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Diffstat (limited to 'docs/running-on-yarn.md')
| -rw-r--r-- | docs/running-on-yarn.md | 55 |
1 files changed, 18 insertions, 37 deletions
diff --git a/docs/running-on-yarn.md b/docs/running-on-yarn.md index 66fb8d73e8..fe5334ffdc 100644 --- a/docs/running-on-yarn.md +++ b/docs/running-on-yarn.md @@ -3,50 +3,33 @@ layout: global title: Launching Spark on YARN --- -Experimental support for running over a [YARN (Hadoop +Support for running on [YARN (Hadoop NextGen)](http://hadoop.apache.org/docs/r2.0.2-alpha/hadoop-yarn/hadoop-yarn-site/YARN.html) -cluster was added to Spark in version 0.6.0. This was merged into master as part of 0.7 effort. -To build spark core with YARN support, please use the hadoop2-yarn profile. -Ex: mvn -Phadoop2-yarn clean install +was added to Spark in version 0.6.0, and improved in 0.7.0 and 0.8.0. -# Building spark core consolidated jar. +# Building a YARN-Enabled Assembly JAR -We need a consolidated spark core jar (which bundles all the required dependencies) to run Spark jobs on a yarn cluster. -This can be built either through sbt or via maven. +We need a consolidated Spark JAR (which bundles all the required dependencies) to run Spark jobs on a YARN cluster. +This can be built by setting the Hadoop version and `SPARK_YARN` environment variable, as follows: -- Building spark assembled jar via sbt. - It is a manual process of enabling it in project/SparkBuild.scala. -Please comment out the - HADOOP_VERSION, HADOOP_MAJOR_VERSION and HADOOP_YARN -variables before the line 'For Hadoop 2 YARN support' -Next, uncomment the subsequent 3 variable declaration lines (for these three variables) which enable hadoop yarn support. + SPARK_HADOOP_VERSION=2.0.5-alpha SPARK_YARN=true ./sbt/sbt assembly -Assembly of the jar Ex: +The assembled JAR will be something like this: +`./assembly/target/scala-{{site.SCALA_VERSION}}/spark-assembly_{{site.SPARK_VERSION}}-hadoop2.0.5.jar`. - ./sbt/sbt clean assembly - -The assembled jar would typically be something like : -`./core/target/spark-core-assembly-0.8.0-SNAPSHOT.jar` - - -- Building spark assembled jar via Maven. - Use the hadoop2-yarn profile and execute the package target. - -Something like this. Ex: - - mvn -Phadoop2-yarn clean package -DskipTests=true +# Preparations -This will build the shaded (consolidated) jar. Typically something like : -`./repl-bin/target/spark-repl-bin-<VERSION>-shaded-hadoop2-yarn.jar` +- Building a YARN-enabled assembly (see above). +- Your application code must be packaged into a separate JAR file. +If you want to test out the YARN deployment mode, you can use the current Spark examples. A `spark-examples_{{site.SCALA_VERSION}}-{{site.SPARK_VERSION}}` file can be generated by running `sbt/sbt assembly`. NOTE: since the documentation you're reading is for Spark version {{site.SPARK_VERSION}}, we are assuming here that you have downloaded Spark {{site.SPARK_VERSION}} or checked it out of source control. If you are using a different version of Spark, the version numbers in the jar generated by the sbt package command will obviously be different. -# Preparations +# Configuration -- Building spark core assembled jar (see above). -- Your application code must be packaged into a separate JAR file. +Most of the configs are the same for Spark on YARN as other deploys. See the Configuration page for more information on those. These are configs that are specific to SPARK on YARN. -If you want to test out the YARN deployment mode, you can use the current Spark examples. A `spark-examples_{{site.SCALA_VERSION}}-{{site.SPARK_VERSION}}` file can be generated by running `sbt/sbt package`. NOTE: since the documentation you're reading is for Spark version {{site.SPARK_VERSION}}, we are assuming here that you have downloaded Spark {{site.SPARK_VERSION}} or checked it out of source control. If you are using a different version of Spark, the version numbers in the jar generated by the sbt package command will obviously be different. +* `SPARK_YARN_USER_ENV`, to add environment variables to the Spark processes launched on YARN. This can be a comma separated list of environment variables, e.g. `SPARK_YARN_USER_ENV="JAVA_HOME=/jdk64,FOO=bar"`. # Launching Spark on YARN @@ -55,7 +38,7 @@ This would be used to connect to the cluster, write to the dfs and submit jobs t The command to launch the YARN Client is as follows: - SPARK_JAR=<SPARK_YAR_FILE> ./run spark.deploy.yarn.Client \ + SPARK_JAR=<SPARK_YARN_JAR_FILE> ./spark-class spark.deploy.yarn.Client \ --jar <YOUR_APP_JAR_FILE> \ --class <APP_MAIN_CLASS> \ --args <APP_MAIN_ARGUMENTS> \ @@ -63,12 +46,11 @@ The command to launch the YARN Client is as follows: --master-memory <MEMORY_FOR_MASTER> \ --worker-memory <MEMORY_PER_WORKER> \ --worker-cores <CORES_PER_WORKER> \ - --user <hadoop_user> \ --queue <queue_name> For example: - SPARK_JAR=./core/target/spark-core-assembly-{{site.SPARK_VERSION}}.jar ./run spark.deploy.yarn.Client \ + SPARK_JAR=./yarn/target/spark-yarn-assembly-{{site.SPARK_VERSION}}.jar ./spark-class spark.deploy.yarn.Client \ --jar examples/target/scala-{{site.SCALA_VERSION}}/spark-examples_{{site.SCALA_VERSION}}-{{site.SPARK_VERSION}}.jar \ --class spark.examples.SparkPi \ --args yarn-standalone \ @@ -83,5 +65,4 @@ The above starts a YARN Client programs which periodically polls the Application - When your application instantiates a Spark context it must use a special "yarn-standalone" master url. This starts the scheduler without forcing it to connect to a cluster. A good way to handle this is to pass "yarn-standalone" as an argument to your program, as shown in the example above. - We do not requesting container resources based on the number of cores. Thus the numbers of cores given via command line arguments cannot be guaranteed. -- Currently, we have not yet integrated with hadoop security. If --user is present, the hadoop_user specified will be used to run the tasks on the cluster. If unspecified, current user will be used (which should be valid in cluster). - Once hadoop security support is added, and if hadoop cluster is enabled with security, additional restrictions would apply via delegation tokens passed. +- The local directories used for spark will be the local directories configured for YARN (Hadoop Yarn config yarn.nodemanager.local-dirs). If the user specifies spark.local.dir, it will be ignored. |