Change to use Yarn appropriate directories rather then /tmp or the user specified spark.local.dir

yarn/src/main/scala/spark/deploy/yarn/ApplicationMaster.scala

@@ -47,6 +47,9 @@ class ApplicationMaster(args: ApplicationMasterArguments, conf: Configuration) e
   private var isFinished:Boolean = false
 
   def run() {
+    // setup the directories so things go to yarn approved directories rather
+    // then user specified and /tmp
+    System.setProperty("spark.local.dir", getLocalDirs())
     
     appAttemptId = getApplicationAttemptId()
     resourceManager = registerWithResourceManager()
@@ -89,6 +92,20 @@ class ApplicationMaster(args: ApplicationMasterArguments, conf: Configuration) e
 
     System.exit(0)
   }
+
+  /** Get the Yarn approved local directories. */
+  private def getLocalDirs(): String = {
+    // Hadoop 0.23 and 2.x have different Environment variable names for the
+    // local dirs, so lets check both. We assume one of the 2 is set.
+    // LOCAL_DIRS => 2.X, YARN_LOCAL_DIRS => 0.23.X
+    var localDirs = System.getenv("LOCAL_DIRS")
+    val yarnLocalSysDirs = Option(System.getenv("YARN_LOCAL_DIRS"))
+    yarnLocalSysDirs match {
+        case Some(s) => localDirs = s
+        case None => if (localDirs == null) localDirs = ""
+    }
+    return localDirs
+  }
   
   private def getApplicationAttemptId(): ApplicationAttemptId = {
     val envs = System.getenv()

yarn/src/main/scala/spark/deploy/yarn/Client.scala

@@ -221,6 +221,10 @@ class Client(conf: Configuration, args: ClientArguments) extends YarnClientImpl
     // Add Xmx for am memory
     JAVA_OPTS += "-Xmx" + amMemory + "m "
 
+    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)

yarn/src/main/scala/spark/deploy/yarn/WorkerRunnable.scala

@@ -75,6 +75,10 @@ class WorkerRunnable(container: Container, conf: Configuration, masterAddress: S
     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)