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| <h1 class="title">Using Spark's "Hadoop Free" Build</h1> |
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| <p>Spark uses Hadoop client libraries for HDFS and YARN. Starting in version Spark 1.4, the project packages “Hadoop free” builds that lets you more easily connect a single Spark binary to any Hadoop version. To use these builds, you need to modify <code class="language-plaintext highlighter-rouge">SPARK_DIST_CLASSPATH</code> to include Hadoop’s package jars. The most convenient place to do this is by adding an entry in <code class="language-plaintext highlighter-rouge">conf/spark-env.sh</code>.</p> |
| |
| <p>This page describes how to connect Spark to Hadoop for different types of distributions.</p> |
| |
| <h1 id="apache-hadoop">Apache Hadoop</h1> |
| <p>For Apache distributions, you can use Hadoop’s ‘classpath’ command. For instance:</p> |
| |
| <figure class="highlight"><pre><code class="language-bash" data-lang="bash"><span class="c">### in conf/spark-env.sh ###</span> |
| |
| <span class="c"># If 'hadoop' binary is on your PATH</span> |
| <span class="nb">export </span><span class="nv">SPARK_DIST_CLASSPATH</span><span class="o">=</span><span class="si">$(</span>hadoop classpath<span class="si">)</span> |
| |
| <span class="c"># With explicit path to 'hadoop' binary</span> |
| <span class="nb">export </span><span class="nv">SPARK_DIST_CLASSPATH</span><span class="o">=</span><span class="si">$(</span>/path/to/hadoop/bin/hadoop classpath<span class="si">)</span> |
| |
| <span class="c"># Passing a Hadoop configuration directory</span> |
| <span class="nb">export </span><span class="nv">SPARK_DIST_CLASSPATH</span><span class="o">=</span><span class="si">$(</span>hadoop <span class="nt">--config</span> /path/to/configs classpath<span class="si">)</span></code></pre></figure> |
| |
| <h1 id="hadoop-free-build-setup-for-spark-on-kubernetes">Hadoop Free Build Setup for Spark on Kubernetes</h1> |
| <p>To run the Hadoop free build of Spark on Kubernetes, the executor image must have the appropriate version of Hadoop binaries and the correct <code class="language-plaintext highlighter-rouge">SPARK_DIST_CLASSPATH</code> value set. See the example below for the relevant changes needed in the executor Dockerfile:</p> |
| |
| <figure class="highlight"><pre><code class="language-bash" data-lang="bash"><span class="c">### Set environment variables in the executor dockerfile ###</span> |
| |
| ENV <span class="nv">SPARK_HOME</span><span class="o">=</span><span class="s2">"/opt/spark"</span> |
| ENV <span class="nv">HADOOP_HOME</span><span class="o">=</span><span class="s2">"/opt/hadoop"</span> |
| ENV <span class="nv">PATH</span><span class="o">=</span><span class="s2">"</span><span class="nv">$SPARK_HOME</span><span class="s2">/bin:</span><span class="nv">$HADOOP_HOME</span><span class="s2">/bin:</span><span class="nv">$PATH</span><span class="s2">"</span> |
| ... |
| |
| <span class="c">#Copy your target hadoop binaries to the executor hadoop home </span> |
| |
| COPY /opt/hadoop3 <span class="nv">$HADOOP_HOME</span> |
| ... |
| |
| <span class="c">#Copy and use the Spark provided entrypoint.sh. It sets your SPARK_DIST_CLASSPATH using the hadoop binary in $HADOOP_HOME and starts the executor. If you choose to customize the value of SPARK_DIST_CLASSPATH here, the value will be retained in entrypoint.sh</span> |
| |
| ENTRYPOINT <span class="o">[</span> <span class="s2">"/opt/entrypoint.sh"</span> <span class="o">]</span> |
| ... </code></pre></figure> |
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