Mirror of Apache Spark
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Andy Konwinski b63109763b Fix broken link in Quick Start. 2013-03-13 02:02:34 -07:00
bagel Fix doc style 2013-03-11 09:14:00 +02:00
bin Detect whether we run on EC2 using ec2-metadata as well 2013-01-26 23:03:11 -08:00
conf Document how to configure SPARK_MEM & co on a per-job basis 2012-10-13 16:20:25 -07:00
core Send block sizes as longs. 2013-03-11 14:17:05 -07:00
docs Fix broken link in Quick Start. 2013-03-13 02:02:34 -07:00
ec2 Use new Spark EC2 scripts by default 2013-02-26 23:38:50 -08:00
examples bump version to 0.7.1-SNAPSHOT in the subproject poms to keep the maven build building. 2013-02-28 23:34:34 -08:00
project Fix reference bug in Kryo serializer, add test, update version 2013-03-07 22:16:11 -08:00
python Change numSplits to numPartitions in PySpark. 2013-02-24 13:25:09 -08:00
repl bump version to 0.7.1-SNAPSHOT in the subproject poms to keep the maven build building. 2013-02-28 23:34:34 -08:00
repl-bin bump version to 0.7.1-SNAPSHOT in the subproject poms to keep the maven build building. 2013-02-28 23:34:34 -08:00
sbt Update Windows scripts to launch daemons with less RAM and fix a few 2013-02-10 21:51:49 -08:00
streaming Instead of failing to bind to a fixed, already-in-use port, let the OS choose an available port for TestServer. 2013-03-01 15:05:07 -08:00
.gitignore Merge branch 'mesos' 2013-01-24 10:27:02 +08:00
LICENSE Added BSD license 2010-12-07 10:32:17 -08:00
README.md tweak 2012-10-14 12:04:58 -07:00
kmeans_data.txt Fixed bugs 2012-01-09 11:59:52 -08:00
lr_data.txt Test commit 2012-02-06 09:58:06 -08:00
pom.xml Update kryo-serializers version in pom.xml to match previous commit 2013-03-10 15:49:11 -07:00
pyspark Adding IPYTHON environment variable support for launching pyspark using ipython shell 2013-02-07 16:54:31 +02:00
run Small hack to work around multiple JARs being built by sbt package 2013-02-26 12:24:18 -08:00
run.cmd Add spark-shell.cmd 2012-09-25 07:26:29 -07:00
run2.cmd Fix Windows script for finding examples JAR 2013-02-25 20:23:36 -08:00
spark-executor Further refactoring, and start of a standalone scheduler backend 2012-07-06 17:56:44 -07:00
spark-shell More work to allow Spark to run on the standalone deploy cluster. 2012-07-08 14:00:04 -07:00
spark-shell.cmd Add spark-shell.cmd 2012-09-25 07:26:29 -07:00

README.md

Spark

Lightning-Fast Cluster Computing - http://www.spark-project.org/

Online Documentation

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

Building

Spark requires Scala 2.9.2. The project is built using Simple Build Tool (SBT), which is packaged with it. To build Spark and its example programs, run:

sbt/sbt package

To run Spark, you will need to have Scala's bin directory in your PATH, or you will need to set the SCALA_HOME environment variable to point to where you've installed Scala. Scala must be accessible through one of these methods on your cluster's worker nodes as well as its master.

To run one of the examples, use ./run <class> <params>. For example:

./run 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 <host> 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.

A Note About Hadoop Versions

Spark uses the Hadoop core library to talk to HDFS and other Hadoop-supported storage systems. Because the HDFS API has 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 HADOOP_VERSION variable at the top of project/SparkBuild.scala, then rebuilding Spark.

Configuration

Please refer to the "Configuration" guide in the online documentation for a full overview on how to configure Spark. At the minimum, you will need to create a conf/spark-env.sh script (copy conf/spark-env.sh.template) and set the following two variables:

  • SCALA_HOME: Location where Scala is installed.

  • MESOS_NATIVE_LIBRARY: Your Mesos library (only needed if you want to run on Mesos). For example, this might be /usr/local/lib/libmesos.so on Linux.

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.