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diff --git a/docs/spark-standalone.md b/docs/spark-standalone.md index d81b4cd0eb..30641bd777 100644 --- a/docs/spark-standalone.md +++ b/docs/spark-standalone.md @@ -5,6 +5,17 @@ title: Spark Standalone Mode In addition to running on the Mesos or YARN cluster managers, Spark also provides a simple standalone deploy mode. You can launch a standalone cluster either manually, by starting a master and workers by hand, or use our provided [launch scripts](#cluster-launch-scripts). It is also possible to run these daemons on a single machine for testing. +# Deploying Spark Standalone to a Cluster + +The easiest way to deploy Spark is by running the `./make-distribution.sh` script to create a binary distribution. +This distribution can be deployed to any machine with the Java runtime installed; there is no need to install Scala. + +The recommended procedure is to deploy and start the master on one node first, get the master spark URL, +then modify `conf/spark-env.sh` in the `dist/` directory before deploying to all the other nodes. + +It is also possible to deploy the source directory once you have built it with `sbt assembly`. Scala 2.9.3 +will need to be deployed on all the machines as well, and SCALA_HOME will need to point to the Scala installation. + # Starting a Cluster Manually You can start a standalone master server by executing: |