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Posted to commits@mahout.apache.org by bu...@apache.org on 2015/04/26 17:49:28 UTC
svn commit: r949237 - in /websites/staging/mahout/trunk/content: ./
users/environment/how-to-build-an-app.html
Author: buildbot
Date: Sun Apr 26 15:49:28 2015
New Revision: 949237
Log:
Staging update by buildbot for mahout
Modified:
websites/staging/mahout/trunk/content/ (props changed)
websites/staging/mahout/trunk/content/users/environment/how-to-build-an-app.html
Propchange: websites/staging/mahout/trunk/content/
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--- cms:source-revision (original)
+++ cms:source-revision Sun Apr 26 15:49:28 2015
@@ -1 +1 @@
-1675715
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Modified: websites/staging/mahout/trunk/content/users/environment/how-to-build-an-app.html
==============================================================================
--- websites/staging/mahout/trunk/content/users/environment/how-to-build-an-app.html (original)
+++ websites/staging/mahout/trunk/content/users/environment/how-to-build-an-app.html Sun Apr 26 15:49:28 2015
@@ -263,24 +263,27 @@
<div id="content-wrap" class="clearfix">
<div id="main">
<h1 id="how-to-create-and-app-using-mahout">How to create and App using Mahout</h1>
-<p>This is an example of how to create a simple app using Mahout as a Library. The source is available on Github in the <a href="https://github.com/pferrel/3-input-cooc">3-input-cooc project</a> with more explanation about what it does. For this tutorial we'll concentrate on how to create an app.</p>
-<p>This example is for reading three interactions types and creating indicators for them using cooccurrence and cross-cooccurrence. The indicators will be written to text files in a format ready for search engine indexing in recommender.</p>
+<p>This is an example of how to create a simple app using Mahout as a Library. The source is available on Github in the <a href="https://github.com/pferrel/3-input-cooc">3-input-cooc project</a> with more explanation about what it does (has to do with collaborative filtering). For this tutorial we'll concentrate on the app rather than the data science.</p>
+<p>The app reads in three user-item interactions types and creats indicators for them using cooccurrence and cross-cooccurrence. The indicators will be written to text files in a format ready for search engine indexing in search engine based recommender.</p>
<h2 id="setup">Setup</h2>
<p>In order to build and run the CooccurrenceDriver you need to install the following:</p>
<ul>
<li>Install the Java 7 JDK from Oracle. Mac users look here: <a href="http://www.oracle.com/technetwork/java/javase/downloads/jdk7-downloads-1880260.html">Java SE Development Kit 7u72</a>.</li>
-<li>Install sbt (simple build tool) 0.13.x for <a href="http://www.scala-sbt.org/release/tutorial/Installing-sbt-on-Mac.html">Mac</a>,<a href="http://www.scala-sbt.org/release/tutorial/Installing-sbt-on-Linux.html">Linux</a> or <a href="http://www.scala-sbt.org/release/tutorial/Manual-Installation.html">manual instalation</a>.</li>
-<li>Install <a href="http://mahout.apache.org/general/downloads.html">Mahout</a>. Don't forget to setup MAHOUT_HOME and MAHOUT_LOCAL</li>
+<li>Install sbt (simple build tool) 0.13.x for <a href="http://www.scala-sbt.org/release/tutorial/Installing-sbt-on-Mac.html">Mac</a>, <a href="http://www.scala-sbt.org/release/tutorial/Installing-sbt-on-Linux.html">Linux</a> or <a href="http://www.scala-sbt.org/release/tutorial/Manual-Installation.html">manual instalation</a>.</li>
+<li>Install <a href="https://spark.apache.org/docs/1.1.1/spark-standalone.html">Spark 1.1.1</a>. Don't forget to setup SPARK_HOME</li>
+<li>Install <a href="http://mahout.apache.org/general/downloads.html">Mahout 0.10.0</a>. Don't forget to setup MAHOUT_HOME and MAHOUT_LOCAL</li>
</ul>
+<p>Why install if you are only using them as a library? Certain binaries and scripts are required by the libraries to get information about the environment like discovering where jars are located.</p>
+<p>Spark requires a set of jars on the classpath for the client side part of an app and another set of jars must be passed to the Spark Context for running distributed code. The example should discover all the neccessary classes automatically.</p>
<h2 id="application">Application</h2>
-<p>Using Mahout as a library in an application will require a little Scala code. We have an App trait in Scala so we'll create an object, which inherits from <code>App</code></p>
+<p>Using Mahout as a library in an application will require a little Scala code. Scala has an App trait so we'll create an object, which inherits from <code>App</code></p>
<div class="codehilite"><pre><span class="n">object</span> <span class="n">CooccurrenceDriver</span> <span class="n">extends</span> <span class="n">App</span> <span class="p">{</span>
<span class="p">}</span>
</pre></div>
-<p>This will look a little different than Java since <code>App</code> does delayed initialization, which causes the main body to be executed when the App is launched, just as in Java you would create a CooccurrenceDriver.main.</p>
-<p>Before we can execute something on Spark we'll need to create a context. We could use raw Spark calls here but default values are setup for a Mahout context.</p>
+<p>This will look a little different than Java since <code>App</code> does delayed initialization, which causes the body to be executed when the App is launched, just as in Java you would create a main method.</p>
+<p>Before we can execute something on Spark we'll need to create a context. We could use raw Spark calls here but default values are setup for a Mahout context by using the Mahout helper function.</p>
<div class="codehilite"><pre><span class="n">implicit</span> <span class="n">val</span> <span class="n">mc</span> <span class="p">=</span> <span class="n">mahoutSparkContext</span><span class="p">(</span><span class="n">masterUrl</span> <span class="p">=</span> "<span class="n">local</span>"<span class="p">,</span>
<span class="n">appName</span> <span class="p">=</span> "<span class="n">CooccurrenceDriver</span>"<span class="p">)</span>
</pre></div>
@@ -298,8 +301,8 @@
</pre></div>
-<p>Mahout has a helper function that reads the text delimited in SparkEngine.indexedDatasetDFSReadElements. The function reads single elements in a distributed way to create the IndexedDataset. </p>
-<p>Notice we read in all datasets before we adjust the number of rows in them to match the total number of users in the data. This is so the math works out even if some users took one action but not another.</p>
+<p>Mahout has a helper function that reads the text delimited files SparkEngine.indexedDatasetDFSReadElements. The function reads single element tuples (user-id,item-id) in a distributed way to create the IndexedDataset. Distributed Row Matrices (DRM) and Vectors are important data types supplied by Mahout and IndexedDataset is like a very lightweight Dataframe in R, it wraps a DRM with HashBiMaps for row and column IDs. </p>
+<p>One important thing to note about this example is that we read in all datasets before we adjust the number of rows in them to match the total number of users in the data. This is so the math works out <a href="http://mahout.apache.org/users/algorithms/intro-cooccurrence-spark.html">(A'A, A'B, A'C)</a> even if some users took one action but not another there must be the same number of rows in all matrices.</p>
<div class="codehilite"><pre><span class="o">/**</span>
<span class="o">*</span> Read files of element tuples and create IndexedDatasets one per action. These
<span class="o">*</span> share a userID BiMap but have their own itemID BiMaps
@@ -338,8 +341,9 @@ def readActions<span class="p">(</span>a
<p>Now that we have the data read in we can perform the cooccurrence calculation.</p>
-<div class="codehilite"><pre><span class="c1">// strip off names, method takes an array of IndexedDatasets</span>
-<span class="n">val</span> <span class="n">indicatorMatrices</span> <span class="o">=</span> <span class="n">SimilarityAnalysis</span><span class="p">.</span><span class="n">cooccurrencesIDSs</span><span class="p">(</span><span class="n">actions</span><span class="p">.</span><span class="n">map</span><span class="p">(</span><span class="n">a</span> <span class="o">=></span> <span class="n">a</span><span class="p">.</span><span class="n">_2</span><span class="p">))</span>
+<div class="codehilite"><pre><span class="c1">// actions.map creates an array of just the IndeedDatasets</span>
+<span class="n">val</span> <span class="n">indicatorMatrices</span> <span class="o">=</span> <span class="n">SimilarityAnalysis</span><span class="p">.</span><span class="n">cooccurrencesIDSs</span><span class="p">(</span>
+ <span class="n">actions</span><span class="p">.</span><span class="n">map</span><span class="p">(</span><span class="n">a</span> <span class="o">=></span> <span class="n">a</span><span class="p">.</span><span class="n">_2</span><span class="p">))</span>
</pre></div>
@@ -418,9 +422,9 @@ def writeIndicators<span class="p">(</sp
<p>To build and run this example in a debugger like IntelliJ IDEA. Install from the IntelliJ site and add the Scala plugin.</p>
<p>Open IDEA and go to the menu File->New->Project from existing sources->SBT->/path/to/3-input-cooc. This will create an IDEA project from <code>build.sbt</code> in the root directory.</p>
<p>At this point you may create a "Debug Configuration" to run. In the menu choose Run->Edit Configurations. Under "Default" choose "Application". In the dialog hit the elipsis button "..." to the right of "Environment Variables" and fill in your versions of JAVA_HOME, SPARK_HOME, and MAHOUT_HOME. In configuration editor under "Use classpath from" choose root-3-input-cooc module. </p>
-<p><img alt="image" src="http://mahout.apache.org/images/debug-config.png" title="=400x" /></p>
+<p><img alt="image" src="http://mahout.apache.org/images/debug-config.png" /></p>
<p>Now choose "Application" in the left pane and hit the plus sign "+". give the config a name and hit the elipsis button to the right of the "Main class" field as shown.</p>
-<p><img alt="image" src="http://mahout.apache.org/images/debug-config-2.png" title="=600x" /></p>
+<p><img alt="image" src="http://mahout.apache.org/images/debug-config-2.png" /></p>
<p>After setting breakpoints you are now ready to debug the configuration. Go to the Run->Debug... menu and pick your configuration. This will execute using a local standalone instance of Spark.</p>
<h2 id="the-mahout-shell">The Mahout Shell</h2>
<p>For small script-like apps you may wish to use the Mahout shell. It is a Scala REPL type interactive shell built on the Spark shell with Mahout-Samsara extensions.</p>