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Posted to issues@spark.apache.org by "Luca Canali (Jira)" <ji...@apache.org> on 2020/05/14 14:13:00 UTC
[jira] [Updated] (SPARK-31711) Register the executor source with
the metrics system when running in local mode.
[ https://issues.apache.org/jira/browse/SPARK-31711?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]
Luca Canali updated SPARK-31711:
--------------------------------
Description:
The Apache Spark metrics system provides many useful insights on the Spark workload. In particular, the executor source metrics (https://github.com/apache/spark/blob/master/docs/monitoring.md#component-instance--executor) provide detailed info, including the number of active tasks, some I/O metrics, and task metrics details. Executor source metrics, contrary to other sources (for example ExecutorMetrics source), are not yet available when running in local mode.
This JIRA proposes to register the executor source with the Spark metrics system when running in local mode, as this can be very useful when testing and troubleshooting Spark workloads.
was:
The Apache Spark metrics system provides many useful insights on the Spark workload. In particular, the [executor source metrics](https://github.com/apache/spark/blob/master/docs/monitoring.md#component-instance--executor) provide detailed info, including number of active tasks, some I/O metrics, and task metrics details. Executor source, contrary to other sources (for example ExecutorMetrics source), are not yet available when running in local mode.
This JIRA proposes to register the executor source with the Spark metrics system when running in local mode, as this can be very useful when testing and troubleshooting Spark workloads.
> Register the executor source with the metrics system when running in local mode.
> --------------------------------------------------------------------------------
>
> Key: SPARK-31711
> URL: https://issues.apache.org/jira/browse/SPARK-31711
> Project: Spark
> Issue Type: Improvement
> Components: Spark Core
> Affects Versions: 3.0.0
> Reporter: Luca Canali
> Priority: Minor
>
> The Apache Spark metrics system provides many useful insights on the Spark workload. In particular, the executor source metrics (https://github.com/apache/spark/blob/master/docs/monitoring.md#component-instance--executor) provide detailed info, including the number of active tasks, some I/O metrics, and task metrics details. Executor source metrics, contrary to other sources (for example ExecutorMetrics source), are not yet available when running in local mode.
> This JIRA proposes to register the executor source with the Spark metrics system when running in local mode, as this can be very useful when testing and troubleshooting Spark workloads.
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