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https://issues.apache.org/jira/browse/SPARK-24295?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16772322#comment-16772322
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Jungtaek Lim commented on SPARK-24295:
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FileStreamSinkLog cannot be removed even we don't leverage file sink metadata
in other query, but it can be purged since it only leverages the last batch.
Given that in high volume both of maintaining file sink metadata and reading
file sink metadata would be problematic, I guess we could add an option to
disable reading from metadata: let file stream sink purge metadata log just
after adding new batch, and let file stream source skip using file sink
metadata even it is available. Makes sense?
> Purge Structured streaming FileStreamSinkLog metadata compact file data.
> ------------------------------------------------------------------------
>
> Key: SPARK-24295
> URL: https://issues.apache.org/jira/browse/SPARK-24295
> Project: Spark
> Issue Type: Bug
> Components: Structured Streaming
> Affects Versions: 2.3.0
> Reporter: Iqbal Singh
> Priority: Major
>
> FileStreamSinkLog metadata logs are concatenated to a single compact file
> after defined compact interval.
> For long running jobs, compact file size can grow up to 10's of GB's, Causing
> slowness while reading the data from FileStreamSinkLog dir as spark is
> defaulting to the "__spark__metadata" dir for the read.
> We need a functionality to purge the compact file size.
>
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