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
