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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-unassigned stale-minor (was:
auto-deprioritized-major auto-unassigned)
I am the [Flink Jira Bot|https://github.com/apache/flink-jira-bot/] and I help
the community manage its development. I see this issues has been marked as
Minor but is unassigned and neither itself nor its Sub-Tasks have been updated
for 180 days. I have gone ahead and marked it "stale-minor". If this ticket is
still Minor, please either assign yourself or give an update. Afterwards,
please remove the label or in 7 days the issue will be deprioritized.
> 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: Minor
> Labels: auto-deprioritized-major, auto-unassigned, stale-minor
>
> 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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