Hi Chieh, You can increase the heap size by exporting the java options (See below, will increase the heap size to 10Gb)
export _JAVA_OPTIONS="-Xmx10g" On Mon, Apr 21, 2014 at 11:43 AM, Chieh-Yen <r01944...@csie.ntu.edu.tw>wrote: > Can anybody help me? > Thanks. > > Chieh-Yen > > > On Wed, Apr 16, 2014 at 5:18 PM, Chieh-Yen <r01944...@csie.ntu.edu.tw>wrote: > >> Dear all, >> >> I developed a application that the message size of communication >> is greater than 10 MB sometimes. >> For smaller datasets it works fine, but fails for larger datasets. >> Please check the error message following. >> >> I surveyed the situation online and lots of people said >> the problem can be solved by modifying the property >> of spark.akka.frameSize >> and spark.reducer.maxMbInFlight. >> It may look like: >> >> 134 val conf = new SparkConf() >> 135 .setMaster(master) >> 136 .setAppName("SparkLR") >> 137 >> .setSparkHome("/home/user/spark-0.9.0-incubating-bin-hadoop2") >> 138 .setJars(List(jarPath)) >> 139 .set("spark.akka.frameSize", "100") >> 140 .set("spark.reducer.maxMbInFlight", "100") >> 141 val sc = new SparkContext(conf) >> >> However, the task still fails with the same error message. >> The communication message is the weight vectors of each sub-problem, >> it may be larger than 10 MB for higher dimensional dataset. >> >> Is there anybody can help me? >> Thanks a lot. >> >> ==== >> [error] (run-main) org.apache.spark.SparkException: Job aborted: >> Exception while deserializing and fetching task:*java.lang.OutOfMemoryError: >> Java heap space* >> org.apache.spark.SparkException: Job aborted: Exception while >> deserializing and fetching task: java.lang.OutOfMemoryError: Java heap space >> at >> org.apache.spark.scheduler.DAGScheduler$$anonfun$org$apache$spark$scheduler$DAGScheduler$$abortStage$1.apply(DAGScheduler.scala:1028) >> at >> org.apache.spark.scheduler.DAGScheduler$$anonfun$org$apache$spark$scheduler$DAGScheduler$$abortStage$1.apply(DAGScheduler.scala:1026) >> at >> scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:59) >> at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:47) >> at >> org.apache.spark.scheduler.DAGScheduler.org<http://org.apache.spark.scheduler.dagscheduler.org/> >> $apache$spark$scheduler$DAGScheduler$$abortStage(DAGScheduler.scala:1026) >> at >> org.apache.spark.scheduler.DAGScheduler$$anonfun$processEvent$10.apply(DAGScheduler.scala:619) >> at >> org.apache.spark.scheduler.DAGScheduler$$anonfun$processEvent$10.apply(DAGScheduler.scala:619) >> at scala.Option.foreach(Option.scala:236) >> at >> org.apache.spark.scheduler.DAGScheduler.processEvent(DAGScheduler.scala:619) >> at >> org.apache.spark.scheduler.DAGScheduler$$anonfun$start$1$$anon$2$$anonfun$receive$1.applyOrElse(DAGScheduler.scala:207) >> at akka.actor.ActorCell.receiveMessage(ActorCell.scala:498) >> at akka.actor.ActorCell.invoke(ActorCell.scala:456) >> at akka.dispatch.Mailbox.processMailbox(Mailbox.scala:237) >> at akka.dispatch.Mailbox.run(Mailbox.scala:219) >> at >> akka.dispatch.ForkJoinExecutorConfigurator$AkkaForkJoinTask.exec(AbstractDispatcher.scala:386) >> at scala.concurrent.forkjoin.ForkJoinTask.doExec(ForkJoinTask.java:260) >> at >> scala.concurrent.forkjoin.ForkJoinPool$WorkQueue.runTask(ForkJoinPool.java:1339) >> at >> scala.concurrent.forkjoin.ForkJoinPool.runWorker(ForkJoinPool.java:1979) >> at >> scala.concurrent.forkjoin.ForkJoinWorkerThread.run(ForkJoinWorkerThread.java:107) >> [trace] Stack trace suppressed: run last compile:run for the full output. >> ==== >> >> Chieh-Yen >> > > -- Thanks Best Regards