Hi Kyle, Have you tried increasing the default parallelization to say 3 x NumCores or more?
Ashish On Oct 13, 2013 12:49 AM, "Kyle Ellrott" <[email protected]> wrote: > I'm working on a program that takes an RDD of file names and runs a > flatMap operation on the loading function to produce an RDD of loaded > values. If I take that RDD and then call saveAsHadoopFile, the program > works fine. However, I need to do a reduceByKey, and the total amount of > data is larger then the available memory in the cluster, so I started > getting JavaHeap errors and GC overhead errors. That was expected, and I > knew the next step would be to run persist with one of the DISK options, > but I kept getting memory errors. > I've simplified the problem, just trying to run persist before running > saveAsHadoopFile (skipping the reduceByKey), and I still get memory errors. > I've tried MEMORY_AND_DISK and DISK_ONLY, and still get the memory errors. > I've tried setting spark.executor.memory=2g and > spark.storage.memoryFraction=0.25, no dice. Switching to > 'org.apache.spark.serializer.KryoSerializer' doesn't help either. > > > TL;DR > > (spark.executor.memory = 512m) > myInputs.flatMap( readFile(_) ).saveAsHadoopFile( ... ) : Works fine > > (spark.executor.memory = 2g) > myInputs.flatMap( readFile(_) ).persist(MEMORY_AND_DISK).saveAsHadoopFile( > ... ) : Lots of memory java.lang.OutOfMemoryError exceptions (example > below). > > Any ideas of things I could try? > > > Kyle > > > Typical error: > > java.lang.OutOfMemoryError: GC overhead limit exceeded > at > java.io.ObjectOutputStream$HandleTable.growSpine(ObjectOutputStream.java:2295) > at > java.io.ObjectOutputStream$HandleTable.assign(ObjectOutputStream.java:2240) > at java.io.ObjectOutputStream.writeString(ObjectOutputStream.java:1262) > at java.io.ObjectOutputStream.writeObject0(ObjectOutputStream.java:1144) > at > java.io.ObjectOutputStream.defaultWriteFields(ObjectOutputStream.java:1509) > at > java.io.ObjectOutputStream.writeSerialData(ObjectOutputStream.java:1474) > at > java.io.ObjectOutputStream.writeOrdinaryObject(ObjectOutputStream.java:1392) > at java.io.ObjectOutputStream.writeObject0(ObjectOutputStream.java:1150) > at > java.io.ObjectOutputStream.defaultWriteFields(ObjectOutputStream.java:1509) > at > java.io.ObjectOutputStream.writeSerialData(ObjectOutputStream.java:1474) > at > java.io.ObjectOutputStream.writeOrdinaryObject(ObjectOutputStream.java:1392) > at java.io.ObjectOutputStream.writeObject0(ObjectOutputStream.java:1150) > at java.io.ObjectOutputStream.writeArray(ObjectOutputStream.java:1338) > at java.io.ObjectOutputStream.writeObject0(ObjectOutputStream.java:1146) > at > java.io.ObjectOutputStream.defaultWriteFields(ObjectOutputStream.java:1509) > at > java.io.ObjectOutputStream.writeSerialData(ObjectOutputStream.java:1474) > at > java.io.ObjectOutputStream.writeOrdinaryObject(ObjectOutputStream.java:1392) > at java.io.ObjectOutputStream.writeObject0(ObjectOutputStream.java:1150) > at java.io.ObjectOutputStream.writeObject(ObjectOutputStream.java:326) > at > org.apache.spark.serializer.JavaSerializationStream.writeObject(JavaSerializer.scala:27) > at > org.apache.spark.serializer.SerializationStream$class.writeAll(Serializer.scala:80) > at > org.apache.spark.serializer.JavaSerializationStream.writeAll(JavaSerializer.scala:25) > at org.apache.spark.storage.DiskStore.putValues(DiskStore.scala:178) > at > org.apache.spark.storage.BlockManager.liftedTree1$1(BlockManager.scala:618) > at org.apache.spark.storage.BlockManager.put(BlockManager.scala:604) > at org.apache.spark.CacheManager.getOrCompute(CacheManager.scala:75) > at org.apache.spark.rdd.RDD.iterator(RDD.scala:224) > at org.apache.spark.rdd.MappedRDD.compute(MappedRDD.scala:29) > at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:237) > at org.apache.spark.rdd.RDD.iterator(RDD.scala:226) > at org.apache.spark.scheduler.ResultTask.run(ResultTask.scala:99) > at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:158) > >
