Skip to content

HTTPS clone URL

Subversion checkout URL

You can clone with HTTPS or Subversion.

Download ZIP
Lightning-fast cluster computing in Java, Scala and Python.

This branch is 97 commits ahead, 2775 commits behind master

Fetching latest commit…

Cannot retrieve the latest commit at this time

Failed to load latest commit information.
bagel/src
bin
conf
core/src
docs
ec2
examples/src/main
project
repl
sbt
.gitignore
LICENSE
README.md
kmeans_data.txt
lr_data.txt
run
run.cmd
run2.cmd
spark-executor
spark-shell
spark-shell.cmd

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.

Something went wrong with that request. Please try again.