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author | lianhuiwang <lianhuiwang09@gmail.com> | 2015-02-02 12:32:28 -0800 |
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committer | Andrew Or <andrew@databricks.com> | 2015-02-02 12:32:28 -0800 |
commit | f5e63751f0ed50ceafdc2ec5173b161a5155b646 (patch) | |
tree | 75a199b5fa514ecd48ef634666e4d32d2036ef1b /core | |
parent | b2047b55c5fc85de6b63276d8ab9610d2496e08b (diff) | |
download | spark-f5e63751f0ed50ceafdc2ec5173b161a5155b646.tar.gz spark-f5e63751f0ed50ceafdc2ec5173b161a5155b646.tar.bz2 spark-f5e63751f0ed50ceafdc2ec5173b161a5155b646.zip |
[SPARK-5173]support python application running on yarn cluster mode
now when we run python application on yarn cluster mode through spark-submit, spark-submit does not support python application on yarn cluster mode. so i modify code of submit and yarn's AM in order to support it.
through specifying .py file or primaryResource file via spark-submit, we can make pyspark run in yarn-cluster mode.
example:spark-submit --master yarn-master --num-executors 1 --driver-memory 1g --executor-memory 1g xx.py --primaryResource yy.conf
this config is same as pyspark on yarn-client mode.
firstly,we put local path of .py or primaryResource to yarn's dist.files.that can be distributed on slave nodes.and then in spark-submit we transfer --py-files and --primaryResource to yarn.Client and use "org.apache.spark.deploy.PythonRunner" to user class that can run .py files on ApplicationMaster.
in yarn.Client we transfer --py-files and --primaryResource to ApplicationMaster.
in ApplicationMaster, user's class is org.apache.spark.deploy.PythonRunner, and user's args is primaryResource and -py-files. so that can make pyspark run on ApplicationMaster.
JoshRosen tgravescs sryza
Author: lianhuiwang <lianhuiwang09@gmail.com>
Author: Wang Lianhui <lianhuiwang09@gmail.com>
Closes #3976 from lianhuiwang/SPARK-5173 and squashes the following commits:
28a8a58 [lianhuiwang] fix variable name
67f8cee [lianhuiwang] update with andrewor's comments
0319ae3 [lianhuiwang] address with sryza's comments
2385ef6 [lianhuiwang] address with sryza's comments
03640ab [lianhuiwang] add sparkHome to env
47d2fc3 [lianhuiwang] fix test
2adc8f5 [lianhuiwang] add spark.test.home
d60bc60 [lianhuiwang] fix test
5b30064 [lianhuiwang] add test
097a5ec [lianhuiwang] fix line length exceeds 100
905a106 [lianhuiwang] update with sryza and andrewor 's comments
f1f55b6 [lianhuiwang] when yarn-cluster, all python files can be non-local
172eec1 [Wang Lianhui] fix a min submit's bug
9c941bc [lianhuiwang] support python application running on yarn cluster mode
Diffstat (limited to 'core')
3 files changed, 43 insertions, 20 deletions
diff --git a/core/src/main/scala/org/apache/spark/deploy/PythonRunner.scala b/core/src/main/scala/org/apache/spark/deploy/PythonRunner.scala index 039c8719e2..53e18c4bce 100644 --- a/core/src/main/scala/org/apache/spark/deploy/PythonRunner.scala +++ b/core/src/main/scala/org/apache/spark/deploy/PythonRunner.scala @@ -26,7 +26,7 @@ import org.apache.spark.api.python.PythonUtils import org.apache.spark.util.{RedirectThread, Utils} /** - * A main class used by spark-submit to launch Python applications. It executes python as a + * A main class used to launch Python applications. It executes python as a * subprocess and then has it connect back to the JVM to access system properties, etc. */ object PythonRunner { diff --git a/core/src/main/scala/org/apache/spark/deploy/SparkSubmit.scala b/core/src/main/scala/org/apache/spark/deploy/SparkSubmit.scala index c240bcd705..02021be9f9 100644 --- a/core/src/main/scala/org/apache/spark/deploy/SparkSubmit.scala +++ b/core/src/main/scala/org/apache/spark/deploy/SparkSubmit.scala @@ -23,6 +23,8 @@ import java.net.URL import scala.collection.mutable.{ArrayBuffer, HashMap, Map} +import org.apache.hadoop.fs.Path + import org.apache.spark.executor.ExecutorURLClassLoader import org.apache.spark.util.Utils @@ -134,12 +136,27 @@ object SparkSubmit { } } + val isYarnCluster = clusterManager == YARN && deployMode == CLUSTER + + // Require all python files to be local, so we can add them to the PYTHONPATH + // In YARN cluster mode, python files are distributed as regular files, which can be non-local + if (args.isPython && !isYarnCluster) { + if (Utils.nonLocalPaths(args.primaryResource).nonEmpty) { + printErrorAndExit(s"Only local python files are supported: $args.primaryResource") + } + val nonLocalPyFiles = Utils.nonLocalPaths(args.pyFiles).mkString(",") + if (nonLocalPyFiles.nonEmpty) { + printErrorAndExit(s"Only local additional python files are supported: $nonLocalPyFiles") + } + } + // The following modes are not supported or applicable (clusterManager, deployMode) match { case (MESOS, CLUSTER) => printErrorAndExit("Cluster deploy mode is currently not supported for Mesos clusters.") - case (_, CLUSTER) if args.isPython => - printErrorAndExit("Cluster deploy mode is currently not supported for python applications.") + case (STANDALONE, CLUSTER) if args.isPython => + printErrorAndExit("Cluster deploy mode is currently not supported for python " + + "applications on standalone clusters.") case (_, CLUSTER) if isShell(args.primaryResource) => printErrorAndExit("Cluster deploy mode is not applicable to Spark shells.") case (_, CLUSTER) if isSqlShell(args.mainClass) => @@ -150,7 +167,7 @@ object SparkSubmit { } // If we're running a python app, set the main class to our specific python runner - if (args.isPython) { + if (args.isPython && deployMode == CLIENT) { if (args.primaryResource == PYSPARK_SHELL) { args.mainClass = "py4j.GatewayServer" args.childArgs = ArrayBuffer("--die-on-broken-pipe", "0") @@ -167,6 +184,13 @@ object SparkSubmit { } } + // In yarn-cluster mode for a python app, add primary resource and pyFiles to files + // that can be distributed with the job + if (args.isPython && isYarnCluster) { + args.files = mergeFileLists(args.files, args.primaryResource) + args.files = mergeFileLists(args.files, args.pyFiles) + } + // Special flag to avoid deprecation warnings at the client sysProps("SPARK_SUBMIT") = "true" @@ -245,7 +269,6 @@ object SparkSubmit { // Add the application jar automatically so the user doesn't have to call sc.addJar // For YARN cluster mode, the jar is already distributed on each node as "app.jar" // For python files, the primary resource is already distributed as a regular file - val isYarnCluster = clusterManager == YARN && deployMode == CLUSTER if (!isYarnCluster && !args.isPython) { var jars = sysProps.get("spark.jars").map(x => x.split(",").toSeq).getOrElse(Seq.empty) if (isUserJar(args.primaryResource)) { @@ -270,10 +293,22 @@ object SparkSubmit { // In yarn-cluster mode, use yarn.Client as a wrapper around the user class if (isYarnCluster) { childMainClass = "org.apache.spark.deploy.yarn.Client" - if (args.primaryResource != SPARK_INTERNAL) { - childArgs += ("--jar", args.primaryResource) + if (args.isPython) { + val mainPyFile = new Path(args.primaryResource).getName + childArgs += ("--primary-py-file", mainPyFile) + if (args.pyFiles != null) { + // These files will be distributed to each machine's working directory, so strip the + // path prefix + val pyFilesNames = args.pyFiles.split(",").map(p => (new Path(p)).getName).mkString(",") + childArgs += ("--py-files", pyFilesNames) + } + childArgs += ("--class", "org.apache.spark.deploy.PythonRunner") + } else { + if (args.primaryResource != SPARK_INTERNAL) { + childArgs += ("--jar", args.primaryResource) + } + childArgs += ("--class", args.mainClass) } - childArgs += ("--class", args.mainClass) if (args.childArgs != null) { args.childArgs.foreach { arg => childArgs += ("--arg", arg) } } diff --git a/core/src/main/scala/org/apache/spark/deploy/SparkSubmitArguments.scala b/core/src/main/scala/org/apache/spark/deploy/SparkSubmitArguments.scala index 81ec08cb6d..73e921fd83 100644 --- a/core/src/main/scala/org/apache/spark/deploy/SparkSubmitArguments.scala +++ b/core/src/main/scala/org/apache/spark/deploy/SparkSubmitArguments.scala @@ -179,18 +179,6 @@ private[spark] class SparkSubmitArguments(args: Seq[String], env: Map[String, St SparkSubmit.printErrorAndExit("--py-files given but primary resource is not a Python script") } - // Require all python files to be local, so we can add them to the PYTHONPATH - if (isPython) { - if (Utils.nonLocalPaths(primaryResource).nonEmpty) { - SparkSubmit.printErrorAndExit(s"Only local python files are supported: $primaryResource") - } - val nonLocalPyFiles = Utils.nonLocalPaths(pyFiles).mkString(",") - if (nonLocalPyFiles.nonEmpty) { - SparkSubmit.printErrorAndExit( - s"Only local additional python files are supported: $nonLocalPyFiles") - } - } - if (master.startsWith("yarn")) { val hasHadoopEnv = env.contains("HADOOP_CONF_DIR") || env.contains("YARN_CONF_DIR") if (!hasHadoopEnv && !Utils.isTesting) { |