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https://issues.apache.org/jira/browse/IGNITE-3018?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15878234#comment-15878234
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Taras Ledkov commented on IGNITE-3018:
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Chi^2 test:
|| Nodes || Fair || Rendezvous (old) || FastRendezvous ||
|*5* | 0.002531 | 0.003618 | 0.002531 |
|*64* | 0.077637 | 0.063599 | 0.077637 |
|*100* | 0.115036 | 0.113892 | 0.115036 |
|*128* | 0.125732 | 0.121094 | 0.125732 |
|*200* | 0.216888 | 0.203918 | 0.216888 |
|*256* | 0.269531 | 0.248535 | 0.269531 |
|*300* | 0.287460 | 0.280594 | 0.287460 |
|*400* | 0.396179 | 0.361847 | 0.396179 |
|*500* | 0.504898 | 0.501083 | 0.504898 |
|*600* | 0.617050 | 0.589584 | 0.617050 |
> 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: Yakov Zhdanov
> 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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