[jira] [Created] (KAFKA-8736) Performance: ThreadCache uses size() for empty cache check

["Matthew Jarvie (JIRA)" <ji...@apache.org>]

Matthew Jarvie created KAFKA-8736:
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             Summary: Performance: ThreadCache uses size() for empty cache check
                 Key: KAFKA-8736
                 URL: https://issues.apache.org/jira/browse/KAFKA-8736
             Project: Kafka
          Issue Type: Improvement
          Components: streams
    Affects Versions: 2.3.0
            Reporter: Matthew Jarvie
         Attachments: size.patch

While load testing Kafka Streams in 2.3.0, we stumbled across a potential performance improvement. The test showed we were spending 80% of CPU time in ConcurrentSkipListMap.size():

 
{noformat}
100% org.apache.kafka.streams.processor.internals.StreamThread.run():774
100% org.apache.kafka.streams.processor.internals.StreamThread.runLoop():805
96.84% org.apache.kafka.streams.processor.internals.StreamThread.runOnce():890
96.84% org.apache.kafka.streams.processor.internals.TaskManager.process(long):420
96.83% org.apache.kafka.streams.processor.internals.AssignedStreamsTasks.process(long):199
96.4% org.apache.kafka.streams.processor.internals.StreamTask.process():366
96.3% org.apache.kafka.streams.processor.internals.SourceNode.process(java.lang.Object, java.lang.Object):87
96.3% org.apache.kafka.streams.processor.internals.ProcessorContextImpl.forward(java.lang.Object, java.lang.Object):133
96.3% org.apache.kafka.streams.processor.internals.ProcessorContextImpl.forward(java.lang.Object, java.lang.Object, org.apache.kafka.streams.processor.To):180
96.3% org.apache.kafka.streams.processor.internals.ProcessorContextImpl.forward(org.apache.kafka.streams.processor.internals.ProcessorNode, java.lang.Object, java.lang.Object):201
96.23% org.apache.kafka.streams.processor.internals.ProcessorNode.process(java.lang.Object, java.lang.Object):117
96.12% org.apache.kafka.streams.kstream.internals.KStreamFilter$KStreamFilterProcessor.process(java.lang.Object, java.lang.Object):43
96.12% org.apache.kafka.streams.processor.internals.ProcessorContextImpl.forward(java.lang.Object, java.lang.Object):133
96.12% org.apache.kafka.streams.processor.internals.ProcessorContextImpl.forward(java.lang.Object, java.lang.Object, org.apache.kafka.streams.processor.To):180
96.12% org.apache.kafka.streams.processor.internals.ProcessorContextImpl.forward(org.apache.kafka.streams.processor.internals.ProcessorNode, java.lang.Object, java.lang.Object):201
96.08% org.apache.kafka.streams.processor.internals.ProcessorNode.process(java.lang.Object, java.lang.Object):117
82.78% org.apache.kafka.streams.kstream.internals.KStreamSessionWindowAggregate$KStreamSessionWindowAggregateProcessor.process(java.lang.Object, java.lang.Object):169
82.78% org.apache.kafka.streams.processor.internals.ProcessorContextImpl$SessionStoreReadWriteDecorator.put(org.apache.kafka.streams.kstream.Windowed, java.lang.Object):612
82.59% org.apache.kafka.streams.state.internals.MeteredSessionStore.put(org.apache.kafka.streams.kstream.Windowed, java.lang.Object):127
81.11% org.apache.kafka.streams.state.internals.CachingSessionStore.put(org.apache.kafka.streams.kstream.Windowed, java.lang.Object):35
81.09% org.apache.kafka.streams.state.internals.CachingSessionStore.put(org.apache.kafka.streams.kstream.Windowed, byte[]):131
81.09% org.apache.kafka.streams.state.internals.ThreadCache.put(java.lang.String, org.apache.kafka.common.utils.Bytes, org.apache.kafka.streams.state.internals.LRUCacheEntry):151
80.53% org.apache.kafka.streams.state.internals.ThreadCache.maybeEvict(java.lang.String):238
80.53% org.apache.kafka.streams.state.internals.NamedCache.size():266
80.53% java.util.concurrent.ConcurrentSkipListMap.size():1639{noformat}
According to [https://docs.oracle.com/javase/8/docs/api/java/util/concurrent/ConcurrentSkipListMap.html#size--], the size method has to traverse all elements to get a count. It looks like the count is being compared against 0 to determine if the map is empty; In this case, we don't need a full count. Instead, the isEmpty() method should be used, which just looks for one node. We patched this and gained about 25% max throughput, and this method disappeared from thread dumps as a hot spot.



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