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author | Reynold Xin <rxin@apache.org> | 2015-09-17 22:07:42 +0000 |
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committer | Reynold Xin <rxin@apache.org> | 2015-09-17 22:07:42 +0000 |
commit | ee9ffe89d608e7640a2487406b618d27e58026d6 (patch) | |
tree | 50ec819abb41a9a769d7f64eed1f0ab2084aa6ff /site/docs/1.5.0/index.html | |
parent | c7104724b279f09486ea62f4a24252e8d06f5c96 (diff) | |
download | spark-website-ee9ffe89d608e7640a2487406b618d27e58026d6.tar.gz spark-website-ee9ffe89d608e7640a2487406b618d27e58026d6.tar.bz2 spark-website-ee9ffe89d608e7640a2487406b618d27e58026d6.zip |
delete 1.5.0
Diffstat (limited to 'site/docs/1.5.0/index.html')
-rw-r--r-- | site/docs/1.5.0/index.html | 329 |
1 files changed, 0 insertions, 329 deletions
diff --git a/site/docs/1.5.0/index.html b/site/docs/1.5.0/index.html deleted file mode 100644 index 622276ee1..000000000 --- a/site/docs/1.5.0/index.html +++ /dev/null @@ -1,329 +0,0 @@ -<!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>Overview - Spark 1.5.0 Documentation</title> - - <meta name="description" content="Apache Spark 1.5.0 documentation homepage"> - - - - - <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"> - - - <!-- Google analytics script --> - <script type="text/javascript"> - var _gaq = _gaq || []; - _gaq.push(['_setAccount', 'UA-32518208-2']); - _gaq.push(['_trackPageview']); - - (function() { - var ga = document.createElement('script'); ga.type = 'text/javascript'; ga.async = true; - ga.src = ('https:' == document.location.protocol ? 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This documentation is for Spark version 1.5.0. Spark uses Hadoop’s client libraries for HDFS and YARN. Downloads are pre-packaged for a handful of popular Hadoop versions. -Users can also download a “Hadoop free” binary and run Spark with any Hadoop version -<a href="hadoop-provided.html">by augmenting Spark’s classpath</a>. </p> - -<p>If you’d like to build Spark from -source, visit <a href="building-spark.html">Building Spark</a>.</p> - -<p>Spark runs on both Windows and UNIX-like systems (e.g. Linux, Mac OS). It’s easy to run -locally on one machine — all you need is to have <code>java</code> installed on your system <code>PATH</code>, -or the <code>JAVA_HOME</code> environment variable pointing to a Java installation.</p> - -<p>Spark runs on Java 7+, Python 2.6+ and R 3.1+. For the Scala API, Spark 1.5.0 uses -Scala 2.10. You will need to use a compatible Scala version -(2.10.x).</p> - -<h1 id="running-the-examples-and-shell">Running the Examples and Shell</h1> - -<p>Spark comes with several sample programs. Scala, Java, Python and R examples are in the -<code>examples/src/main</code> directory. To run one of the Java or Scala sample programs, use -<code>bin/run-example <class> [params]</code> in the top-level Spark directory. (Behind the scenes, this -invokes the more general -<a href="submitting-applications.html"><code>spark-submit</code> script</a> for -launching applications). For example,</p> - -<pre><code>./bin/run-example SparkPi 10 -</code></pre> - -<p>You can also run Spark interactively through a modified version of the Scala shell. This is a -great way to learn the framework.</p> - -<pre><code>./bin/spark-shell --master local[2] -</code></pre> - -<p>The <code>--master</code> option specifies the -<a href="submitting-applications.html#master-urls">master URL for a distributed cluster</a>, or <code>local</code> to run -locally with one thread, or <code>local[N]</code> to run locally with N threads. You should start by using -<code>local</code> for testing. For a full list of options, run Spark shell with the <code>--help</code> option.</p> - -<p>Spark also provides a Python API. To run Spark interactively in a Python interpreter, use -<code>bin/pyspark</code>:</p> - -<pre><code>./bin/pyspark --master local[2] -</code></pre> - -<p>Example applications are also provided in Python. For example,</p> - -<pre><code>./bin/spark-submit examples/src/main/python/pi.py 10 -</code></pre> - -<p>Spark also provides an experimental <a href="sparkr.html">R API</a> since 1.4 (only DataFrames APIs included). -To run Spark interactively in a R interpreter, use <code>bin/sparkR</code>:</p> - -<pre><code>./bin/sparkR --master local[2] -</code></pre> - -<p>Example applications are also provided in R. For example,</p> - -<pre><code>./bin/spark-submit examples/src/main/r/dataframe.R -</code></pre> - -<h1 id="launching-on-a-cluster">Launching on a Cluster</h1> - -<p>The Spark <a href="cluster-overview.html">cluster mode overview</a> explains the key concepts in running on a cluster. -Spark can run both by itself, or over several existing cluster managers. It currently provides several -options for deployment:</p> - -<ul> - <li><a href="ec2-scripts.html">Amazon EC2</a>: our EC2 scripts let you launch a cluster in about 5 minutes</li> - <li><a href="spark-standalone.html">Standalone Deploy Mode</a>: simplest way to deploy Spark on a private cluster</li> - <li><a href="running-on-mesos.html">Apache Mesos</a></li> - <li><a href="running-on-yarn.html">Hadoop YARN</a></li> -</ul> - -<h1 id="where-to-go-from-here">Where to Go from Here</h1> - -<p><strong>Programming Guides:</strong></p> - -<ul> - <li><a href="quick-start.html">Quick Start</a>: a quick introduction to the Spark API; start here!</li> - <li><a href="programming-guide.html">Spark Programming Guide</a>: detailed overview of Spark -in all supported languages (Scala, Java, Python, R)</li> - <li>Modules built on Spark: - <ul> - <li><a href="streaming-programming-guide.html">Spark Streaming</a>: processing real-time data streams</li> - <li><a href="sql-programming-guide.html">Spark SQL and DataFrames</a>: support for structured data and relational queries</li> - <li><a href="mllib-guide.html">MLlib</a>: built-in machine learning library</li> - <li><a href="graphx-programming-guide.html">GraphX</a>: Spark’s new API for graph processing</li> - <li><a href="bagel-programming-guide.html">Bagel (Pregel on Spark)</a>: older, simple graph processing model</li> - </ul> - </li> -</ul> - -<p><strong>API Docs:</strong></p> - -<ul> - <li><a href="api/scala/index.html#org.apache.spark.package">Spark Scala API (Scaladoc)</a></li> - <li><a href="api/java/index.html">Spark Java API (Javadoc)</a></li> - <li><a href="api/python/index.html">Spark Python API (Sphinx)</a></li> - <li><a href="api/R/index.html">Spark R API (Roxygen2)</a></li> -</ul> - -<p><strong>Deployment Guides:</strong></p> - -<ul> - <li><a href="cluster-overview.html">Cluster Overview</a>: overview of concepts and components when running on a cluster</li> - <li><a href="submitting-applications.html">Submitting Applications</a>: packaging and deploying applications</li> - <li>Deployment modes: - <ul> - <li><a href="ec2-scripts.html">Amazon EC2</a>: scripts that let you launch a cluster on EC2 in about 5 minutes</li> - <li><a href="spark-standalone.html">Standalone Deploy Mode</a>: launch a standalone cluster quickly without a third-party cluster manager</li> - <li><a href="running-on-mesos.html">Mesos</a>: deploy a private cluster using - <a href="http://mesos.apache.org">Apache Mesos</a></li> - <li><a href="running-on-yarn.html">YARN</a>: deploy Spark on top of Hadoop NextGen (YARN)</li> - </ul> - </li> -</ul> - -<p><strong>Other Documents:</strong></p> - -<ul> - <li><a href="configuration.html">Configuration</a>: customize Spark via its configuration system</li> - <li><a href="monitoring.html">Monitoring</a>: track the behavior of your applications</li> - <li><a href="tuning.html">Tuning Guide</a>: best practices to optimize performance and memory use</li> - <li><a href="job-scheduling.html">Job Scheduling</a>: scheduling resources across and within Spark applications</li> - <li><a href="security.html">Security</a>: Spark security support</li> - <li><a href="hardware-provisioning.html">Hardware Provisioning</a>: recommendations for cluster hardware</li> - <li><a href="hadoop-third-party-distributions.html">3<sup>rd</sup> Party Hadoop Distributions</a>: using common Hadoop distributions</li> - <li>Integration with other storage systems: - <ul> - <li><a href="storage-openstack-swift.html">OpenStack Swift</a></li> - </ul> - </li> - <li><a href="building-spark.html">Building Spark</a>: build Spark using the Maven system</li> - <li><a href="https://cwiki.apache.org/confluence/display/SPARK/Contributing+to+Spark">Contributing to Spark</a></li> - <li><a href="https://cwiki.apache.org/confluence/display/SPARK/Supplemental+Spark+Projects">Supplemental Projects</a>: related third party Spark projects</li> -</ul> - -<p><strong>External Resources:</strong></p> - -<ul> - <li><a href="http://spark.apache.org">Spark Homepage</a></li> - <li><a href="https://cwiki.apache.org/confluence/display/SPARK">Spark Wiki</a></li> - <li><a href="http://spark.apache.org/community.html">Spark Community</a> resources, including local meetups</li> - <li><a href="http://stackoverflow.com/questions/tagged/apache-spark">StackOverflow tag <code>apache-spark</code></a></li> - <li><a href="http://spark.apache.org/mailing-lists.html">Mailing Lists</a>: ask questions about Spark here</li> - <li><a href="http://ampcamp.berkeley.edu/">AMP Camps</a>: a series of training camps at UC Berkeley that featured talks and -exercises about Spark, Spark Streaming, Mesos, and more. <a href="http://ampcamp.berkeley.edu/3/">Videos</a>, -<a href="http://ampcamp.berkeley.edu/3/">slides</a> and <a href="http://ampcamp.berkeley.edu/3/exercises/">exercises</a> are -available online for free.</li> - <li><a href="http://spark.apache.org/examples.html">Code Examples</a>: more are also available in the <code>examples</code> subfolder of Spark (<a href="https://github.com/apache/spark/tree/master/examples/src/main/scala/org/apache/spark/examples">Scala</a>, - <a href="https://github.com/apache/spark/tree/master/examples/src/main/java/org/apache/spark/examples">Java</a>, - <a href="https://github.com/apache/spark/tree/master/examples/src/main/python">Python</a>, - <a href="https://github.com/apache/spark/tree/master/examples/src/main/r">R</a>)</li> -</ul> - - - </div> <!-- /container --> - - <script src="js/vendor/jquery-1.8.0.min.js"></script> - <script src="js/vendor/bootstrap.min.js"></script> - <script src="js/vendor/anchor.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> - // Note that we load MathJax this way to work with local file (file://), HTTP and HTTPS. - // We could use "//cdn.mathjax...", but that won't support "file://". - (function(d, script) { - script = d.createElement('script'); - script.type = 'text/javascript'; - script.async = true; - script.onload = function(){ - 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