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Posted to issues@ignite.apache.org by "Semen Boikov (JIRA)" <ji...@apache.org> on 2016/11/14 09:49:58 UTC
[jira] [Updated] (IGNITE-3018) Cache affinity calculation is slow
with large nodes number
[ https://issues.apache.org/jira/browse/IGNITE-3018?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]
Semen Boikov updated IGNITE-3018:
---------------------------------
Fix Version/s: (was: 1.8)
2.0
> Cache affinity calculation is slow with large nodes number
> ----------------------------------------------------------
>
> Key: IGNITE-3018
> URL: https://issues.apache.org/jira/browse/IGNITE-3018
> Project: Ignite
> Issue Type: Bug
> Components: cache
> Reporter: Semen Boikov
> Assignee: Taras Ledkov
> Priority: Critical
> Fix For: 2.0
>
> Attachments: 003.png, 064.png, 100.png, 128.png, 200.png, 300.png, 400.png, 500.png, 600.png
>
>
> With large number of cache server nodes (> 200) RendezvousAffinityFunction and FairAffinityFunction work pretty slow .
> For RendezvousAffinityFunction.assignPartitions can take hundredes of milliseconds, for FairAffinityFunction it can take seconds.
> For RendezvousAffinityFunction most time is spent in MD5 hash calculation and nodes list sorting. As optimization we can try to cache {partion, node} MD5 hash or try another hash function. Also several minor optimizations are possible (avoid unncecessary allocations, only one thread local 'get', etc).
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