ignite-issues mailing list archives

Site index · List index
Message view « Date » · « Thread »
Top « Date » · « Thread »
From "Taras Ledkov (JIRA)" <j...@apache.org>
Subject [jira] [Comment Edited] (IGNITE-3018) Cache affinity calculation is slow with large nodes number
Date Tue, 28 Mar 2017 11:55:42 GMT

    [ https://issues.apache.org/jira/browse/IGNITE-3018?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15943316#comment-15943316
] 

Taras Ledkov edited comment on IGNITE-3018 at 3/28/17 11:54 AM:
----------------------------------------------------------------

TC [results|http://195.239.208.174/project.html?projectId=IgniteTests&tab=projectOverview&branch_IgniteTests=pull%2F1647%2Fhead]

Tests results are OK with me. I don't see significant difference of the tests results between
the master branch and the patch.


was (Author: tledkov-gridgain):
Waits for TC [results|http://195.239.208.174/project.html?projectId=IgniteTests&tab=projectOverview&branch_IgniteTests=pull%2F1647%2Fhead]

> 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
>             Fix For: 2.0
>
>         Attachments: 003.png, 004.png, 008.png, 016.png, 064.png, 100.png, 128.png, 200.png,
256.png, 400.png, 600.png, balanced.003.png, balanced.004.png, balanced.008.png, balanced.016.png,
balanced.064.png, balanced.100.png, balanced.128.png, balanced.200.png, balanced.256.png,
balanced.400.png, balanced.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).



--
This message was sent by Atlassian JIRA
(v6.3.15#6346)

Mime
View raw message