Re: Anyone else having trouble with replicated off heap RDD persistence?
FYI, I've updated the issue's description to include a very simple program which reproduces the issue for me. Cheers, Michael > On Aug 23, 2016, at 4:54 PM, Michael Allman <mich...@videoamp.com> wrote: > > 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 >> <mailto: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
Re: Anyone else having trouble with replicated off heap RDD persistence?
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
Re: Anyone else having trouble with replicated off heap RDD persistence?
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> wrote: > FYI, I posted this to user@ and have followed up with a bug report: > https://issues.apache.org/jira/browse/SPARK-17204 > > Michael > > Begin forwarded message: > > *From: *Michael Allman <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> > > 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(Unkno
