You are viewing a plain text version of this content. The canonical link for it is here.
Posted to issues@spark.apache.org by "Hyukjin Kwon (JIRA)" <ji...@apache.org> on 2019/05/21 04:04:14 UTC
[jira] [Updated] (SPARK-15176) Job Scheduling Within Application
Suffers from Priority Inversion
[ https://issues.apache.org/jira/browse/SPARK-15176?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]
Hyukjin Kwon updated SPARK-15176:
---------------------------------
Labels: bulk-closed (was: )
> Job Scheduling Within Application Suffers from Priority Inversion
> -----------------------------------------------------------------
>
> Key: SPARK-15176
> URL: https://issues.apache.org/jira/browse/SPARK-15176
> Project: Spark
> Issue Type: Bug
> Components: Scheduler
> Affects Versions: 1.6.1
> Reporter: Nick White
> Priority: Major
> Labels: bulk-closed
>
> Say I have two pools, and N cores in my cluster:
> * I submit a job to one, which has M >> N tasks
> * N of the M tasks are scheduled
> * I submit a job to the second pool - but none of its tasks get scheduled until a task from the other pool finishes!
> This can lead to unbounded denial-of-service for the second pool - regardless of `minShare` or `weight` settings. Ideally Spark would support a pre-emption mechanism, or an upper bound on a pool's resource usage.
--
This message was sent by Atlassian JIRA
(v7.6.3#76005)
---------------------------------------------------------------------
To unsubscribe, e-mail: issues-unsubscribe@spark.apache.org
For additional commands, e-mail: issues-help@spark.apache.org