Mirror of Apache Spark

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Matei Zaharia 5d4a0ac794 Some tweaks to docs		2013-02-25 14:23:03 -08:00
bagel	Renamed "splits" to "partitions"	2013-02-17 22:13:26 -08:00
bin	Detect whether we run on EC2 using ec2-metadata as well	2013-01-26 23:03:11 -08:00
conf	Removed streaming-env.sh.template	2013-01-06 14:15:07 -08:00
core	Add a config property for Akka lifecycle event logging	2013-02-25 14:01:24 -08:00
docs	Some tweaks to docs	2013-02-25 14:23:03 -08:00
ec2	Print cluster url after setup completes	2013-02-18 18:30:36 -08:00
examples	Fix compile error	2013-02-25 14:01:16 -08:00
project	Moving akka dependency resolver to shared.	2013-02-25 13:37:07 +05:30
python	Change numSplits to numPartitions in PySpark.	2013-02-24 13:25:09 -08:00
repl	Remove activation of profiles by default	2013-01-31 13:30:41 -08:00
repl-bin	Remove activation of profiles by default	2013-01-31 13:30:41 -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	Fixed class paths and dependencies based on Matei's comments.	2013-02-24 16:24:52 -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	Fixed class paths and dependencies based on Matei's comments.	2013-02-24 16:24:52 -08:00
pyspark	Adding IPYTHON environment variable support for launching pyspark using ipython shell	2013-02-07 16:54:31 +02:00
run	Change tabs to spaces	2013-02-25 11:53:55 -08:00
run.cmd	Add spark-shell.cmd	2012-09-25 07:26:29 -07:00
run2.cmd	Fixed class paths and dependencies based on Matei's comments.	2013-02-24 16:24:52 -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.