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From "Etienne Chauchot (JIRA)" <j...@apache.org>
Subject [jira] [Commented] (BEAM-1802) Spark Runner does not shutdown correctly when executing multiple pipelines in sequence
Date Fri, 14 Apr 2017 14:05:41 GMT

    [ https://issues.apache.org/jira/browse/BEAM-1802?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15969068#comment-15969068
] 

Etienne Chauchot commented on BEAM-1802:
----------------------------------------

It works in batch mode but not in streaming mode:
in streaming mode calling {{pipelineResult.cancel()}} after {{pipelineResult.waitUntilFinish()}}
did an infinite loop. {{pipelineResult.waitUntilFinish()}} seems blocking forever and {{pipelineResult.cancel()}}
never gets called. Is this the expected behavior? 
I did a work around by calling  {{pipelineResult.waitUntilFinish(timeout)}}

In direct runner it behaves differently {{pipelineResult.waitUntilFinish()}} returns no need
for {{pipelineResult.cancel()}} or for timeout
WDYT?

> Spark Runner does not shutdown correctly when executing multiple pipelines in sequence
> --------------------------------------------------------------------------------------
>
>                 Key: BEAM-1802
>                 URL: https://issues.apache.org/jira/browse/BEAM-1802
>             Project: Beam
>          Issue Type: Bug
>          Components: runner-spark
>            Reporter: Ismaël Mejía
>            Assignee: Aviem Zur
>             Fix For: First stable release
>
>
> I found this while running the Nexmark queries in sequence in local mode. I had the correct
configuration but it didn't seem to work.
> 17/03/24 12:07:49 WARN org.apache.spark.SparkContext: Multiple running SparkContexts
detected in the same JVM!
> org.apache.spark.SparkException: Only one SparkContext may be running in this JVM (see
SPARK-2243). To ignore this error, set spark.driver.allowMultipleContexts = true. The currently
running SparkContext was created at:
> org.apache.spark.api.java.JavaSparkContext.<init>(JavaSparkContext.scala:59)
> org.apache.beam.runners.spark.translation.SparkContextFactory.createSparkContext(SparkContextFactory.java:100)
> org.apache.beam.runners.spark.translation.SparkContextFactory.getSparkContext(SparkContextFactory.java:69)
> org.apache.beam.runners.spark.SparkRunner.run(SparkRunner.java:206)
> org.apache.beam.runners.spark.SparkRunner.run(SparkRunner.java:91)
> org.apache.beam.sdk.Pipeline.run(Pipeline.java:266)
> org.apache.beam.integration.nexmark.NexmarkRunner.run(NexmarkRunner.java:1233)
> org.apache.beam.integration.nexmark.NexmarkDriver.runAll(NexmarkDriver.java:69)
> org.apache.beam.integration.nexmark.drivers.NexmarkSparkDriver.main(NexmarkSparkDriver.java:46)
> 	at org.apache.spark.SparkContext$$anonfun$assertNoOtherContextIsRunning$1.apply(SparkContext.scala:2257)
> 	at org.apache.spark.SparkContext$$anonfun$assertNoOtherContextIsRunning$1.apply(SparkContext.scala:2239)



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