You are viewing a plain text version of this content. The canonical link for it is here.
Posted to issues@spark.apache.org by "Davies Liu (JIRA)" <ji...@apache.org> on 2014/09/09 23:51:28 UTC

[jira] [Updated] (SPARK-3465) Task metrics are not aggregated correctly in local mode

     [ https://issues.apache.org/jira/browse/SPARK-3465?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]

Davies Liu updated SPARK-3465:
------------------------------
    Description: 
In local mode, after onExecutorMetricsUpdate(), t.taskMetrics will be the same object with that in TaskContext (because there is no serialization for MetricsUpdate in local mode), then all the upcoming changes in metrics will be lost, because updateAggregateMetrics() only counts the difference in these two. 

This bug was introduced in #2099.

  was:In local mode, after onExecutorMetricsUpdate(), t.taskMetrics will be the same object with that in TaskContext (because there is no serialization for MetricsUpdate in local mode), then all the upcoming changes in metrics will be lost, because updateAggregateMetrics() only counts the difference in these two. 


> Task metrics are not aggregated correctly in local mode
> -------------------------------------------------------
>
>                 Key: SPARK-3465
>                 URL: https://issues.apache.org/jira/browse/SPARK-3465
>             Project: Spark
>          Issue Type: Bug
>          Components: Spark Core
>    Affects Versions: 1.1.0
>            Reporter: Davies Liu
>            Assignee: Davies Liu
>            Priority: Blocker
>
> In local mode, after onExecutorMetricsUpdate(), t.taskMetrics will be the same object with that in TaskContext (because there is no serialization for MetricsUpdate in local mode), then all the upcoming changes in metrics will be lost, because updateAggregateMetrics() only counts the difference in these two. 
> This bug was introduced in #2099.



--
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