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https://issues.apache.org/jira/browse/PHOENIX-1452?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14349660#comment-14349660
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Samarth Jain commented on PHOENIX-1452:
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Thanks. I will make the change before I commit. And yes, I am up for being the 
RM for 4.3. Would be ideal to get this change in 4.3 cause like you said it 
doesn't break any compatibility and provides a much needed mechanism for 
monitoring phoenix internal metrics. 

> Add Phoenix client-side logging and capture resource utilization metrics
> ------------------------------------------------------------------------
>
>                 Key: PHOENIX-1452
>                 URL: https://issues.apache.org/jira/browse/PHOENIX-1452
>             Project: Phoenix
>          Issue Type: New Feature
>    Affects Versions: 5.0.0, 4.2
>            Reporter: Jan Fernando
>            Assignee: Samarth Jain
>         Attachments: PHOENIX-1452.patch, PHOENIX-1452_v2.patch, 
> PHOENIX-1452_v3.patch, PHOENIX-1452_v4.patch, wip.patch
>
>
> For performance testing and tuning of features that use Phoenix and for 
> production monitoring it would be really helpful to easily be able to extract 
> statistics about Phoenix's client-side Thread Pool and Queue Depth usage to 
> help with tuning and being able to correlate the impact of tuning these 2 
> parameters to query performance.
> For global per JVM logging one of the following would meet my needs, with a 
> preference for #2:
> 1. A simple log line that that logs the data in ThreadPoolExecutor.toString() 
> at a configurable interval
> 2. Exposing the ThreadPoolExecutor metrics in PhoenixRuntime or other global 
> client exposed class and allow client to do their own logging.
> In addition to this it would also be really valuable to have a single log 
> line per query that provides statistics about the level of parallelism i.e. 
> number of parallel scans being executed. I don't full explain plan level of 
> data but a good heuristic to be able to track over time how queries are 
> utilizing the thread pool as data size grows etc. 



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