[
https://issues.apache.org/jira/browse/BEAM-13981?focusedWorklogId=739915&page=com.atlassian.jira.plugin.system.issuetabpanels:worklog-tabpanel#worklog-739915
]
ASF GitHub Bot logged work on BEAM-13981:
-----------------------------------------
Author: ASF GitHub Bot
Created on: 11/Mar/22 08:00
Start Date: 11/Mar/22 08:00
Worklog Time Spent: 10m
Work Description: iemejia opened a new pull request #17073:
URL: https://github.com/apache/beam/pull/17073
R: @aromanenko-dev
CC: @ibzib
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Issue Time Tracking
-------------------
Worklog Id: (was: 739915)
Remaining Estimate: 0h
Time Spent: 10m
> Job event log empty on Spark History Server
> -------------------------------------------
>
> Key: BEAM-13981
> URL: https://issues.apache.org/jira/browse/BEAM-13981
> Project: Beam
> Issue Type: Bug
> Components: runner-spark
> Affects Versions: 2.33.0
> Reporter: Jozef Vilcek
> Assignee: Ismaël Mejía
> Priority: P2
> Time Spent: 10m
> Remaining Estimate: 0h
>
> After upgrade from Beam 2.24.0 -> 2.33.0 Spark jobs run on YARN after
> complete shows empty data on History server.
> The problem seems to be a race condition and 2
> {noformat}
> 22/02/22 10:51:11 INFO EventLoggingListener: Logging events to
> hdfs:/user/spark/jobhistory/application_1553109013416_12079975_1
> ...
> 22/02/22 10:51:41 INFO EventLoggingListener: Logging events to
> hdfs:/user/spark/jobhistory/application_1553109013416_12079975_1{noformat}
> At the end failure:
> {noformat}
> 22/02/22 11:17:57 INFO SchedulerExtensionServices: Stopping
> SchedulerExtensionServices
> (serviceOption=None,
> services=List(),
> started=false)
> 22/02/22 11:17:57 ERROR Utils: Uncaught exception in thread Driver
> java.io.IOException: Target log file already exists
> (hdfs:/user/spark/jobhistory/application_1553109013416_12079975_1)
> at
> org.apache.spark.scheduler.EventLoggingListener.stop(EventLoggingListener.scala:255)
> at
> org.apache.spark.SparkContext.$anonfun$stop$13(SparkContext.scala:1960)
> at
> org.apache.spark.SparkContext.$anonfun$stop$13$adapted(SparkContext.scala:1960)
> at scala.Option.foreach(Option.scala:274)
> at
> org.apache.spark.SparkContext.$anonfun$stop$12(SparkContext.scala:1960)
> at org.apache.spark.util.Utils$.tryLogNonFatalError(Utils.scala:1340)
> at org.apache.spark.SparkContext.stop(SparkContext.scala:1960)
> at
> org.apache.spark.api.java.JavaSparkContext.stop(JavaSparkContext.scala:654)
> at
> org.apache.beam.runners.spark.translation.SparkContextFactory.stopSparkContext(SparkContextFactory.java:73)
> at
> org.apache.beam.runners.spark.SparkPipelineResult$BatchMode.stop(SparkPipelineResult.java:133)
> at
> org.apache.beam.runners.spark.SparkPipelineResult.offerNewState(SparkPipelineResult.java:234)
> at
> org.apache.beam.runners.spark.SparkPipelineResult.waitUntilFinish(SparkPipelineResult.java:99)
> at
> org.apache.beam.runners.spark.SparkPipelineResult.waitUntilFinish(SparkPipelineResult.java:92)
> at
> com.sizmek.dp.dsp.pipeline.driver.PipelineDriver.$anonfun$main$1(PipelineDriver.scala:41)
> at scala.util.Try$.apply(Try.scala:213)
> at
> com.sizmek.dp.dsp.pipeline.driver.PipelineDriver.main(PipelineDriver.scala:34)
> at
> com.sizmek.dp.dsp.pipeline.driver.PipelineDriver.main$(PipelineDriver.scala:17)
> at
> com.zetaglobal.dp.dsp.jobs.dealstats.DealStatsDriver$.main(DealStatsDriver.scala:18)
> at
> com.zetaglobal.dp.dsp.jobs.dealstats.DealStatsDriver.main(DealStatsDriver.scala)
> at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
> at
> sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)
> at
> sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
> at java.lang.reflect.Method.invoke(Method.java:497)
> at
> org.apache.spark.deploy.yarn.ApplicationMaster$$anon$2.run(ApplicationMaster.scala:684){noformat}
> This ends up with very empty file in HDFS and empty job details in history
> server.
>
> Problem seems to by introduced by this change:
> [https://github.com/apache/beam/pull/14409]
> Why Beam runs concurrent event listener to what spark is doing internally?
> When I roll back change for SparkRunner, problem disappear for me.
> I am running native SparkRunner with Spark 2.4.4
>
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