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https://issues.apache.org/jira/browse/SPARK-22783?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Dongjoon Hyun updated SPARK-22783:
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Parent: SPARK-28594
Issue Type: Sub-task (was: Bug)
> event log directory(spark-history) filled by large .inprogress files for
> spark streaming applications
> -----------------------------------------------------------------------------------------------------
>
> Key: SPARK-22783
> URL: https://issues.apache.org/jira/browse/SPARK-22783
> Project: Spark
> Issue Type: Sub-task
> Components: Spark Core
> Affects Versions: 1.6.0, 2.1.0
> Environment: Linux(Generic)
> Reporter: omkar kankalapati
> Priority: Major
>
> When running long running streaming applications, the HDFS storage gets
> filled up with large *.inprogress files in hdfs://spark-history/ directory
> For example:
> hadoop fs -du -h /spark-history
> 234 /spark-history/<Application_1_ID>.inprogress
> 46.6 G /spark-history/<Application_2_ID>.inprogress
> Instead of continuing to write to a very large (multi GB) .inprogress file,
> Spark should instead rotate the current log file when it reaches a size (for
> example: 100 MB) or interval
> and perhaps expose a configuration parameter for the size/interval.
> This is also mentioned in SPARK-12140 as a concern.
> It is very important and useful to support rotating the log files because
> users may have limited HDFS quota and these large files consume the available
> limited quota.
> Also the users do not have a viable workaround
> 1) Can not move the files to an another location because the moving the file
> causes the event logging to stop
> 2) Trying to copy the .inprogress file to another location and truncate the
> .inprogress file fails because the file is still opened by
> EventLoggingListener for writing
> hdfs dfs -truncate -w 0 /spark-history/<application_id>.inprogress
> truncate: Failed to TRUNCATE_FILE /spark-history/<application_id>.inprogress
> for DFSClient_NONMAPREDUCE_<#ID>on <IP> because this file lease is currently
> owned by DFSClient_NONMAPREDUCE_<#ID> on <IP>
> The only workaround available is to disable the event logging for streaming
> applications by setting "spark.eventLog.enabled" to false
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