[ https://issues.apache.org/jira/browse/SPARK-4751?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14633145#comment-14633145 ]
Apache Spark commented on SPARK-4751: ------------------------------------- User 'andrewor14' has created a pull request for this issue: https://github.com/apache/spark/pull/7532 > Support dynamic allocation for standalone mode > ---------------------------------------------- > > Key: SPARK-4751 > URL: https://issues.apache.org/jira/browse/SPARK-4751 > Project: Spark > Issue Type: New Feature > Components: Spark Core > Affects Versions: 1.2.0 > Reporter: Andrew Or > Assignee: Andrew Or > Priority: Critical > > This is equivalent to SPARK-3822 but for standalone mode. > This is actually a very tricky issue because the scheduling mechanism in the > standalone Master uses different semantics. In standalone mode we allocate > resources based on cores. By default, an application will grab all the cores > in the cluster unless "spark.cores.max" is specified. Unfortunately, this > means an application could get executors of different sizes (in terms of > cores) if: > 1) App 1 kills an executor > 2) App 2, with "spark.cores.max" set, grabs a subset of cores on a worker > 3) App 1 requests an executor > In this case, the new executor that App 1 gets back will be smaller than the > rest and can execute fewer tasks in parallel. Further, standalone mode is > subject to the constraint that only one executor can be allocated on each > worker per application. As a result, it is rather meaningless to request new > executors if the existing ones are already spread out across all nodes. -- This message was sent by Atlassian JIRA (v6.3.4#6332) --------------------------------------------------------------------- To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org For additional commands, e-mail: issues-h...@spark.apache.org