| <!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>Spark Streaming + Kafka Integration Guide - Spark 1.2.2 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"> |
| |
| |
| <!-- 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 ? 'https://ssl' : 'http://www') + '.google-analytics.com/ga.js'; |
| var s = document.getElementsByTagName('script')[0]; s.parentNode.insertBefore(ga, s); |
| })(); |
| </script> |
| |
| |
| </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">1.2.2</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">Scala</a></li> |
| <li><a href="api/java/index.html">Java</a></li> |
| <li><a href="api/python/index.html">Python</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="spark-standalone.html">Spark Standalone</a></li> |
| <li><a href="running-on-mesos.html">Mesos</a></li> |
| <li><a href="running-on-yarn.html">YARN</a></li> |
| <li class="divider"></li> |
| <li><a href="ec2-scripts.html">Amazon EC2</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-spark.html">Building Spark</a></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></li> |
| </ul> |
| </li> |
| </ul> |
| <!--<p class="navbar-text pull-right"><span class="version-text">v1.2.2</span></p>--> |
| </div> |
| </div> |
| </div> |
| |
| <div class="container" id="content"> |
| |
| <h1 class="title">Spark Streaming + Kafka Integration Guide</h1> |
| |
| |
| <p><a href="http://kafka.apache.org/">Apache Kafka</a> is publish-subscribe messaging rethought as a distributed, partitioned, replicated commit log service. Here we explain how to configure Spark Streaming to receive data from Kafka.</p> |
| |
| <ol> |
| <li> |
| <p><strong>Linking:</strong> In your SBT/Maven project definition, link your streaming application against the following artifact (see <a href="streaming-programming-guide.html#linking">Linking section</a> in the main programming guide for further information).</p> |
| |
| <pre><code> groupId = org.apache.spark |
| artifactId = spark-streaming-kafka_2.10 |
| version = 1.2.2 |
| </code></pre> |
| </li> |
| <li> |
| <p><strong>Programming:</strong> In the streaming application code, import <code>KafkaUtils</code> and create input DStream as follows.</p> |
| |
| <div class="codetabs"> |
| <div data-lang="scala"> |
| <pre><code> import org.apache.spark.streaming.kafka._ |
| |
| val kafkaStream = KafkaUtils.createStream( |
| streamingContext, [zookeeperQuorum], [group id of the consumer], [per-topic number of Kafka partitions to consume]) |
| </code></pre> |
| |
| <p>See the <a href="api/scala/index.html#org.apache.spark.streaming.kafka.KafkaUtils$">API docs</a> |
| and the <a href="https://github.com/apache/spark/blob/master/examples/scala-2.10/src/main/scala/org/apache/spark/examples/streaming/KafkaWordCount.scala">example</a>.</p> |
| </div> |
| <div data-lang="java"> |
| <pre><code> import org.apache.spark.streaming.kafka.*; |
| |
| JavaPairReceiverInputDStream<String, String> kafkaStream = KafkaUtils.createStream( |
| streamingContext, [zookeeperQuorum], [group id of the consumer], [per-topic number of Kafka partitions to consume]); |
| </code></pre> |
| |
| <p>See the <a href="api/java/index.html?org/apache/spark/streaming/kafka/KafkaUtils.html">API docs</a> |
| and the <a href="https://github.com/apache/spark/blob/master/examples/scala-2.10/src/main/java/org/apache/spark/examples/streaming/JavaKafkaWordCount.java">example</a>.</p> |
| </div> |
| </div> |
| |
| <p><em>Points to remember:</em></p> |
| |
| <ul> |
| <li> |
| <p>Topic partitions in Kafka does not correlate to partitions of RDDs generated in Spark Streaming. So increasing the number of topic-specific partitions in the <code>KafkaUtils.createStream()</code> only increases the number of threads using which topics that are consumed within a single receiver. It does not increase the parallelism of Spark in processing the data. Refer to the main document for more information on that.</p> |
| </li> |
| <li> |
| <p>Multiple Kafka input DStreams can be created with different groups and topics for parallel receiving of data using multiple receivers.</p> |
| </li> |
| </ul> |
| </li> |
| <li> |
| <p><strong>Deploying:</strong> Package <code>spark-streaming-kafka_2.10</code> and its dependencies (except <code>spark-core_2.10</code> and <code>spark-streaming_2.10</code> which are provided by <code>spark-submit</code>) into the application JAR. Then use <code>spark-submit</code> to launch your application (see <a href="streaming-programming-guide.html#deploying-applications">Deploying section</a> in the main programming guide).</p> |
| </li> |
| </ol> |
| |
| <p>Note that the Kafka receiver used by default is an |
| <a href="streaming-programming-guide.html#receiver-reliability"><em>unreliable</em> receiver</a> section in the |
| programming guide). In Spark 1.2, we have added an experimental <em>reliable</em> Kafka receiver that |
| provides stronger |
| <a href="streaming-programming-guide.html#fault-tolerance-semantics">fault-tolerance guarantees</a> of zero |
| data loss on failures. This receiver is automatically used when the write ahead log |
| (also introduced in Spark 1.2) is enabled |
| (see <a href="#deploying-applications.html">Deployment</a> section in the programming guide). This |
| may reduce the receiving throughput of individual Kafka receivers compared to the unreliable |
| receivers, but this can be corrected by running |
| <a href="streaming-programming-guide.html#level-of-parallelism-in-data-receiving">more receivers in parallel</a> |
| to increase aggregate throughput. Additionally, it is recommended that the replication of the |
| received data within Spark be disabled when the write ahead log is enabled as the log is already stored |
| in a replicated storage system. This can be done by setting the storage level for the input |
| stream to <code>StorageLevel.MEMORY_AND_DISK_SER</code> (that is, use |
| <code>KafkaUtils.createStream(..., StorageLevel.MEMORY_AND_DISK_SER)</code>).</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> |
| // 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(){ |
| MathJax.Hub.Config({ |
| tex2jax: { |
| inlineMath: [ ["$", "$"], ["\\\\(","\\\\)"] ], |
| displayMath: [ ["$$","$$"], ["\\[", "\\]"] ], |
| processEscapes: true, |
| skipTags: ['script', 'noscript', 'style', 'textarea', 'pre'] |
| } |
| }); |
| }; |
| script.src = ('https:' == document.location.protocol ? 'https://' : 'http://') + |
| 'cdn.mathjax.org/mathjax/latest/MathJax.js?config=TeX-AMS-MML_HTMLorMML'; |
| d.getElementsByTagName('head')[0].appendChild(script); |
| }(document)); |
| </script> |
| </body> |
| </html> |
