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From "ASF GitHub Bot (Jira)" <j...@apache.org>
Subject [jira] [Work logged] (HDDS-1783) Latency metric for applyTransaction in ContainerStateMachine
Date Wed, 28 Aug 2019 15:54:00 GMT

     [ https://issues.apache.org/jira/browse/HDDS-1783?focusedWorklogId=302982&page=com.atlassian.jira.plugin.system.issuetabpanels:worklog-tabpanel#worklog-302982
]

ASF GitHub Bot logged work on HDDS-1783:
----------------------------------------

                Author: ASF GitHub Bot
            Created on: 28/Aug/19 15:53
            Start Date: 28/Aug/19 15:53
    Worklog Time Spent: 10m 
      Work Description: avijayanhwx commented on issue #1363: HDDS-1783 : Latency metric for
applyTransaction in ContainerStateMach…
URL: https://github.com/apache/hadoop/pull/1363#issuecomment-525807821
 
 
   @bshashikant Isn't the per operation latency covered in org.apache.hadoop.ozone.container.common.transport.server.ratis.CSMMetrics#opsLatency?
This metric was only intended to cover the whole latency including thread scheduling. 
 
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Issue Time Tracking
-------------------

    Worklog Id:     (was: 302982)
    Time Spent: 1h 10m  (was: 1h)

> Latency metric for applyTransaction in ContainerStateMachine
> ------------------------------------------------------------
>
>                 Key: HDDS-1783
>                 URL: https://issues.apache.org/jira/browse/HDDS-1783
>             Project: Hadoop Distributed Data Store
>          Issue Type: Improvement
>          Components: Ozone Datanode
>            Reporter: Supratim Deka
>            Assignee: Aravindan Vijayan
>            Priority: Major
>              Labels: pull-request-available
>          Time Spent: 1h 10m
>  Remaining Estimate: 0h
>
> applyTransaction is invoked from the Ratis pipeline and the ContainerStateMachine
> uses a async executor to complete the task.
>  
> We require a latency metric to track the performance of log apply operations in the state
machine. This will measure the end-to-end latency of apply which includes the queueing delay
in the executor queues. Combined with the latency measurement in HddsDispatcher, this will
be an indicator if the executors are overloaded.



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