http://git-wip-us.apache.org/repos/asf/incubator-predictionio-site/blob/0bdbf8fe/templates/recommendation/customize-data-prep/index.html ---------------------------------------------------------------------- diff --git a/templates/recommendation/customize-data-prep/index.html b/templates/recommendation/customize-data-prep/index.html new file mode 100644 index 0000000..219e7be --- /dev/null +++ b/templates/recommendation/customize-data-prep/index.html @@ -0,0 +1,143 @@ +<!DOCTYPE html><html><head><title>Customizing Data Preparator (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="Customizing Data Preparator (Recommendation)"/><link rel="canonical" href="https://docs.prediction.io/templates/recommendation/customize-data-prep/"/><link href="/images/favicon/normal-b330020a.png" rel="shortcut 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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>Customizing Data Preparator (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-data-preparator-component">The Data Preparator Component</a > </li> <li> <a href="#modify-the-preparator">Modify the Preparator</a> </li> > <li> <a href="#deploy-the-modified-engine">Deploy the Modified Engine</a> > </li> <li> <a href="#adding-preparator-parameters">Adding Preparator > Parameters</a> </li> </ul> </aside><hr/><a id="edit-page-link" > href="https://github.com/apache/incubator-predictionio/tree/livedoc/docs/manual/source/templates/recommendation/customize-data-prep.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>Customizing Data Preparator > (Recommendation)</h1></div></div><div class="content"><p>Data Preparator is > where pre-processing actions occurs. For example, one may want to remove > some very popular items from the training data because she thinks that these > items may not help finding individual person's tastes or one may have a > black list of item that she wants to remove from the training data before > feeding it to the al gorithm.</p><p>This section assumes that you have created a <em>MyRecommendation</em> engine based on the <a href="/templates/recommendation/quickstart/">Recommendation Engine Template: QuickStart</a>. We will demonstrate how to add a filtering logic to exclude a list of items in the training data.</p><p>A sample black list file containing the items to be excluded is provided in <code>./data/sample_not_train_data.txt</code>.</p><p>A full end-to-end example can be found on <a href="https://github.com/apache/incubator-predictionio/tree/develop/examples/scala-parallel-recommendation/custom-prepartor";>GitHub</a>.</p><h2 id='the-data-preparator-component' class='header-anchors'>The Data Preparator Component</h2><p>Recall <a href="/start/engines/">the DASE Architecture</a>, data is prepared by 2 components sequentially: <em>Data Source</em> and <em>Data Preparator</em>. <em>Data Source</em> reads data from the data store of Event Server and then <em>Data Preparator</em> prepares <code>RDD [Rating]</code> for the ALS algorithm.</p><p>You may modify any component in an engine template to fit your needs. This example shows you how to add the filtering logics in Data Preparator.</p><h2 id='modify-the-preparator' class='header-anchors'>Modify the Preparator</h2><p>The Data Preparator component can be found in <code>src/main/scala/Preparator.scala</code> in the "MyRecommendation" directory. The unmodified version looks like 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">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> +</pre></td></tr></tbody></table> </div> <p>The <code>prepare</code> method simply passes the ratings from <code>TrainingData</code> to <code>PreparedData</code>.</p><p>You can modify the <code>prepare</code> method to read a black list of items from a file and remove them from <code>TrainingData</code>, so it becomes:</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">scala.io.Source</span> <span class="c1">// ADDED +</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="c1">// MODIFIED HERE +</span> <span class="k">val</span> <span class="n">noTrainItems</span> <span class="k">=</span> <span class="nc">Source</span><span class="o">.</span><span class="n">fromFile</span><span class="o">(</span><span class="s">"./data/sample_not_train_data.txt"</span><span class="o">)</span> + <span class="o">.</span><span class="n">getLines</span><span class="o">.</span><span class="n">toSet</span> + <span class="c1">// exclude noTrainItems from original trainingData +</span> <span class="k">val</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="n">filter</span><span class="o">(</span> <span class="n">r</span> <span class="k">=></span> + <span class="o">!</span><span class="n">noTrainItems</span><span class="o">.</span><span class="n">contains</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="k">new</span> <span class="nc">PreparedData</span><span class="o">(</span><span class="n">ratings</span><span class="o">)</span> + <span class="o">}</span> +<span class="o">}</span> +</pre></td></tr></tbody></table> </div> <blockquote> <p>We will show you how not to hardcode the path <code>./data/sample_not_train_data.txt</code> soon.</p></blockquote> <h2 id='deploy-the-modified-engine' class='header-anchors'>Deploy the Modified Engine</h2><p>Now you can deploy the modified engine as described in <a href="/templates/recommendation/quickstart/">Quick Start</a>.</p><p>Make sure the <code>appName</code> defined in the file <code>engine.json</code> matches your <em>App Name</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 +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">"YourAppName"</span> + <span class="o">}</span> +<span class="o">}</span>, +... +</pre></td></tr></tbody></table> </div> <p>To build <em>MyRecommendation</em> and deploy it as a service:</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> <p>This will deploy an engine that binds to <a href="http://localhost:8000";>http://localhost:8000</a>. You can visit that page in your web browser to check its status.</p><p>Now, You can try to retrieve predicted results. To recommend 4 movies to user whose ID is 1, send this JSON <code>{ "user": "1", "num": 4 }</code> 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">'{ "user": "1", "num": 4 }'</span> http://localhost:8000/queries.json +</pre></td></tr></tbody></table> </div> <p>and it will return a JSON of recommended movies.</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">"itemScores"</span><span class="p">:</span><span class="w"> </span><span class="p">[</span><span class="w"> + </span><span class="p">{</span><span class="s2">"item"</span><span class="p">:</span><span class="w"> </span><span class="s2">"22"</span><span class="p">,</span><span class="w"> </span><span class="s2">"score"</span><span class="p">:</span><span class="w"> </span><span class="mf">4.072304374729956</span><span class="p">},</span><span class="w"> + </span><span class="p">{</span><span class="s2">"item"</span><span class="p">:</span><span class="w"> </span><span class="s2">"62"</span><span class="p">,</span><span class="w"> </span><span class="s2">"score"</span><span class="p">:</span><span class="w"> </span><span class="mf">4.058482414005789</span><span class="p">},</span><span class="w"> + </span><span class="p">{</span><span class="s2">"item"</span><span class="p">:</span><span class="w"> </span><span class="s2">"75"</span><span class="p">,</span><span class="w"> </span><span class="s2">"score"</span><span class="p">:</span><span class="w"> </span><span class="mf">4.046063009943821</span><span class="p">},</span><span class="w"> + </span><span class="p">{</span><span class="s2">"item"</span><span class="p">:</span><span class="w"> </span><span class="s2">"68"</span><span class="p">,</span><span class="w"> </span><span class="s2">"score"</span><span class="p">:</span><span class="w"> </span><span class="mf">3.8153661512945325</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>Congratulations! You have learned how to add customized logic to your Data Preparator!</p><h2 id='adding-preparator-parameters' class='header-anchors'>Adding Preparator Parameters</h2><p>Optionally, you may want to take the hardcoded path (<code>./data/sample_not_train_data.txt</code>) away from the source code.</p><p>PredictionIO offers <code>PreparatorParams</code> so you can read variable values from <code>engine.json</code> instead.</p><p>Modify <code>src/main/scala/Preparator.scala</code> again in the <em>MyRecommendation</em> directory 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">import</span> <span class="nn">org.apache.predictionio.controller.Params</span> <span class="c1">// ADDED +</span> + <span class="c1">// ADDED CustomPreparatorParams case class +</span><span class="k">case</span> <span class="k">class</span> <span class="nc">CustomPreparatorParams</span><span class="o">(</span> + <span class="n">filepath</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">Preparator</span><span class="o">(</span><span class="n">pp</span><span class="k">:</span> <span class="kt">CustomPreparatorParams</span><span class="o">)</span> <span class="c1">// ADDED CustomPreparatorParams +</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">val</span> <span class="n">noTrainItems</span> <span class="k">=</span> <span class="nc">Source</span><span class="o">.</span><span class="n">fromFile</span><span class="o">(</span><span class="n">pp</span><span class="o">.</span><span class="n">filepath</span><span class="o">).</span><span class="n">getLines</span><span class="o">.</span><span class="n">toSet</span> <span class="c1">//CHANGED +</span> <span class="k">val</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="n">filter</span><span class="o">(</span> <span class="n">r</span> <span class="k">=></span> + <span class="o">!</span><span class="n">noTrainItems</span><span class="o">.</span><span class="n">contains</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="k">new</span> <span class="nc">PreparedData</span><span class="o">(</span><span class="n">ratings</span><span class="o">)</span> + <span class="o">}</span> +<span class="o">}</span> + +</pre></td></tr></tbody></table> </div> <p>In <code>engine.json</code>, you define the parameters <code>filepath</code> for the Data Preparator:</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="err">...</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">"filepath"</span><span class="p">:</span><span class="w"> </span><span class="s2">"./data/sample_not_train_data.txt"</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="err">}</span><span class="w"> +</span></pre></td></tr></tbody></table> </div> <p>Try to build <em>MyRecommendation</em> and deploy it 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 +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> <p>You can change the 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http://git-wip-us.apache.org/repos/asf/incubator-predictionio-site/blob/0bdbf8fe/templates/recommendation/customize-data-prep/index.html.gz ---------------------------------------------------------------------- diff --git a/templates/recommendation/customize-data-prep/index.html.gz b/templates/recommendation/customize-data-prep/index.html.gz new file mode 100644 index 0000000..7594122 Binary files /dev/null and b/templates/recommendation/customize-data-prep/index.html.gz differ http://git-wip-us.apache.org/repos/asf/incubator-predictionio-site/blob/0bdbf8fe/templates/recommendation/customize-serving/index.html ---------------------------------------------------------------------- diff --git a/templates/recommendation/customize-serving/index.html b/templates/recommendation/customize-serving/index.html new file mode 100644 index 0000000..07b38b4 --- /dev/null +++ b/templates/recommendation/customize-serving/index.html @@ -0,0 +1,173 @@ +<!DOCTYPE html><html><head><title>Customizing 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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 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/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></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" hre f="/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="/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/"><s pan>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>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>Customizing Serving Component (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-serving-component">The Serving Component</a> </li> <l i> <a href="#modify-the-serving-interface">Modify the Serving Interface</a> </li> <li> <a href="#deploy-the-modified-engine">Deploy the Modified Engine</a> </li> <li> <a href="#adding-serving-parameters">Adding Serving Parameters</a> </li> </ul> </aside><hr/><a id="edit-page-link" href="https://github.com/apache/incubator-predictionio/tree/livedoc/docs/manual/source/templates/recommendation/customize-serving.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>Customizing Serving Component (Recommendation)</h1></div></div><div class="content"><p>Serving component is where post-processing occurs. For example, if you are recommending items to users, you may want to remove items that are not currently in stock from the list of recommendation.</p><p>This section is based on the <a href="/templates/recommendation/quickstart/">Recommendation Engine Template</a>.</p><p>A full end-to-end example can be found on <a href="https://github.com/apache/incubator-predictionio/tree/develop/examples/scala-parallel-recommendation/custom-serving";>GitHub</a>.</p> <h2 id='the-serving-component' class='header-anchors'>The Serving Component</h2><p>Recall <a href="/start/engines/">the DASE Architecture</a>, a PredictionIO engine has 4 main components: Data Source, Data Preparator, Algorithm, and Serving components. When a Query comes in, it is passed to the Algorithm component for making Predictions.</p><p>The Engine's serving component can be found in <code>src/main/scala/Serving.scala</code> in the <em>MyRecommendation</em> directory. By default, it looks like 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</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>We will customize the Serving component to remove temporarily disabled items from the Prediction made by Algorithms.</p><h2 id='modify-the-serving-interface' class='header-anchors'>Modify the Serving Interface</h2><p>We will use a file to specify a list of disabled items. When the <code>serve</code> method is called, it loads the file and removes items in the disabled list from <code>PredictedResult</code>. The following code snippet illustrates the logic:</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">scala.io.Source</span> <span class="c1">// ADDED +</span> +<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="c1">// Read the disabled item from file. +</span> <span class="k">val</span> <span class="n">disabledProducts</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="nc">Source</span> + <span class="o">.</span><span class="n">fromFile</span><span class="o">(</span><span class="s">"./data/sample_disabled_items.txt"</span><span class="o">)</span> + <span class="o">.</span><span class="n">getLines</span> + <span class="o">.</span><span class="n">toSet</span> + + <span class="k">val</span> <span class="n">itemScores</span> <span class="k">=</span> <span class="n">predictedResults</span><span class="o">.</span><span class="n">head</span><span class="o">.</span><span class="n">itemScores</span> + <span class="c1">// Remove items from the original predictedResult +</span> <span class="nc">PredictedResult</span><span class="o">(</span><span class="n">itemScores</span><span class="o">.</span><span class="n">filter</span><span class="o">(</span><span class="n">ps</span> <span class="k">=></span> <span class="o">!</span><span class="n">disabledProducts</span><span class="o">(</span><span class="n">ps</span><span class="o">.</span><span class="n">item</span><span class="o">)))</span> + <span class="o">}</span> +<span class="o">}</span> +</pre></td></tr></tbody></table> </div> <div class="alert-message info"><p>We will show you how not to hardcode the path <code>./data/sample_disabled_items.txt</code> soon.</p></div><div class="alert-message warning"><p>This example code uses a local relative path. For remote deployment, it is recommended to use a globally accessible absolute path.</p></div><div class="alert-message danger"><p>This example is only for demonstration purpose. Reading from disk for every query leads to terrible system performance. Use a more efficient implementation for production deployment.</p></div><h2 id='deploy-the-modified-engine' class='header-anchors'>Deploy the Modified Engine</h2><p>Now you can deploy the modified engine as described in the <a href="/templates/recommendation/quickstart/">Quick Start</a> guide.</p><p>Make sure the <code>appId</code> defined in the file <code>engine.json</code> match your <em>App ID</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 +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">"appId"</span>: 1 + <span class="o">}</span> +<span class="o">}</span>, +... +</pre></td></tr></tbody></table> </div> <p>To build <em>MyRecommendation</em> and deploy it as a service:</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> <p>This will deploy an engine that binds to <a href="http://localhost:8000";>http://localhost:8000</a>. You can visit that page in your web browser to check its status.</p><p>Now, you can try to retrieve predicted results. To recommend 4 movies to user whose ID is 1, send this JSON <code>{ "user": "1", "num": 4 }</code> 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 +2</pre></td><td class="code"><pre><span class="gp">$ </span>curl -H <span class="s2">"Content-Type: application/json"</span> -d <span class="s1">'{ "user": "1", "num": 4 }'</span> <span class="se">\</span> + http://localhost:8000/queries.json +</pre></td></tr></tbody></table> </div> <p>and it will return a JSON of recommended movies.</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">"itemScores"</span><span class="p">:</span><span class="w"> </span><span class="p">[</span><span class="w"> + </span><span class="p">{</span><span class="s2">"item"</span><span class="p">:</span><span class="w"> </span><span class="s2">"65"</span><span class="p">,</span><span class="w"> </span><span class="s2">"score"</span><span class="p">:</span><span class="w"> </span><span class="mf">6.537168137254073</span><span class="p">},</span><span class="w"> + </span><span class="p">{</span><span class="s2">"item"</span><span class="p">:</span><span class="w"> </span><span class="s2">"69"</span><span class="p">,</span><span class="w"> </span><span class="s2">"score"</span><span class="p">:</span><span class="w"> </span><span class="mf">6.391430405762495</span><span class="p">},</span><span class="w"> + </span><span class="p">{</span><span class="s2">"item"</span><span class="p">:</span><span class="w"> </span><span class="s2">"38"</span><span class="p">,</span><span class="w"> </span><span class="s2">"score"</span><span class="p">:</span><span class="w"> </span><span class="mf">5.829957095096519</span><span class="p">},</span><span class="w"> + </span><span class="p">{</span><span class="s2">"item"</span><span class="p">:</span><span class="w"> </span><span class="s2">"11"</span><span class="p">,</span><span class="w"> </span><span class="s2">"score"</span><span class="p">:</span><span class="w"> </span><span class="mf">5.5991291456974</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>Now, to verify the blacklisting logic, we add the item 69 (the second item) to the blacklisting file <code>data/sample_disabled_items.txt</code>. Rerun the <code>curl</code> query, and the change should take effect immediately as the disabled item list is reloaded every time the <code>serve</code> method is called.</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">echo</span> <span class="s2">"69"</span> >> ./data/sample_disabled_items.txt +<span class="gp">$ </span>curl -H <span class="s2">"Content-Type: application/json"</span> -d <span class="s1">'{ "user": "1", "num": 4 }'</span> <span class="se">\</span> + http://localhost:8000/queries.json +</pre></td></tr></tbody></table> </div> <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">"itemScores"</span><span class="p">:</span><span class="w"> </span><span class="p">[</span><span class="w"> + </span><span class="p">{</span><span class="s2">"item"</span><span class="p">:</span><span class="w"> </span><span class="s2">"65"</span><span class="p">,</span><span class="w"> </span><span class="s2">"score"</span><span class="p">:</span><span class="w"> </span><span class="mf">6.537168137254073</span><span class="p">},</span><span class="w"> + </span><span class="p">{</span><span class="s2">"item"</span><span class="p">:</span><span class="w"> </span><span class="s2">"38"</span><span class="p">,</span><span class="w"> </span><span class="s2">"score"</span><span class="p">:</span><span class="w"> </span><span class="mf">5.829957095096519</span><span class="p">},</span><span class="w"> + </span><span class="p">{</span><span class="s2">"item"</span><span class="p">:</span><span class="w"> </span><span class="s2">"11"</span><span class="p">,</span><span class="w"> </span><span class="s2">"score"</span><span class="p">:</span><span class="w"> </span><span class="mf">5.5991291456974</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>Congratulations! You have learned how to add customized realtime blacklisting logic to your Serving component!</p><h2 id='adding-serving-parameters' class='header-anchors'>Adding Serving Parameters</h2><p>Optionally, you may want to take the hardcoded path (<code>./data/sample_disabled_items.txt</code>) away from the source code.</p><p>PredictionIO offers <code>ServingParams</code> so you can read variable values from <code>engine.json</code> instead. PredictionIO transforms the JSON object specified in <code>engine.json</code>'s <code>serving</code> field into the <code>ServingParams</code> class.</p><p>Modify <code>src/main/scala/Serving.scala</code> again in the <em>MyRecommendation</em> directory 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 +20 +21 +22</pre></td><td class="code"><pre><span class="k">import</span> <span class="nn">scala.io.Source</span> + +<span class="k">import</span> <span class="nn">org.apache.predictionio.controller.Params</span> <span class="c1">// ADDED +</span> +<span class="c1">// ADDED ServingParams to specify the blacklisting file location. +</span><span class="k">case</span> <span class="k">class</span> <span class="nc">ServingParams</span><span class="o">(</span><span class="n">filepath</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">Serving</span><span class="o">(</span><span class="k">val</span> <span class="n">params</span><span class="k">:</span> <span class="kt">ServingParams</span><span class="o">)</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="k">val</span> <span class="n">disabledProducts</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="nc">Source</span> + <span class="o">.</span><span class="n">fromFile</span><span class="o">(</span><span class="n">params</span><span class="o">.</span><span class="n">filepath</span><span class="o">)</span> + <span class="o">.</span><span class="n">getLines</span> + <span class="o">.</span><span class="n">toSet</span> + + <span class="k">val</span> <span class="n">itemScores</span> <span class="k">=</span> <span class="n">predictedResults</span><span class="o">.</span><span class="n">head</span><span class="o">.</span><span class="n">itemScores</span> + <span class="nc">PredictedResult</span><span class="o">(</span><span class="n">itemScores</span><span class="o">.</span><span class="n">filter</span><span class="o">(</span><span class="n">ps</span> <span class="k">=></span> <span class="o">!</span><span class="n">disabledProducts</span><span class="o">(</span><span class="n">ps</span><span class="o">.</span><span class="n">item</span><span class="o">)))</span> + <span class="o">}</span> +<span class="o">}</span> +</pre></td></tr></tbody></table> </div> <p>In <code>engine.json</code>, you specify the parameter <code>serving</code> for the Serving component (the JSON4S library automatically extract the JSON object into a Scala class under the hood):</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="err">...</span><span class="w"> + </span><span class="s2">"serving"</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">"filepath"</span><span class="p">:</span><span class="w"> </span><span class="s2">"./data/sample_disabled_items.txt"</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="err">}</span><span class="w"> +</span></pre></td></tr></tbody></table> </div> <p>Again, to build <em>MyRecommendation</em> and deploy it as a service:</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> <p>You can change the <code>filepath</code> value without re-building the code next time.</p><h4 id='<a-href="/templates/recommendation/blacklist-items/">next:-filter-recommended-items-by-blacklist-in-query</a>' class='header-anchors' ><a href="/templates/recommendation/blacklist-items/">Next: Filter Recommended Items by Blacklist in Query</a></h4></div></div></div></div><footer><div class="container"><div class="seperator"></div><div class="row"><div class="col-md-6 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></li><li><a href="//docs.prediction.io/" target="blank">Docs</a></li><li><a href="//github.com/apache/incubator-predictionio" target="blank">GitHub</a></li><li><a href="mailto:user-subscr...@predictionio.incubator.apache.org"; target="blank">Subscribe to User Mailing List</a></li><li><a href="//stackoverflow.com/questions/tagg ed/predictionio" 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