Pavel Kovalenko created IGNITE-10799:
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Summary: 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: 2.1
Reporter: Pavel Kovalenko
Assignee: Pavel Kovalenko
Fix For: 2.8
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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