[
https://issues.apache.org/jira/browse/SPARK-21829?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
Sean Owen resolved SPARK-21829.
-------------------------------
Resolution: Won't Fix
> Enable config to permanently blacklist a list of nodes
> ------------------------------------------------------
>
> Key: SPARK-21829
> URL: https://issues.apache.org/jira/browse/SPARK-21829
> Project: Spark
> Issue Type: New Feature
> Components: Scheduler, Spark Core
> Affects Versions: 2.1.1, 2.2.0
> Reporter: Luca Canali
> Priority: Minor
>
> The idea for this proposal comes from a performance incident in a local
> cluster where a job was found very slow because of a log tail of stragglers
> due to 2 nodes in the cluster being slow to access a remote filesystem.
> The issue was limited to the 2 machines and was related to external
> configurations: the 2 machines that performed badly when accessing the remote
> file system were behaving normally for other jobs in the cluster (a shared
> YARN cluster).
> With this new feature I propose to introduce a mechanism to allow users to
> specify a list of nodes in the cluster where executors/tasks should not run
> for a specific job.
> The proposed implementation that I tested (see PR) uses the Spark blacklist
> mechanism. With the parameter spark.blacklist.alwaysBlacklistedNodes, a list
> of user-specified nodes is added to the blacklist at the start of the Spark
> Context and it is never expired.
> I have tested this on a YARN cluster on a case taken from the original
> production problem and I confirm a performance improvement of about 5x for
> the specific test case I have. I imagine that there can be other cases where
> Spark users may want to blacklist a set of nodes. This can be used for
> troubleshooting, including cases where certain nodes/executors are slow for a
> given workload and this is caused by external agents, so the anomaly is not
> picked up by the cluster manager.
--
This message was sent by Atlassian JIRA
(v6.4.14#64029)
---------------------------------------------------------------------
To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org
For additional commands, e-mail: issues-h...@spark.apache.org
