[jira] [Commented] (SPARK-3377) Metrics can be accidentally aggregated against our intention

["Apache Spark (JIRA)" <ji...@apache.org>]

    [ https://issues.apache.org/jira/browse/SPARK-3377?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14137669#comment-14137669 ] 

Apache Spark commented on SPARK-3377:
-------------------------------------

User 'sarutak' has created a pull request for this issue:
https://github.com/apache/spark/pull/2432

> Metrics can be accidentally aggregated against our intention
> ------------------------------------------------------------
>
>                 Key: SPARK-3377
>                 URL: https://issues.apache.org/jira/browse/SPARK-3377
>             Project: Spark
>          Issue Type: Bug
>          Components: Spark Core
>    Affects Versions: 1.1.0
>            Reporter: Kousuke Saruta
>            Priority: Critical
>
> I'm using codahale base MetricsSystem of Spark with JMX or Graphite, and I saw following 2 problems.
> (1) When applications which have same spark.app.name run on cluster at the same time, some metrics names are mixed. For instance, if 2+ application is running on the cluster at the same time, each application emits the same named metric like  "SparkPi.DAGScheduler.stage.failedStages" and Graphite cannot distinguish the metrics is for which application.
> (2) When 2+ executors run on the same machine, JVM metrics of each executors are mixed. For instance, 2+ executors running on the same node can emit the same named metric "jvm.memory" and Graphite cannot distinguish the metrics is from which application.



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