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From "Marcelo Vanzin (JIRA)" <j...@apache.org>
Subject [jira] [Resolved] (SPARK-19649) Spark YARN client throws exception if job succeeds and max-completed-applications=0
Date Tue, 12 Feb 2019 21:33:00 GMT

     [ https://issues.apache.org/jira/browse/SPARK-19649?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]

Marcelo Vanzin resolved SPARK-19649.
------------------------------------
    Resolution: Won't Fix

There isn't a reliable way to do this in Spark without the RM tracking this info.

> Spark YARN client throws exception if job succeeds and max-completed-applications=0
> -----------------------------------------------------------------------------------
>
>                 Key: SPARK-19649
>                 URL: https://issues.apache.org/jira/browse/SPARK-19649
>             Project: Spark
>          Issue Type: Bug
>          Components: YARN
>    Affects Versions: 1.6.3
>         Environment: EMR release label 4.8.x
>            Reporter: Joshua Caplan
>            Priority: Minor
>
> I believe the patch in SPARK-3877 created a new race condition between YARN and the Spark
client.
> I typically configure YARN not to keep *any* recent jobs in memory, as some of my jobs
get pretty large.
> {code}
> yarn-site	yarn.resourcemanager.max-completed-applications	0
> {code}
> The once-per-second call to getApplicationReport may thus encounter a RUNNING application
followed by a not found application, and report a false negative.
> (typical) Executor log:
> {code}
> 17/01/09 19:31:23 INFO ApplicationMaster: Final app status: SUCCEEDED, exitCode: 0
> 17/01/09 19:31:23 INFO SparkContext: Invoking stop() from shutdown hook
> 17/01/09 19:31:24 INFO SparkUI: Stopped Spark web UI at http://10.0.0.168:37046
> 17/01/09 19:31:24 INFO YarnClusterSchedulerBackend: Shutting down all executors
> 17/01/09 19:31:24 INFO YarnClusterSchedulerBackend: Asking each executor to shut down
> 17/01/09 19:31:24 INFO MapOutputTrackerMasterEndpoint: MapOutputTrackerMasterEndpoint
stopped!
> 17/01/09 19:31:24 INFO MemoryStore: MemoryStore cleared
> 17/01/09 19:31:24 INFO BlockManager: BlockManager stopped
> 17/01/09 19:31:24 INFO BlockManagerMaster: BlockManagerMaster stopped
> 17/01/09 19:31:24 INFO OutputCommitCoordinator$OutputCommitCoordinatorEndpoint: OutputCommitCoordinator
stopped!
> 17/01/09 19:31:24 INFO SparkContext: Successfully stopped SparkContext
> 17/01/09 19:31:24 INFO ApplicationMaster: Unregistering ApplicationMaster with SUCCEEDED
> 17/01/09 19:31:24 INFO RemoteActorRefProvider$RemotingTerminator: Shutting down remote
daemon.
> 17/01/09 19:31:24 INFO RemoteActorRefProvider$RemotingTerminator: Remote daemon shut
down; proceeding with flushing remote transports.
> 17/01/09 19:31:24 INFO AMRMClientImpl: Waiting for application to be successfully unregistered.
> 17/01/09 19:31:24 INFO RemoteActorRefProvider$RemotingTerminator: Remoting shut down.
> {code}
> Client log:
> {code}
> 17/01/09 19:31:23 INFO Client: Application report for application_1483983939941_0056
(state: RUNNING)
> 17/01/09 19:31:24 ERROR Client: Application application_1483983939941_0056 not found.
> Exception in thread "main" org.apache.spark.SparkException: Application application_1483983939941_0056
is killed
> 	at org.apache.spark.deploy.yarn.Client.run(Client.scala:1038)
> 	at org.apache.spark.deploy.yarn.Client$.main(Client.scala:1081)
> 	at org.apache.spark.deploy.yarn.Client.main(Client.scala)
> 	at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
> 	at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:57)
> 	at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
> 	at java.lang.reflect.Method.invoke(Method.java:606)
> 	at org.apache.spark.deploy.SparkSubmit$.org$apache$spark$deploy$SparkSubmit$$runMain(SparkSubmit.scala:731)
> 	at org.apache.spark.deploy.SparkSubmit$.doRunMain$1(SparkSubmit.scala:181)
> 	at org.apache.spark.deploy.SparkSubmit$.submit(SparkSubmit.scala:206)
> 	at org.apache.spark.deploy.SparkSubmit$.main(SparkSubmit.scala:121)
> 	at org.apache.spark.deploy.SparkSubmit.main(SparkSubmit.scala)
> {code}



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