You are viewing a plain text version of this content. The canonical link for it is here.

Posted to issues@spark.apache.org by "Andrew Or (JIRA)" <ji...@apache.org> on 2015/06/30 20:31:06 UTC

[jira] [Updated] (SPARK-8735) Expose metrics for runtime memory usage

     [ https://issues.apache.org/jira/browse/SPARK-8735?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]

Andrew Or updated SPARK-8735:
-----------------------------
    Target Version/s: 1.5.0

> Expose metrics for runtime memory usage
> ---------------------------------------
>
>                 Key: SPARK-8735
>                 URL: https://issues.apache.org/jira/browse/SPARK-8735
>             Project: Spark
>          Issue Type: Improvement
>          Components: Spark Core
>            Reporter: Andrew Or
>            Assignee: Andrew Or
>
> Spark has many uses of memory: caching, shuffle, metadata etc. It is useful for users to be able to drill down on the internal memory allocation for memory-intensive operations like aggregations and joins. The goal is to do this for both tungsten and non-tungsten applications.



--
This message was sent by Atlassian JIRA
(v6.3.4#6332)

---------------------------------------------------------------------
To unsubscribe, e-mail: issues-unsubscribe@spark.apache.org
For additional commands, e-mail: issues-help@spark.apache.org