Skip to content
Snippets Groups Projects
user avatar
Tathagata Das authored
Updated Spark Streaming Programming Guide

Here is the updated version of the Spark Streaming Programming Guide. This is still a work in progress, but the major changes are in place. So feedback is most welcome.

In general, I have tried to make the guide to easier to understand even if the reader does not know much about Spark. The updated website is hosted here -

http://www.eecs.berkeley.edu/~tdas/spark_docs/streaming-programming-guide.html

The major changes are:
- Overview illustrates the usecases of Spark Streaming - various input sources and various output sources
- An example right after overview to quickly give an idea of what Spark Streaming program looks like
- Made Java API and examples a first class citizen like Scala by using tabs to show both Scala and Java examples (similar to AMPCamp tutorial's code tabs)
- Highlighted the DStream operations updateStateByKey and transform because of their powerful nature
- Updated driver node failure recovery text to highlight automatic recovery in Spark standalone mode
- Added information about linking and using the external input sources like Kafka and Flume
- In general, reorganized the sections to better show the Basic section and the more advanced sections like Tuning and Recovery.

Todos:
- Links to the docs of external Kafka, Flume, etc
- Illustrate window operation with figure as well as example.

Author: Tathagata Das <tathagata.das1565@gmail.com>

== Merge branch commits ==

commit 18ff10556570b39d672beeb0a32075215cfcc944
Author: Tathagata Das <tathagata.das1565@gmail.com>
Date:   Tue Jan 28 21:49:30 2014 -0800

    Fixed a lot of broken links.

commit 34a5a6008dac2e107624c7ff0db0824ee5bae45f
Author: Tathagata Das <tathagata.das1565@gmail.com>
Date:   Tue Jan 28 18:02:28 2014 -0800

    Updated github url to use SPARK_GITHUB_URL variable.

commit f338a60ae8069e0a382d2cb170227e5757cc0b7a
Author: Tathagata Das <tathagata.das1565@gmail.com>
Date:   Mon Jan 27 22:42:42 2014 -0800

    More updates based on Patrick and Harvey's comments.

commit 89a81ff25726bf6d26163e0dd938290a79582c0f
Author: Tathagata Das <tathagata.das1565@gmail.com>
Date:   Mon Jan 27 13:08:34 2014 -0800

    Updated docs based on Patricks PR comments.

commit d5b6196b532b5746e019b959a79ea0cc013a8fc3
Author: Tathagata Das <tathagata.das1565@gmail.com>
Date:   Sun Jan 26 20:15:58 2014 -0800

    Added spark.streaming.unpersist config and info on StreamingListener interface.

commit e3dcb46ab83d7071f611d9b5008ba6bc16c9f951
Author: Tathagata Das <tathagata.das1565@gmail.com>
Date:   Sun Jan 26 18:41:12 2014 -0800

    Fixed docs on StreamingContext.getOrCreate.

commit 6c29524639463f11eec721e4d17a9d7159f2944b
Author: Tathagata Das <tathagata.das1565@gmail.com>
Date:   Thu Jan 23 18:49:39 2014 -0800

    Added example and figure for window operations, and links to Kafka and Flume API docs.

commit f06b964a51bb3b21cde2ff8bdea7d9785f6ce3a9
Author: Tathagata Das <tathagata.das1565@gmail.com>
Date:   Wed Jan 22 22:49:12 2014 -0800

    Fixed missing endhighlight tag in the MLlib guide.

commit 036a7d46187ea3f2a0fb8349ef78f10d6c0b43a9
Merge: eab351d a1cd1851
Author: Tathagata Das <tathagata.das1565@gmail.com>
Date:   Wed Jan 22 22:17:42 2014 -0800

    Merge remote-tracking branch 'apache/master' into docs-update

commit eab351d05c0baef1d4b549e1581310087158d78d
Author: Tathagata Das <tathagata.das1565@gmail.com>
Date:   Wed Jan 22 22:17:15 2014 -0800

    Update Spark Streaming Programming Guide.
79302096
History

Apache Spark

Lightning-Fast Cluster Computing - http://spark.incubator.apache.org/

Online Documentation

You can find the latest Spark documentation, including a programming guide, on the project webpage at http://spark.incubator.apache.org/documentation.html. This README file only contains basic setup instructions.

Building

Spark requires Scala 2.10. The project is built using Simple Build Tool (SBT), which can be obtained here. If SBT is installed we will use the system version of sbt otherwise we will attempt to download it automatically. To build Spark and its example programs, run:

./sbt/sbt assembly

Once you've built Spark, the easiest way to start using it is the shell:

./bin/spark-shell

Or, for the Python API, the Python shell (./bin/pyspark).

Spark also comes with several sample programs in the examples directory. To run one of them, use ./bin/run-example <class> <params>. For example:

./bin/run-example org.apache.spark.examples.SparkLR local[2]

will run the Logistic Regression example locally on 2 CPUs.

Each of the example programs prints usage help if no params are given.

All of the Spark samples take a <master> parameter that is the cluster URL to connect to. This can be a mesos:// or spark:// URL, or "local" to run locally with one thread, or "local[N]" to run locally with N threads.

Running tests

Testing first requires Building Spark. Once Spark is built, tests can be run using:

./sbt/sbt test

A Note About Hadoop Versions

Spark uses the Hadoop core library to talk to HDFS and other Hadoop-supported storage systems. Because the protocols have changed in different versions of Hadoop, you must build Spark against the same version that your cluster runs. You can change the version by setting the SPARK_HADOOP_VERSION environment when building Spark.

For Apache Hadoop versions 1.x, Cloudera CDH MRv1, and other Hadoop versions without YARN, use:

# Apache Hadoop 1.2.1
$ SPARK_HADOOP_VERSION=1.2.1 sbt/sbt assembly

# Cloudera CDH 4.2.0 with MapReduce v1
$ SPARK_HADOOP_VERSION=2.0.0-mr1-cdh4.2.0 sbt/sbt assembly

For Apache Hadoop 2.2.X, 2.1.X, 2.0.X, 0.23.x, Cloudera CDH MRv2, and other Hadoop versions with YARN, also set SPARK_YARN=true:

# Apache Hadoop 2.0.5-alpha
$ SPARK_HADOOP_VERSION=2.0.5-alpha SPARK_YARN=true sbt/sbt assembly

# Cloudera CDH 4.2.0 with MapReduce v2
$ SPARK_HADOOP_VERSION=2.0.0-cdh4.2.0 SPARK_YARN=true sbt/sbt assembly

# Apache Hadoop 2.2.X and newer
$ SPARK_HADOOP_VERSION=2.2.0 SPARK_YARN=true sbt/sbt assembly

When developing a Spark application, specify the Hadoop version by adding the "hadoop-client" artifact to your project's dependencies. For example, if you're using Hadoop 1.2.1 and build your application using SBT, add this entry to libraryDependencies:

"org.apache.hadoop" % "hadoop-client" % "1.2.1"

If your project is built with Maven, add this to your POM file's <dependencies> section:

<dependency>
  <groupId>org.apache.hadoop</groupId>
  <artifactId>hadoop-client</artifactId>
  <version>1.2.1</version>
</dependency>

Configuration

Please refer to the Configuration guide in the online documentation for an overview on how to configure Spark.

Apache Incubator Notice

Apache Spark is an effort undergoing incubation at The Apache Software Foundation (ASF), sponsored by the Apache Incubator. Incubation is required of all newly accepted projects until a further review indicates that the infrastructure, communications, and decision making process have stabilized in a manner consistent with other successful ASF projects. While incubation status is not necessarily a reflection of the completeness or stability of the code, it does indicate that the project has yet to be fully endorsed by the ASF.

Contributing to Spark

Contributions via GitHub pull requests are gladly accepted from their original author. Along with any pull requests, please state that the contribution is your original work and that you license the work to the project under the project's open source license. Whether or not you state this explicitly, by submitting any copyrighted material via pull request, email, or other means you agree to license the material under the project's open source license and warrant that you have the legal authority to do so.