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https://issues.apache.org/jira/browse/FLINK-4942?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Flink Jira Bot updated FLINK-4942:
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Labels: auto-deprioritized-major auto-deprioritized-minor auto-unassigned
(was: auto-deprioritized-major auto-unassigned stale-minor)
Priority: Not a Priority (was: Minor)
This issue was labeled "stale-minor" 7 days ago and has not received any
updates so it is being deprioritized. If this ticket is actually Minor, please
raise the priority and ask a committer to assign you the issue or revive the
public discussion.
> Improve processing performance of HeapInternalTimerService with key groups
> --------------------------------------------------------------------------
>
> Key: FLINK-4942
> URL: https://issues.apache.org/jira/browse/FLINK-4942
> Project: Flink
> Issue Type: Improvement
> Components: Runtime / State Backends
> Reporter: Stefan Richter
> Priority: Not a Priority
> Labels: auto-deprioritized-major, auto-deprioritized-minor,
> auto-unassigned
>
> Currently, key groups awareness in `HeapInternalTimerService` is basically
> implemented as (hash) map of (hash) sets. Purpose of this is grouping key
> groups together in a way that allows easy serialization into key groups.
> However, this data layout comes along with some significant performance
> decrease, in particular when the number of key groups is high.
> I suggest to keep all timers in one set again at runtime, thus being as fast
> as in previous versions without key groups.
> Instead, we can perform a very fast online partitioning into key groups
> before a snapshot.
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