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https://issues.apache.org/jira/browse/SPARK-12883?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15106005#comment-15106005
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Saisai Shao commented on SPARK-12883:
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I think this doc is still valid, current way of setting a different timeout
threshold for executors with cached data is a kind of workaround, not a
thorough solution, so the doc is still valid some how, we could leave as it was
unless it is fixed thoroughly.
> 1.6 Dynamic allocation doc still refers to 1.2
> ----------------------------------------------
>
> Key: SPARK-12883
> URL: https://issues.apache.org/jira/browse/SPARK-12883
> Project: Spark
> Issue Type: Documentation
> Components: Documentation
> Affects Versions: 1.6.0
> Reporter: Manoj Samel
> Priority: Trivial
>
> Spark 1.6 dynamic allocation documentation still refers to 1.2.
> See text "There is currently not yet a solution for this in Spark 1.2. In
> future releases, the cached data may be preserved through an off-heap storage
> similar in spirit to how shuffle files are preserved through the external
> shuffle service"
> It appears 1.6 has parameter to address cache executor
> spark.dynamicAllocation.cachedExecutorIdleTimeout with default value as
> infinity.
> Pl update 1.6 documentation to refer to latest release and features
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