Yarn workerRunnable refactor
Project: http://git-wip-us.apache.org/repos/asf/incubator-spark/repo Commit: http://git-wip-us.apache.org/repos/asf/incubator-spark/commit/161ab939 Tree: http://git-wip-us.apache.org/repos/asf/incubator-spark/tree/161ab939 Diff: http://git-wip-us.apache.org/repos/asf/incubator-spark/diff/161ab939 Branch: refs/heads/master Commit: 161ab93989d6fafdfb772e9230df984a5f902c7d Parents: 79a5ba3 Author: Raymond Liu <raymond....@intel.com> Authored: Thu Jan 9 14:16:07 2014 +0800 Committer: Raymond Liu <raymond....@intel.com> Committed: Tue Jan 14 10:36:00 2014 +0800 ---------------------------------------------------------------------- .../spark/deploy/yarn/WorkerRunnable.scala | 126 +------------ .../spark/deploy/yarn/WorkerRunnableUtil.scala | 175 +++++++++++++++++++ .../spark/deploy/yarn/WorkerRunnable.scala | 130 +------------- 3 files changed, 184 insertions(+), 247 deletions(-) ---------------------------------------------------------------------- http://git-wip-us.apache.org/repos/asf/incubator-spark/blob/161ab939/yarn/alpha/src/main/scala/org/apache/spark/deploy/yarn/WorkerRunnable.scala ---------------------------------------------------------------------- diff --git a/yarn/alpha/src/main/scala/org/apache/spark/deploy/yarn/WorkerRunnable.scala b/yarn/alpha/src/main/scala/org/apache/spark/deploy/yarn/WorkerRunnable.scala index 1c28d6c..8c686e3 100644 --- a/yarn/alpha/src/main/scala/org/apache/spark/deploy/yarn/WorkerRunnable.scala +++ b/yarn/alpha/src/main/scala/org/apache/spark/deploy/yarn/WorkerRunnable.scala @@ -25,12 +25,10 @@ import scala.collection.JavaConversions._ import scala.collection.mutable.HashMap import org.apache.hadoop.conf.Configuration -import org.apache.hadoop.fs.Path import org.apache.hadoop.io.DataOutputBuffer import org.apache.hadoop.net.NetUtils import org.apache.hadoop.security.UserGroupInformation import org.apache.hadoop.yarn.api._ -import org.apache.hadoop.yarn.api.ApplicationConstants.Environment import org.apache.hadoop.yarn.api.records._ import org.apache.hadoop.yarn.api.protocolrecords._ import org.apache.hadoop.yarn.conf.YarnConfiguration @@ -43,16 +41,17 @@ import org.apache.spark.{SparkConf, Logging} class WorkerRunnable( container: Container, conf: Configuration, - sparkConf: SparkConf, + spConf: SparkConf, masterAddress: String, slaveId: String, hostname: String, workerMemory: Int, workerCores: Int) - extends Runnable with Logging { + extends Runnable with WorkerRunnableUtil with Logging { var rpc: YarnRPC = YarnRPC.create(conf) var cm: ContainerManager = _ + val sparkConf = spConf val yarnConf: YarnConfiguration = new YarnConfiguration(conf) def run = { @@ -75,43 +74,6 @@ class WorkerRunnable( val env = prepareEnvironment ctx.setEnvironment(env) - // Extra options for the JVM - var JAVA_OPTS = "" - // Set the JVM memory - val workerMemoryString = workerMemory + "m" - JAVA_OPTS += "-Xms" + workerMemoryString + " -Xmx" + workerMemoryString + " " - if (env.isDefinedAt("SPARK_JAVA_OPTS")) { - JAVA_OPTS += env("SPARK_JAVA_OPTS") + " " - } - - JAVA_OPTS += " -Djava.io.tmpdir=" + - new Path(Environment.PWD.$(), YarnConfiguration.DEFAULT_CONTAINER_TEMP_DIR) + " " - - // Commenting it out for now - so that people can refer to the properties if required. Remove - // it once cpuset version is pushed out. - // The context is, default gc for server class machines end up using all cores to do gc - hence - // if there are multiple containers in same node, spark gc effects all other containers - // performance (which can also be other spark containers) - // Instead of using this, rely on cpusets by YARN to enforce spark behaves 'properly' in - // multi-tenant environments. Not sure how default java gc behaves if it is limited to subset - // of cores on a node. -/* - else { - // If no java_opts specified, default to using -XX:+CMSIncrementalMode - // It might be possible that other modes/config is being done in SPARK_JAVA_OPTS, so we dont - // want to mess with it. - // In our expts, using (default) throughput collector has severe perf ramnifications in - // multi-tennent machines - // The options are based on - // http://www.oracle.com/technetwork/java/gc-tuning-5-138395.html#0.0.0.%20When%20to%20Use%20the%20Concurrent%20Low%20Pause%20Collector|outline - JAVA_OPTS += " -XX:+UseConcMarkSweepGC " - JAVA_OPTS += " -XX:+CMSIncrementalMode " - JAVA_OPTS += " -XX:+CMSIncrementalPacing " - JAVA_OPTS += " -XX:CMSIncrementalDutyCycleMin=0 " - JAVA_OPTS += " -XX:CMSIncrementalDutyCycle=10 " - } -*/ - ctx.setUser(UserGroupInformation.getCurrentUser().getShortUserName()) val credentials = UserGroupInformation.getCurrentUser().getCredentials() @@ -119,28 +81,7 @@ class WorkerRunnable( credentials.writeTokenStorageToStream(dob) ctx.setContainerTokens(ByteBuffer.wrap(dob.getData())) - var javaCommand = "java" - val javaHome = System.getenv("JAVA_HOME") - if ((javaHome != null && !javaHome.isEmpty()) || env.isDefinedAt("JAVA_HOME")) { - javaCommand = Environment.JAVA_HOME.$() + "/bin/java" - } - - val commands = List[String](javaCommand + - " -server " + - // Kill if OOM is raised - leverage yarn's failure handling to cause rescheduling. - // Not killing the task leaves various aspects of the worker and (to some extent) the jvm in - // an inconsistent state. - // TODO: If the OOM is not recoverable by rescheduling it on different node, then do - // 'something' to fail job ... akin to blacklisting trackers in mapred ? - " -XX:OnOutOfMemoryError='kill %p' " + - JAVA_OPTS + - " org.apache.spark.executor.CoarseGrainedExecutorBackend " + - masterAddress + " " + - slaveId + " " + - hostname + " " + - workerCores + - " 1> " + ApplicationConstants.LOG_DIR_EXPANSION_VAR + "/stdout" + - " 2> " + ApplicationConstants.LOG_DIR_EXPANSION_VAR + "/stderr") + val commands = prepareCommand(masterAddress, slaveId, hostname, workerMemory, workerCores) logInfo("Setting up worker with commands: " + commands) ctx.setCommands(commands) @@ -151,65 +92,6 @@ class WorkerRunnable( cm.startContainer(startReq) } - private def setupDistributedCache( - file: String, - rtype: LocalResourceType, - localResources: HashMap[String, LocalResource], - timestamp: String, - size: String, - vis: String) = { - val uri = new URI(file) - val amJarRsrc = Records.newRecord(classOf[LocalResource]).asInstanceOf[LocalResource] - amJarRsrc.setType(rtype) - amJarRsrc.setVisibility(LocalResourceVisibility.valueOf(vis)) - amJarRsrc.setResource(ConverterUtils.getYarnUrlFromURI(uri)) - amJarRsrc.setTimestamp(timestamp.toLong) - amJarRsrc.setSize(size.toLong) - localResources(uri.getFragment()) = amJarRsrc - } - - def prepareLocalResources: HashMap[String, LocalResource] = { - logInfo("Preparing Local resources") - val localResources = HashMap[String, LocalResource]() - - if (System.getenv("SPARK_YARN_CACHE_FILES") != null) { - val timeStamps = System.getenv("SPARK_YARN_CACHE_FILES_TIME_STAMPS").split(',') - val fileSizes = System.getenv("SPARK_YARN_CACHE_FILES_FILE_SIZES").split(',') - val distFiles = System.getenv("SPARK_YARN_CACHE_FILES").split(',') - val visibilities = System.getenv("SPARK_YARN_CACHE_FILES_VISIBILITIES").split(',') - for( i <- 0 to distFiles.length - 1) { - setupDistributedCache(distFiles(i), LocalResourceType.FILE, localResources, timeStamps(i), - fileSizes(i), visibilities(i)) - } - } - - if (System.getenv("SPARK_YARN_CACHE_ARCHIVES") != null) { - val timeStamps = System.getenv("SPARK_YARN_CACHE_ARCHIVES_TIME_STAMPS").split(',') - val fileSizes = System.getenv("SPARK_YARN_CACHE_ARCHIVES_FILE_SIZES").split(',') - val distArchives = System.getenv("SPARK_YARN_CACHE_ARCHIVES").split(',') - val visibilities = System.getenv("SPARK_YARN_CACHE_ARCHIVES_VISIBILITIES").split(',') - for( i <- 0 to distArchives.length - 1) { - setupDistributedCache(distArchives(i), LocalResourceType.ARCHIVE, localResources, - timeStamps(i), fileSizes(i), visibilities(i)) - } - } - - logInfo("Prepared Local resources " + localResources) - localResources - } - - def prepareEnvironment: HashMap[String, String] = { - val env = new HashMap[String, String]() - - ClientBase.populateClasspath(yarnConf, sparkConf, System.getenv("SPARK_YARN_LOG4J_PATH") != null, env) - - // Allow users to specify some environment variables - Apps.setEnvFromInputString(env, System.getenv("SPARK_YARN_USER_ENV")) - - System.getenv().filterKeys(_.startsWith("SPARK")).foreach { case (k,v) => env(k) = v } - env - } - def connectToCM: ContainerManager = { val cmHostPortStr = container.getNodeId().getHost() + ":" + container.getNodeId().getPort() val cmAddress = NetUtils.createSocketAddr(cmHostPortStr) http://git-wip-us.apache.org/repos/asf/incubator-spark/blob/161ab939/yarn/common/src/main/scala/org/apache/spark/deploy/yarn/WorkerRunnableUtil.scala ---------------------------------------------------------------------- diff --git a/yarn/common/src/main/scala/org/apache/spark/deploy/yarn/WorkerRunnableUtil.scala b/yarn/common/src/main/scala/org/apache/spark/deploy/yarn/WorkerRunnableUtil.scala new file mode 100644 index 0000000..3c9379d --- /dev/null +++ b/yarn/common/src/main/scala/org/apache/spark/deploy/yarn/WorkerRunnableUtil.scala @@ -0,0 +1,175 @@ +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.deploy.yarn + +import java.net.URI +import java.nio.ByteBuffer +import java.security.PrivilegedExceptionAction + +import scala.collection.JavaConversions._ +import scala.collection.mutable.HashMap + +import org.apache.hadoop.conf.Configuration +import org.apache.hadoop.fs.Path +import org.apache.hadoop.io.DataOutputBuffer +import org.apache.hadoop.net.NetUtils +import org.apache.hadoop.security.UserGroupInformation +import org.apache.hadoop.yarn.api._ +import org.apache.hadoop.yarn.api.ApplicationConstants.Environment +import org.apache.hadoop.yarn.api.records._ +import org.apache.hadoop.yarn.api.protocolrecords._ +import org.apache.hadoop.yarn.util.{Apps, ConverterUtils, Records} + +import org.apache.spark.{SparkConf, Logging} +import org.apache.hadoop.yarn.conf.YarnConfiguration + + +trait WorkerRunnableUtil extends Logging { + + val yarnConf: YarnConfiguration + val sparkConf: SparkConf + lazy val env = prepareEnvironment + + def prepareCommand(masterAddress: String, + slaveId: String, + hostname: String, + workerMemory: Int, + workerCores: Int) = { + // Extra options for the JVM + var JAVA_OPTS = "" + // Set the JVM memory + val workerMemoryString = workerMemory + "m" + JAVA_OPTS += "-Xms" + workerMemoryString + " -Xmx" + workerMemoryString + " " + if (env.isDefinedAt("SPARK_JAVA_OPTS")) { + JAVA_OPTS += env("SPARK_JAVA_OPTS") + " " + } + + JAVA_OPTS += " -Djava.io.tmpdir=" + + new Path(Environment.PWD.$(), YarnConfiguration.DEFAULT_CONTAINER_TEMP_DIR) + " " + + // Commenting it out for now - so that people can refer to the properties if required. Remove + // it once cpuset version is pushed out. + // The context is, default gc for server class machines end up using all cores to do gc - hence + // if there are multiple containers in same node, spark gc effects all other containers + // performance (which can also be other spark containers) + // Instead of using this, rely on cpusets by YARN to enforce spark behaves 'properly' in + // multi-tenant environments. Not sure how default java gc behaves if it is limited to subset + // of cores on a node. + /* + else { + // If no java_opts specified, default to using -XX:+CMSIncrementalMode + // It might be possible that other modes/config is being done in SPARK_JAVA_OPTS, so we dont + // want to mess with it. + // In our expts, using (default) throughput collector has severe perf ramnifications in + // multi-tennent machines + // The options are based on + // http://www.oracle.com/technetwork/java/gc-tuning-5-138395.html#0.0.0.%20When%20to%20Use%20the%20Concurrent%20Low%20Pause%20Collector|outline + JAVA_OPTS += " -XX:+UseConcMarkSweepGC " + JAVA_OPTS += " -XX:+CMSIncrementalMode " + JAVA_OPTS += " -XX:+CMSIncrementalPacing " + JAVA_OPTS += " -XX:CMSIncrementalDutyCycleMin=0 " + JAVA_OPTS += " -XX:CMSIncrementalDutyCycle=10 " + } + */ + + var javaCommand = "java" + val javaHome = System.getenv("JAVA_HOME") + if ((javaHome != null && !javaHome.isEmpty()) || env.isDefinedAt("JAVA_HOME")) { + javaCommand = Environment.JAVA_HOME.$() + "/bin/java" + } + + val commands = List[String](javaCommand + + " -server " + + // Kill if OOM is raised - leverage yarn's failure handling to cause rescheduling. + // Not killing the task leaves various aspects of the worker and (to some extent) the jvm in + // an inconsistent state. + // TODO: If the OOM is not recoverable by rescheduling it on different node, then do + // 'something' to fail job ... akin to blacklisting trackers in mapred ? + " -XX:OnOutOfMemoryError='kill %p' " + + JAVA_OPTS + + " org.apache.spark.executor.CoarseGrainedExecutorBackend " + + masterAddress + " " + + slaveId + " " + + hostname + " " + + workerCores + + " 1> " + ApplicationConstants.LOG_DIR_EXPANSION_VAR + "/stdout" + + " 2> " + ApplicationConstants.LOG_DIR_EXPANSION_VAR + "/stderr") + + commands + } + + private def setupDistributedCache( + file: String, + rtype: LocalResourceType, + localResources: HashMap[String, LocalResource], + timestamp: String, + size: String, + vis: String) = { + val uri = new URI(file) + val amJarRsrc = Records.newRecord(classOf[LocalResource]).asInstanceOf[LocalResource] + amJarRsrc.setType(rtype) + amJarRsrc.setVisibility(LocalResourceVisibility.valueOf(vis)) + amJarRsrc.setResource(ConverterUtils.getYarnUrlFromURI(uri)) + amJarRsrc.setTimestamp(timestamp.toLong) + amJarRsrc.setSize(size.toLong) + localResources(uri.getFragment()) = amJarRsrc + } + + def prepareLocalResources: HashMap[String, LocalResource] = { + logInfo("Preparing Local resources") + val localResources = HashMap[String, LocalResource]() + + if (System.getenv("SPARK_YARN_CACHE_FILES") != null) { + val timeStamps = System.getenv("SPARK_YARN_CACHE_FILES_TIME_STAMPS").split(',') + val fileSizes = System.getenv("SPARK_YARN_CACHE_FILES_FILE_SIZES").split(',') + val distFiles = System.getenv("SPARK_YARN_CACHE_FILES").split(',') + val visibilities = System.getenv("SPARK_YARN_CACHE_FILES_VISIBILITIES").split(',') + for( i <- 0 to distFiles.length - 1) { + setupDistributedCache(distFiles(i), LocalResourceType.FILE, localResources, timeStamps(i), + fileSizes(i), visibilities(i)) + } + } + + if (System.getenv("SPARK_YARN_CACHE_ARCHIVES") != null) { + val timeStamps = System.getenv("SPARK_YARN_CACHE_ARCHIVES_TIME_STAMPS").split(',') + val fileSizes = System.getenv("SPARK_YARN_CACHE_ARCHIVES_FILE_SIZES").split(',') + val distArchives = System.getenv("SPARK_YARN_CACHE_ARCHIVES").split(',') + val visibilities = System.getenv("SPARK_YARN_CACHE_ARCHIVES_VISIBILITIES").split(',') + for( i <- 0 to distArchives.length - 1) { + setupDistributedCache(distArchives(i), LocalResourceType.ARCHIVE, localResources, + timeStamps(i), fileSizes(i), visibilities(i)) + } + } + + logInfo("Prepared Local resources " + localResources) + localResources + } + + def prepareEnvironment: HashMap[String, String] = { + val env = new HashMap[String, String]() + + ClientBase.populateClasspath(yarnConf, sparkConf, System.getenv("SPARK_YARN_LOG4J_PATH") != null, env) + + // Allow users to specify some environment variables + Apps.setEnvFromInputString(env, System.getenv("SPARK_YARN_USER_ENV")) + + System.getenv().filterKeys(_.startsWith("SPARK")).foreach { case (k,v) => env(k) = v } + env + } + +} http://git-wip-us.apache.org/repos/asf/incubator-spark/blob/161ab939/yarn/stable/src/main/scala/org/apache/spark/deploy/yarn/WorkerRunnable.scala ---------------------------------------------------------------------- diff --git a/yarn/stable/src/main/scala/org/apache/spark/deploy/yarn/WorkerRunnable.scala b/yarn/stable/src/main/scala/org/apache/spark/deploy/yarn/WorkerRunnable.scala index 06d40df..ab4a79b 100644 --- a/yarn/stable/src/main/scala/org/apache/spark/deploy/yarn/WorkerRunnable.scala +++ b/yarn/stable/src/main/scala/org/apache/spark/deploy/yarn/WorkerRunnable.scala @@ -17,20 +17,16 @@ package org.apache.spark.deploy.yarn -import java.net.URI import java.nio.ByteBuffer import java.security.PrivilegedExceptionAction import scala.collection.JavaConversions._ -import scala.collection.mutable.HashMap import org.apache.hadoop.conf.Configuration -import org.apache.hadoop.fs.Path import org.apache.hadoop.io.DataOutputBuffer import org.apache.hadoop.net.NetUtils import org.apache.hadoop.security.UserGroupInformation import org.apache.hadoop.yarn.api._ -import org.apache.hadoop.yarn.api.ApplicationConstants.Environment import org.apache.hadoop.yarn.api.records._ import org.apache.hadoop.yarn.api.records.impl.pb.ProtoUtils import org.apache.hadoop.yarn.api.protocolrecords._ @@ -45,16 +41,17 @@ import org.apache.spark.{SparkConf, Logging} class WorkerRunnable( container: Container, conf: Configuration, - sparkConf: SparkConf, + spConf: SparkConf, masterAddress: String, slaveId: String, hostname: String, workerMemory: Int, workerCores: Int) - extends Runnable with Logging { + extends Runnable with WorkerRunnableUtil with Logging { var rpc: YarnRPC = YarnRPC.create(conf) var nmClient: NMClient = _ + val sparkConf = spConf val yarnConf: YarnConfiguration = new YarnConfiguration(conf) def run = { @@ -74,73 +71,15 @@ class WorkerRunnable( val localResources = prepareLocalResources ctx.setLocalResources(localResources) - val env = prepareEnvironment ctx.setEnvironment(env) - // Extra options for the JVM - var JAVA_OPTS = "" - // Set the JVM memory - val workerMemoryString = workerMemory + "m" - JAVA_OPTS += "-Xms" + workerMemoryString + " -Xmx" + workerMemoryString + " " - if (env.isDefinedAt("SPARK_JAVA_OPTS")) { - JAVA_OPTS += env("SPARK_JAVA_OPTS") + " " - } - - JAVA_OPTS += " -Djava.io.tmpdir=" + - new Path(Environment.PWD.$(), YarnConfiguration.DEFAULT_CONTAINER_TEMP_DIR) + " " - - // Commenting it out for now - so that people can refer to the properties if required. Remove - // it once cpuset version is pushed out. - // The context is, default gc for server class machines end up using all cores to do gc - hence - // if there are multiple containers in same node, spark gc effects all other containers - // performance (which can also be other spark containers) - // Instead of using this, rely on cpusets by YARN to enforce spark behaves 'properly' in - // multi-tenant environments. Not sure how default java gc behaves if it is limited to subset - // of cores on a node. -/* - else { - // If no java_opts specified, default to using -XX:+CMSIncrementalMode - // It might be possible that other modes/config is being done in SPARK_JAVA_OPTS, so we dont - // want to mess with it. - // In our expts, using (default) throughput collector has severe perf ramnifications in - // multi-tennent machines - // The options are based on - // http://www.oracle.com/technetwork/java/gc-tuning-5-138395.html#0.0.0.%20When%20to%20Use%20the%20Concurrent%20Low%20Pause%20Collector|outline - JAVA_OPTS += " -XX:+UseConcMarkSweepGC " - JAVA_OPTS += " -XX:+CMSIncrementalMode " - JAVA_OPTS += " -XX:+CMSIncrementalPacing " - JAVA_OPTS += " -XX:CMSIncrementalDutyCycleMin=0 " - JAVA_OPTS += " -XX:CMSIncrementalDutyCycle=10 " - } -*/ - val credentials = UserGroupInformation.getCurrentUser().getCredentials() val dob = new DataOutputBuffer() credentials.writeTokenStorageToStream(dob) ctx.setTokens(ByteBuffer.wrap(dob.getData())) - var javaCommand = "java" - val javaHome = System.getenv("JAVA_HOME") - if ((javaHome != null && !javaHome.isEmpty()) || env.isDefinedAt("JAVA_HOME")) { - javaCommand = Environment.JAVA_HOME.$() + "/bin/java" - } - - val commands = List[String](javaCommand + - " -server " + - // Kill if OOM is raised - leverage yarn's failure handling to cause rescheduling. - // Not killing the task leaves various aspects of the worker and (to some extent) the jvm in - // an inconsistent state. - // TODO: If the OOM is not recoverable by rescheduling it on different node, then do - // 'something' to fail job ... akin to blacklisting trackers in mapred ? - " -XX:OnOutOfMemoryError='kill %p' " + - JAVA_OPTS + - " org.apache.spark.executor.CoarseGrainedExecutorBackend " + - masterAddress + " " + - slaveId + " " + - hostname + " " + - workerCores + - " 1> " + ApplicationConstants.LOG_DIR_EXPANSION_VAR + "/stdout" + - " 2> " + ApplicationConstants.LOG_DIR_EXPANSION_VAR + "/stderr") + val commands = prepareCommand(masterAddress, slaveId, hostname, workerMemory, workerCores) + logInfo("Setting up worker with commands: " + commands) ctx.setCommands(commands) @@ -148,63 +87,4 @@ class WorkerRunnable( nmClient.startContainer(container, ctx) } - private def setupDistributedCache( - file: String, - rtype: LocalResourceType, - localResources: HashMap[String, LocalResource], - timestamp: String, - size: String, - vis: String) = { - val uri = new URI(file) - val amJarRsrc = Records.newRecord(classOf[LocalResource]).asInstanceOf[LocalResource] - amJarRsrc.setType(rtype) - amJarRsrc.setVisibility(LocalResourceVisibility.valueOf(vis)) - amJarRsrc.setResource(ConverterUtils.getYarnUrlFromURI(uri)) - amJarRsrc.setTimestamp(timestamp.toLong) - amJarRsrc.setSize(size.toLong) - localResources(uri.getFragment()) = amJarRsrc - } - - def prepareLocalResources: HashMap[String, LocalResource] = { - logInfo("Preparing Local resources") - val localResources = HashMap[String, LocalResource]() - - if (System.getenv("SPARK_YARN_CACHE_FILES") != null) { - val timeStamps = System.getenv("SPARK_YARN_CACHE_FILES_TIME_STAMPS").split(',') - val fileSizes = System.getenv("SPARK_YARN_CACHE_FILES_FILE_SIZES").split(',') - val distFiles = System.getenv("SPARK_YARN_CACHE_FILES").split(',') - val visibilities = System.getenv("SPARK_YARN_CACHE_FILES_VISIBILITIES").split(',') - for( i <- 0 to distFiles.length - 1) { - setupDistributedCache(distFiles(i), LocalResourceType.FILE, localResources, timeStamps(i), - fileSizes(i), visibilities(i)) - } - } - - if (System.getenv("SPARK_YARN_CACHE_ARCHIVES") != null) { - val timeStamps = System.getenv("SPARK_YARN_CACHE_ARCHIVES_TIME_STAMPS").split(',') - val fileSizes = System.getenv("SPARK_YARN_CACHE_ARCHIVES_FILE_SIZES").split(',') - val distArchives = System.getenv("SPARK_YARN_CACHE_ARCHIVES").split(',') - val visibilities = System.getenv("SPARK_YARN_CACHE_ARCHIVES_VISIBILITIES").split(',') - for( i <- 0 to distArchives.length - 1) { - setupDistributedCache(distArchives(i), LocalResourceType.ARCHIVE, localResources, - timeStamps(i), fileSizes(i), visibilities(i)) - } - } - - logInfo("Prepared Local resources " + localResources) - localResources - } - - def prepareEnvironment: HashMap[String, String] = { - val env = new HashMap[String, String]() - - ClientBase.populateClasspath(yarnConf, sparkConf, System.getenv("SPARK_YARN_LOG4J_PATH") != null, env) - - // Allow users to specify some environment variables - Apps.setEnvFromInputString(env, System.getenv("SPARK_YARN_USER_ENV")) - - System.getenv().filterKeys(_.startsWith("SPARK")).foreach { case (k,v) => env(k) = v } - env - } - }
