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https://issues.apache.org/jira/browse/IGNITE-10799?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16791719#comment-16791719
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Ignite TC Bot commented on IGNITE-10799:
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[TeamCity *--> Run :: All*
Results|https://ci.ignite.apache.org/viewLog.html?buildId=3256705&buildTypeId=IgniteTests24Java8_RunAll]
> Optimize affinity initialization/re-calculation
> -----------------------------------------------
>
> Key: IGNITE-10799
> URL: https://issues.apache.org/jira/browse/IGNITE-10799
> Project: Ignite
> Issue Type: Improvement
> Components: cache
> Affects Versions: 2.4
> Reporter: Pavel Kovalenko
> Assignee: Pavel Kovalenko
> Priority: Major
> Fix For: 2.8
>
> Time Spent: 10m
> Remaining Estimate: 0h
>
> In case of persistence enabled and a baseline is set we have 2 main
> approaches to recalculate affinity:
> {noformat}
> org.apache.ignite.internal.processors.cache.CacheAffinitySharedManager#onServerJoinWithExchangeMergeProtocol
> org.apache.ignite.internal.processors.cache.CacheAffinitySharedManager#onServerLeftWithExchangeMergeProtocol
> {noformat}
> Both of them following the same approach of recalculating:
> 1) Take a current baseline (ideal assignment).
> 2) Filter out offline nodes from it.
> 3) Choose new primary nodes if previous went away.
> 4) Place temporal primary nodes to late affinity assignment set.
> Looking at implementation details we may notice that we do a lot of
> unnecessary online nodes cache lookups and array list copies. The performance
> becomes too slow if we do recalculate affinity for replicated caches (It
> takes P * N on each node, where P - partitions count, N - the number of nodes
> in the cluster). In case of large partitions count or large cluster, it may
> take few seconds, which is unacceptable, because this process happens during
> PME and freezes ongoing cluster operations.
> We should investigate possible bottlenecks and improve the performance of
> affinity recalculation.
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