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 <div class="page-header"><h1 id="r-on-spark">R on Spark<a class="anchor" aria-label="anchor" href="#r-on-spark"></a>
 </h1></div>
 <p>SparkR is an R package that provides a light-weight frontend to use Spark from R.</p>
 <div class="section level3">
 <h3 id="installing-sparkr">Installing sparkR<a class="anchor" aria-label="anchor" href="#installing-sparkr"></a>
 </h3>
 <p>Libraries of sparkR need to be created in <code>$SPARK_HOME/R/lib</code>. This can be done by running the script <code>$SPARK_HOME/R/install-dev.sh</code>. By default the above script uses the system wide installation of R. However, this can be changed to any user installed location of R by setting the environment variable <code>R_HOME</code> the full path of the base directory where R is installed, before running install-dev.sh script. Example:</p>
 <div class="sourceCode" id="cb1"><pre class="sourceCode bash"><code class="sourceCode bash"><a class="sourceLine" id="cb1-1" title="1"><span class="co"># where /home/username/R is where R is installed and /home/username/R/bin contains the files R and RScript</span></a>
 <a class="sourceLine" id="cb1-2" title="2"><span class="bu">export</span> <span class="va">R_HOME=</span>/home/username/R</a>
 <a class="sourceLine" id="cb1-3" title="3"><span class="ex">./install-dev.sh</span></a></code></pre></div>
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 <h3 id="sparkr-development">SparkR development<a class="anchor" aria-label="anchor" href="#sparkr-development"></a>
 </h3>
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 <h4 id="build-spark">Build Spark<a class="anchor" aria-label="anchor" href="#build-spark"></a>
 </h4>
 <p>Build Spark with <a href="https://spark.apache.org/docs/latest/building-spark.html#buildmvn" class="external-link">Maven</a> or <a href="https://spark.apache.org/docs/latest/building-spark.html#building-with-sbt" class="external-link">SBT</a>, and include the <code>-Psparkr</code> profile to build the R package. For example to use the default Hadoop versions you can run</p>
 <div class="sourceCode" id="cb2"><pre class="sourceCode bash"><code class="sourceCode bash"><a class="sourceLine" id="cb2-1" title="1"><span class="co"># Maven</span></a>
 <a class="sourceLine" id="cb2-2" title="2"><span class="ex">./build/mvn</span> -DskipTests -Psparkr package</a>
 <a class="sourceLine" id="cb2-3" title="3"></a>
 <a class="sourceLine" id="cb2-4" title="4"><span class="co"># SBT</span></a>
 <a class="sourceLine" id="cb2-5" title="5"><span class="ex">./build/sbt</span> -Psparkr package</a></code></pre></div>
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 <h4 id="running-sparkr">Running sparkR<a class="anchor" aria-label="anchor" href="#running-sparkr"></a>
 </h4>
 <p>You can start using SparkR by launching the SparkR shell with</p>
 <div class="sourceCode" id="cb3"><pre class="sourceCode R"><code class="sourceCode r"><a class="sourceLine" id="cb3-1" title="1">.<span class="op">/</span>bin<span class="op">/</span>sparkR</a></code></pre></div>
 <p>The <code>sparkR</code> script automatically creates a SparkContext with Spark by default in local mode. To specify the Spark master of a cluster for the automatically created SparkContext, you can run</p>
 <div class="sourceCode" id="cb4"><pre class="sourceCode R"><code class="sourceCode r"><a class="sourceLine" id="cb4-1" title="1">.<span class="op">/</span>bin<span class="op">/</span>sparkR <span class="op">--</span>master <span class="st">"local[2]"</span></a></code></pre></div>
 <p>To set other options like driver memory, executor memory etc. you can pass in the <a href="https://spark.apache.org/docs/latest/submitting-applications.html" class="external-link">spark-submit</a> arguments to <code>./bin/sparkR</code></p>
 </div>
 <div class="section level4">
 <h4 id="using-sparkr-from-rstudio">Using SparkR from RStudio<a class="anchor" aria-label="anchor" href="#using-sparkr-from-rstudio"></a>
 </h4>
 <p>If you wish to use SparkR from RStudio, please refer <a href="https://spark.apache.org/docs/latest/sparkr.html#starting-up-from-rstudio" class="external-link">SparkR documentation</a>.</p>
 </div>
 <div class="section level4">
 <h4 id="making-changes-to-sparkr">Making changes to SparkR<a class="anchor" aria-label="anchor" href="#making-changes-to-sparkr"></a>
 </h4>
 <p>The <a href="https://spark.apache.org/contributing.html" class="external-link">instructions</a> for making contributions to Spark also apply to SparkR. If you only make R file changes (i.e. no Scala changes) then you can just re-install the R package using <code>R/install-dev.sh</code> and test your changes. Once you have made your changes, please include unit tests for them and run existing unit tests using the <code>R/run-tests.sh</code> script as described below.</p>
 </div>
 <div class="section level4">
 <h4 id="generating-documentation">Generating documentation<a class="anchor" aria-label="anchor" href="#generating-documentation"></a>
 </h4>
 <p>The SparkR documentation (Rd files and HTML files) are not a part of the source repository. To generate them you can run the script <code>R/create-docs.sh</code>. This script uses <code>devtools</code> and <code>knitr</code> to generate the docs and these packages need to be installed on the machine before using the script. Also, you may need to install these <a href="https://github.com/apache/spark/tree/master/docs#prerequisites" class="external-link">prerequisites</a>. See also, <code>R/DOCUMENTATION.md</code></p>
 </div>
 </div>
 <div class="section level3">
 <h3 id="examples-unit-tests">Examples, Unit tests<a class="anchor" aria-label="anchor" href="#examples-unit-tests"></a>
 </h3>
 <p>SparkR comes with several sample programs in the <code>examples/src/main/r</code> directory. To run one of them, use <code>./bin/spark-submit &lt;filename&gt; &lt;args&gt;</code>. For example:</p>
 <div class="sourceCode" id="cb5"><pre class="sourceCode bash"><code class="sourceCode bash"><a class="sourceLine" id="cb5-1" title="1"><span class="ex">./bin/spark-submit</span> examples/src/main/r/dataframe.R</a></code></pre></div>
 <p>You can run R unit tests by following the instructions under <a href="https://spark.apache.org/docs/latest/building-spark.html#running-r-tests" class="external-link">Running R Tests</a>.</p>
 </div>
 <div class="section level3">
 <h3 id="running-on-yarn">Running on YARN<a class="anchor" aria-label="anchor" href="#running-on-yarn"></a>
 </h3>
 <p>The <code>./bin/spark-submit</code> can also be used to submit jobs to YARN clusters. You will need to set YARN conf dir before doing so. For example on CDH you can run</p>
 <div class="sourceCode" id="cb6"><pre class="sourceCode bash"><code class="sourceCode bash"><a class="sourceLine" id="cb6-1" title="1"><span class="bu">export</span> <span class="va">YARN_CONF_DIR=</span>/etc/hadoop/conf</a>
 <a class="sourceLine" id="cb6-2" title="2"><span class="ex">./bin/spark-submit</span> --master yarn examples/src/main/r/dataframe.R</a></code></pre></div>
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	<div class="page-header"><h1 id="r-on-spark">R on Spark<a class="anchor" aria-label="anchor" href="#r-on-spark"></a>
	</h1></div>
	<p>SparkR is an R package that provides a light-weight frontend to use Spark from R.</p>
	<div class="section level3">
	<h3 id="installing-sparkr">Installing sparkR<a class="anchor" aria-label="anchor" href="#installing-sparkr"></a>
	</h3>
	<p>Libraries of sparkR need to be created in <code>$SPARK_HOME/R/lib</code>. This can be done by running the script <code>$SPARK_HOME/R/install-dev.sh</code>. By default the above script uses the system wide installation of R. However, this can be changed to any user installed location of R by setting the environment variable <code>R_HOME</code> the full path of the base directory where R is installed, before running install-dev.sh script. Example:</p>
	<div class="sourceCode" id="cb1"><pre class="sourceCode bash"><code class="sourceCode bash"><a class="sourceLine" id="cb1-1" title="1"><span class="co"># where /home/username/R is where R is installed and /home/username/R/bin contains the files R and RScript</span></a>
	<a class="sourceLine" id="cb1-2" title="2"><span class="bu">export</span> <span class="va">R_HOME=</span>/home/username/R</a>
	<a class="sourceLine" id="cb1-3" title="3"><span class="ex">./install-dev.sh</span></a></code></pre></div>
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	<div class="section level3">
	<h3 id="sparkr-development">SparkR development<a class="anchor" aria-label="anchor" href="#sparkr-development"></a>
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	<h4 id="build-spark">Build Spark<a class="anchor" aria-label="anchor" href="#build-spark"></a>
	</h4>
	<p>Build Spark with <a href="https://spark.apache.org/docs/latest/building-spark.html#buildmvn" class="external-link">Maven</a> or <a href="https://spark.apache.org/docs/latest/building-spark.html#building-with-sbt" class="external-link">SBT</a>, and include the <code>-Psparkr</code> profile to build the R package. For example to use the default Hadoop versions you can run</p>
	<div class="sourceCode" id="cb2"><pre class="sourceCode bash"><code class="sourceCode bash"><a class="sourceLine" id="cb2-1" title="1"><span class="co"># Maven</span></a>
	<a class="sourceLine" id="cb2-2" title="2"><span class="ex">./build/mvn</span> -DskipTests -Psparkr package</a>
	<a class="sourceLine" id="cb2-3" title="3"></a>
	<a class="sourceLine" id="cb2-4" title="4"><span class="co"># SBT</span></a>
	<a class="sourceLine" id="cb2-5" title="5"><span class="ex">./build/sbt</span> -Psparkr package</a></code></pre></div>
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	<div class="section level4">
	<h4 id="running-sparkr">Running sparkR<a class="anchor" aria-label="anchor" href="#running-sparkr"></a>
	</h4>
	<p>You can start using SparkR by launching the SparkR shell with</p>
	<div class="sourceCode" id="cb3"><pre class="sourceCode R"><code class="sourceCode r"><a class="sourceLine" id="cb3-1" title="1">.<span class="op">/</span>bin<span class="op">/</span>sparkR</a></code></pre></div>
	<p>The <code>sparkR</code> script automatically creates a SparkContext with Spark by default in local mode. To specify the Spark master of a cluster for the automatically created SparkContext, you can run</p>
	<div class="sourceCode" id="cb4"><pre class="sourceCode R"><code class="sourceCode r"><a class="sourceLine" id="cb4-1" title="1">.<span class="op">/</span>bin<span class="op">/</span>sparkR <span class="op">--</span>master <span class="st">"local[2]"</span></a></code></pre></div>
	<p>To set other options like driver memory, executor memory etc. you can pass in the <a href="https://spark.apache.org/docs/latest/submitting-applications.html" class="external-link">spark-submit</a> arguments to <code>./bin/sparkR</code></p>
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	<div class="section level4">
	<h4 id="using-sparkr-from-rstudio">Using SparkR from RStudio<a class="anchor" aria-label="anchor" href="#using-sparkr-from-rstudio"></a>
	</h4>
	<p>If you wish to use SparkR from RStudio, please refer <a href="https://spark.apache.org/docs/latest/sparkr.html#starting-up-from-rstudio" class="external-link">SparkR documentation</a>.</p>
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	<h4 id="making-changes-to-sparkr">Making changes to SparkR<a class="anchor" aria-label="anchor" href="#making-changes-to-sparkr"></a>
	</h4>
	<p>The <a href="https://spark.apache.org/contributing.html" class="external-link">instructions</a> for making contributions to Spark also apply to SparkR. If you only make R file changes (i.e. no Scala changes) then you can just re-install the R package using <code>R/install-dev.sh</code> and test your changes. Once you have made your changes, please include unit tests for them and run existing unit tests using the <code>R/run-tests.sh</code> script as described below.</p>
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	<div class="section level4">
	<h4 id="generating-documentation">Generating documentation<a class="anchor" aria-label="anchor" href="#generating-documentation"></a>
	</h4>
	<p>The SparkR documentation (Rd files and HTML files) are not a part of the source repository. To generate them you can run the script <code>R/create-docs.sh</code>. This script uses <code>devtools</code> and <code>knitr</code> to generate the docs and these packages need to be installed on the machine before using the script. Also, you may need to install these <a href="https://github.com/apache/spark/tree/master/docs#prerequisites" class="external-link">prerequisites</a>. See also, <code>R/DOCUMENTATION.md</code></p>
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	<h3 id="examples-unit-tests">Examples, Unit tests<a class="anchor" aria-label="anchor" href="#examples-unit-tests"></a>
	</h3>
	<p>SparkR comes with several sample programs in the <code>examples/src/main/r</code> directory. To run one of them, use <code>./bin/spark-submit <filename> <args></code>. For example:</p>
	<div class="sourceCode" id="cb5"><pre class="sourceCode bash"><code class="sourceCode bash"><a class="sourceLine" id="cb5-1" title="1"><span class="ex">./bin/spark-submit</span> examples/src/main/r/dataframe.R</a></code></pre></div>
	<p>You can run R unit tests by following the instructions under <a href="https://spark.apache.org/docs/latest/building-spark.html#running-r-tests" class="external-link">Running R Tests</a>.</p>
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	<h3 id="running-on-yarn">Running on YARN<a class="anchor" aria-label="anchor" href="#running-on-yarn"></a>
	</h3>
	<p>The <code>./bin/spark-submit</code> can also be used to submit jobs to YARN clusters. You will need to set YARN conf dir before doing so. For example on CDH you can run</p>
	<div class="sourceCode" id="cb6"><pre class="sourceCode bash"><code class="sourceCode bash"><a class="sourceLine" id="cb6-1" title="1"><span class="bu">export</span> <span class="va">YARN_CONF_DIR=</span>/etc/hadoop/conf</a>
	<a class="sourceLine" id="cb6-2" title="2"><span class="ex">./bin/spark-submit</span> --master yarn examples/src/main/r/dataframe.R</a></code></pre></div>
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