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Posted to issues@spark.apache.org by "Cristian Opris (JIRA)" <ji...@apache.org> on 2014/11/12 14:40:33 UTC
[jira] [Commented] (SPARK-3633) Fetches failure observed after
SPARK-2711
[ https://issues.apache.org/jira/browse/SPARK-3633?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14208028#comment-14208028 ]
Cristian Opris commented on SPARK-3633:
---------------------------------------
FWIW I get this as well, with a very straightforward job and setup.
Spark 1.1.0, executors configured to 2GB, storage.fraction=0.2, shuffle.spill=true
50GB dataset on ext4, spread over 7000 files, hence the coalescing below
The jobs is only doing: input.coalesce(72, false).groupBy(key).count
The groupBy is successful then I get the dreaded fetch error on count stage (oddly enough), but it seems to me that's when it does the actual shuffling for groupBy ?
> Fetches failure observed after SPARK-2711
> -----------------------------------------
>
> Key: SPARK-3633
> URL: https://issues.apache.org/jira/browse/SPARK-3633
> Project: Spark
> Issue Type: Bug
> Components: Block Manager
> Affects Versions: 1.1.0
> Reporter: Nishkam Ravi
> Priority: Critical
>
> Running a variant of PageRank on a 6-node cluster with a 30Gb input dataset. Recently upgraded to Spark 1.1. The workload fails with the following error message(s):
> {code}
> 14/09/19 12:10:38 WARN TaskSetManager: Lost task 51.0 in stage 2.1 (TID 552, c1705.halxg.cloudera.com): FetchFailed(BlockManagerId(1, c1706.halxg.cloudera.com, 49612, 0), shuffleId=3, mapId=75, reduceId=120)
> 14/09/19 12:10:38 INFO DAGScheduler: Resubmitting failed stages
> {code}
> In order to identify the problem, I carried out change set analysis. As I go back in time, the error message changes to:
> {code}
> 14/09/21 12:56:54 WARN TaskSetManager: Lost task 35.0 in stage 3.0 (TID 519, c1706.halxg.cloudera.com): java.io.FileNotFoundException: /var/lib/jenkins/workspace/tmp/spark-local-20140921123257-68ee/1c/temp_3a1ade13-b48a-437a-a466-673995304034 (Too many open files)
> java.io.FileOutputStream.open(Native Method)
> java.io.FileOutputStream.<init>(FileOutputStream.java:221)
> org.apache.spark.storage.DiskBlockObjectWriter.open(BlockObjectWriter.scala:117)
> org.apache.spark.storage.DiskBlockObjectWriter.write(BlockObjectWriter.scala:185)
> org.apache.spark.util.collection.ExternalAppendOnlyMap.spill(ExternalAppendOnlyMap.scala:197)
> org.apache.spark.util.collection.ExternalAppendOnlyMap.insertAll(ExternalAppendOnlyMap.scala:145)
> org.apache.spark.Aggregator.combineValuesByKey(Aggregator.scala:58)
> org.apache.spark.shuffle.hash.HashShuffleWriter.write(HashShuffleWriter.scala:51)
> org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:68)
> org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:41)
> org.apache.spark.scheduler.Task.run(Task.scala:54)
> org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:199)
> java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1145)
> java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:615)
> java.lang.Thread.run(Thread.java:745)
> {code}
> All the way until Aug 4th. Turns out the problem changeset is 4fde28c.
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