Hi, Zuhair
According to my experience, you could try following steps to avoid Spark
OOM:
1. Increase JVM memory by adding export SPARK_JAVA_OPTS=-Xmx2g
2. Use .persist(storage.StorageLevel.MEMORY_AND_DISK) instead of .cache()
3. Have you set spark.executor.memory value? It's 512m by default.
4. Add more memory to the workers.
I haven't tried to modify the spark.shuffle.memoryFraction value. But it is
said it's a threshold for contents being spilled to disk or not. I think
you may decrease this value to mitigate pressure on memory.
Regards,
Wang Hao(王灏)
CloudTeam | School of Software Engineering
Shanghai Jiao Tong University
Address:800 Dongchuan Road, Minhang District, Shanghai, 200240
Email:wh.s...@gmail.com
On Sun, May 25, 2014 at 4:15 PM, Zuhair Khayyat zuhair.khay...@gmail.comwrote:
Dear all,
I am getting a OutOfMemoryError in class ByteString.java from package
com.google.protobuf when processing very large data using spark 0.9. Does
increasing spark.shuffle.memoryFraction helps or I should add more memory
to my workers? Below the error I get during execution.
14/05/25 07:26:05 INFO MapOutputTrackerMasterActor: Asked to send map
output locations for shuffle 0 to spark@cloud21:47985
14/05/25 07:26:05 INFO MapOutputTrackerMasterActor: Asked to send map
output locations for shuffle 0 to spark@cloud5:46977
14/05/25 07:26:05 INFO MapOutputTrackerMasterActor: Asked to send map
output locations for shuffle 0 to spark@cloud14:51948
14/05/25 07:26:05 INFO MapOutputTrackerMasterActor: Asked to send map
output locations for shuffle 0 to spark@cloud12:45368
14/05/25 07:26:05 INFO MapOutputTrackerMasterActor: Asked to send map
output locations for shuffle 0 to spark@cloud9:50926
14/05/25 07:26:05 INFO MapOutputTrackerMasterActor: Asked to send map
output locations for shuffle 0 to spark@cloud10:50690
14/05/25 07:26:12 ERROR ActorSystemImpl: Uncaught fatal error from thread
[spark-akka.actor.default-dispatcher-5] shutting down ActorSystem [spark]
java.lang.OutOfMemoryError: Java heap space
at
com.google.protobuf_spark.ByteString.copyFrom(ByteString.java:90)
at
com.google.protobuf_spark.ByteString.copyFrom(ByteString.java:99)
at
akka.remote.MessageSerializer$.serialize(MessageSerializer.scala:36)
at
akka.remote.EndpointWriter$$anonfun$akka$remote$EndpointWriter$$serializeMessage$1.apply(Endpoint.scala:672)
at
akka.remote.EndpointWriter$$anonfun$akka$remote$EndpointWriter$$serializeMessage$1.apply(Endpoint.scala:672)
at scala.util.DynamicVariable.withValue(DynamicVariable.scala:57)
at
akka.remote.EndpointWriter.akka$remote$EndpointWriter$$serializeMessage(Endpoint.scala:671)
at
akka.remote.EndpointWriter$$anonfun$7.applyOrElse(Endpoint.scala:559)
at
akka.remote.EndpointWriter$$anonfun$7.applyOrElse(Endpoint.scala:544)
at
scala.runtime.AbstractPartialFunction.apply(AbstractPartialFunction.scala:33)
at akka.actor.FSM$class.processEvent(FSM.scala:595)
at akka.remote.EndpointWriter.processEvent(Endpoint.scala:443)
at akka.actor.FSM$class.akka$actor$FSM$$processMsg(FSM.scala:589)
at akka.actor.FSM$$anonfun$receive$1.applyOrElse(FSM.scala:583)
at akka.actor.ActorCell.receiveMessage(ActorCell.scala:498)
at akka.actor.ActorCell.invoke(ActorCell.scala:456)
at akka.dispatch.Mailbox.processMailbox(Mailbox.scala:237)
at akka.dispatch.Mailbox.run(Mailbox.scala:219)
at
akka.dispatch.ForkJoinExecutorConfigurator$AkkaForkJoinTask.exec(AbstractDispatcher.scala:385)
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)
Thank you,
