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https://issues.apache.org/jira/browse/FLINK-19177?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Xintong Song closed FLINK-19177.
--------------------------------
Release Note: In cases where Python UDFs are used together with RocksDB
state backend in streaming or built-in batch algorithms in batch, the user can
control how managed memory should be shared between data processing (RocksDB
state backend or batch algorithms) and Python, by overwriting [managed memory
consumer weights]({% link ops/mem_setup_tm.md %}#consumer-weights).
Resolution: Done
All subtasks are resolved.
> 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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