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https://issues.apache.org/jira/browse/SPARK-31711?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Luca Canali updated SPARK-31711:
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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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