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| author | Patrick Wendell <pwendell@apache.org> | 2014-05-30 08:55:36 +0000 |
|---|---|---|
| committer | Patrick Wendell <pwendell@apache.org> | 2014-05-30 08:55:36 +0000 |
| commit | 66fb4b11cbae79d9044b2bbf2e53351642a58ff5 (patch) | |
| tree | 2a3238ae425816d2296c2972987e56b3e949ea0b /site/docs/1.0.0/submitting-applications.html | |
| parent | 3936fd5d223549bfa06bd6eeba6becfc88daee52 (diff) | |
| download | spark-website-66fb4b11cbae79d9044b2bbf2e53351642a58ff5.tar.gz spark-website-66fb4b11cbae79d9044b2bbf2e53351642a58ff5.tar.bz2 spark-website-66fb4b11cbae79d9044b2bbf2e53351642a58ff5.zip | |
Docs for Spark 1.0.0
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| -rw-r--r-- | site/docs/1.0.0/submitting-applications.html | 287 |
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diff --git a/site/docs/1.0.0/submitting-applications.html b/site/docs/1.0.0/submitting-applications.html new file mode 100644 index 000000000..258e15918 --- /dev/null +++ b/site/docs/1.0.0/submitting-applications.html @@ -0,0 +1,287 @@ +<!DOCTYPE html> +<!--[if lt IE 7]> <html class="no-js lt-ie9 lt-ie8 lt-ie7"> <![endif]--> +<!--[if IE 7]> <html class="no-js lt-ie9 lt-ie8"> <![endif]--> +<!--[if IE 8]> <html class="no-js lt-ie9"> <![endif]--> +<!--[if gt IE 8]><!--> <html class="no-js"> <!--<![endif]--> + <head> + <meta charset="utf-8"> + <meta http-equiv="X-UA-Compatible" content="IE=edge,chrome=1"> + <title>Submitting Applications - Spark 1.0.0 Documentation</title> + <meta name="description" content=""> + + + + <link rel="stylesheet" href="css/bootstrap.min.css"> + <style> + body { + padding-top: 60px; + padding-bottom: 40px; + } + </style> + <meta name="viewport" content="width=device-width"> + <link rel="stylesheet" href="css/bootstrap-responsive.min.css"> + <link rel="stylesheet" href="css/main.css"> + + <script src="js/vendor/modernizr-2.6.1-respond-1.1.0.min.js"></script> + + <link rel="stylesheet" href="css/pygments-default.css"> + + + + </head> + <body> + <!--[if lt IE 7]> + <p class="chromeframe">You are using an outdated browser. <a href="http://browsehappy.com/">Upgrade your browser today</a> or <a href="http://www.google.com/chromeframe/?redirect=true">install Google Chrome Frame</a> to better experience this site.</p> + <![endif]--> + + <!-- This code is taken from http://twitter.github.com/bootstrap/examples/hero.html --> + + <div class="navbar navbar-fixed-top" id="topbar"> + <div class="navbar-inner"> + <div class="container"> + <div class="brand"><a href="index.html"> + <img src="img/spark-logo-hd.png" style="height:50px;"/></a><span class="version">1.0.0</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="programming-guide.html">Spark Programming Guide</a></li> + <li class="divider"></li> + <li><a href="streaming-programming-guide.html">Spark Streaming</a></li> + <li><a href="sql-programming-guide.html">Spark SQL</a></li> + <li><a href="mllib-guide.html">MLlib (Machine Learning)</a></li> + <li><a href="graphx-programming-guide.html">GraphX (Graph Processing)</a></li> + <li><a href="bagel-programming-guide.html">Bagel (Pregel on Spark)</a></li> + </ul> + </li> + + <li class="dropdown"> + <a href="#" class="dropdown-toggle" data-toggle="dropdown">API Docs<b class="caret"></b></a> + <ul class="dropdown-menu"> + <li><a href="api/scala/index.html#org.apache.spark.package">Scaladoc</a></li> + <li><a href="api/java/index.html">Javadoc</a></li> + <li><a href="api/python/index.html">Python API</a></li> + </ul> + </li> + + <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="submitting-applications.html">Submitting Applications</a></li> + <li class="divider"></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> + </ul> + </li> + + <li class="dropdown"> + <a href="api.html" class="dropdown-toggle" data-toggle="dropdown">More<b class="caret"></b></a> + <ul class="dropdown-menu"> + <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="job-scheduling.html">Job Scheduling</a></li> + <li><a href="security.html">Security</a></li> + <li><a href="hardware-provisioning.html">Hardware Provisioning</a></li> + <li><a href="hadoop-third-party-distributions.html">3<sup>rd</sup>-Party Hadoop Distros</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">v1.0.0</span></p>--> + </div> + </div> + </div> + + <div class="container" id="content"> + + <h1 class="title">Submitting Applications</h1> + + + <p>The <code>spark-submit</code> script in Spark’s <code>bin</code> directory is used to launch applications on a cluster. +It can use all of Spark’s supported <a href="cluster-overview.html#cluster-manager-types">cluster managers</a> +through a uniform interface so you don’t have to configure your application specially for each one.</p> + +<h1 id="bundling-your-applications-dependencies">Bundling Your Application’s Dependencies</h1> +<p>If your code depends on other projects, you will need to package them alongside +your application in order to distribute the code to a Spark cluster. To do this, +to create an assembly jar (or “uber” jar) containing your code and its dependencies. Both +<a href="https://github.com/sbt/sbt-assembly">sbt</a> and +<a href="http://maven.apache.org/plugins/maven-shade-plugin/">Maven</a> +have assembly plugins. When creating assembly jars, list Spark and Hadoop +as <code>provided</code> dependencies; these need not be bundled since they are provided by +the cluster manager at runtime. Once you have an assembled jar you can call the <code>bin/spark-submit</code> +script as shown here while passing your jar.</p> + +<p>For Python, you can use the <code>--py-files</code> argument of <code>spark-submit</code> to add <code>.py</code>, <code>.zip</code> or <code>.egg</code> +files to be distributed with your application. If you depend on multiple Python files we recommend +packaging them into a <code>.zip</code> or <code>.egg</code>.</p> + +<h1 id="launching-applications-with-spark-submit">Launching Applications with spark-submit</h1> + +<p>Once a user application is bundled, it can be launched using the <code>bin/spark-submit</code> script. +This script takes care of setting up the classpath with Spark and its +dependencies, and can support different cluster managers and deploy modes that Spark supports:</p> + +<div class="highlight"><pre><code class="bash">./bin/spark-submit <span class="se">\</span> + --class <main-class> + --master <master-url> <span class="se">\</span> + --deploy-mode <deploy-mode> <span class="se">\</span> + ... <span class="c"># other options</span> + <application-jar> <span class="se">\</span> + <span class="o">[</span>application-arguments<span class="o">]</span> +</code></pre></div> + +<p>Some of the commonly used options are:</p> + +<ul> + <li><code>--class</code>: The entry point for your application (e.g. <code>org.apache.spark.examples.SparkPi</code>)</li> + <li><code>--master</code>: The <a href="#master-urls">master URL</a> for the cluster (e.g. <code>spark://23.195.26.187:7077</code>)</li> + <li><code>--deploy-mode</code>: Whether to deploy your driver program within the cluster or run it locally as an external client (either <code>cluster</code> or <code>client</code>)</li> + <li><code>application-jar</code>: Path to a bundled jar including your application and all dependencies. The URL must be globally visible inside of your cluster, for instance, an <code>hdfs://</code> path or a <code>file://</code> path that is present on all nodes.</li> + <li><code>application-arguments</code>: Arguments passed to the main method of your main class, if any</li> +</ul> + +<p>For Python applications, simply pass a <code>.py</code> file in the place of <code><application-jar></code> instead of a JAR, +and add Python <code>.zip</code>, <code>.egg</code> or <code>.py</code> files to the search path with <code>--py-files</code>.</p> + +<p>To enumerate all options available to <code>spark-submit</code> run it with <code>--help</code>. Here are a few +examples of common options:</p> + +<div class="highlight"><pre><code class="bash"><span class="c"># Run application locally on 8 cores</span> +./bin/spark-submit <span class="se">\</span> + --class org.apache.spark.examples.SparkPi <span class="se">\</span> + --master <span class="nb">local</span><span class="o">[</span>8<span class="o">]</span> <span class="se">\</span> + /path/to/examples.jar <span class="se">\</span> + 100 + +<span class="c"># Run on a Spark standalone cluster</span> +./bin/spark-submit <span class="se">\</span> + --class org.apache.spark.examples.SparkPi <span class="se">\</span> + --master spark://207.184.161.138:7077 <span class="se">\</span> + --executor-memory 20G <span class="se">\</span> + --total-executor-cores 100 <span class="se">\</span> + /path/to/examples.jar <span class="se">\</span> + 1000 + +<span class="c"># Run on a YARN cluster</span> +<span class="nb">export </span><span class="nv">HADOOP_CONF_DIR</span><span class="o">=</span>XXX +./bin/spark-submit <span class="se">\</span> + --class org.apache.spark.examples.SparkPi <span class="se">\</span> + --master yarn-cluster <span class="se">\ </span> <span class="c"># can also be `yarn-client` for client mode</span> + --executor-memory 20G <span class="se">\</span> + --num-executors 50 <span class="se">\</span> + /path/to/examples.jar <span class="se">\</span> + 1000 + +<span class="c"># Run a Python application on a cluster</span> +./bin/spark-submit <span class="se">\</span> + --master spark://207.184.161.138:7077 <span class="se">\</span> + examples/src/main/python/pi.py <span class="se">\</span> + 1000 +</code></pre></div> + +<h1 id="master-urls">Master URLs</h1> + +<p>The master URL passed to Spark can be in one of the following formats:</p> + +<table class="table"> +<tr><th>Master URL</th><th>Meaning</th></tr> +<tr><td> local </td><td> Run Spark locally with one worker thread (i.e. no parallelism at all). </td></tr> +<tr><td> local[K] </td><td> Run Spark locally with K worker threads (ideally, set this to the number of cores on your machine). </td></tr> +<tr><td> local[*] </td><td> Run Spark locally with as many worker threads as logical cores on your machine.</td></tr> +<tr><td> spark://HOST:PORT </td><td> Connect to the given <a href="spark-standalone.html">Spark standalone + cluster</a> master. The port must be whichever one your master is configured to use, which is 7077 by default. +</td></tr> +<tr><td> mesos://HOST:PORT </td><td> Connect to the given <a href="running-on-mesos.html">Mesos</a> cluster. + The port must be whichever one your is configured to use, which is 5050 by default. + Or, for a Mesos cluster using ZooKeeper, use <code>mesos://zk://...</code>. +</td></tr> +<tr><td> yarn-client </td><td> Connect to a <a href="running-on-yarn.html"> YARN </a> cluster in +client mode. The cluster location will be found based on the HADOOP_CONF_DIR variable. +</td></tr> +<tr><td> yarn-cluster </td><td> Connect to a <a href="running-on-yarn.html"> YARN </a> cluster in +cluster mode. The cluster location will be found based on HADOOP_CONF_DIR. +</td></tr> +</table> + +<h1 id="loading-configuration-from-a-file">Loading Configuration from a File</h1> + +<p>The <code>spark-submit</code> script can load default <a href="configuration.html">Spark configuration values</a> from a +properties file and pass them on to your application. By default it will read options +from <code>conf/spark-defaults.conf</code> in the Spark directory. For more detail, see the section on +<a href="configuration.html#loading-default-configurations">loading default configurations</a>.</p> + +<p>Loading default Spark configurations this way can obviate the need for certain flags to +<code>spark-submit</code>. For instance, if the <code>spark.master</code> property is set, you can safely omit the +<code>--master</code> flag from <code>spark-submit</code>. In general, configuration values explicitly set on a +<code>SparkConf</code> take the highest precedence, then flags passed to <code>spark-submit</code>, then values in the +defaults file.</p> + +<p>If you are ever unclear where configuration options are coming from, you can print out fine-grained +debugging information by running <code>spark-submit</code> with the <code>--verbose</code> option.</p> + +<h1 id="advanced-dependency-management">Advanced Dependency Management</h1> +<p>When using <code>spark-submit</code>, the application jar along with any jars included with the <code>--jars</code> option +will be automatically transferred to the cluster. Spark uses the following URL scheme to allow +different strategies for disseminating jars:</p> + +<ul> + <li><strong>file:</strong> - Absolute paths and <code>file:/</code> URIs are served by the driver’s HTTP file server, and +every executor pulls the file from the driver HTTP server.</li> + <li><strong>hdfs:</strong>, <strong>http:</strong>, <strong>https:</strong>, <strong>ftp:</strong> - these pull down files and JARs from the URI as expected</li> + <li><strong>local:</strong> - a URI starting with local:/ is expected to exist as a local file on each worker node. This +means that no network IO will be incurred, and works well for large files/JARs that are pushed to each worker, +or shared via NFS, GlusterFS, etc.</li> +</ul> + +<p>Note that JARs and files are copied to the working directory for each SparkContext on the executor nodes. +This can use up a significant amount of space over time and will need to be cleaned up. With YARN, cleanup +is handled automatically, and with Spark standalone, automatic cleanup can be configured with the +<code>spark.worker.cleanup.appDataTtl</code> property.</p> + +<p>For python, the equivalent <code>--py-files</code> option can be used to distribute <code>.egg</code>, <code>.zip</code> and <code>.py</code> libraries +to executors.</p> + +<h1 id="more-information">More Information</h1> + +<p>Once you have deployed your application, the <a href="cluster-overview.html">cluster mode overview</a> describes +the components involved in distributed execution, and how to monitor and debug applications.</p> + + + </div> <!-- /container --> + + <script src="js/vendor/jquery-1.8.0.min.js"></script> + <script src="js/vendor/bootstrap.min.js"></script> + <script src="js/main.js"></script> + + <!-- MathJax Section --> + <script type="text/x-mathjax-config"> + MathJax.Hub.Config({ + TeX: { equationNumbers: { autoNumber: "AMS" } } + }); + </script> + <script type="text/javascript" + src="http://cdn.mathjax.org/mathjax/latest/MathJax.js?config=TeX-AMS-MML_HTMLorMML"></script> + <script> + MathJax.Hub.Config({ + tex2jax: { + inlineMath: [ ["$", "$"], ["\\\\(","\\\\)"] ], + displayMath: [ ["$$","$$"], ["\\[", "\\]"] ], + processEscapes: true, + skipTags: ['script', 'noscript', 'style', 'textarea', 'pre'] + } + }); + </script> + </body> +</html> |