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https://issues.apache.org/jira/browse/SPARK-10543?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Andrew Or resolved SPARK-10543.
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Resolution: Fixed
Assignee: Sen Fang
Fix Version/s: 1.5.1
1.6.0
Target Version/s: 1.6.0, 1.5.1
> Peak Execution Memory Quantile should be Per-task Basis
> -------------------------------------------------------
>
> Key: SPARK-10543
> URL: https://issues.apache.org/jira/browse/SPARK-10543
> Project: Spark
> Issue Type: Bug
> Components: Spark Core
> Affects Versions: 1.5.0
> Reporter: Sen Fang
> Assignee: Sen Fang
> Priority: Minor
> Fix For: 1.6.0, 1.5.1
>
>
> Currently the Peak Execution Memory quantiles seem to be cumulative rather
> than per task basis. For example, I have seen a value of 2TB in one of my
> jobs on the quantile metric but each individual task shows less than 1GB on
> the bottom table.
> [~andrewor14] In your PR https://github.com/apache/spark/pull/7770, the
> screenshot shows the Max Peak Execution Memory of 792.5KB while in the bottom
> it's about 50KB per task (unless your workload is skewed)
> The fix seems straightforward that we use the `update` rather than `value`
> from the accumulable. I'm happy to provide a PR if people agree this is the
> right behavior.
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