Apache Spark - A unified analytics engine for large-scale data processing
Go to file
Matei Zaharia 3ef82496f4 Merge pull request #363 from heuermh/quick-start-fix
add repositories section to quick-start SimpleJob pom.xml
2013-01-12 16:15:10 -08:00
bagel Rename environment variable for hadoop profiles to hadoopVersion 2013-01-12 15:24:13 -08:00
bin Use spark-env.sh to configure standalone master. See SPARK-638. 2012-12-14 01:20:00 +00:00
conf Document how to configure SPARK_MEM & co on a per-job basis 2012-10-13 16:20:25 -07:00
core Merge pull request #355 from shivaram/default-hadoop-pom 2013-01-12 15:38:36 -08:00
docs add repositories section to simple job pom.xml 2013-01-11 11:40:17 -06:00
ec2 Merge pull request #323 from admobius/master 2012-12-11 12:01:42 -08:00
examples Rename environment variable for hadoop profiles to hadoopVersion 2013-01-12 15:24:13 -08:00
project Merge pull request #357 from tysonjh/master 2013-01-10 19:06:07 -08:00
repl Rename environment variable for hadoop profiles to hadoopVersion 2013-01-12 15:24:13 -08:00
repl-bin Rename environment variable for hadoop profiles to hadoopVersion 2013-01-12 15:24:13 -08:00
sbt Made run script add test-classes onto the classpath only if SPARK_TESTING is set; fixes #216 2012-10-07 04:19:16 +00:00
.gitignore Fixed repl maven build to produce artifacts with the appropriate hadoop classifier and extracted repl fat-jar and debian packaging into a separate project to make Maven happy 2012-12-18 12:08:19 -08:00
kmeans_data.txt Fixed bugs 2012-01-09 11:59:52 -08:00
LICENSE Added BSD license 2010-12-07 10:32:17 -08:00
lr_data.txt Test commit 2012-02-06 09:58:06 -08:00
pom.xml Rename environment variable for hadoop profiles to hadoopVersion 2013-01-12 15:24:13 -08:00
README.md tweak 2012-10-14 12:04:58 -07:00
run Retrieve jars to a flat directory so * can be used for the classpath. 2013-01-08 14:44:33 -06:00
run.cmd Add spark-shell.cmd 2012-09-25 07:26:29 -07:00
run2.cmd Fix Java/Scala home having spaces on Windows 2012-11-14 22:37:05 -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

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.