metricbuild/"><span>Building Evaluation Metrics</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>System Architecture</span></a><ul><li class="level-2"><a class="final" href="/system/"><span>Architecture Overview</span></a></li><li class="level-2"><a class="final" href="/system/anotherdatastore/"><span>Using Another Data Store</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Engine Template Gallery</span></a><ul><li class="level-2"><a class="final" href="http://templates.prediction.io"><span>Browse</span></a></li><li class="level-2"><a class="final" href="/community/submit-template/"><span>Submit your Engine as a Template</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Demo Tutorials</span></a><ul><li class="level-2"><a class="final" href="/demo/tapster/"><span>Comics Recommendation Demo</span></a></li><li class="level-2"><a class="final" href="/demo/community/"><sp
an>Community Contributed Demo</span></a></li><li class="level-2"><a class="final" href="/demo/textclassification/"><span>Text Classification Engine Tutorial</span></a></li></ul></li><li class="level-1"><a class="expandible" href="/community/"><span>Getting Involved</span></a><ul><li class="level-2"><a class="final" href="/community/contribute-code/"><span>Contribute Code</span></a></li><li class="level-2"><a class="final" href="/community/contribute-documentation/"><span>Contribute Documentation</span></a></li><li class="level-2"><a class="final" href="/community/contribute-sdk/"><span>Contribute a SDK</span></a></li><li class="level-2"><a class="final" href="/community/contribute-webhook/"><span>Contribute a Webhook</span></a></li><li class="level-2"><a class="final" href="/community/projects/"><span>Community Projects</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Getting Help</span></a><ul><li class="level-2"><a class="final" href="/resources/fa
q/"><span>FAQs</span></a></li><li class="level-2"><a class="final" href="/support/"><span>Community Support</span></a></li><li class="level-2"><a class="final" href="/support/#enterprise-support"><span>Enterprise Support</span></a></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Resources</span></a><ul><li class="level-2"><a class="final" href="/resources/intellij/"><span>Developing Engines with IntelliJ IDEA</span></a></li><li class="level-2"><a class="final" href="/resources/upgrade/"><span>Upgrade Instructions</span></a></li><li class="level-2"><a class="final" href="/resources/glossary/"><span>Glossary</span></a></li></ul></li></ul></nav></div><div class="col-md-9 col-sm-12"><div class="content-header hidden-md hidden-lg"><div id="breadcrumbs" class="hidden-sm hidden xs"><ul><li><a href="#">ML Tuning and Evaluation</a><span class="spacer">></span></li><li><span class="last">Hyperparameter Tuning</span></li></ul></div><div id="page-title"><h1>Hyperparame
ter Tuning</h1></div></div><div id="table-of-content-wrapper"><h5>On this page</h5><aside id="table-of-contents"><ul> <li> <a href="#quick-start">Quick Start</a> </li> <li> <a href="#detailed-explanation">Detailed Explanation</a> </li> <li> <a href="#the-evaluation-design">The Evaluation Design</a> </li> <li> <a href="#evaluation-data-generation">Evaluation Data Generation</a> </li> <li> <a href="#evaluation-metrics">Evaluation Metrics</a> </li> <li> <a href="#parameters-generation">Parameters Generation</a> </li> <li> <a href="#running-the-evaluation">Running the Evaluation</a> </li> <li> <a href="#notes">Notes</a> </li> </ul> </aside><hr/><a id="edit-page-link" href="https://github.com/apache/incubator-predictionio/tree/livedoc/docs/manual/source/evaluation/paramtuning.html.md"><img src="/images/icons/edit-pencil-d6c1bb3d.png"/>Edit this page</a></div><div class="content-header hidden-sm hidden-xs"><div id="breadcrumbs" class="hidden-sm hidden xs"><ul><li><a href="#">ML Tuning and
Evaluation</a><span class="spacer">></span></li><li><span class="last">Hyperparameter Tuning</span></li></ul></div><div id="page-title"><h1>Hyperparameter Tuning</h1></div></div><div class="content"><p>A PredictionIO engine is instantiated by a set of parameters. These parameters define which algorithm is to be used, as well supply the parameters for the algorithm itself. This naturally raises the question of how to choose the best set of parameters. The evaluation module streamlines the process of <em>tuning</em> the engine to the best parameter set and deploys it.</p><h2 id='quick-start' class='header-anchors'>Quick Start</h2><p>We demonstrate the evaluation with <a href="/templates/classification/quickstart/">the classification template</a>. The classification template uses a naive bayesian algorithm that has a smoothing parameter. We evaluate the prediction quality against different parameter values to find the best parameter values, and then deploy it.</p><h3 id='edit-the-a
ppid' class='header-anchors'>Edit the AppId</h3><p>Edit MyClassification/src/main/scala/<strong><em>Evaluation.scala</em></strong> to specify the <em>appId</em> you used to import the data.</p><div class="highlight scala"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1
+2
+3
+4
+5
+6</pre></td><td class="code"><pre><span class="k">object</span> <span class="nc">EngineParamsList</span> <span class="k">extends</span> <span class="nc">EngineParamsGenerator</span> <span class="o">{</span>
+ <span class="o">...</span>
+ <span class="k">private</span><span class="o">[</span><span class="kt">this</span><span class="o">]</span> <span class="k">val</span> <span class="n">baseEP</span> <span class="k">=</span> <span class="nc">EngineParams</span><span class="o">(</span>
+ <span class="n">dataSourceParams</span> <span class="k">=</span> <span class="nc">DataSourceParams</span><span class="o">(</span><span class="n">appId</span> <span class="k">=</span> <span class="o"><</span><span class="nc">YOUR_APP_ID</span><span class="o">>,</span> <span class="n">evalK</span> <span class="k">=</span> <span class="nc">Some</span><span class="o">(</span><span class="mi">5</span><span class="o">)))</span>
+ <span class="o">...</span>
+<span class="o">}</span>
+</pre></td></tr></tbody></table> </div> <h3 id='build-and-run-the-evaluation' class='header-anchors'>Build and run the evaluation</h3><p>To run an evaluation, the command <code>pio eval</code> is used. It takes two mandatory parameter, 1. the <code>Evaluation</code> object, which tells PredictionIO the engine and metric we use for the evaluation; and 2. the <code>EngineParamsGenerator</code>, which contains a list of engine params to test against. The following command kickstarts the evaluation workflow for the classification template.</p><div class="highlight shell"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1
+2
+3
+4</pre></td><td class="code"><pre><span class="gp">$ </span>pio build
+...
+<span class="gp">$ </span>pio <span class="nb">eval </span>org.template.classification.AccuracyEvaluation <span class="se">\</span>
+ org.template.classification.EngineParamsList
+</pre></td></tr></tbody></table> </div> <p>You will see the following output:</p><div class="highlight shell"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1
+2
+3
+4
+5
+6
+7
+8
+9
+10
+11
+12
+13
+14
+15
+16
+17
+18
+19
+20
+21
+22
+23
+24
+25
+26
+27
+28
+29
+30
+31
+32
+33
+34
+35
+36
+37
+38
+39
+40
+41
+42
+43
+44
+45</pre></td><td class="code"><pre>...
+<span class="o">[</span>INFO] <span class="o">[</span>CoreWorkflow<span class="nv">$]</span> runEvaluation started
+...
+<span class="o">[</span>INFO] <span class="o">[</span>MetricEvaluator] Iteration 0
+<span class="o">[</span>INFO] <span class="o">[</span>MetricEvaluator] EngineParams: <span class="o">{</span><span class="s2">"dataSourceParams"</span>:<span class="o">{</span><span class="s2">""</span>:<span class="o">{</span><span class="s2">"appId"</span>:19,<span class="s2">"evalK"</span>:5<span class="o">}}</span>,<span class="s2">"preparatorParams"</span>:<span class="o">{</span><span class="s2">""</span>:<span class="o">{}}</span>,<span class="s2">"algorithmParamsList"</span>:[<span class="o">{</span><span class="s2">"naive"</span>:<span class="o">{</span><span class="s2">"lambda"</span>:10.0<span class="o">}}]</span>,<span class="s2">"servingParams"</span>:<span class="o">{</span><span class="s2">""</span>:<span class="o">{}}}</span>
+<span class="o">[</span>INFO] <span class="o">[</span>MetricEvaluator] Result: MetricScores<span class="o">(</span>0.9281045751633987,List<span class="o">())</span>
+<span class="o">[</span>INFO] <span class="o">[</span>MetricEvaluator] Iteration 1
+<span class="o">[</span>INFO] <span class="o">[</span>MetricEvaluator] EngineParams: <span class="o">{</span><span class="s2">"dataSourceParams"</span>:<span class="o">{</span><span class="s2">""</span>:<span class="o">{</span><span class="s2">"appId"</span>:19,<span class="s2">"evalK"</span>:5<span class="o">}}</span>,<span class="s2">"preparatorParams"</span>:<span class="o">{</span><span class="s2">""</span>:<span class="o">{}}</span>,<span class="s2">"algorithmParamsList"</span>:[<span class="o">{</span><span class="s2">"naive"</span>:<span class="o">{</span><span class="s2">"lambda"</span>:100.0<span class="o">}}]</span>,<span class="s2">"servingParams"</span>:<span class="o">{</span><span class="s2">""</span>:<span class="o">{}}}</span>
+<span class="o">[</span>INFO] <span class="o">[</span>MetricEvaluator] Result: MetricScores<span class="o">(</span>0.9150326797385621,List<span class="o">())</span>
+<span class="o">[</span>INFO] <span class="o">[</span>MetricEvaluator] Iteration 2
+<span class="o">[</span>INFO] <span class="o">[</span>MetricEvaluator] EngineParams: <span class="o">{</span><span class="s2">"dataSourceParams"</span>:<span class="o">{</span><span class="s2">""</span>:<span class="o">{</span><span class="s2">"appId"</span>:19,<span class="s2">"evalK"</span>:5<span class="o">}}</span>,<span class="s2">"preparatorParams"</span>:<span class="o">{</span><span class="s2">""</span>:<span class="o">{}}</span>,<span class="s2">"algorithmParamsList"</span>:[<span class="o">{</span><span class="s2">"naive"</span>:<span class="o">{</span><span class="s2">"lambda"</span>:1000.0<span class="o">}}]</span>,<span class="s2">"servingParams"</span>:<span class="o">{</span><span class="s2">""</span>:<span class="o">{}}}</span>
+<span class="o">[</span>INFO] <span class="o">[</span>MetricEvaluator] Result: MetricScores<span class="o">(</span>0.4444444444444444,List<span class="o">())</span>
+<span class="o">[</span>INFO] <span class="o">[</span>MetricEvaluator] Writing best variant params to disk...
+<span class="o">[</span>INFO] <span class="o">[</span>CoreWorkflow<span class="nv">$]</span> Updating evaluation instance with result: MetricEvaluatorResult:
+ <span class="c"># engine params evaluated: 3</span>
+Optimal Engine Params:
+ <span class="o">{</span>
+ <span class="s2">"dataSourceParams"</span>:<span class="o">{</span>
+ <span class="s2">""</span>:<span class="o">{</span>
+ <span class="s2">"appId"</span>:19,
+ <span class="s2">"evalK"</span>:5
+ <span class="o">}</span>
+ <span class="o">}</span>,
+ <span class="s2">"preparatorParams"</span>:<span class="o">{</span>
+ <span class="s2">""</span>:<span class="o">{</span>
+
+ <span class="o">}</span>
+ <span class="o">}</span>,
+ <span class="s2">"algorithmParamsList"</span>:[
+ <span class="o">{</span>
+ <span class="s2">"naive"</span>:<span class="o">{</span>
+ <span class="s2">"lambda"</span>:10.0
+ <span class="o">}</span>
+ <span class="o">}</span>
+ <span class="o">]</span>,
+ <span class="s2">"servingParams"</span>:<span class="o">{</span>
+ <span class="s2">""</span>:<span class="o">{</span>
+
+ <span class="o">}</span>
+ <span class="o">}</span>
+<span class="o">}</span>
+Metrics:
+ org.template.classification.Accuracy: 0.9281045751633987
+The best variant params can be found <span class="k">in </span>best.json
+<span class="o">[</span>INFO] <span class="o">[</span>CoreWorkflow<span class="nv">$]</span> runEvaluation completed
+</pre></td></tr></tbody></table> </div> <p>The console prints out the evaluation metric score of each engine params, and finally pretty print the optimal engine params. Amongst the 3 engine params we evaluate, <em>lambda = 10.0</em> yields the highest accuracy score of ~0.9281.</p><h3 id='deploy-the-best-engine-parameter' class='header-anchors'>Deploy the best engine parameter</h3><p>The evaluation module also writes out the best engine parameter to disk at <code>best.json</code>. We can train and deploy this specify engine variant using the extra parameter <code>-v</code>. For example:</p><div class="highlight shell"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1
+2
+3
+4
+5
+6
+7</pre></td><td class="code"><pre><span class="gp">$ </span>pio train -v best.json
+...
+<span class="o">[</span>INFO] <span class="o">[</span>CoreWorkflow<span class="nv">$]</span> Training completed successfully.
+<span class="gp">$ </span>pio deploy -v best.json
+...
+<span class="o">[</span>INFO] <span class="o">[</span>HttpListener] Bound to localhost/127.0.0.1:8000
+<span class="o">[</span>INFO] <span class="o">[</span>MasterActor] Bind successful. Ready to serve.
+</pre></td></tr></tbody></table> </div> <p>At this point, we have successfully deployed the best engine variant we found through the evaluation process.</p><h2 id='detailed-explanation' class='header-anchors'>Detailed Explanation</h2><p>An engine often depends on a number of parameters, for example, the naive bayesian classification algorithm has a smoothing parameter to make the model more adaptive to unseen data. Compared with parameters which are <em>learnt</em> by the machine learning algorithm, this smoothing parameter <em>teaches</em> the algorithm how to work. Therefore, such parameters are usually called <em>hyperparameters</em>.</p><p>In PredictionIO, we always take a holistic view of an engine. An engine is comprised of a set of <strong><em>DAS</em></strong> controllers, as well as the necessary parameters for the controllers themselves. In the evaluation, we attempt to find out the best hyperparameters for an <em>engine</em>, which we call <strong><em>engine params</em></
strong>. Using engine params we can deploy a complete engine.</p><p>This section demonstrates how to select the optimal engine params whilst ensuring the model doesn't overfit using PredictionIO's evaluation module.</p><h2 id='the-evaluation-design' class='header-anchors'>The Evaluation Design</h2><p>The PredictionIO evaluation module tests for the best engine params for an engine.</p><p>Given a set of engine params, we instantiate an engine and evaluate it with existing data. The data is split into two sets, a training set and a validation set. The training set is used to train the engine, which is deployed using the same steps described in earlier sections. We query the engine with the test set data, and compare the predicted values in the response with the actual data contained in the validation set. We define a <strong><em>metric</em></strong> to compare <strong><em>predicted result</em></strong> returned from the engine with the <strong><em>actual result</em></strong> w
hich we obtained from the test data. The goal is to maximize the metric score.</p><p>This process is repeated many times with a series of engine params. At the end, PredictionIO returns the best engine params.</p><p>We demonstrate the evaluation with <a href="/templates/classification/quickstart/">the classification template</a>.</p><h2 id='evaluation-data-generation' class='header-anchors'>Evaluation Data Generation</h2><p>In evaluation data generation, the goal is to generate a sequence of (training, validation) data tuple. A common way is to use a <em>k-fold</em> generation process. The data set is split into <em>k folds</em>. We generate k tuples of training and validation sets, for each tuple, the training set takes <em>k - 1</em> of the folds and the validation set takes the remaining fold.</p><p>To enable evaluation data generation, we need to define the <strong><em>actual result</em></strong> and implement the method for generating the (training, validation) data tuple.</p><
h3 id='actual-result' class='header-anchors'>Actual Result</h3><p>In MyClassification/src/main/scala/<strong><em>Engine.scala</em></strong>, the <code>ActualResult</code> class defines the <strong><em>actual result</em></strong>:</p><div class="highlight scala"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1
+2
+3</pre></td><td class="code"><pre><span class="k">class</span> <span class="nc">ActualResult</span><span class="o">(</span>
+ <span class="k">val</span> <span class="n">label</span><span class="k">:</span> <span class="kt">Double</span>
+<span class="o">)</span> <span class="k">extends</span> <span class="nc">Serializable</span>
+</pre></td></tr></tbody></table> </div> <p>This class is used to store the actual label of the data (contrast to <code>PredictedResult</code> which is output of the engine).</p><h3 id='implement-data-generation-method-in-datasource' class='header-anchors'>Implement Data Generation Method in DataSource</h3><p>In MyClassification/src/main/scala/<strong><em>DataSource.scala</em></strong>, the method <code>readEval</code> reads and selects data from datastore and returns a sequence of (training, validation) data.</p><div class="highlight scala"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1
+2
+3
+4
+5
+6
+7
+8
+9
+10
+11
+12
+13
+14
+15
+16
+17
+18
+19
+20
+21
+22
+23
+24
+25
+26
+27
+28
+29
+30
+31
+32
+33
+34
+35
+36
+37
+38
+39
+40
+41
+42
+43
+44
+45
+46
+47
+48
+49
+50
+51
+52
+53
+54
+55
+56
+57
+58
+59
+60</pre></td><td class="code"><pre><span class="k">class</span> <span class="nc">DataSource</span><span class="o">(</span><span class="k">val</span> <span class="n">dsp</span><span class="k">:</span> <span class="kt">DataSourceParams</span><span class="o">)</span>
+ <span class="k">extends</span> <span class="nc">PDataSource</span><span class="o">[</span><span class="kt">TrainingData</span>, <span class="kt">EmptyEvaluationInfo</span>, <span class="kt">Query</span>, <span class="kt">ActualResult</span><span class="o">]</span> <span class="o">{</span>
+
+ <span class="o">...</span>
+
+ <span class="k">override</span>
+ <span class="k">def</span> <span class="n">readEval</span><span class="o">(</span><span class="n">sc</span><span class="k">:</span> <span class="kt">SparkContext</span><span class="o">)</span>
+ <span class="k">:</span> <span class="kt">Seq</span><span class="o">[(</span><span class="kt">TrainingData</span>, <span class="kt">EmptyEvaluationInfo</span>, <span class="kt">RDD</span><span class="o">[(</span><span class="kt">Query</span>, <span class="kt">ActualResult</span><span class="o">)])]</span> <span class="k">=</span> <span class="o">{</span>
+ <span class="n">require</span><span class="o">(!</span><span class="n">dsp</span><span class="o">.</span><span class="n">evalK</span><span class="o">.</span><span class="n">isEmpty</span><span class="o">,</span> <span class="s">"DataSourceParams.evalK must not be None"</span><span class="o">)</span>
+
+ <span class="c1">// The following code reads the data from data store. It is equivalent to
+</span> <span class="c1">// the readTraining method. We copy-and-paste the exact code here for
+</span> <span class="c1">// illustration purpose, a recommended approach is to factor out this logic
+</span> <span class="c1">// into a helper function and have both readTraining and readEval call the
+</span> <span class="c1">// helper.
+</span> <span class="k">val</span> <span class="n">eventsDb</span> <span class="k">=</span> <span class="nc">Storage</span><span class="o">.</span><span class="n">getPEvents</span><span class="o">()</span>
+ <span class="k">val</span> <span class="n">labeledPoints</span><span class="k">:</span> <span class="kt">RDD</span><span class="o">[</span><span class="kt">LabeledPoint</span><span class="o">]</span> <span class="k">=</span> <span class="n">eventsDb</span><span class="o">.</span><span class="n">aggregateProperties</span><span class="o">(</span>
+ <span class="n">appId</span> <span class="k">=</span> <span class="n">dsp</span><span class="o">.</span><span class="n">appId</span><span class="o">,</span>
+ <span class="n">entityType</span> <span class="k">=</span> <span class="s">"user"</span><span class="o">,</span>
+ <span class="c1">// only keep entities with these required properties defined
+</span> <span class="n">required</span> <span class="k">=</span> <span class="nc">Some</span><span class="o">(</span><span class="nc">List</span><span class="o">(</span><span class="s">"plan"</span><span class="o">,</span> <span class="s">"attr0"</span><span class="o">,</span> <span class="s">"attr1"</span><span class="o">,</span> <span class="s">"attr2"</span><span class="o">)))(</span><span class="n">sc</span><span class="o">)</span>
+ <span class="c1">// aggregateProperties() returns RDD pair of
+</span> <span class="c1">// entity ID and its aggregated properties
+</span> <span class="o">.</span><span class="n">map</span> <span class="o">{</span> <span class="k">case</span> <span class="o">(</span><span class="n">entityId</span><span class="o">,</span> <span class="n">properties</span><span class="o">)</span> <span class="k">=></span>
+ <span class="k">try</span> <span class="o">{</span>
+ <span class="nc">LabeledPoint</span><span class="o">(</span><span class="n">properties</span><span class="o">.</span><span class="n">get</span><span class="o">[</span><span class="kt">Double</span><span class="o">](</span><span class="s">"plan"</span><span class="o">),</span>
+ <span class="nc">Vectors</span><span class="o">.</span><span class="n">dense</span><span class="o">(</span><span class="nc">Array</span><span class="o">(</span>
+ <span class="n">properties</span><span class="o">.</span><span class="n">get</span><span class="o">[</span><span class="kt">Double</span><span class="o">](</span><span class="s">"attr0"</span><span class="o">),</span>
+ <span class="n">properties</span><span class="o">.</span><span class="n">get</span><span class="o">[</span><span class="kt">Double</span><span class="o">](</span><span class="s">"attr1"</span><span class="o">),</span>
+ <span class="n">properties</span><span class="o">.</span><span class="n">get</span><span class="o">[</span><span class="kt">Double</span><span class="o">](</span><span class="s">"attr2"</span><span class="o">)</span>
+ <span class="o">))</span>
+ <span class="o">)</span>
+ <span class="o">}</span> <span class="k">catch</span> <span class="o">{</span>
+ <span class="k">case</span> <span class="n">e</span><span class="k">:</span> <span class="kt">Exception</span> <span class="o">=></span> <span class="o">{</span>
+ <span class="n">logger</span><span class="o">.</span><span class="n">error</span><span class="o">(</span><span class="n">s</span><span class="s">"Failed to get properties ${properties} of"</span> <span class="o">+</span>
+ <span class="n">s</span><span class="s">" ${entityId}. Exception: ${e}."</span><span class="o">)</span>
+ <span class="k">throw</span> <span class="n">e</span>
+ <span class="o">}</span>
+ <span class="o">}</span>
+ <span class="o">}.</span><span class="n">cache</span><span class="o">()</span>
+ <span class="c1">// End of reading from data store
+</span>
+ <span class="c1">// K-fold splitting
+</span> <span class="k">val</span> <span class="n">evalK</span> <span class="k">=</span> <span class="n">dsp</span><span class="o">.</span><span class="n">evalK</span><span class="o">.</span><span class="n">get</span>
+ <span class="k">val</span> <span class="n">indexedPoints</span><span class="k">:</span> <span class="kt">RDD</span><span class="o">[(</span><span class="kt">LabeledPoint</span>, <span class="kt">Long</span><span class="o">)]</span> <span class="k">=</span> <span class="n">labeledPoints</span><span class="o">.</span><span class="n">zipWithIndex</span>
+
+ <span class="o">(</span><span class="mi">0</span> <span class="n">until</span> <span class="n">evalK</span><span class="o">).</span><span class="n">map</span> <span class="o">{</span> <span class="n">idx</span> <span class="k">=></span>
+ <span class="k">val</span> <span class="n">trainingPoints</span> <span class="k">=</span> <span class="n">indexedPoints</span><span class="o">.</span><span class="n">filter</span><span class="o">(</span><span class="k">_</span><span class="o">.</span><span class="n">_2</span> <span class="o">%</span> <span class="n">evalK</span> <span class="o">!=</span> <span class="n">idx</span><span class="o">).</span><span class="n">map</span><span class="o">(</span><span class="k">_</span><span class="o">.</span><span class="n">_1</span><span class="o">)</span>
+ <span class="k">val</span> <span class="n">testingPoints</span> <span class="k">=</span> <span class="n">indexedPoints</span><span class="o">.</span><span class="n">filter</span><span class="o">(</span><span class="k">_</span><span class="o">.</span><span class="n">_2</span> <span class="o">%</span> <span class="n">evalK</span> <span class="o">==</span> <span class="n">idx</span><span class="o">).</span><span class="n">map</span><span class="o">(</span><span class="k">_</span><span class="o">.</span><span class="n">_1</span><span class="o">)</span>
+
+ <span class="o">(</span>
+ <span class="k">new</span> <span class="nc">TrainingData</span><span class="o">(</span><span class="n">trainingPoints</span><span class="o">),</span>
+ <span class="k">new</span> <span class="nc">EmptyEvaluationInfo</span><span class="o">(),</span>
+ <span class="n">testingPoints</span><span class="o">.</span><span class="n">map</span> <span class="o">{</span>
+ <span class="n">p</span> <span class="k">=></span> <span class="o">(</span><span class="k">new</span> <span class="nc">Query</span><span class="o">(</span><span class="n">p</span><span class="o">.</span><span class="n">features</span><span class="o">.</span><span class="n">toArray</span><span class="o">),</span> <span class="k">new</span> <span class="nc">ActualResult</span><span class="o">(</span><span class="n">p</span><span class="o">.</span><span class="n">label</span><span class="o">))</span>
+ <span class="o">}</span>
+ <span class="o">)</span>
+ <span class="o">}</span>
+ <span class="o">}</span>
+<span class="o">}</span>
+</pre></td></tr></tbody></table> </div> <p>The <code>readEval</code> method returns a sequence of (<code>TrainingData</code>, <code>EvaluationInfo</code>, <code>RDD[(Query, ActualResult)]</code>. <code>TrainingData</code> is the same class we use for deploy, <code>RDD[(Query, ActualResult)]</code> is the validation set, <code>EvaluationInfo</code> can be used to hold some global evaluation data ; it is not used in the current example.</p><p>Lines 11 to 41 is the logic of reading and transforming data from the datastore; it is equvialent to the existing <code>readTraining</code> method. After line 41, the variable <code>labeledPoints</code> contains the complete dataset with which we use to generate the (training, validation) sequence.</p><p>Lines 43 to 57 is the <em>k-fold</em> logic. Line 45 gives each data point a unique id, and we decide whether the point belongs to the training or validation set depends on the <em>mod</em> of the id (lines 48 to 49). For each point in the valida
tion set, we construct the <code>Query</code> and <code>ActualResult</code> (line 55) which is used validate the engine.</p><h2 id='evaluation-metrics' class='header-anchors'>Evaluation Metrics</h2><p>We define a <code>Metric</code> which gives a <em>score</em> to engine params. The higher the score, the better the engine params are. In this template, we use accuray score which measures the portion of correct prediction among all data points.</p><p>In MyClassification/src/main/scala/<strong>Evaluation.scala</strong>, the class <code>Accuracy</code> implements the <em>accuracy</em> score. It extends a base helper class <code>AverageMetric</code> which calculates the average score overall <em>(Query, PredictionResult, ActualResult)</em> tuple.</p><div class="highlight scala"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1
+2
+3
+4
+5</pre></td><td class="code"><pre><span class="k">case</span> <span class="k">class</span> <span class="nc">Accuracy</span>
+ <span class="k">extends</span> <span class="nc">AverageMetric</span><span class="o">[</span><span class="kt">EmptyEvaluationInfo</span>, <span class="kt">Query</span>, <span class="kt">PredictedResult</span>, <span class="kt">ActualResult</span><span class="o">]</span> <span class="o">{</span>
+ <span class="k">def</span> <span class="n">calculate</span><span class="o">(</span><span class="n">query</span><span class="k">:</span> <span class="kt">Query</span><span class="o">,</span> <span class="n">predicted</span><span class="k">:</span> <span class="kt">PredictedResult</span><span class="o">,</span> <span class="n">actual</span><span class="k">:</span> <span class="kt">ActualResult</span><span class="o">)</span>
+ <span class="k">:</span> <span class="kt">Double</span> <span class="o">=</span> <span class="o">(</span><span class="k">if</span> <span class="o">(</span><span class="n">predicted</span><span class="o">.</span><span class="n">label</span> <span class="o">==</span> <span class="n">actual</span><span class="o">.</span><span class="n">label</span><span class="o">)</span> <span class="mf">1.0</span> <span class="k">else</span> <span class="mf">0.0</span><span class="o">)</span>
+<span class="o">}</span>
+</pre></td></tr></tbody></table> </div> <p>Then, implement a <code>Evaluation</code> object to define the engine and metric used in this evaluation.</p><div class="highlight scala"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1
+2
+3</pre></td><td class="code"><pre><span class="k">object</span> <span class="nc">AccuracyEvaluation</span> <span class="k">extends</span> <span class="nc">Evaluation</span> <span class="o">{</span>
+ <span class="n">engineMetric</span> <span class="k">=</span> <span class="o">(</span><span class="nc">ClassificationEngine</span><span class="o">(),</span> <span class="k">new</span> <span class="nc">Accuracy</span><span class="o">())</span>
+<span class="o">}</span>
+</pre></td></tr></tbody></table> </div> <h2 id='parameters-generation' class='header-anchors'>Parameters Generation</h2><p>The last component is to specify the list of engine params we want to evaluate. In this guide, we discuss the simplest method. We specify an explicit list of engine params to be evaluated. </p><p>In MyClassification/src/main/scala/<strong>Evaluation.scala</strong>, the object <code>EngineParamsList</code> specifies the engine params list to be used.</p><div class="highlight scala"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1
+2
+3
+4
+5
+6
+7
+8
+9
+10
+11
+12
+13
+14
+15
+16
+17</pre></td><td class="code"><pre><span class="k">object</span> <span class="nc">EngineParamsList</span> <span class="k">extends</span> <span class="nc">EngineParamsGenerator</span> <span class="o">{</span>
+ <span class="c1">// Define list of EngineParams used in Evaluation
+</span>
+ <span class="c1">// First, we define the base engine params. It specifies the appId from which
+</span> <span class="c1">// the data is read, and a evalK parameter is used to define the
+</span> <span class="c1">// cross-validation.
+</span> <span class="k">private</span><span class="o">[</span><span class="kt">this</span><span class="o">]</span> <span class="k">val</span> <span class="n">baseEP</span> <span class="k">=</span> <span class="nc">EngineParams</span><span class="o">(</span>
+ <span class="n">dataSourceParams</span> <span class="k">=</span> <span class="nc">DataSourceParams</span><span class="o">(</span><span class="n">appId</span> <span class="k">=</span> <span class="mi">18</span><span class="o">,</span> <span class="n">evalK</span> <span class="k">=</span> <span class="nc">Some</span><span class="o">(</span><span class="mi">5</span><span class="o">)))</span>
+
+ <span class="c1">// Second, we specify the engine params list by explicitly listing all
+</span> <span class="c1">// algorithm parameters. In this case, we evaluate 3 engine params, each with
+</span> <span class="c1">// a different algorithm params value.
+</span> <span class="n">engineParamsList</span> <span class="k">=</span> <span class="nc">Seq</span><span class="o">(</span>
+ <span class="n">baseEP</span><span class="o">.</span><span class="n">copy</span><span class="o">(</span><span class="n">algorithmParamsList</span> <span class="k">=</span> <span class="nc">Seq</span><span class="o">((</span><span class="s">"naive"</span><span class="o">,</span> <span class="nc">AlgorithmParams</span><span class="o">(</span><span class="mf">10.0</span><span class="o">)))),</span>
+ <span class="n">baseEP</span><span class="o">.</span><span class="n">copy</span><span class="o">(</span><span class="n">algorithmParamsList</span> <span class="k">=</span> <span class="nc">Seq</span><span class="o">((</span><span class="s">"naive"</span><span class="o">,</span> <span class="nc">AlgorithmParams</span><span class="o">(</span><span class="mf">100.0</span><span class="o">)))),</span>
+ <span class="n">baseEP</span><span class="o">.</span><span class="n">copy</span><span class="o">(</span><span class="n">algorithmParamsList</span> <span class="k">=</span> <span class="nc">Seq</span><span class="o">((</span><span class="s">"naive"</span><span class="o">,</span> <span class="nc">AlgorithmParams</span><span class="o">(</span><span class="mf">1000.0</span><span class="o">)))))</span>
+<span class="o">}</span>
+</pre></td></tr></tbody></table> </div> <p>A good practise is to first define a base engine params, it contains the common parameters used in all evaluations (lines 7 to 8). With the base params, we construct the list of engine params we want to evaluation by adding or replacing the controller parameter. Lines 13 to 16 generate 3 engine parameters, each has a different smoothing parameters.</p><h2 id='running-the-evaluation' class='header-anchors'>Running the Evaluation</h2><p>It remains to run the evaluation. Let's recap the quick start section above. The <code>pio eval</code> command kick starts the evaluation, and the result can be seen from the console.</p><div class="highlight shell"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1
+2
+3
+4</pre></td><td class="code"><pre><span class="gp">$ </span>pio build
+...
+<span class="gp">$ </span>pio <span class="nb">eval </span>org.template.classification.AccuracyEvaluation <span class="se">\</span>
+ org.template.classification.EngineParamsList
+</pre></td></tr></tbody></table> </div> <p>You will see the following output:</p><div class="highlight shell"><table style="border-spacing: 0"><tbody><tr><td class="gutter gl" style="text-align: right"><pre class="lineno">1
+2
+3
+4
+5
+6
+7
+8
+9
+10
+11
+12
+13
+14
+15
+16
+17
+18
+19
+20
+21
+22
+23
+24
+25
+26
+27
+28
+29
+30
+31
+32
+33
+34
+35
+36
+37
+38
+39
+40
+41
+42
+43
+44
+45</pre></td><td class="code"><pre>...
+<span class="o">[</span>INFO] <span class="o">[</span>CoreWorkflow<span class="nv">$]</span> runEvaluation started
+...
+<span class="o">[</span>INFO] <span class="o">[</span>MetricEvaluator] Iteration 0
+<span class="o">[</span>INFO] <span class="o">[</span>MetricEvaluator] EngineParams: <span class="o">{</span><span class="s2">"dataSourceParams"</span>:<span class="o">{</span><span class="s2">""</span>:<span class="o">{</span><span class="s2">"appId"</span>:19,<span class="s2">"evalK"</span>:5<span class="o">}}</span>,<span class="s2">"preparatorParams"</span>:<span class="o">{</span><span class="s2">""</span>:<span class="o">{}}</span>,<span class="s2">"algorithmParamsList"</span>:[<span class="o">{</span><span class="s2">"naive"</span>:<span class="o">{</span><span class="s2">"lambda"</span>:10.0<span class="o">}}]</span>,<span class="s2">"servingParams"</span>:<span class="o">{</span><span class="s2">""</span>:<span class="o">{}}}</span>
+<span class="o">[</span>INFO] <span class="o">[</span>MetricEvaluator] Result: MetricScores<span class="o">(</span>0.9281045751633987,List<span class="o">())</span>
+<span class="o">[</span>INFO] <span class="o">[</span>MetricEvaluator] Iteration 1
+<span class="o">[</span>INFO] <span class="o">[</span>MetricEvaluator] EngineParams: <span class="o">{</span><span class="s2">"dataSourceParams"</span>:<span class="o">{</span><span class="s2">""</span>:<span class="o">{</span><span class="s2">"appId"</span>:19,<span class="s2">"evalK"</span>:5<span class="o">}}</span>,<span class="s2">"preparatorParams"</span>:<span class="o">{</span><span class="s2">""</span>:<span class="o">{}}</span>,<span class="s2">"algorithmParamsList"</span>:[<span class="o">{</span><span class="s2">"naive"</span>:<span class="o">{</span><span class="s2">"lambda"</span>:100.0<span class="o">}}]</span>,<span class="s2">"servingParams"</span>:<span class="o">{</span><span class="s2">""</span>:<span class="o">{}}}</span>
+<span class="o">[</span>INFO] <span class="o">[</span>MetricEvaluator] Result: MetricScores<span class="o">(</span>0.9150326797385621,List<span class="o">())</span>
+<span class="o">[</span>INFO] <span class="o">[</span>MetricEvaluator] Iteration 2
+<span class="o">[</span>INFO] <span class="o">[</span>MetricEvaluator] EngineParams: <span class="o">{</span><span class="s2">"dataSourceParams"</span>:<span class="o">{</span><span class="s2">""</span>:<span class="o">{</span><span class="s2">"appId"</span>:19,<span class="s2">"evalK"</span>:5<span class="o">}}</span>,<span class="s2">"preparatorParams"</span>:<span class="o">{</span><span class="s2">""</span>:<span class="o">{}}</span>,<span class="s2">"algorithmParamsList"</span>:[<span class="o">{</span><span class="s2">"naive"</span>:<span class="o">{</span><span class="s2">"lambda"</span>:1000.0<span class="o">}}]</span>,<span class="s2">"servingParams"</span>:<span class="o">{</span><span class="s2">""</span>:<span class="o">{}}}</span>
+<span class="o">[</span>INFO] <span class="o">[</span>MetricEvaluator] Result: MetricScores<span class="o">(</span>0.4444444444444444,List<span class="o">())</span>
+<span class="o">[</span>INFO] <span class="o">[</span>MetricEvaluator] Writing best variant params to disk...
+<span class="o">[</span>INFO] <span class="o">[</span>CoreWorkflow<span class="nv">$]</span> Updating evaluation instance with result: MetricEvaluatorResult:
+ <span class="c"># engine params evaluated: 3</span>
+Optimal Engine Params:
+ <span class="o">{</span>
+ <span class="s2">"dataSourceParams"</span>:<span class="o">{</span>
+ <span class="s2">""</span>:<span class="o">{</span>
+ <span class="s2">"appId"</span>:19,
+ <span class="s2">"evalK"</span>:5
+ <span class="o">}</span>
+ <span class="o">}</span>,
+ <span class="s2">"preparatorParams"</span>:<span class="o">{</span>
+ <span class="s2">""</span>:<span class="o">{</span>
+
+ <span class="o">}</span>
+ <span class="o">}</span>,
+ <span class="s2">"algorithmParamsList"</span>:[
+ <span class="o">{</span>
+ <span class="s2">"naive"</span>:<span class="o">{</span>
+ <span class="s2">"lambda"</span>:10.0
+ <span class="o">}</span>
+ <span class="o">}</span>
+ <span class="o">]</span>,
+ <span class="s2">"servingParams"</span>:<span class="o">{</span>
+ <span class="s2">""</span>:<span class="o">{</span>
+
+ <span class="o">}</span>
+ <span class="o">}</span>
+<span class="o">}</span>
+Metrics:
+ org.template.classification.Accuracy: 0.9281045751633987
+The best variant params can be found <span class="k">in </span>best.json
+<span class="o">[</span>INFO] <span class="o">[</span>CoreWorkflow<span class="nv">$]</span> runEvaluation completed
+</pre></td></tr></tbody></table> </div> <h2 id='notes' class='header-anchors'>Notes</h2> <ul> <li>We deliberately not metion <strong><em>test set</em></strong> in this hyperparameter tuning guide. In machine learning literature, the <strong><em>test set</em></strong> is a separate piece of data which is used to evaluate the final engine params outputted by the evaluation process. This guarantees that no information in the training / validation set is <em>leaked</em> into the engine params and yields a biased outcome. With PredictionIO, there are multiple ways of conducting robust tuning, we will cover this topic in the coming sections.</li> </ul> </div></div></div></div><footer><div class="container"><div class="seperator"></div><div class="row"><div class="col-md-4 col-md-push-8 col-xs-12"><div class="subscription-form-wrapper"><h4>Subscribe to our Newsletter</h4><form class="ajax-form" id="subscribe-form" method="POST" action="https://script.google.com/macros/s/AKfycbwhzeKCQJjQ52e
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