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-<!DOCTYPE html><html><head><title>Batch Predictions</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="Batch Predictions"/><link rel="canonical" href="https://predictionio.apache.org/batchpredict/"/><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-eccfc6cb.css" rel="stylesheet" type="text/css"/><script src="//cdnjs.cloudflare.com/ajax/libs/html5shiv/3.7.2/html5shiv.min.js"></script><script src="//cdn.mathjax.org/mathjax/latest/MathJax.js?co
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 -md hidden-lg" id="mobile-page-heading-wrapper"><p>PredictionIO Docs</p><h4>Batch Predictions</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"><n
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 <aside id="table-of-contents"><ul> <li> <a href="#overview">Overview</a> </li> <li> <a href="#compatibility">Compatibility</a> </li> <li> <a href="#usage">Usage</a> </li> <li> <a href="#example">Example</a> </li> </ul> </aside><hr/><a id="edit-page-link" href="https://github.com/apache/incubator-predictionio/tree/livedoc/docs/manual/source/batchpredict/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">&gt;</span></li><li><span class="last">Batch Predictions</span></li></ul></div><div id="page-title"><h1>Batch Predictions</h1></div></div><div class="content"> <h2 id='overview' class='header-anchors'>Overview</h2><p>Process predictions for many queries using efficient parallelization through Spark. Useful for mass auditing of predictions and for generating predictions to push into other
  systems.</p><p>Batch predict reads and writes multi-object JSON files similar to the <a href="/datacollection/batchimport/">batch import</a> format. JSON objects are separated by newlines and cannot themselves contain unencoded newlines.</p><h2 id='compatibility' class='header-anchors'>Compatibility</h2><p><code>pio batchpredict</code> loads the engine and processes queries exactly like <code>pio deploy</code>. There is only one additional requirement for engines to utilize batch predict:</p><div class="alert-message warning"><p>All algorithm classes used in the engine must be <a href="https://www.scala-lang.org/api/2.11.8/index.html#scala.Serializable">serializable</a>. <strong>This is already true for PredictionIO&#39;s base algorithm classes</strong>, but may be broken by including non-serializable fields in their constructor. Using the <a href="http://fdahms.com/2015/10/14/scala-and-the-transient-lazy-val-pattern/"><code>@transient</code> annotation</a> may help in these cases.
 </p></div><p>This requirement is due to processing the input queries as a <a href="https://spark.apache.org/docs/latest/rdd-programming-guide.html#resilient-distributed-datasets-rdds">Spark RDD</a> which enables high-performance parallelization, even on a single machine.</p><h2 id='usage' class='header-anchors'>Usage</h2><h3 id='<code>pio-batchpredict</code>' class='header-anchors' ><code>pio batchpredict</code></h3><p>Command to process bulk predictions. Takes the same options as <code>pio deploy</code> plus:</p><h3 id='<code>--input-&lt;value&gt;</code>' class='header-anchors' ><code>--input &lt;value&gt;</code></h3><p>Path to file containing queries; a multi-object JSON file with one query object per line. Accepts any valid Hadoop file URL.</p><p>Default: <code>batchpredict-input.json</code></p><h3 id='<code>--output-&lt;value&gt;</code>' class='header-anchors' ><code>--output &lt;value&gt;</code></h3><p>Path to file to receive results; a multi-object JSON file with one object pe
 r line, the prediction + original query. Accepts any valid Hadoop file URL. Actual output will be written as Hadoop partition files in a directory with the output name.</p><p>Default: <code>batchpredict-output.json</code></p><h3 id='<code>--query-partitions-&lt;value&gt;</code>' class='header-anchors' ><code>--query-partitions &lt;value&gt;</code></h3><p>Configure the concurrency of predictions by setting the number of partitions used internally for the RDD of queries. This will directly effect the number of resulting <code>part-*</code> output files. While setting to <code>1</code> may seem appealing to get a single output file, this will remove parallelization for the batch process, reducing performance and possibly exhausting memory.</p><p>Default: number created by Spark context&#39;s <code>textFile</code> (probably the number of cores available on the local machine)</p><h3 id='<code>--engine-instance-id-&lt;value&gt;</code>' class='header-anchors' ><code>--engine-instance-id &l
 t;value&gt;</code></h3><p>Identifier for the trained instance to use for batch predict.</p><p>Default: the latest trained instance.</p><h2 id='example' class='header-anchors'>Example</h2><h3 id='input' class='header-anchors'>Input</h3><p>A multi-object JSON file of queries as they would be sent to the engine&#39;s HTTP Queries API.</p><div class="alert-message note"><p>Read via <a href="https://spark.apache.org/docs/latest/rdd-programming-guide.html#external-datasets">SparkContext&#39;s <code>textFile</code></a> and so may be a single file or any supported Hadoop format.</p></div><p>File: <code>batchpredict-input.json</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
+<!DOCTYPE html><html><head><title>Batch Predictions</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="Batch Predictions"/><link rel="canonical" href="https://predictionio.apache.org/batchpredict/"/><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-eccfc6cb.css" rel="stylesheet" type="text/css"/><script src="//cdnjs.cloudflare.com/ajax/libs/html5shiv/3.7.2/html5shiv.min.js"></script><script src="//cdn.mathjax.org/mathjax/latest/MathJax.js?co
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 on</span></a><ul><li class="level-2"><a class="final" href="https://www.apache.org/"><span>Apache Homepage</span></a></li><li class="level-2"><a class="final" href="https://www.apache.org/licenses/"><span>License</span></a></li><li class="level-2"><a class="final" href="https://www.apache.org/foundation/sponsorship.html"><span>Sponsorship</span></a></li><li class="level-2"><a class="final" href="https://www.apache.org/foundation/thanks.html"><span>Thanks</span></a></li><li class="level-2"><a class="final" href="https://www.apache.org/security/"><span>Security</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">&gt;</span></li><li><span class="last">Batch Predictions</span></li></ul></div><div id="page-title"><h1>Batch Predictions</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="#compatibility">Compatibility</a> </li> <li> <a href="#usage">Usage</a> </li> <li> <a href="#example">Example</a> </li> </ul> </aside><hr/><a id="edit-page-link" href="https://github.com/apache/incubator-predictionio/tree/livedoc/docs/manual/source/batchpredict/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">&gt;</span></li><li><span class="last">Batch Predictions</span></li></ul></div><div id="page-title"><h1>Batch Predictions</h1></div></div><div class="content"> <h2 id='overview' class='header-anchors'>Overview</h2><p>Process predictions for many queries using efficient parallelization through Spark. Useful for mass auditing of predictions and for generating predictions to push into other 
 systems.</p><p>Batch predict reads and writes multi-object JSON files similar to the <a href="/datacollection/batchimport/">batch import</a> format. JSON objects are separated by newlines and cannot themselves contain unencoded newlines.</p><h2 id='compatibility' class='header-anchors'>Compatibility</h2><p><code>pio batchpredict</code> loads the engine and processes queries exactly like <code>pio deploy</code>. There is only one additional requirement for engines to utilize batch predict:</p><div class="alert-message warning"><p>All algorithm classes used in the engine must be <a href="https://www.scala-lang.org/api/2.11.8/index.html#scala.Serializable">serializable</a>. <strong>This is already true for PredictionIO&#39;s base algorithm classes</strong>, but may be broken by including non-serializable fields in their constructor. Using the <a href="http://fdahms.com/2015/10/14/scala-and-the-transient-lazy-val-pattern/"><code>@transient</code> annotation</a> may help in these cases.<
 /p></div><p>This requirement is due to processing the input queries as a <a href="https://spark.apache.org/docs/latest/rdd-programming-guide.html#resilient-distributed-datasets-rdds">Spark RDD</a> which enables high-performance parallelization, even on a single machine.</p><h2 id='usage' class='header-anchors'>Usage</h2><h3 id='<code>pio-batchpredict</code>' class='header-anchors' ><code>pio batchpredict</code></h3><p>Command to process bulk predictions. Takes the same options as <code>pio deploy</code> plus:</p><h3 id='<code>--input-&lt;value&gt;</code>' class='header-anchors' ><code>--input &lt;value&gt;</code></h3><p>Path to file containing queries; a multi-object JSON file with one query object per line. Accepts any valid Hadoop file URL.</p><p>Default: <code>batchpredict-input.json</code></p><h3 id='<code>--output-&lt;value&gt;</code>' class='header-anchors' ><code>--output &lt;value&gt;</code></h3><p>Path to file to receive results; a multi-object JSON file with one object per
  line, the prediction + original query. Accepts any valid Hadoop file URL. Actual output will be written as Hadoop partition files in a directory with the output name.</p><p>Default: <code>batchpredict-output.json</code></p><h3 id='<code>--query-partitions-&lt;value&gt;</code>' class='header-anchors' ><code>--query-partitions &lt;value&gt;</code></h3><p>Configure the concurrency of predictions by setting the number of partitions used internally for the RDD of queries. This will directly effect the number of resulting <code>part-*</code> output files. While setting to <code>1</code> may seem appealing to get a single output file, this will remove parallelization for the batch process, reducing performance and possibly exhausting memory.</p><p>Default: number created by Spark context&#39;s <code>textFile</code> (probably the number of cores available on the local machine)</p><h3 id='<code>--engine-instance-id-&lt;value&gt;</code>' class='header-anchors' ><code>--engine-instance-id &lt
 ;value&gt;</code></h3><p>Identifier for the trained instance to use for batch predict.</p><p>Default: the latest trained instance.</p><h2 id='example' class='header-anchors'>Example</h2><h3 id='input' class='header-anchors'>Input</h3><p>A multi-object JSON file of queries as they would be sent to the engine&#39;s HTTP Queries API.</p><div class="alert-message note"><p>Read via <a href="https://spark.apache.org/docs/latest/rdd-programming-guide.html#external-datasets">SparkContext&#39;s <code>textFile</code></a> and so may be a single file or any supported Hadoop format.</p></div><p>File: <code>batchpredict-input.json</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
@@ -21,7 +21,7 @@
 2</pre></td><td class="code"><pre><span class="p">{</span><span class="s2">"query"</span><span class="p">:{</span><span class="s2">"user"</span><span class="p">:</span><span class="s2">"2"</span><span class="p">},</span><span class="s2">"prediction"</span><span class="p">:{</span><span class="s2">"itemScores"</span><span class="p">:[{</span><span class="s2">"item"</span><span class="p">:</span><span class="s2">"5"</span><span class="p">,</span><span class="s2">"score"</span><span class="p">:</span><span class="mi">55</span><span class="p">},{</span><span class="s2">"item"</span><span class="p">:</span><span class="s2">"3"</span><span class="p">,</span><span class="s2">"score"</span><span class="p">:</span><span class="mi">28</span><span class="p">}]}}</span><span class="w">
 </span><span class="p">{</span><span class="s2">"query"</span><span class="p">:{</span><span class="s2">"user"</span><span class="p">:</span><span class="s2">"5"</span><span class="p">},</span><span class="s2">"prediction"</span><span class="p">:{</span><span class="s2">"itemScores"</span><span class="p">:[{</span><span class="s2">"item"</span><span class="p">:</span><span class="s2">"1"</span><span class="p">,</span><span class="s2">"score"</span><span class="p">:</span><span class="mi">24</span><span class="p">},{</span><span class="s2">"item"</span><span class="p">:</span><span class="s2">"4"</span><span class="p">,</span><span class="s2">"score"</span><span class="p">:</span><span class="mi">14</span><span class="p">}]}}</span><span class="w">
 </span></pre></td></tr></tbody></table> </div> <h3 id='post-processing-results' class='header-anchors'>Post-processing Results</h3><p>After the process exits successfully, the parts may be concatenated into a single output file using a command 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</pre></td><td class="code"><pre>cat batchpredict-output.json/part-<span class="k">*</span> &gt; batchpredict-output-all.json
-</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-6 footer-link-column"><div class="footer-link-column-row"><h4>Community</h4><ul><li><a href="//predictionio.apache.org/install/" target="blank">Download</a></li><li><a href="//predictionio.apache.org/" target="blank">Docs</a></li><li><a href="//github.com/apache/incubator-predictionio" target="blank">GitHub</a></li><li><a href="mailto:user-subscribe@predictionio.apache.org" target="blank">Subscribe to User Mailing List</a></li><li><a href="//stackoverflow.com/questions/tagged/predictionio" target="blank">Stackoverflow</a></li></ul></div></div><div class="col-md-6 footer-link-column"><div class="footer-link-column-row"><h4>Contribute</h4><ul><li><a href="//predictionio.apache.org/community/contribute-code/" target="blank">Contribute</a></li><li><a href="//github.com/apache/incubator-predictionio" target="blank">Source Code</a>
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