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Posted to commits@predictionio.apache.org by gi...@apache.org on 2018/09/20 19:08:30 UTC
[03/16] predictionio-site git commit: Documentation based on
apache/predictionio#6c607aa23f2ffaf70f5ba50bdc9bff11f5ebc345
http://git-wip-us.apache.org/repos/asf/predictionio-site/blob/9fe018b6/templates/productranking/quickstart/index.html
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diff --git a/templates/productranking/quickstart/index.html b/templates/productranking/quickstart/index.html
index 6d97cfe..c6924fe 100644
--- a/templates/productranking/quickstart/index.html
+++ b/templates/productranking/quickstart/index.html
@@ -32,7 +32,7 @@ Your system is all ready to go.
<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">$]</span> Finished listing 2 app<span class="o">(</span>s<span class="o">)</span>.
-</pre></td></tr></tbody></table> </div> <p><a href="#"></a></p> <h2 id='4.-collecting-data' class='header-anchors'>4. Collecting Data</h2><p>Next, let's collect some training data for the app of this Engine. By default, the Product Ranking Engine Template supports 2 types of entities: <strong>user</strong> and <strong>item</strong>, and event <strong>view</strong>. A user can view an item. This template requires '$set' user event, '$set' item event and user-view-item events.</p> <p>You can send these events to PredictionIO Event Server in real-time easily by making a HTTP request or through the provided SDK. Please see <a href="/appintegration/">App Integration Overview</a> for more details how to integrate your app with SDK.</p><p>Let's try sending events to EventServer with the following <code>curl</code> commands (The corresponding SDK code is showed in other tabs).</p><p>Replace <code><ACCCESS_KEY></code> by the Access Key generated in above steps.
Note that <code>localhost:7070</code> is the default URL of the Event Server.</p><p>For convenience, set your access key to the shell variable, run:</p><p><code>$ ACCESS_KEY=<ACCESS_KEY></code></p> <p><a href="#"></a></p> <p>For example, when a new user with id "u0" is created in your app 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 <code>$set</code> event for this user. To send this event, run the following <code>curl</code> command:</p><div class="tabs"> <ul class="control"> <li data-lang="json"><a href="#tab-4c1ffc0e-a65a-482e-8434-891f254db660">REST API</a></li> <li data-lang="python"><a href="#tab-089201ba-5d33-458d-8c82-b5f3eb1e404c">Python SDK</a></li> <li data-lang="php"><a href="#tab-e2ef4c0c-95d3-4ed3-89a2-0abae5017a40">PHP SDK</a></li> <li data-lang="ruby"><a href="#tab-d6b8ed68-cb24-4a55-be69-eaed1deee57f">Ruby SDK</a></li> <li data-lang="java"><a href="#tab-64d78c9a-079d-4de9
-8035-e80ad709dd3e">Java SDK</a></li> </ul> <div data-tab="REST API" data-lang="json" id="tab-4c1ffc0e-a65a-482e-8434-891f254db660"> <div class="highlight shell"> <table style="border-spacing: 0"><tbody><tr> <td class="gutter gl" style="text-align: right"><pre class="lineno">1
+</pre></td></tr></tbody></table> </div> <p><a href="#"></a></p> <h2 id='4.-collecting-data' class='header-anchors'>4. Collecting Data</h2><p>Next, let's collect some training data for the app of this Engine. By default, the Product Ranking Engine Template supports 2 types of entities: <strong>user</strong> and <strong>item</strong>, and event <strong>view</strong>. A user can view an item. This template requires '$set' user event, '$set' item event and user-view-item events.</p> <p>You can send these events to PredictionIO Event Server in real-time easily by making a HTTP request or through the provided SDK. Please see <a href="/appintegration/">App Integration Overview</a> for more details how to integrate your app with SDK.</p><p>Let's try sending events to EventServer with the following <code>curl</code> commands (The corresponding SDK code is showed in other tabs).</p><p>Replace <code><ACCCESS_KEY></code> by the Access Key generated in above steps.
Note that <code>localhost:7070</code> is the default URL of the Event Server.</p><p>For convenience, set your access key to the shell variable, run:</p><p><code>$ ACCESS_KEY=<ACCESS_KEY></code></p> <p><a href="#"></a></p> <p>For example, when a new user with id "u0" is created in your app 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 <code>$set</code> event for this 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-2bb82c5f-5151-465d-9722-5016f073897b">REST API</a></li> <li data-lang="python"><a href="#tab-003c26cf-5e2d-4559-8d30-2ca40fc007e4">Python SDK</a></li> <li data-lang="php"><a href="#tab-e0bb0a6d-de10-45ee-a74c-f51be724982c">PHP SDK</a></li> <li data-lang="ruby"><a href="#tab-2b43116f-0cbe-4f97-a800-d2917715a817">Ruby SDK</a></li> <li data-lang="java"><a href="#tab-b958944b-91ec-45d7
-b3bd-da02f4f6bec6">Java SDK</a></li> </ul> <div data-tab="REST API" data-lang="json" id="tab-2bb82c5f-5151-465d-9722-5016f073897b"> <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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@@ -47,7 +47,7 @@ Your system is all ready to go.
"entityId" : "u0",
"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-089201ba-5d33-458d-8c82-b5f3eb1e404c"> <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> </tr></tbody></table> </div> </div> <div data-tab="Python SDK" data-lang="python" id="tab-003c26cf-5e2d-4559-8d30-2ca40fc007e4"> <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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@@ -78,7 +78,7 @@ Your system is all ready to go.
<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_ID</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-e2ef4c0c-95d3-4ed3-89a2-0abae5017a40"> <div class="highlight php"> <table style="border-spacing: 0"><tbody><tr> <td class="gutter gl" style="text-align: right"><pre class="lineno">1
+</pre></td> </tr></tbody></table> </div> </div> <div data-tab="PHP SDK" data-lang="php" id="tab-e0bb0a6d-de10-45ee-a74c-f51be724982c"> <div class="highlight php"> <table style="border-spacing: 0"><tbody><tr> <td class="gutter gl" style="text-align: right"><pre class="lineno">1
2
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@@ -103,7 +103,7 @@ Your system is all ready to go.
<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="cp">?></span>
-</pre></td> </tr></tbody></table> </div> </div> <div data-tab="Ruby SDK" data-lang="ruby" id="tab-d6b8ed68-cb24-4a55-be69-eaed1deee57f"> <div class="highlight ruby"> <table style="border-spacing: 0"><tbody><tr> <td class="gutter gl" style="text-align: right"><pre class="lineno">1
+</pre></td> </tr></tbody></table> </div> </div> <div data-tab="Ruby SDK" data-lang="ruby" id="tab-2b43116f-0cbe-4f97-a800-d2917715a817"> <div class="highlight ruby"> <table style="border-spacing: 0"><tbody><tr> <td class="gutter gl" style="text-align: right"><pre class="lineno">1
2
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@@ -120,7 +120,7 @@ Your system is all ready to go.
<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>
-</pre></td> </tr></tbody></table> </div> </div> <div data-tab="Java SDK" data-lang="java" id="tab-64d78c9a-079d-4de9-8035-e80ad709dd3e"> <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> </tr></tbody></table> </div> </div> <div data-tab="Java SDK" data-lang="java" id="tab-b958944b-91ec-45d7-b3bd-da02f4f6bec6"> <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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@@ -145,7 +145,7 @@ Your system is all ready to go.
<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="n">client</span><span class="o">.</span><span class="na">createEvent</span><span class="o">(</span><span class="n">userEvent</span><span class="o">);</span>
-</pre></td> </tr></tbody></table> </div> </div> </div> <p>When a new item "i0" is created in your app 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 <code>$set</code> event for the item. Run the following <code>curl</code> command:</p><div class="tabs"> <ul class="control"> <li data-lang="json"><a href="#tab-0b9829e1-cbe8-47e7-abe5-7a199adc658b">REST API</a></li> <li data-lang="python"><a href="#tab-cf24fdc0-898a-4b0f-ac6f-e175dd590439">Python SDK</a></li> <li data-lang="php"><a href="#tab-7110b2a4-2be5-4d35-94fb-eb71278ea0a7">PHP SDK</a></li> <li data-lang="ruby"><a href="#tab-3862ede1-a99b-451f-ba55-b51bc29899a0">Ruby SDK</a></li> <li data-lang="java"><a href="#tab-26c462a0-35d3-409f-bbf1-2f5735650158">Java SDK</a></li> </ul> <div data-tab="REST API" data-lang="json" id="tab-0b9829e1-cbe8-47e7-abe5-7a199adc658b"> <div class="highlight shell"> <table style="border-spacing: 0"><tbody><tr> <td cla
ss="gutter gl" style="text-align: right"><pre class="lineno">1
+</pre></td> </tr></tbody></table> </div> </div> </div> <p>When a new item "i0" is created in your app 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 <code>$set</code> event for the item. Run the following <code>curl</code> command:</p><div class="tabs"> <ul class="control"> <li data-lang="json"><a href="#tab-ce99a60b-e560-4ff7-b320-8320c68d1ef0">REST API</a></li> <li data-lang="python"><a href="#tab-82fba617-7af8-433d-b2e8-39e0896de3fb">Python SDK</a></li> <li data-lang="php"><a href="#tab-d97b59b0-b770-4f07-84db-89e97c3786c5">PHP SDK</a></li> <li data-lang="ruby"><a href="#tab-058ea976-b6df-4fe4-a5a1-6d6a71a4e118">Ruby SDK</a></li> <li data-lang="java"><a href="#tab-ac205d09-8dcf-4ec3-bd00-8e0ba2e13590">Java SDK</a></li> </ul> <div data-tab="REST API" data-lang="json" id="tab-ce99a60b-e560-4ff7-b320-8320c68d1ef0"> <div class="highlight shell"> <table style="border-spacing: 0"><tbody><tr> <td cla
ss="gutter gl" style="text-align: right"><pre class="lineno">1
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@@ -160,7 +160,7 @@ Your system is all ready to go.
"entityId" : "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-cf24fdc0-898a-4b0f-ac6f-e175dd590439"> <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> </tr></tbody></table> </div> </div> <div data-tab="Python SDK" data-lang="python" id="tab-82fba617-7af8-433d-b2e8-39e0896de3fb"> <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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@@ -173,7 +173,7 @@ Your system is all ready to go.
<span class="n">entity_type</span><span class="o">=</span><span class="s">"item"</span><span class="p">,</span>
<span class="n">entity_id</span><span class="o">=<</span><span class="n">ITEM_ID</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-7110b2a4-2be5-4d35-94fb-eb71278ea0a7"> <div class="highlight php"> <table style="border-spacing: 0"><tbody><tr> <td class="gutter gl" style="text-align: right"><pre class="lineno">1
+</pre></td> </tr></tbody></table> </div> </div> <div data-tab="PHP SDK" data-lang="php" id="tab-d97b59b0-b770-4f07-84db-89e97c3786c5"> <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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@@ -190,7 +190,7 @@ Your system is all ready to go.
<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-3862ede1-a99b-451f-ba55-b51bc29899a0"> <div class="highlight ruby"> <table style="border-spacing: 0"><tbody><tr> <td class="gutter gl" style="text-align: right"><pre class="lineno">1
+</pre></td> </tr></tbody></table> </div> </div> <div data-tab="Ruby SDK" data-lang="ruby" id="tab-058ea976-b6df-4fe4-a5a1-6d6a71a4e118"> <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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@@ -203,7 +203,7 @@ Your system is all ready to go.
<span class="o"><</span><span class="no">ITEM</span> <span class="no">ID</span><span class="o">></span>
<span class="p">)</span>
-</pre></td> </tr></tbody></table> </div> </div> <div data-tab="Java SDK" data-lang="java" id="tab-26c462a0-35d3-409f-bbf1-2f5735650158"> <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> </tr></tbody></table> </div> </div> <div data-tab="Java SDK" data-lang="java" id="tab-ac205d09-8dcf-4ec3-bd00-8e0ba2e13590"> <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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@@ -214,7 +214,7 @@ Your system is all ready to go.
<span class="o">.</span><span class="na">entityType</span><span class="o">(</span><span class="s">"item"</span><span class="o">)</span>
<span class="o">.</span><span class="na">entityId</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">itemEvent</span><span class="o">)</span>
-</pre></td> </tr></tbody></table> </div> </div> </div> <p>When the user "u0" view item "i0" on time <code>2014-11-10T12:34:56.123-08:00</code> (current time will be used if eventTime is not specified), you can send a view event. Run the following <code>curl</code> command:</p><div class="tabs"> <ul class="control"> <li data-lang="json"><a href="#tab-b3b22b1f-d83b-4584-8303-a404d92f91fd">REST API</a></li> <li data-lang="python"><a href="#tab-f0c87f47-f3c4-49e8-8910-a010a992dbdf">Python SDK</a></li> <li data-lang="php"><a href="#tab-93b7e5ed-ea83-4686-9032-d3c68eff6f7e">PHP SDK</a></li> <li data-lang="ruby"><a href="#tab-4d29ccc1-c9ed-4425-a807-2756a0b25cb4">Ruby SDK</a></li> <li data-lang="java"><a href="#tab-141a88f8-2428-4a50-bc48-33463e493774">Java SDK</a></li> </ul> <div data-tab="REST API" data-lang="json" id="tab-b3b22b1f-d83b-4584-8303-a404d92f91fd"> <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> </tr></tbody></table> </div> </div> </div> <p>When the user "u0" view item "i0" on time <code>2014-11-10T12:34:56.123-08:00</code> (current time will be used if eventTime is not specified), you can send a view event. Run the following <code>curl</code> command:</p><div class="tabs"> <ul class="control"> <li data-lang="json"><a href="#tab-78a2d46c-907a-4d38-b093-c105949d9cc5">REST API</a></li> <li data-lang="python"><a href="#tab-2c3ec4d5-78c5-47a1-a7b6-9aaa058522a5">Python SDK</a></li> <li data-lang="php"><a href="#tab-700f4c35-1170-40d9-9baf-434f62a5e04d">PHP SDK</a></li> <li data-lang="ruby"><a href="#tab-1aebdfa8-cfc5-4627-ae12-5719ef0c8cc6">Ruby SDK</a></li> <li data-lang="java"><a href="#tab-8e940c62-6b7e-45bd-b12c-0171bdbf41e4">Java SDK</a></li> </ul> <div data-tab="REST API" data-lang="json" id="tab-78a2d46c-907a-4d38-b093-c105949d9cc5"> <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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@@ -233,7 +233,7 @@ Your system is all ready to go.
"targetEntityId" : "i0",
"eventTime" : "2014-11-10T12:34:56.123-08:00"
}'</span>
-</pre></td> </tr></tbody></table> </div> </div> <div data-tab="Python SDK" data-lang="python" id="tab-f0c87f47-f3c4-49e8-8910-a010a992dbdf"> <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> </tr></tbody></table> </div> </div> <div data-tab="Python SDK" data-lang="python" id="tab-2c3ec4d5-78c5-47a1-a7b6-9aaa058522a5"> <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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@@ -250,7 +250,7 @@ Your system is all ready to go.
<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>
-</pre></td> </tr></tbody></table> </div> </div> <div data-tab="PHP SDK" data-lang="php" id="tab-93b7e5ed-ea83-4686-9032-d3c68eff6f7e"> <div class="highlight php"> <table style="border-spacing: 0"><tbody><tr> <td class="gutter gl" style="text-align: right"><pre class="lineno">1
+</pre></td> </tr></tbody></table> </div> </div> <div data-tab="PHP SDK" data-lang="php" id="tab-700f4c35-1170-40d9-9baf-434f62a5e04d"> <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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@@ -269,7 +269,7 @@ Your system is all ready to go.
<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="cp">?></span>
-</pre></td> </tr></tbody></table> </div> </div> <div data-tab="Ruby SDK" data-lang="ruby" id="tab-4d29ccc1-c9ed-4425-a807-2756a0b25cb4"> <div class="highlight ruby"> <table style="border-spacing: 0"><tbody><tr> <td class="gutter gl" style="text-align: right"><pre class="lineno">1
+</pre></td> </tr></tbody></table> </div> </div> <div data-tab="Ruby SDK" data-lang="ruby" id="tab-1aebdfa8-cfc5-4627-ae12-5719ef0c8cc6"> <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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@@ -286,7 +286,7 @@ Your system is all ready to go.
<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>
-</pre></td> </tr></tbody></table> </div> </div> <div data-tab="Java SDK" data-lang="java" id="tab-141a88f8-2428-4a50-bc48-33463e493774"> <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> </tr></tbody></table> </div> </div> <div data-tab="Java SDK" data-lang="java" id="tab-8e940c62-6b7e-45bd-b12c-0171bdbf41e4"> <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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@@ -344,14 +344,14 @@ User u10 views item i7
</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 retrieve predicted results. To rank items with IDs "i1", "i3", "i10", "i2", "i5", "i31", "i9" for user "u2". You send this JSON <code>{ "user": "u2", "items": ["i1", "i3", "i10", "i2", "i5", "i31", "i9"] }</code> to the deployed engine and it will return a JSON of the ranked items. Simply send a query by making a HTTP request or through the <code>EngineCl
ient</code> of an SDK.</p><p>With the deployed engine running, open another terminal 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-47d490aa-146a-4663-a5ce-656b36ebca04">REST API</a></li> <li data-lang="python"><a href="#tab-9dd2f54e-8f7d-4168-971d-62270b6e2ad0">Python SDK</a></li> <li data-lang="php"><a href="#tab-3cc211d0-1fdc-4a9f-ad73-e853dc77b67e">PHP SDK</a></li> <li data-lang="ruby"><a href="#tab-999bf93c-90de-43c4-bb22-a6e2408e081e">Ruby SDK</a></li> <li data-lang="java"><a href="#tab-faa847f6-6d49-4d16-abe1-d3d377ea61e9">Java SDK</a></li> </ul> <div data-tab="REST API" data-lang="json" id="tab-47d490aa-146a-4663-a5ce-656b36ebca04"> <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></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 retrieve predicted results. To rank items with IDs "i1", "i3", "i10", "i2", "i5", "i31", "i9" for user "u2". You send this JSON <code>{ "user": "u2", "items": ["i1", "i3", "i10", "i2", "i5", "i31", "i9"] }</code> to the deployed engine and it will return a JSON of the ranked items. Simply send a query by making a HTTP request or through the <code>EngineCl
ient</code> of an SDK.</p><p>With the deployed engine running, open another terminal 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-967ff989-f440-4108-94b1-5eb7f8c1af9a">REST API</a></li> <li data-lang="python"><a href="#tab-3fdceca5-3645-46f2-9bb3-28c11fe8dbe1">Python SDK</a></li> <li data-lang="php"><a href="#tab-b74462d2-81de-4a87-9da3-d9e6ff704357">PHP SDK</a></li> <li data-lang="ruby"><a href="#tab-93504f25-577b-4887-8e0a-319f692260b2">Ruby SDK</a></li> <li data-lang="java"><a href="#tab-59a355fe-d73f-4fa0-885c-29d7b6d66f24">Java SDK</a></li> </ul> <div data-tab="REST API" data-lang="json" id="tab-967ff989-f440-4108-94b1-5eb7f8c1af9a"> <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>curl -H <span class="s2">"Content-Type: application/json"</span> <span class="se">\</span>
-d <span class="s1">'{ "user": "u2", "items": ["i1", "i3", "i10", "i2", "i5", "i31", "i9"]}'</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-9dd2f54e-8f7d-4168-971d-62270b6e2ad0"> <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> </tr></tbody></table> </div> </div> <div data-tab="Python SDK" data-lang="python" id="tab-3fdceca5-3645-46f2-9bb3-28c11fe8dbe1"> <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
@@ -362,7 +362,7 @@ http://localhost:8000/queries.json
<span class="s">"user"</span><span class="p">:</span> <span class="s">"u2"</span><span class="p">,</span>
<span class="s">"items"</span><span class="p">:</span> <span class="p">[</span><span class="s">"i1"</span><span class="p">,</span> <span class="s">"i3"</span><span class="p">,</span> <span class="s">"i10"</span><span class="p">,</span> <span class="s">"i2"</span><span class="p">,</span> <span class="s">"i5"</span><span class="p">,</span> <span class="s">"i31"</span><span class="p">,</span> <span class="s">"i9"</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-3cc211d0-1fdc-4a9f-ad73-e853dc77b67e"> <div class="highlight php"> <table style="border-spacing: 0"><tbody><tr> <td class="gutter gl" style="text-align: right"><pre class="lineno">1
+</pre></td> </tr></tbody></table> </div> </div> <div data-tab="PHP SDK" data-lang="php" id="tab-b74462d2-81de-4a87-9da3-d9e6ff704357"> <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
@@ -385,7 +385,7 @@ http://localhost:8000/queries.json
<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-999bf93c-90de-43c4-bb22-a6e2408e081e"> <div class="highlight ruby"> <table style="border-spacing: 0"><tbody><tr> <td class="gutter gl" style="text-align: right"><pre class="lineno">1
+</pre></td> </tr></tbody></table> </div> </div> <div data-tab="Ruby SDK" data-lang="ruby" id="tab-93504f25-577b-4887-8e0a-319f692260b2"> <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
@@ -402,7 +402,7 @@ http://localhost:8000/queries.json
<span class="s1">'items'</span> <span class="o">=></span> <span class="p">[</span><span class="s1">'i1'</span><span class="p">,</span> <span class="s1">'i3'</span><span class="p">,</span> <span class="s1">'i10'</span><span class="p">,</span> <span class="s1">'i2'</span><span class="p">,</span> <span class="s1">'i5'</span><span class="p">,</span> <span class="s1">'i31'</span><span class="p">,</span> <span class="s1">'i9'</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-faa847f6-6d49-4d16-abe1-d3d377ea61e9"> <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> </tr></tbody></table> </div> </div> <div data-tab="Java SDK" data-lang="java" id="tab-59a355fe-d73f-4fa0-885c-29d7b6d66f24"> <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
http://git-wip-us.apache.org/repos/asf/predictionio-site/blob/9fe018b6/templates/recommendation/batch-evaluator/index.html
----------------------------------------------------------------------
diff --git a/templates/recommendation/batch-evaluator/index.html b/templates/recommendation/batch-evaluator/index.html
index 566ae62..6f905ba 100644
--- a/templates/recommendation/batch-evaluator/index.html
+++ b/templates/recommendation/batch-evaluator/index.html
@@ -1,4 +1,4 @@
-<!DOCTYPE html><html><head><title>Batch Persistable Evaluator (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="Batch Persistable Evaluator (Recommendation)"/><link rel="canonical" href="https://predictionio.apache.org/templates/recommendation/batch-evaluator/"/><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/html
5shiv.min.js"></script><script src="//cdn.mathjax.org/mathjax/latest/MathJax.js?config=TeX-AMS-MML_HTMLorMML"></script><script src="//use.typekit.net/pqo0itb.js"></script><script>try{Typekit.load({ async: true });}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://predictionio.apache.org/"><img alt="Apache PredictionIO" id="logo" src="/images/logos/logo-ee2b9bb3.png"/></a><span>®</span></div><div id="menu-wrapper"><div id="pill-wrapper"><a class="pill left" href="/gallery/template-gallery">TEMPLATES</a> <a class="pill right" href="//github.com/apache/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 c
lass="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>Batch Persistable Evaluator (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® Documentation</span></a><ul><li class="level-2"><a class="final" href="/"><span>Welcome to Apache PredictionIO®</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</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" hr
ef="#"><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="/batchpredict/"><span>Batch Prediction
s</span></a></li><li class="level-2"><a class="final" href="/deploy/monitoring/"><span>Monitoring Engine</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><li class="level-2"><a class="final" href="/deploy/plugin/"><span>Engine Server Plugin</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="/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><li class="level-2"><a class="final" href="/datacollection/plugin/"><span>Event Server Plugin</span></a
></li></ul></li><li class="level-1"><a class="expandible" href="#"><span>Choosing an Algorithm</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>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>PredictionIO® Official Templates</span></a><ul><li class="level-2"><a class="final" href="/templates/"><span>Intro</span></a></li><li class="level-2"><a class="expandible" href="#"><span>Recommendation</span></a><ul><li class="level-3"><a class="final" href="/templates/recommendation/quickstart/"><span>Quick Start</span></a></li><li class="level-3"><a class="final" href="/templates/recommendatio
n/dase/"><span>DASE</span></a></li><li class="level-3"><a class="final" href="/templates/recommendation/evaluation/"><span>Evaluation Explained</span></a></li><li class="level-3"><a class="final" href="/templates/recommendation/how-to/"><span>How-To</span></a></li><li class="level-3"><a class="final" href="/templates/recommendation/reading-custom-events/"><span>Read Custom Events</span></a></li><li class="level-3"><a class="final" href="/templates/recommendation/customize-data-prep/"><span>Customize Data Preparator</span></a></li><li class="level-3"><a class="final" href="/templates/recommendation/customize-serving/"><span>Customize Serving</span></a></li><li class="level-3"><a class="final" href="/templates/recommendation/training-with-implicit-preference/"><span>Train with Implicit Preference</span></a></li><li class="level-3"><a class="final" href="/templates/recommendation/blacklist-items/"><span>Filter Recommended Items by Blacklist in Query</span></a></li><li class="level-3"><
a class="final active" href="/templates/recommendation/batch-evaluator/"><span>Batch Persistable Evaluator</span></a></li></ul></li><li class="level-2"><a class="expandible" href="#"><span>E-Commerce Recommendation</span></a><ul><li class="level-3"><a class="final" href="/templates/ecommercerecommendation/quickstart/"><span>Quick Start</span></a></li><li class="level-3"><a class="final" href="/templates/ecommercerecommendation/dase/"><span>DASE</span></a></li><li class="level-3"><a class="final" href="/templates/ecommercerecommendation/how-to/"><span>How-To</span></a></li><li class="level-3"><a class="final" href="/templates/ecommercerecommendation/train-with-rate-event/"><span>Train with Rate Event</span></a></li><li class="level-3"><a class="final" href="/templates/ecommercerecommendation/adjust-score/"><span>Adjust Score</span></a></li></ul></li><li class="level-2"><a class="expandible" href="#"><span>Similar Product</span></a><ul><li class="level-3"><a class="final" href="/templ
ates/similarproduct/quickstart/"><span>Quick Start</span></a></li><li class="level-3"><a class="final" href="/templates/similarproduct/dase/"><span>DASE</span></a></li><li class="level-3"><a class="final" href="/templates/similarproduct/how-to/"><span>How-To</span></a></li><li class="level-3"><a class="final" href="/templates/similarproduct/multi-events-multi-algos/"><span>Multiple Events and Multiple Algorithms</span></a></li><li class="level-3"><a class="final" href="/templates/similarproduct/return-item-properties/"><span>Returns Item Properties</span></a></li><li class="level-3"><a class="final" href="/templates/similarproduct/train-with-rate-event/"><span>Train with Rate Event</span></a></li><li class="level-3"><a class="final" href="/templates/similarproduct/rid-user-set-event/"><span>Get Rid of Events for Users</span></a></li><li class="level-3"><a class="final" href="/templates/similarproduct/recommended-user/"><span>Recommend Users</span></a></li></ul></li><li class="level-
2"><a class="expandible" href="#"><span>Classification</span></a><ul><li class="level-3"><a class="final" href="/templates/classification/quickstart/"><span>Quick Start</span></a></li><li class="level-3"><a class="final" href="/templates/classification/dase/"><span>DASE</span></a></li><li class="level-3"><a class="final" href="/templates/classification/how-to/"><span>How-To</span></a></li><li class="level-3"><a class="final" href="/templates/classification/add-algorithm/"><span>Use Alternative Algorithm</span></a></li><li class="level-3"><a class="final" href="/templates/classification/reading-custom-properties/"><span>Read Custom Properties</span></a></li></ul></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="/gallery/template-gallery/"><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 Web
hook</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>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="/cli/"><span>Command-line Interface</span></a></li><li class="level-2"><a class="final" href="/resources/release/"><span>Release Cadence</span></a></li><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></l
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li><span class="last">Batch Persistable Evaluator</span></li></ul></div><div id="page-title"><h1>Batch Persistable Evaluator (Recommendation)</h1></div></div><div id="table-of-content-wrapper"><h5>On this page</h5><aside id="table-of-contents"><ul> <li> <a href="#1-modify-datasource">1. Modify DataSource</a> </li> <li> <a href="#2-add-a-new-evaluator">2. Add a new Evaluator</a> </li> <li> <a href="#3-define-evaluation-and-engineparamsgenerator-object">3. Define Evaluation and EngineParamsGenerator object</a> </li> <li> <a href="#4-build-and-run">4. build and run</a> </li> </ul> </aside><hr/><a id="edit-page-link" href="https://github.com/apache/predictionio/tree/livedoc/docs/manual/source/templates/recommendation/batch-evaluator.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="#">PredictionIO® Official Templates</a><span class="spacer
">></span></li><li><a href="#">Recommendation</a><span class="spacer">></span></li><li><span class="last">Batch Persistable Evaluator</span></li></ul></div><div id="page-title"><h1>Batch Persistable Evaluator (Recommendation)</h1></div></div><div class="content"> <p>This how-to tutorial would explain how you can also use <code>$pio eval</code> to persist predicted result for a batch of queries. Please read the <a href="/templates/recommendation/evaluation/">Evaluation</a> to understand the usage of DataSoure's <code>readEval()</code> and the Evaluation component first.</p><div class="alert-message warning"><p>This tutorial is based on some experimental and developer features, which may be changed in future release.</p></div><div class="alert-message note"><p>This tutorial is based on Recommendation template version v0.3.2</p></div><h2 id='1.-modify-datasource' class='header-anchors'>1. Modify DataSource</h2><p>Modify DataSource's <code>readEval()</code> to generate the
batch Queries which you want to run batch 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
+<!DOCTYPE html><html><head><title>Batch Persistable Evaluator (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="Batch Persistable Evaluator (Recommendation)"/><link rel="canonical" href="https://predictionio.apache.org/templates/recommendation/batch-evaluator/"/><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/html
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ates/similarproduct/quickstart/"><span>Quick Start</span></a></li><li class="level-3"><a class="final" href="/templates/similarproduct/dase/"><span>DASE</span></a></li><li class="level-3"><a class="final" href="/templates/similarproduct/how-to/"><span>How-To</span></a></li><li class="level-3"><a class="final" href="/templates/similarproduct/multi-events-multi-algos/"><span>Multiple Events and Multiple Algorithms</span></a></li><li class="level-3"><a class="final" href="/templates/similarproduct/return-item-properties/"><span>Returns Item Properties</span></a></li><li class="level-3"><a class="final" href="/templates/similarproduct/train-with-rate-event/"><span>Train with Rate Event</span></a></li><li class="level-3"><a class="final" href="/templates/similarproduct/rid-user-set-event/"><span>Get Rid of Events for Users</span></a></li><li class="level-3"><a class="final" href="/templates/similarproduct/recommended-user/"><span>Recommend Users</span></a></li></ul></li><li class="level-
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/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 Web
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i></ul></li><li class="level-1"><a class="expandible" href="#"><span>Apache Software Foundation</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="#">PredictionIO® Official Templates</a><span class="spacer">></span></li><li><a href="#">Recommendation</a><span class="spacer">></span></li><
li><span class="last">Batch Persistable Evaluator</span></li></ul></div><div id="page-title"><h1>Batch Persistable Evaluator (Recommendation)</h1></div></div><div id="table-of-content-wrapper"><h5>On this page</h5><aside id="table-of-contents"><ul> <li> <a href="#1-modify-datasource">1. Modify DataSource</a> </li> <li> <a href="#2-add-a-new-evaluator">2. Add a new Evaluator</a> </li> <li> <a href="#3-define-evaluation-and-engineparamsgenerator-object">3. Define Evaluation and EngineParamsGenerator object</a> </li> <li> <a href="#4-build-and-run">4. build and run</a> </li> </ul> </aside><hr/><a id="edit-page-link" href="https://github.com/apache/predictionio/tree/livedoc/docs/manual/source/templates/recommendation/batch-evaluator.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="#">PredictionIO® Official Templates</a><span class="spacer
">></span></li><li><a href="#">Recommendation</a><span class="spacer">></span></li><li><span class="last">Batch Persistable Evaluator</span></li></ul></div><div id="page-title"><h1>Batch Persistable Evaluator (Recommendation)</h1></div></div><div class="content"> <p>This how-to tutorial would explain how you can also use <code>$pio eval</code> to persist predicted result for a batch of queries. Please read the <a href="/templates/recommendation/evaluation/">Evaluation</a> to understand the usage of DataSource's <code>readEval()</code> and the Evaluation component first.</p><div class="alert-message warning"><p>This tutorial is based on some experimental and developer features, which may be changed in future release.</p></div><div class="alert-message note"><p>This tutorial is based on Recommendation template version v0.3.2</p></div><h2 id='1.-modify-datasource' class='header-anchors'>1. Modify DataSource</h2><p>Modify DataSource's <code>readEval()</code> to generate th
e batch Queries which you want to run batch 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
2
3
4
http://git-wip-us.apache.org/repos/asf/predictionio-site/blob/9fe018b6/templates/recommendation/dase/index.html
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diff --git a/templates/recommendation/dase/index.html b/templates/recommendation/dase/index.html
index eb6cddf..e802c20 100644
--- a/templates/recommendation/dase/index.html
+++ b/templates/recommendation/dase/index.html
@@ -313,7 +313,7 @@ val itemStringIntMap <span class="o">=</span> BiMap.stringInt<span class="o">(</
<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="k">extends</span> <span class="nc">Params</span>
-</pre></td></tr></tbody></table> </div> <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.train</code> then returns a <code>MatrixFactorizationModel</code> model which contains RDD data. RDD is a distributed collection of items which <em>does not</em> persist. To store the model, you convert the model to <code>ALSModel</code> class at the end. <code>ALSModel</code> is a persistable class that extends <code>MatrixFactorizationModel</code>.</p> <blockquote> <p>The detailed implementation can be found at MyRecommendation/src/main/scala/<strong><em>ALSModel.scala</em></strong></p></blockquote> <p>PredictionIO will automatically store th
e returned model, i.e. <code>ALSModel</code> in this case.</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": "1", "num": 4 }</code> to the <code>Query</code> class you defined previously.</p><p>The predictive model <code>MatrixFactorizationModel</code> of MLlib ALS, which is now extended as <code>ALSModel</code>, offers a method called <code>recommendProducts</code>. <code>recommendProducts</code> takes two parameters: user id (i.e. the <code>Int</code> index of <code>query.user</code>) and the number of items to be returned (i.e. <code>query.num</code>). It predicts the top <em>num</em> of items a user will like.</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></tr></tbody></table> </div> <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 results. 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.train</code> then returns a <code>MatrixFactorizationModel</code> model which contains RDD data. RDD is a distributed collection of items which <em>does not</em> persist. To store the model, you convert the model to <code>ALSModel</code> class at the end. <code>ALSModel</code> is a persistable class that extends <code>MatrixFactorizationModel</code>.</p> <blockquote> <p>The detailed implementation can be found at MyRecommendation/src/main/scala/<strong><em>ALSModel.scala</em></strong></p></blockquote> <p>PredictionIO will automatically store th
e returned model, i.e. <code>ALSModel</code> in this case.</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": "1", "num": 4 }</code> to the <code>Query</code> class you defined previously.</p><p>The predictive model <code>MatrixFactorizationModel</code> of MLlib ALS, which is now extended as <code>ALSModel</code>, offers a method called <code>recommendProducts</code>. <code>recommendProducts</code> takes two parameters: user id (i.e. the <code>Int</code> index of <code>query.user</code>) and the number of items to be returned (i.e. <code>query.num</code>). It predicts the top <em>num</em> of items a user will like.</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
http://git-wip-us.apache.org/repos/asf/predictionio-site/blob/9fe018b6/templates/recommendation/evaluation/index.html
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@@ -111,7 +111,7 @@ Metrics:
PositiveCount <span class="o">(</span><span class="nv">threshold</span><span class="o">=</span>1.0<span class="o">)</span>: 10.006666666666666
<span class="o">[</span>INFO 2015-03-31 00:36:01,516] <span class="o">[</span>CoreWorkflow<span class="nv">$]</span> runEvaluation completed
-</pre></td></tr></tbody></table> </div> <p>The console prints out the evaluation meric score of each engine params, and finally pretty print the optimal engine params. Amongs the 3 engine params we evaluate, the best Prediction@k has a score of ~0.1521.</p><h2 id='the-evaluation-design' class='header-anchors'>The Evaluation Design</h2><p>We assume you have read the <a href="/evaluation">Tuning and Evaluation</a> section. We will cover the evaluation aspects which are specific to the recommendation engine.</p><p>In recommendation evaluation, the raw data is a sequence of known ratings. A rating has 3 components: user, item, and a score. We use the $k-fold$ method for evaluation, the raw data is sliced into a sequence of (training, validation) data tuple.</p><p>In the validation data, we construct a query for <em>each user</em>, and get a list of recommended items from the engine. It is vastly different from the classification tutorial, where there is a one-to-one corresponding betwee
n the training data point and the validation data point. In this evaluation, our unit of evaluation is <em>user</em>, we evaluate the quality of an engine using the known rating of a user.</p><h3 id='key-assumptions' class='header-anchors'>Key assumptions</h3><p>There are multiple assumptions we have to make when we evaluate a recommendation engine:</p> <ul> <li><p>Definition of 'good'. We want to quantify if the engine is able to recommend items which the user likes, we need to define what is meant by 'good'. In this examle, we have two kinds of events: 'rate' and 'buy'. The 'rate' event is associated with a rating value which ranges between 1 to 4, and the 'buy' event is mapped to a rating of 4. When we implement the metric, we have to specify a rating threshold, only the rating above the threshold is considered 'good'.</p></li> <li><p>The absence of complete rating. It is extremely unlikely that the training data contains ra
ting for all user-item tuples. In contrast, of a system containing 1000 items, a user may only have rated 20 of them, leaving 980 items unrated. There is no way for us to certainly tell if the user likes an unrated product. When we examine the evaluation result, it is important for us to keep in mind that the final metric is only an approximation of the actual result.</p></li> <li><p>Recommendation affects user behavior. Suppose you are a e-commerce company and would like to use the recommendation engine to personalize the landing page, the item you show in the langing page directly impacts what the user is going to purchase. This is different from weather prediction, whatever the weather forecast engine predicts, tomorrow's weather won't be affected. Therefore, when we conduct offline evaluation for recommendation engines, it is possible that the final user behavior is dramatically different from the evaluation result. However, in the evaluation, for simplicity, we have to
assume that user behavior is homogenous.</p></li> </ul> <h2 id='evaluation-data-generation' class='header-anchors'>Evaluation Data Generation</h2><h3 id='actual-result' class='header-anchors'>Actual Result</h3><p>In MyRecommendation/src/main/scala/<strong><em>Engine.scala</em></strong>, we define the <code>ActualResult</code> which represents the user rating for validation. It stores the list of ratings in the validation set for a user.</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></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, the best Prediction@k has a score of ~0.1521.</p><h2 id='the-evaluation-design' class='header-anchors'>The Evaluation Design</h2><p>We assume you have read the <a href="/evaluation">Tuning and Evaluation</a> section. We will cover the evaluation aspects which are specific to the recommendation engine.</p><p>In recommendation evaluation, the raw data is a sequence of known ratings. A rating has 3 components: user, item, and a score. We use the $k-fold$ method for evaluation, the raw data is sliced into a sequence of (training, validation) data tuple.</p><p>In the validation data, we construct a query for <em>each user</em>, and get a list of recommended items from the engine. It is vastly different from the classification tutorial, where there is a one-to-one corresponding betw
een the training data point and the validation data point. In this evaluation, our unit of evaluation is <em>user</em>, we evaluate the quality of an engine using the known rating of a user.</p><h3 id='key-assumptions' class='header-anchors'>Key assumptions</h3><p>There are multiple assumptions we have to make when we evaluate a recommendation engine:</p> <ul> <li><p>Definition of 'good'. We want to quantify if the engine is able to recommend items which the user likes, we need to define what is meant by 'good'. In this example, we have two kinds of events: 'rate' and 'buy'. The 'rate' event is associated with a rating value which ranges between 1 to 4, and the 'buy' event is mapped to a rating of 4. When we implement the metric, we have to specify a rating threshold, only the rating above the threshold is considered 'good'.</p></li> <li><p>The absence of complete rating. It is extremely unlikely that the training data contains
rating for all user-item tuples. In contrast, of a system containing 1000 items, a user may only have rated 20 of them, leaving 980 items unrated. There is no way for us to certainly tell if the user likes an unrated product. When we examine the evaluation result, it is important for us to keep in mind that the final metric is only an approximation of the actual result.</p></li> <li><p>Recommendation affects user behavior. Suppose you are a e-commerce company and would like to use the recommendation engine to personalize the landing page, the item you show in the landing page directly impacts what the user is going to purchase. This is different from weather prediction, whatever the weather forecast engine predicts, tomorrow's weather won't be affected. Therefore, when we conduct offline evaluation for recommendation engines, it is possible that the final user behavior is dramatically different from the evaluation result. However, in the evaluation, for simplicity, we have
to assume that user behavior is homogenous.</p></li> </ul> <h2 id='evaluation-data-generation' class='header-anchors'>Evaluation Data Generation</h2><h3 id='actual-result' class='header-anchors'>Actual Result</h3><p>In MyRecommendation/src/main/scala/<strong><em>Engine.scala</em></strong>, we define the <code>ActualResult</code> which represents the user rating for validation. It stores the list of ratings in the validation set for a user.</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">ActualResult</span><span class="o">(</span>
<span class="n">ratings</span><span class="k">:</span> <span class="kt">Array</span><span class="o">[</span><span class="kt">Rating</span><span class="o">]</span>