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https://issues.apache.org/jira/browse/SPARK-24786?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Josh Rosen resolved SPARK-24786.
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Resolution: Duplicate
I'm resolving this PR because it's marked as a duplicate of SPARK-20286, which
has been fixed for Spark 3.0.
> Executors not being released after all cached data is unpersisted
> -----------------------------------------------------------------
>
> Key: SPARK-24786
> URL: https://issues.apache.org/jira/browse/SPARK-24786
> Project: Spark
> Issue Type: Bug
> Components: Scheduler
> Affects Versions: 2.3.0
> Environment: Zeppelin in EMR
> Reporter: Jeffrey Charles
> Priority: Minor
>
> I'm persisting a dataframe in Zeppelin which has dynamic allocation enabled
> to get a sense of how much memory the dataframe takes up. After I note the
> size, I unpersist the dataframe. For some reason, Yarn is not releasing the
> executors that were added to Zeppelin. If I don't run the persist and
> unpersist steps, the executors that were added are removed about a minute
> after the paragraphs complete. Looking at the storage tab in the Spark UI for
> the Zeppelin job, I don't see anything cached. I do not want to set
> spark.dynamicAllocation.cachedExecutorIdleTimeout to a lower value because I
> do not want executors with cached data to be released, but I do want ones
> that had cached data and no longer have cached data to be released.
>
> Steps to reproduce:
> # Enable dynamic allocation
> # Set spark.dynamicAllocation.executorIdleTimeout to 60s
> # Set spark.dynamicAllocation.cachedExecutorIdleTimeout to infinity
> # Load a dataset, persist it, run a count on the persisted dataset,
> unpersist the persisted dataset
> # Wait a couple minutes
> Expected behaviour:
> All executors will be released as the executors are no longer caching any data
> Observed behaviour:
> No executors were released
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