[
https://issues.apache.org/jira/browse/SPARK-20286?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15965411#comment-15965411
]
Saisai Shao commented on SPARK-20286:
-------------------------------------
bq. Maybe the best approach is to change from cachedExecutorIdleTimeout to
executorIdleTimeout on all cached executors when the last RDD has been
unpersisted, and then restart the time counter (unpersist will then count as an
action).
Yes, I think this is a feasible solution. I can help out it if you're not
familiar with that code.
> dynamicAllocation.executorIdleTimeout is ignored after unpersist
> ----------------------------------------------------------------
>
> Key: SPARK-20286
> URL: https://issues.apache.org/jira/browse/SPARK-20286
> Project: Spark
> Issue Type: Bug
> Components: Spark Core
> Affects Versions: 2.0.1
> Reporter: Miguel Pérez
>
> With dynamic allocation enabled, it seems that executors with cached data
> which are unpersisted are still being killed using the
> {{dynamicAllocation.cachedExecutorIdleTimeout}} configuration, instead of
> {{dynamicAllocation.executorIdleTimeout}}. Assuming the default configuration
> ({{dynamicAllocation.cachedExecutorIdleTimeout = Infinity}}), an executor
> with unpersisted data won't be released until the job ends.
> *How to reproduce*
> - Set different values for {{dynamicAllocation.executorIdleTimeout}} and
> {{dynamicAllocation.cachedExecutorIdleTimeout}}
> - Load a file into a RDD and persist it
> - Execute an action on the RDD (like a count) so some executors are activated.
> - When the action has finished, unpersist the RDD
> - The application UI removes correctly the persisted data from the *Storage*
> tab, but if you look in the *Executors* tab, you will find that the executors
> remain *active* until ({{dynamicAllocation.cachedExecutorIdleTimeout}} is
> reached.
--
This message was sent by Atlassian JIRA
(v6.3.15#6346)
---------------------------------------------------------------------
To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org
For additional commands, e-mail: issues-h...@spark.apache.org
