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https://issues.apache.org/jira/browse/PHOENIX-1452?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14340363#comment-14340363
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Jan Fernando commented on PHOENIX-1452:
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[~samarthjain] In terms of the thread pool, the simple thing that would be
really useful would just be know what the max number of threads and the max
queue depth size was for - that would provide me with a very useful highlevel
overview of usage relative to configuration. I was thinking of something like
every time a task was enqueued you checked the size of the queue and threads in
use and if > max set size on a counter. Do you think something like that is
lightweight and easy to do? If so it would be a really useful heuristic.
> 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: Improvement
> Affects Versions: 5.0.0, 4.2
> Reporter: Jan Fernando
> Assignee: Samarth Jain
> Attachments: 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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