KAFKA-19606: Fix anomaly of JMX metrics RequestHandlerAvgIdlePercent in kraft combined mode #20481
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0xffff-zhiyan
changed the title
kevin-wu24
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Sep 8, 2025
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Thanks for the changes @0xffff-zhiyan. Left a review of the code changes.
| @@ -93,7 +94,8 @@ class KafkaRequestHandler( | |||
| val requestChannel: RequestChannel, | |||
| apis: ApiRequestHandler, | |||
| time: Time, | |||
| nodeName: String = "broker" | |||
| nodeName: String = "broker", | |||
| val perPoolIdleMeter: Meter, | |||
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Can we group this with aggregateIdleMeter in the class header?
| @@ -192,6 +197,10 @@ class KafkaRequestHandler( | |||
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| } | |||
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| object KafkaRequestHandlerPool { | |||
| val sharedAggregateTotalThreads = new AtomicInteger(0) | |||
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sharedAggregateTotalThreads is redundant. We can just name this totalThreads or aggregateThreads.
| private val aggregateIdleMeter = metricsGroup.newMeter(requestHandlerAvgIdleMetricName, "percent", TimeUnit.NANOSECONDS) | ||
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| this.logIdent = s"[data-plane Kafka Request Handler on ${nodeName.capitalize} $brokerId] " | ||
| val runnables = new mutable.ArrayBuffer[KafkaRequestHandler](numThreads) | ||
| // when using shared aggregate counter, register this pool's threads | ||
| sharedAggregateTotalThreads.addAndGet(numThreads) |
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Lets move this into the synchronized method createHandler and call incrementAndGet when each thread is created.
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This PR implements KIP-1207
https://issues.apache.org/jira/browse/KAFKA-19606
This PR implements a global shared thread counter mechanism to properly calculate the
RequestHandlerAvgIdlePercentmetric across allKafkaRequestHandlerPoolinstances within the same JVM process in Kraft combined mode. This ensures accurate idle percentage calculations, especially in combined KRaft mode where both broker and controller request handler pools coexist.Previously, each
KafkaRequestHandlerPoolcalculated idle percentages independently using only its own thread count as the denominator. In combined KRaft mode, this led to:Core Changes
Added sharedAggregateTotalThreadsas a global AtomicInteger inKafkaRequestHandlerPoolPer-pool metric: Uses local thread count (totalHandlerThreads.get)
Aggregate metric: Uses global thread count (sharedAggregateTotalThreads.get)
Test
Added perPoolIdleMeter parameter to all KafkaRequestHandler instantiations
Added global counter initialization: KafkaRequestHandlerPool.sharedAggregateTotalThreads.set(1) in test class setup
Added new unit test verifies:
1.Global counter accumulation across multiple pools
2.Proper idle percentage calculation within [0, 1.05] range
3.Counter cleanup after pool shutdown
POC locally(in kraft combined mode):
