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https://issues.apache.org/jira/browse/HIVE-21045?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16754018#comment-16754018
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Yongzhi Chen commented on HIVE-21045:
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[~karthik.manamcheri], the tests should be kicked off automatically. Your match
name seems follows the same pattern, although a little different:
I used to name the file as HIVE-21045.01-branch-3.patch .
And it is also possible that the jira is in solved mode.
> Add HMS total api count stats and connection pool stats to metrics
> ------------------------------------------------------------------
>
> Key: HIVE-21045
> URL: https://issues.apache.org/jira/browse/HIVE-21045
> Project: Hive
> Issue Type: Improvement
> Components: Standalone Metastore
> Reporter: Karthik Manamcheri
> Assignee: Karthik Manamcheri
> Priority: Minor
> Fix For: 4.0.0
>
> Attachments: HIVE-21045.1.patch, HIVE-21045.2.patch,
> HIVE-21045.3.patch, HIVE-21045.4.patch, HIVE-21045.5.patch,
> HIVE-21045.6.patch, HIVE-21045.7.patch, HIVE-21045.branch-3.patch
>
>
> There are two key metrics which I think we lack and which would be really
> great to help with scaling visibility in HMS.
> *Total API calls duration stats*
> We already compute and log the duration of API calls in the {{PerfLogger}}.
> We don't have any gauge or timer on what the average duration of an API call
> is for the past some bucket of time. This will give us an insight into if
> there is load on the server which is increasing the average API response time.
>
> *Connection Pool stats*
> We can use different connection pooling libraries such as bonecp or hikaricp.
> These pool managers expose statistics such as average time waiting to get a
> connection, number of connections active, etc. We should expose this as a
> metric so that we can track if the the connection pool size configured is too
> small and we are saturating!
> These metrics would help catch problems with HMS resource contention before
> they actually have jobs failing.
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