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https://issues.apache.org/jira/browse/FLINK-19177?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=17235216#comment-17235216
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Zhu Zhu edited comment on FLINK-19177 at 11/19/20, 7:16 AM:
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[~xintongsong] [~dian.fu]
Do you think we should introduce a section in [memory tuning 
doc|https://ci.apache.org/projects/flink/flink-docs-master/ops/memory/mem_tuning.html]
 to guide users to configure managed memory for python? And also add a pointer 
to it in [managed-memory introduction 
doc|https://ci.apache.org/projects/flink/flink-docs-master/ops/memory/mem_setup_tm.html#managed-memory],
 like the docs for statebackend and batch operators?



was (Author: zhuzh):
[~xintongsong] [~dian.fu]
Do you think we should introduce a section in [memory tuning 
doc|https://ci.apache.org/projects/flink/flink-docs-master/ops/memory/mem_tuning.html]
 to guide users to configure managed memory for python? And also add a pointer 
in [managed-memory introduction 
doc|https://ci.apache.org/projects/flink/flink-docs-master/ops/memory/mem_setup_tm.html#managed-memory]
 like the docs for statebackend and batch operators?


> FLIP-141: Intra-Slot Managed Memory Sharing
> -------------------------------------------
>
>                 Key: FLINK-19177
>                 URL: https://issues.apache.org/jira/browse/FLINK-19177
>             Project: Flink
>          Issue Type: Improvement
>          Components: Runtime / Coordination
>            Reporter: Xintong Song
>            Assignee: Xintong Song
>            Priority: Major
>              Labels: Umbrella
>             Fix For: 1.12.0
>
>
> This is the umbrella ticket of [FLIP-141: Intra-Slot Managed Memory 
> Sharing|https://cwiki.apache.org/confluence/display/FLINK/FLIP-141%3A+Intra-Slot+Managed+Memory+Sharing].
>  
> [FLIP-53|https://cwiki.apache.org/confluence/display/FLINK/FLIP-53%3A+Fine+Grained+Operator+Resource+Management]
>  introduced a fraction based approach for sharing managed memory within a 
> slot. This approach needs to be extended as python operators, which also use 
> managed memory, are introduced. This FLIP proposes a design for extending 
> intra-slot managed memory sharing for python operators and other potential 
> future managed memory use cases.



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