[Re-titling thread.] OK, I see that the exception from my original email is being triggered from this part of UnsafeInMemorySorter:
https://github.com/apache/spark/blob/v2.0.2/core/src/main/java/org/apache/spark/util/collection/unsafe/sort/UnsafeInMemorySorter.java#L209-L212 So I can ask a more refined question now: How can I ensure that UnsafeInMemorySorter has room to insert new records? In other words, how can I ensure that hasSpaceForAnotherRecord() returns a true value? Do I need: - More, smaller partitions? - More memory per executor? - Some Java or Spark option enabled? - etc. I’m running Spark 2.0.2 on Java 7 and YARN. Would Java 8 help here? (Unfortunately, I cannot upgrade at this time, but it would be good to know regardless.) This is morphing into a user-list question, so accept my apologies. Since I can’t find any information anywhere else about this, and the question is about internals like UnsafeInMemorySorter, I hope this is OK here. Nick On Mon, Dec 5, 2016 at 9:11 AM Nicholas Chammas nicholas.cham...@gmail.com <http://mailto:nicholas.cham...@gmail.com> wrote: I was testing out a new project at scale on Spark 2.0.2 running on YARN, > and my job failed with an interesting error message: > > TaskSetManager: Lost task 37.3 in stage 31.0 (TID 10684, server.host.name): > java.lang.IllegalStateException: There is no space for new record > 05:27:09.573 at > org.apache.spark.util.collection.unsafe.sort.UnsafeInMemorySorter.insertRecord(UnsafeInMemorySorter.java:211) > 05:27:09.574 at > org.apache.spark.sql.execution.UnsafeKVExternalSorter.<init>(UnsafeKVExternalSorter.java:127) > 05:27:09.574 at > org.apache.spark.sql.execution.UnsafeFixedWidthAggregationMap.destructAndCreateExternalSorter(UnsafeFixedWidthAggregationMap.java:244) > 05:27:09.575 at > org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIterator.agg_doAggregateWithKeys$(Unknown > Source) > 05:27:09.575 at > org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIterator.processNext(Unknown > Source) > 05:27:09.576 at > org.apache.spark.sql.execution.BufferedRowIterator.hasNext(BufferedRowIterator.java:43) > 05:27:09.576 at > org.apache.spark.sql.execution.WholeStageCodegenExec$anonfun$8$anon$1.hasNext(WholeStageCodegenExec.scala:370) > 05:27:09.577 at > scala.collection.Iterator$anon$11.hasNext(Iterator.scala:408) > 05:27:09.577 at > org.apache.spark.shuffle.sort.BypassMergeSortShuffleWriter.write(BypassMergeSortShuffleWriter.java:125) > 05:27:09.577 at > org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:79) > 05:27:09.578 at > org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:47) > 05:27:09.578 at org.apache.spark.scheduler.Task.run(Task.scala:86) > 05:27:09.578 at > org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:274) > 05:27:09.579 at > java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1145) > 05:27:09.579 at > java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:615) > 05:27:09.579 at java.lang.Thread.run(Thread.java:745) > > I’ve never seen this before, and searching on Google/DDG/JIRA doesn’t > yield any results. There are no other errors coming from that executor, > whether related to memory, storage space, or otherwise. > > Could this be a bug? If so, how would I narrow down the source? Otherwise, > how might I work around the issue? > > Nick > >
