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From "Erik Krogen (JIRA)" <j...@apache.org>
Subject [jira] [Created] (HADOOP-14989) Multiple metrics2 sinks (incl JMX) result in inconsistent Mutable(Stat|Rate) values
Date Fri, 27 Oct 2017 16:42:00 GMT
Erik Krogen created HADOOP-14989:
------------------------------------

             Summary: Multiple metrics2 sinks (incl JMX) result in inconsistent Mutable(Stat|Rate)
values
                 Key: HADOOP-14989
                 URL: https://issues.apache.org/jira/browse/HADOOP-14989
             Project: Hadoop Common
          Issue Type: Bug
          Components: metrics
    Affects Versions: 2.6.5
            Reporter: Erik Krogen
            Priority: Critical


While doing some digging in the metrics2 system recently, we noticed that the way {{MutableStat}}
values are collected (and thus {{MutableRate}}, since it is based off of {{MutableStat}})
mean that each sink configured (including JMX) only receives a portion of the average information.

{{MutableStat}}, to compute its average value, maintains a total value since last snapshot,
as well as operation count since last snapshot. Upon snapshotting, the average is calculated
as (total / opCount) and placed into a gauge metric, and total / operation count are cleared.
So the average value represents the average since the last snapshot. If only a single sink
ever snapshots, this would result in the expected behavior that the value is the average over
the reporting period. However, if multiple sinks are configured, or if the JMX cache is refreshed,
this is another snapshot operation. So, for example, if you have a FileSink configured at
a 60 second interval and your JMX cache refreshes itself 1 second before the FileSink period
fires, the values emitted to your FileSink only represent averages _over the last one second_.

A few ways to solve this issue:
* From an operator perspective, ensure only one sink is configured. This is not realistic
given that the JMX cache exhibits the same behavior.
* Make {{MutableRate}} manage its own average refresh, similar to {{MutableQuantiles}}, which
has a refresh thread and saves a snapshot of the last quantile values that it will serve up
until the next refresh. Given how many {{MutableRate}} metrics there are, a thread per metric
is not really feasible, but could be done on e.g. a per-source basis. This has some downsides:
if multiple sinks are configured with different periods, what is the right refresh period
for the {{MutableRate}}? 
* Make {{MutableRate}} emit two counters, one for total and one for operation count, rather
than an average gauge and an operation count counter. The average could then be calculated
downstream from this information. This is cumbersome for operators and not backwards compatible.
To improve on both of those downsides, we could have it keep the current behavior but _additionally_
emit the total as a counter. The snapshotted average is probably sufficient in the common
case (we've been using it for years), and when more guaranteed accuracy is required, the average
could be derived from the total and operation count.

Open to suggestions & input here.



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