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From "Yongzhi Chen (JIRA)" <j...@apache.org>
Subject [jira] [Issue Comment Deleted] (HIVE-21045) Add HMS total api count stats and connection pool stats to metrics
Date Fri, 25 Jan 2019 20:08:00 GMT

     [ https://issues.apache.org/jira/browse/HIVE-21045?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]

Yongzhi Chen updated HIVE-21045:
--------------------------------
    Comment: was deleted

(was: The patch looks good. +1 pending tests. )

> 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
>         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
>
>
> 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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