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https://issues.apache.org/jira/browse/SOLR-14274?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=17067191#comment-17067191
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ASF subversion and git services commented on SOLR-14274:
--------------------------------------------------------

Commit fe0e1d0b9d90d100cd919e20c0c78192b8ddf741 in lucene-solr's branch 
refs/heads/branch_8x from Mike
[ https://gitbox.apache.org/repos/asf?p=lucene-solr.git;h=fe0e1d0 ]

SOLR-14274 Do not register multiple sets of JVM metrics (#1299)



> Multiple CoreContainers will register the same JVM Metrics
> ----------------------------------------------------------
>
>                 Key: SOLR-14274
>                 URL: https://issues.apache.org/jira/browse/SOLR-14274
>             Project: Solr
>          Issue Type: Bug
>      Security Level: Public(Default Security Level. Issues are Public) 
>            Reporter: Mike Drob
>            Assignee: Mike Drob
>            Priority: Major
>             Fix For: master (9.0), 8.6
>
>          Time Spent: 20m
>  Remaining Estimate: 0h
>
> When running multiple CoreContainer in the same JVM, either because we called 
> {{SolrCloudTestCase.configureCluster(int n)}} with {{n > 1}} or because we 
> have multiple tests running in the same JVM in succession, we will have 
> contention on the shared JVM {{metricsRegistry}} as they each replace the 
> existing metrics with their own. Further, with multiple nodes at the same 
> time, some of these metrics will be incorrect anyway, since they will only 
> reflect a single core container. Others will be fine since I think they are 
> reading system-level information so it doesn't matter where it comes from.
> I think this is a test-only issue, since the circumstances where somebody is 
> running multiple core containers in a single JVM in production should be 
> rare, but maybe there are edge cases affected with EmbeddedSolrServer and 
> MapReduce or Spark, or other unusual deployment patterns.
> Removing the metrics registration entirely can speed up 
> {{configureCluster(100).build()}} on my machine from 2 minutes to 30 seconds, 
> so I'm optimistic that there can be gains here without sacrificing the 
> feature entirely.



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