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Posted to issues@spark.apache.org by "Hyukjin Kwon (JIRA)" <ji...@apache.org> on 2019/05/21 04:04:14 UTC

[jira] [Updated] (SPARK-20128) MetricsSystem not always killed in SparkContext.stop()

     [ https://issues.apache.org/jira/browse/SPARK-20128?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]

Hyukjin Kwon updated SPARK-20128:
---------------------------------
    Labels: bulk-closed flaky-test  (was: flaky-test)

> MetricsSystem not always killed in SparkContext.stop()
> ------------------------------------------------------
>
>                 Key: SPARK-20128
>                 URL: https://issues.apache.org/jira/browse/SPARK-20128
>             Project: Spark
>          Issue Type: Test
>          Components: Spark Core, Tests
>    Affects Versions: 2.2.0
>            Reporter: Imran Rashid
>            Priority: Major
>              Labels: bulk-closed, flaky-test
>
> One Jenkins run failed due to the MetricsSystem never getting killed after a failed test, which led that test to hang and the tests to timeout:
> https://amplab.cs.berkeley.edu/jenkins/job/SparkPullRequestBuilder/75176
> {noformat}
> 17/03/24 13:44:19.537 dag-scheduler-event-loop ERROR DAGSchedulerEventProcessLoop: DAGSchedulerEventProcessLoop failed; shutting down SparkContext
> java.lang.ArrayIndexOutOfBoundsException: -1
>         at org.apache.spark.MapOutputTrackerMaster$$anonfun$getEpochForMapOutput$1.apply(MapOutputTracker.scala:431)
>         at org.apache.spark.MapOutputTrackerMaster$$anonfun$getEpochForMapOutput$1.apply(MapOutputTracker.scala:430)
>         at scala.Option.flatMap(Option.scala:171)
>         at org.apache.spark.MapOutputTrackerMaster.getEpochForMapOutput(MapOutputTracker.scala:430)
>         at org.apache.spark.scheduler.DAGScheduler.handleTaskCompletion(DAGScheduler.scala:1298)
>         at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.doOnReceive(DAGScheduler.scala:1731)
>         at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:1689)
>         at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:1678)
>         at org.apache.spark.util.EventLoop$$anon$1.run(EventLoop.scala:48)
> 17/03/24 13:44:19.540 dispatcher-event-loop-11 INFO MapOutputTrackerMasterEndpoint: MapOutputTrackerMasterEndpoint stopped!
> 17/03/24 13:44:19.546 stop-spark-context INFO MemoryStore: MemoryStore cleared
> 17/03/24 13:44:19.546 stop-spark-context INFO BlockManager: BlockManager stopped
> 17/03/24 13:44:19.546 stop-spark-context INFO BlockManagerMaster: BlockManagerMaster stopped
> 17/03/24 13:44:19.546 dispatcher-event-loop-16 INFO OutputCommitCoordinator$OutputCommitCoordinatorEndpoint: OutputCommitCoordinator stopped!
> 17/03/24 13:44:19.547 stop-spark-context INFO SparkContext: Successfully stopped SparkContext
> 17/03/24 14:02:19.934 metrics-console-reporter-1-thread-1 ERROR ScheduledReporter: RuntimeException thrown from ConsoleReporter#report. Exception was suppressed.
> java.lang.NullPointerException
>         at org.apache.spark.deploy.master.MasterSource$$anon$2.getValue(MasterSource.scala:35)
>         at org.apache.spark.deploy.master.MasterSource$$anon$2.getValue(MasterSource.scala:34)
>         at com.codahale.metrics.ConsoleReporter.printGauge(ConsoleReporter.java:239)
> ...
> {noformat}
> unfortunately I didn't save the entire test logs, but what happens is the initial IndexOutOfBoundsException is a real bug, which causes the SparkContext to stop, and the test to fail.  However, the MetricsSystem somehow stays alive, and since its not a daemon thread, it just hangs, and every 20 mins we get that NPE from within the metrics system as it tries to report.
> I am totally perplexed at how this can happen, it looks like the metric system should always get stopped by the time we see
> {noformat}
> 17/03/24 13:44:19.547 stop-spark-context INFO SparkContext: Successfully stopped SparkContext
> {noformat}
> I don't think I've ever seen this in a real spark use, but it doesn't look like something which is limited to tests, whatever the cause.



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