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From "ASF GitHub Bot (JIRA)" <>
Subject [jira] [Commented] (CASSANDRA-14436) Add sampler for query time and expose with nodetool
Date Sat, 04 Aug 2018 03:06:00 GMT


ASF GitHub Bot commented on CASSANDRA-14436:

Github user dineshjoshi commented on the issue:
    Stepping back a bit, I see the samplers are stateful classes that are enabled and disabled.
This means, if there is an exception in the rmi thread that is executing the `beginLocalSampling`
and `finishLocalSampling`, the samplers will continue to run indefinitely and this might cause
issues. It would be best to instantiate Samplers on demand with a specific Duration. Each
sampler can stop accepting new samples once the duration expires. This would also mean that
you no longer have to keep enabling disabling samplers - allowing you to get rid of `enabled`
and other internal state variables could be made immutable for example in `FrequencySampler`,
`StreamSummary` can be declared as `final` and initialized in the constructor.
    If you want all samplers to start sampling exactly at the same moment (not sure if that
is a requirement) then you could potentially use a shared countdown latch. The thread instantiating
the samplers can decrement it once it is done creating and initializing all samplers. WDYT?

> Add sampler for query time and expose with nodetool
> ---------------------------------------------------
>                 Key: CASSANDRA-14436
>                 URL:
>             Project: Cassandra
>          Issue Type: Improvement
>            Reporter: Chris Lohfink
>            Assignee: Chris Lohfink
>            Priority: Major
> Create a new {{nodetool profileload}} that functions just like toppartitions but with
more data, returning the slowest local reads and writes on the host during a given duration
and highest frequency touched partitions (same as {{nodetool toppartitions}}). Refactor included
to extend use of the sampler for uses outside of top frequency (max instead of total sample
> Future work to this is to include top cpu and allocations by query and possibly tasks/cpu/allocations
by stage during time window.

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