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https://issues.apache.org/jira/browse/KAFKA-19606?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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tony tang updated KAFKA-19606:
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Description:
JMX metrics RequestHandlerAvgIdlePercent reports a value close to 2 in combined
kraft mode but it's expected to be b/w 0 and 1.
This is an issue with combined mode specifically because both controller +
broker are using the same Meter object, defined in
{{{}RequestThreadIdleMeter#requestThreadIdleMeter{}}}, but the controller and
broker are using separate {{KafkaRequestHandlerPool}} objects, where each
object's {{{}threadPoolSize == KafkaConfig.numIoThreads{}}}. This means when
calculating idle time, each pool divides by its own {{numIoThreads}} value
before reporting to the shared meter and {{RequestHandlerAvgIdlePercent}}
calculates the final result by accumulating all the values reported by all
threads. However, since there are actually 2 × numIoThreads total threads
contributing to the metric, the denominator should be doubled to get the
correct average.
was:
JMX metrics reports a value close to 2 in combined kraft mode.
While we document it to be b/w 0 and 1. Is this expected?
> Anomaly of JMX metrics RequestHandlerAvgIdlePercent in kraft combined mode
> --------------------------------------------------------------------------
>
> Key: KAFKA-19606
> URL: https://issues.apache.org/jira/browse/KAFKA-19606
> Project: Kafka
> Issue Type: Bug
> Components: core
> Reporter: tony tang
> Assignee: tony tang
> Priority: Major
>
> JMX metrics RequestHandlerAvgIdlePercent reports a value close to 2 in
> combined kraft mode but it's expected to be b/w 0 and 1.
> This is an issue with combined mode specifically because both controller +
> broker are using the same Meter object, defined in
> {{{}RequestThreadIdleMeter#requestThreadIdleMeter{}}}, but the controller and
> broker are using separate {{KafkaRequestHandlerPool}} objects, where each
> object's {{{}threadPoolSize == KafkaConfig.numIoThreads{}}}. This means when
> calculating idle time, each pool divides by its own {{numIoThreads}} value
> before reporting to the shared meter and {{RequestHandlerAvgIdlePercent}}
> calculates the final result by accumulating all the values reported by all
> threads. However, since there are actually 2 × numIoThreads total threads
> contributing to the metric, the denominator should be doubled to get the
> correct average.
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