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authorPatrick Wendell <pwendell@apache.org>2013-09-25 02:01:24 +0000
committerPatrick Wendell <pwendell@apache.org>2013-09-25 02:01:24 +0000
commit43949b33e0f1ae3f52c878852cc81505276be00b (patch)
tree5e239f079d8cdf563f694cdf29fcfc0797e2ebc0 /site/docs/0.8.0/hadoop-third-party-distributions.html
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+ <title>Running with Cloudera and HortonWorks - Spark 0.8.0 Documentation</title>
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+ <div class="brand"><a href="index.html">
+ <img src="img/spark-logo-hd.png" style="height:50px;"/></a><span class="version">0.8.0</span>
+ </div>
+ <ul class="nav">
+ <!--TODO(andyk): Add class="active" attribute to li some how.-->
+ <li><a href="index.html">Overview</a></li>
+
+ <li class="dropdown">
+ <a href="#" class="dropdown-toggle" data-toggle="dropdown">Programming Guides<b class="caret"></b></a>
+ <ul class="dropdown-menu">
+ <li><a href="quick-start.html">Quick Start</a></li>
+ <li><a href="scala-programming-guide.html">Spark in Scala</a></li>
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+ <li><a href="python-programming-guide.html">Spark in Python</a></li>
+ <li class="divider"></li>
+ <li><a href="streaming-programming-guide.html">Spark Streaming</a></li>
+ <li><a href="mllib-guide.html">MLlib (Machine Learning)</a></li>
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+
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+ <a href="#" class="dropdown-toggle" data-toggle="dropdown">API Docs<b class="caret"></b></a>
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+ <li><a href="api/core/index.html">Spark Core for Java/Scala</a></li>
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+ <li><a href="api/streaming/index.html">Spark Streaming</a></li>
+ <li><a href="api/mllib/index.html">MLlib (Machine Learning)</a></li>
+ <li><a href="api/bagel/index.html">Bagel (Pregel on Spark)</a></li>
+ </ul>
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+
+ <li class="dropdown">
+ <a href="#" class="dropdown-toggle" data-toggle="dropdown">Deploying<b class="caret"></b></a>
+ <ul class="dropdown-menu">
+ <li><a href="cluster-overview.html">Overview</a></li>
+ <li><a href="ec2-scripts.html">Amazon EC2</a></li>
+ <li><a href="spark-standalone.html">Standalone Mode</a></li>
+ <li><a href="running-on-mesos.html">Mesos</a></li>
+ <li><a href="running-on-yarn.html">YARN</a></li>
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+ <a href="api.html" class="dropdown-toggle" data-toggle="dropdown">More<b class="caret"></b></a>
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+ <li><a href="configuration.html">Configuration</a></li>
+ <li><a href="monitoring.html">Monitoring</a></li>
+ <li><a href="tuning.html">Tuning Guide</a></li>
+ <li><a href="hadoop-third-party-distributions.html">Running with CDH/HDP</a></li>
+ <li><a href="hardware-provisioning.html">Hardware Provisioning</a></li>
+ <li><a href="job-scheduling.html">Job Scheduling</a></li>
+ <li class="divider"></li>
+ <li><a href="building-with-maven.html">Building Spark with Maven</a></li>
+ <li><a href="https://cwiki.apache.org/confluence/display/SPARK/Contributing+to+Spark">Contributing to Spark</a></li>
+ </ul>
+ </li>
+ </ul>
+ <!--<p class="navbar-text pull-right"><span class="version-text">v0.8.0</span></p>-->
+ </div>
+ </div>
+ </div>
+
+ <div class="container" id="content">
+ <h1 class="title">Running with Cloudera and HortonWorks</h1>
+
+ <p>Spark can run against all versions of Cloudera&#8217;s Distribution Including Apache Hadoop (CDH) and
+the Hortonworks Data Platform (HDP). There are a few things to keep in mind when using Spark
+with these distributions:</p>
+
+<h1 id="compile-time-hadoop-version">Compile-time Hadoop Version</h1>
+
+<p>When compiling Spark, you&#8217;ll need to
+<a href="http://localhost:4000/index.html#a-note-about-hadoop-versions">set the SPARK_HADOOP_VERSION flag</a>:</p>
+
+<pre><code>SPARK_HADOOP_VERSION=1.0.4 sbt/sbt assembly
+</code></pre>
+
+<p>The table below lists the corresponding <code>SPARK_HADOOP_VERSION</code> code for each CDH/HDP release. Note that
+some Hadoop releases are binary compatible across client versions. This means the pre-built Spark
+distribution may &#8220;just work&#8221; without you needing to compile. That said, we recommend compiling with
+the <em>exact</em> Hadoop version you are running to avoid any compatibility errors.</p>
+
+<table>
+ <tr valign="top">
+ <td>
+ <h3>CDH Releases</h3>
+ <table class="table" style="width:350px; margin-right: 20px;">
+ <tr><th>Release</th><th>Version code</th></tr>
+ <tr><td>CDH 4.X.X (YARN mode)</td><td>2.0.0-chd4.X.X</td></tr>
+ <tr><td>CDH 4.X.X</td><td>2.0.0-mr1-chd4.X.X</td></tr>
+ <tr><td>CDH 3u6</td><td>0.20.2-cdh3u6</td></tr>
+ <tr><td>CDH 3u5</td><td>0.20.2-cdh3u5</td></tr>
+ <tr><td>CDH 3u4</td><td>0.20.2-cdh3u4</td></tr>
+ </table>
+ </td>
+ <td>
+ <h3>HDP Releases</h3>
+ <table class="table" style="width:350px;">
+ <tr><th>Release</th><th>Version code</th></tr>
+ <tr><td>HDP 1.3</td><td>1.2.0</td></tr>
+ <tr><td>HDP 1.2</td><td>1.1.2</td></tr>
+ <tr><td>HDP 1.1</td><td>1.0.3</td></tr>
+ <tr><td>HDP 1.0</td><td>1.0.3</td></tr>
+ </table>
+ </td>
+ </tr>
+</table>
+
+<h1 id="linking-applications-to-the-hadoop-version">Linking Applications to the Hadoop Version</h1>
+
+<p>In addition to compiling Spark itself against the right version, you need to add a Maven dependency on that
+version of <code>hadoop-client</code> to any Spark applications you run, so they can also talk to the HDFS version
+on the cluster. If you are using CDH, you also need to add the Cloudera Maven repository.
+This looks as follows in SBT:</p>
+
+<div class="highlight"><pre><code class="scala"><span class="n">libraryDependencies</span> <span class="o">+=</span> <span class="s">&quot;org.apache.hadoop&quot;</span> <span class="o">%</span> <span class="s">&quot;hadoop-client&quot;</span> <span class="o">%</span> <span class="s">&quot;&lt;version&gt;&quot;</span>
+
+<span class="c1">// If using CDH, also add Cloudera repo</span>
+<span class="n">resolvers</span> <span class="o">+=</span> <span class="s">&quot;Cloudera Repository&quot;</span> <span class="n">at</span> <span class="s">&quot;https://repository.cloudera.com/artifactory/cloudera-repos/&quot;</span>
+</code></pre></div>
+
+<p>Or in Maven:</p>
+
+<div class="highlight"><pre><code class="xml"><span class="nt">&lt;project&gt;</span>
+ <span class="nt">&lt;dependencies&gt;</span>
+ ...
+ <span class="nt">&lt;dependency&gt;</span>
+ <span class="nt">&lt;groupId&gt;</span>org.apache.hadoop<span class="nt">&lt;/groupId&gt;</span>
+ <span class="nt">&lt;artifactId&gt;</span>hadoop-client<span class="nt">&lt;/artifactId&gt;</span>
+ <span class="nt">&lt;version&gt;</span>[version]<span class="nt">&lt;/version&gt;</span>
+ <span class="nt">&lt;/dependency&gt;</span>
+ <span class="nt">&lt;/dependencies&gt;</span>
+
+ <span class="c">&lt;!-- If using CDH, also add Cloudera repo --&gt;</span>
+ <span class="nt">&lt;repositories&gt;</span>
+ ...
+ <span class="nt">&lt;repository&gt;</span>
+ <span class="nt">&lt;id&gt;</span>Cloudera repository<span class="nt">&lt;/id&gt;</span>
+ <span class="nt">&lt;url&gt;</span>https://repository.cloudera.com/artifactory/cloudera-repos/<span class="nt">&lt;/url&gt;</span>
+ <span class="nt">&lt;/repository&gt;</span>
+ <span class="nt">&lt;/repositories&gt;</span>
+<span class="nt">&lt;/project&gt;</span>
+</code></pre></div>
+
+<h1 id="where-to-run-spark">Where to Run Spark</h1>
+
+<p>As described in the <a href="hardware-provisioning.html#storage-systems">Hardware Provisioning</a> guide,
+Spark can run in a variety of deployment modes:</p>
+
+<ul>
+ <li>Using dedicated set of Spark nodes in your cluster. These nodes should be co-located with your
+Hadoop installation.</li>
+ <li>Running on the same nodes as an existing Hadoop installation, with a fixed amount memory and
+cores dedicated to Spark on each node.</li>
+ <li>Run Spark alongside Hadoop using a cluster resource manager, such as YARN or Mesos.</li>
+</ul>
+
+<p>These options are identical for those using CDH and HDP. </p>
+
+<h1 id="inheriting-cluster-configuration">Inheriting Cluster Configuration</h1>
+
+<p>If you plan to read and write from HDFS using Spark, there are two Hadoop configuration files that
+should be included on Spark&#8217;s classpath:</p>
+
+<ul>
+ <li><code>hdfs-site.xml</code>, which provides default behaviors for the HDFS client.</li>
+ <li><code>core-site.xml</code>, which sets the default filesystem name.</li>
+</ul>
+
+<p>The location of these configuration files varies across CDH and HDP versions, but
+a common location is inside of <code>/etc/hadoop/conf</code>. Some tools, such as Cloudera Manager, create
+configurations on-the-fly, but offer a mechanisms to download copies of them.</p>
+
+<p>There are a few ways to make these files visible to Spark:</p>
+
+<ul>
+ <li>You can copy these files into <code>$SPARK_HOME/conf</code> and they will be included in Spark&#8217;s
+classpath automatically.</li>
+ <li>If you are running Spark on the same nodes as Hadoop <em>and</em> your distribution includes both
+<code>hdfs-site.xml</code> and <code>core-site.xml</code> in the same directory, you can set <code>HADOOP_CONF_DIR</code>
+in <code>$SPARK_HOME/spark-env.sh</code> to that directory.</li>
+</ul>
+
+ <!-- Main hero unit for a primary marketing message or call to action -->
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+
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+ <hr>
+ <p style="text-align: center; veritcal-align: middle; color: #999;">
+ Apache Spark is an effort undergoing incubation at the Apache Software Foundation.
+ <a href="http://incubator.apache.org">
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