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https://issues.apache.org/jira/browse/SPARK-3682?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Sandy Ryza updated SPARK-3682:
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Description:
Spark has a zillion configuration options and a zillion different things that
can go wrong with a job. Improvements like incremental and better metrics and
the proposed spark replay debugger provide more insight into what's going on
under the covers. However, it's difficult for non-advanced users to synthesize
this information and understand where to direct their attention. It would be
helpful to have some sort of central location on the UI users could go to that
would provide indications about why an app/job is failing or performing poorly.
Some helpful messages that we could provide:
* Warn that the tasks in a particular stage are spending a long time in GC.
* Warn that spark.shuffle.memoryFraction does not fit inside the young
generation.
* Warn that tasks in a particular stage are very short, and that the number of
partitions should probably be decreased.
* Warn that tasks in a particular stage are spilling a lot, and that the number
of partitions should probably be increased.
* Warn that a cached RDD that gets a lot of use does not fit in memory, and a
lot of time is being spent recomputing it.
To start, probably two kinds of warnings would be most helpful.
* Warnings at the app level that report on misconfigurations, issues with the
general health of executors.
* Warnings at the job level that indicate why a job might be performing slowly.
was:
Spark has a zillion configuration options and a zillion different things that
can go wrong with a job. Improvements like incremental and better metrics and
the proposed spark replay debugger provide more insight into what's going on
under the covers. However, it's difficult for non-advanced users to synthesize
this information and understand where to direct their attention. It would be
helpful to have some sort of central location on the UI users could go to that
would provide indications about why an app/job is failing or performing poorly.
Some helpful messages that we could provide:
* Warn that the tasks in a particular stage are spending a long time in GC.
* Warn that spark.shuffle.memoryFraction does not fit inside the young
generation.
* Warn that tasks in a particular stage are very short, and that the number of
partitions should probably be decreased.
* Warn that tasks in a particular stage are spilling a lot, and that the number
of partitions should probably be decreased.
* Warn that a cached RDD that gets a lot of use does not fit in memory, and a
lot of time is being spent recomputing it.
To start, probably two kinds of warnings would be most helpful.
* Warnings at the app level that report on misconfigurations, issues with the
general health of executors.
* Warnings at the job level that indicate why a job might be performing slowly.
> Add helpful warnings to the UI
> ------------------------------
>
> Key: SPARK-3682
> URL: https://issues.apache.org/jira/browse/SPARK-3682
> Project: Spark
> Issue Type: New Feature
> Components: Web UI
> Affects Versions: 1.1.0
> Reporter: Sandy Ryza
>
> Spark has a zillion configuration options and a zillion different things that
> can go wrong with a job. Improvements like incremental and better metrics
> and the proposed spark replay debugger provide more insight into what's going
> on under the covers. However, it's difficult for non-advanced users to
> synthesize this information and understand where to direct their attention.
> It would be helpful to have some sort of central location on the UI users
> could go to that would provide indications about why an app/job is failing or
> performing poorly.
> Some helpful messages that we could provide:
> * Warn that the tasks in a particular stage are spending a long time in GC.
> * Warn that spark.shuffle.memoryFraction does not fit inside the young
> generation.
> * Warn that tasks in a particular stage are very short, and that the number
> of partitions should probably be decreased.
> * Warn that tasks in a particular stage are spilling a lot, and that the
> number of partitions should probably be increased.
> * Warn that a cached RDD that gets a lot of use does not fit in memory, and a
> lot of time is being spent recomputing it.
> To start, probably two kinds of warnings would be most helpful.
> * Warnings at the app level that report on misconfigurations, issues with the
> general health of executors.
> * Warnings at the job level that indicate why a job might be performing
> slowly.
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