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Posted to issues@spark.apache.org by "Kousuke Saruta (JIRA)" <ji...@apache.org> on 2014/09/03 17:37:51 UTC
[jira] [Updated] (SPARK-3377) codahale base Metrics data between
applications can jumble up together
[ https://issues.apache.org/jira/browse/SPARK-3377?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]
Kousuke Saruta updated SPARK-3377:
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Description:
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 jumble up together. e.g, SparkPi.DAGScheduler.stage.failedStages jumble.
(2) When 2+ executors run on the same machine, JVM metrics of each executors jumble. e.g, We current implementation cannot distinguish metric "jvm.memory" is for which executor.
was:
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 jumble up together. e.g, SparkPi.DAGScheduler.stage.failedStages jumble.
(2) When 2+ executors run on the same machine, JVM metrics of each executors jumble.
> codahale base Metrics data between applications can jumble up together
> ----------------------------------------------------------------------
>
> 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 jumble up together. e.g, SparkPi.DAGScheduler.stage.failedStages jumble.
> (2) When 2+ executors run on the same machine, JVM metrics of each executors jumble. e.g, We current implementation cannot distinguish metric "jvm.memory" is for which executor.
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