I've replied on the issue's page, but in a word, "yes". See https://issues.apache.org/jira/browse/SPARK-17204 <https://issues.apache.org/jira/browse/SPARK-17204>.
Michael > On Aug 23, 2016, at 11:55 AM, Reynold Xin <r...@databricks.com> wrote: > > Does this problem still exist on today's master/branch-2.0? > > SPARK-16550 was merged. It might be fixed already. > > On Tue, Aug 23, 2016 at 9:37 AM, Michael Allman <mich...@videoamp.com > <mailto:mich...@videoamp.com>> wrote: > FYI, I posted this to user@ and have followed up with a bug report: > https://issues.apache.org/jira/browse/SPARK-17204 > <https://issues.apache.org/jira/browse/SPARK-17204> > > Michael > >> Begin forwarded message: >> >> From: Michael Allman <mich...@videoamp.com <mailto:mich...@videoamp.com>> >> Subject: Anyone else having trouble with replicated off heap RDD persistence? >> Date: August 16, 2016 at 3:45:14 PM PDT >> To: user <u...@spark.apache.org <mailto:u...@spark.apache.org>> >> >> Hello, >> >> A coworker was having a problem with a big Spark job failing after several >> hours when one of the executors would segfault. That problem aside, I >> speculated that her job would be more robust against these kinds of executor >> crashes if she used replicated RDD storage. She's using off heap storage >> (for good reason), so I asked her to try running her job with the following >> storage level: `StorageLevel(useDisk = true, useMemory = true, useOffHeap = >> true, deserialized = false, replication = 2)`. The job would immediately >> fail with a rather suspicious looking exception. For example: >> >> com.esotericsoftware.kryo.KryoException: Encountered unregistered class ID: >> 9086 >> at >> com.esotericsoftware.kryo.util.DefaultClassResolver.readClass(DefaultClassResolver.java:137) >> at com.esotericsoftware.kryo.Kryo.readClass(Kryo.java:670) >> at com.esotericsoftware.kryo.Kryo.readClassAndObject(Kryo.java:781) >> at >> org.apache.spark.serializer.KryoDeserializationStream.readObject(KryoSerializer.scala:229) >> at >> org.apache.spark.serializer.DeserializationStream$$anon$1.getNext(Serializer.scala:169) >> at org.apache.spark.util.NextIterator.hasNext(NextIterator.scala:73) >> at >> org.apache.spark.util.CompletionIterator.hasNext(CompletionIterator.scala:32) >> at >> org.apache.spark.InterruptibleIterator.hasNext(InterruptibleIterator.scala:39) >> at scala.collection.Iterator$$anon$13.hasNext(Iterator.scala:461) >> at scala.collection.Iterator$$anon$11.hasNext(Iterator.scala:408) >> at >> org.apache.spark.sql.catalyst.expressions.GeneratedClass$SpecificColumnarIterator.hasNext(Unknown >> Source) >> at >> org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIterator.agg_doAggregateWithoutKey$(Unknown >> Source) >> at >> org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIterator.processNext(Unknown >> Source) >> at >> org.apache.spark.sql.execution.BufferedRowIterator.hasNext(BufferedRowIterator.java:43) >> at >> org.apache.spark.sql.execution.WholeStageCodegenExec$$anonfun$8$$anon$1.hasNext(WholeStageCodegenExec.scala:370) >> at scala.collection.Iterator$$anon$11.hasNext(Iterator.scala:408) >> at >> org.apache.spark.shuffle.sort.BypassMergeSortShuffleWriter.write(BypassMergeSortShuffleWriter.java:125) >> at >> org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:79) >> at >> org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:47) >> at org.apache.spark.scheduler.Task.run(Task.scala:85) >> at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:274) >> at >> java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142) >> at >> java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617) >> at java.lang.Thread.run(Thread.java:745) >> >> or >> >> java.lang.IndexOutOfBoundsException: Index: 6, Size: 0 >> at java.util.ArrayList.rangeCheck(ArrayList.java:653) >> at java.util.ArrayList.get(ArrayList.java:429) >> at >> com.esotericsoftware.kryo.util.MapReferenceResolver.getReadObject(MapReferenceResolver.java:60) >> at com.esotericsoftware.kryo.Kryo.readReferenceOrNull(Kryo.java:834) >> at com.esotericsoftware.kryo.Kryo.readClassAndObject(Kryo.java:788) >> at >> org.apache.spark.serializer.KryoDeserializationStream.readObject(KryoSerializer.scala:229) >> at >> org.apache.spark.serializer.DeserializationStream$$anon$1.getNext(Serializer.scala:169) >> at org.apache.spark.util.NextIterator.hasNext(NextIterator.scala:73) >> at >> org.apache.spark.util.CompletionIterator.hasNext(CompletionIterator.scala:32) >> at >> org.apache.spark.InterruptibleIterator.hasNext(InterruptibleIterator.scala:39) >> at scala.collection.Iterator$$anon$13.hasNext(Iterator.scala:461) >> at scala.collection.Iterator$$anon$11.hasNext(Iterator.scala:408) >> at >> org.apache.spark.sql.catalyst.expressions.GeneratedClass$SpecificColumnarIterator.hasNext(Unknown >> Source) >> at >> org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIterator.agg_doAggregateWithoutKey$(Unknown >> Source) >> at >> org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIterator.processNext(Unknown >> Source) >> at >> org.apache.spark.sql.execution.BufferedRowIterator.hasNext(BufferedRowIterator.java:43) >> at >> org.apache.spark.sql.execution.WholeStageCodegenExec$$anonfun$8$$anon$1.hasNext(WholeStageCodegenExec.scala:370) >> at scala.collection.Iterator$$anon$11.hasNext(Iterator.scala:408) >> at >> org.apache.spark.shuffle.sort.BypassMergeSortShuffleWriter.write(BypassMergeSortShuffleWriter.java:125) >> at >> org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:79) >> at >> org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:47) >> at org.apache.spark.scheduler.Task.run(Task.scala:85) >> at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:274) >> at >> java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142) >> at >> java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617) >> at java.lang.Thread.run(Thread.java:745) >> >> or >> >> java.lang.NullPointerException >> at >> org.apache.spark.sql.execution.columnar.InMemoryTableScanExec$$anonfun$doExecute$1$$anonfun$6.apply(InMemoryTableScanExec.scala:141) >> at >> org.apache.spark.sql.execution.columnar.InMemoryTableScanExec$$anonfun$doExecute$1$$anonfun$6.apply(InMemoryTableScanExec.scala:140) >> at scala.collection.Iterator$$anon$13.hasNext(Iterator.scala:463) >> at scala.collection.Iterator$$anon$11.hasNext(Iterator.scala:408) >> at >> org.apache.spark.sql.catalyst.expressions.GeneratedClass$SpecificColumnarIterator.hasNext(Unknown >> Source) >> at >> org.apache.spark.sql.catalyst.expressions.GeneratedClass$SpecificColumnarIterator.hasNext(Unknown >> Source) >> at >> org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIterator.agg_doAggregateWithoutKey$(Unknown >> Source) >> at >> org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIterator.processNext(Unknown >> Source) >> at >> org.apache.spark.sql.execution.BufferedRowIterator.hasNext(BufferedRowIterator.java:43) >> at >> org.apache.spark.sql.execution.WholeStageCodegenExec$$anonfun$8$$anon$1.hasNext(WholeStageCodegenExec.scala:370) >> at scala.collection.Iterator$$anon$11.hasNext(Iterator.scala:408) >> at >> org.apache.spark.shuffle.sort.BypassMergeSortShuffleWriter.write(BypassMergeSortShuffleWriter.java:125) >> at >> org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:79) >> at >> org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:47) >> at org.apache.spark.scheduler.Task.run(Task.scala:85) >> at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:274) >> at >> java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142) >> at >> java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617) >> at java.lang.Thread.run(Thread.java:745) >> >> I tried switching to Java serialization. I got a different exception: >> >> java.io <http://java.io/>.StreamCorruptedException: invalid stream header: >> 780000D0 >> at >> java.io.ObjectInputStream.readStreamHeader(ObjectInputStream.java:808) >> at java.io.ObjectInputStream.<init>(ObjectInputStream.java:301) >> at >> org.apache.spark.serializer.JavaDeserializationStream$$anon$1.<init>(JavaSerializer.scala:63) >> at >> org.apache.spark.serializer.JavaDeserializationStream.<init>(JavaSerializer.scala:63) >> at >> org.apache.spark.serializer.JavaSerializerInstance.deserializeStream(JavaSerializer.scala:122) >> at >> org.apache.spark.serializer.SerializerManager.dataDeserializeStream(SerializerManager.scala:146) >> at >> org.apache.spark.storage.BlockManager.getLocalValues(BlockManager.scala:433) >> at >> org.apache.spark.storage.BlockManager.getOrElseUpdate(BlockManager.scala:672) >> at org.apache.spark.rdd.RDD.getOrCompute(RDD.scala:330) >> at org.apache.spark.rdd.RDD.iterator(RDD.scala:281) >> at >> org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38) >> at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:319) >> at org.apache.spark.rdd.RDD.iterator(RDD.scala:283) >> at >> org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38) >> at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:319) >> at org.apache.spark.rdd.RDD.iterator(RDD.scala:283) >> at >> org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38) >> at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:319) >> at org.apache.spark.rdd.RDD.iterator(RDD.scala:283) >> at >> org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:79) >> at >> org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:47) >> at org.apache.spark.scheduler.Task.run(Task.scala:85) >> at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:274) >> at >> java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142) >> at >> java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617) >> at java.lang.Thread.run(Thread.java:745) >> >> All of this suggests some kind of memory corruption. Has anyone else had a >> problem like this using off heap storage with replication factor 2? >> >> Thanks, >> >> Michael > >
