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Haruki Okada edited comment on KAFKA-15046 at 8/17/23 4:08 AM: --------------------------------------------------------------- [~junrao] Hi, sorry for the late response. Thanks for your suggestion. > Another way to improve this is to move the LeaderEpochFile flushing logic to > be part of the flushing of rolled segments Yeah, that sounds make sense. I think ProducerState snapshot also should be the unified to existing flushing logic then, instead of fsync-ing ProducerState separately in log.roll (i.e. current Kafka behavior), nor submitting to scheduler separately (i.e. like ongoing patch([https://github.com/apache/kafka/pull/13782]) does) was (Author: ocadaruma): [~junrao] Hi, sorry for the late response. Thanks for your suggestion. > Another way to improve this is to move the LeaderEpochFile flushing logic to > be part of the flushing of rolled segments Yeah, that sounds make sense. I think ProducerState snapshot also should be the unified to existing flushing logic then, instead of fsync-ing ProducerState separately in log.roll (i.e. current Kafka behavior), nor submitting to scheduler separately (i.e. like [ongoing patch|[https://github.com/apache/kafka/pull/13782]] ongoing patch does) > Produce performance issue under high disk load > ---------------------------------------------- > > Key: KAFKA-15046 > URL: https://issues.apache.org/jira/browse/KAFKA-15046 > Project: Kafka > Issue Type: Improvement > Components: core > Affects Versions: 3.3.2 > Reporter: Haruki Okada > Assignee: Haruki Okada > Priority: Major > Labels: performance > Attachments: image-2023-06-01-12-46-30-058.png, > image-2023-06-01-12-52-40-959.png, image-2023-06-01-12-54-04-211.png, > image-2023-06-01-12-56-19-108.png > > > * Phenomenon: > ** !image-2023-06-01-12-46-30-058.png|width=259,height=236! > ** Producer response time 99%ile got quite bad when we performed replica > reassignment on the cluster > *** RequestQueue scope was significant > ** Also request-time throttling happened at the incidental time. This caused > producers to delay sending messages in the mean time. > ** The disk I/O latency was higher than usual due to the high load for > replica reassignment. > *** !image-2023-06-01-12-56-19-108.png|width=255,height=128! > * Analysis: > ** The request-handler utilization was much higher than usual. > *** !image-2023-06-01-12-52-40-959.png|width=278,height=113! > ** Also, thread time utilization was much higher than usual on almost all > users > *** !image-2023-06-01-12-54-04-211.png|width=276,height=110! > ** From taking jstack several times, for most of them, we found that a > request-handler was doing fsync for flusing ProducerState and meanwhile other > request-handlers were waiting Log#lock for appending messages. > * > ** > *** > {code:java} > "data-plane-kafka-request-handler-14" #166 daemon prio=5 os_prio=0 > cpu=51264789.27ms elapsed=599242.76s tid=0x00007efdaeba7770 nid=0x1e704 > runnable [0x00007ef9a12e2000] > java.lang.Thread.State: RUNNABLE > at sun.nio.ch.FileDispatcherImpl.force0(java.base@11.0.17/Native > Method) > at > sun.nio.ch.FileDispatcherImpl.force(java.base@11.0.17/FileDispatcherImpl.java:82) > at > sun.nio.ch.FileChannelImpl.force(java.base@11.0.17/FileChannelImpl.java:461) > at > kafka.log.ProducerStateManager$.kafka$log$ProducerStateManager$$writeSnapshot(ProducerStateManager.scala:451) > at > kafka.log.ProducerStateManager.takeSnapshot(ProducerStateManager.scala:754) > at kafka.log.UnifiedLog.roll(UnifiedLog.scala:1544) > - locked <0x000000060d75d820> (a java.lang.Object) > at kafka.log.UnifiedLog.maybeRoll(UnifiedLog.scala:1523) > - locked <0x000000060d75d820> (a java.lang.Object) > at kafka.log.UnifiedLog.append(UnifiedLog.scala:919) > - locked <0x000000060d75d820> (a java.lang.Object) > at kafka.log.UnifiedLog.appendAsLeader(UnifiedLog.scala:760) > at > kafka.cluster.Partition.$anonfun$appendRecordsToLeader$1(Partition.scala:1170) > at kafka.cluster.Partition.appendRecordsToLeader(Partition.scala:1158) > at > kafka.server.ReplicaManager.$anonfun$appendToLocalLog$6(ReplicaManager.scala:956) > at > kafka.server.ReplicaManager$$Lambda$2379/0x0000000800b7c040.apply(Unknown > Source) > at > scala.collection.StrictOptimizedMapOps.map(StrictOptimizedMapOps.scala:28) > at > scala.collection.StrictOptimizedMapOps.map$(StrictOptimizedMapOps.scala:27) > at scala.collection.mutable.HashMap.map(HashMap.scala:35) > at > kafka.server.ReplicaManager.appendToLocalLog(ReplicaManager.scala:944) > at kafka.server.ReplicaManager.appendRecords(ReplicaManager.scala:602) > at kafka.server.KafkaApis.handleProduceRequest(KafkaApis.scala:666) > at kafka.server.KafkaApis.handle(KafkaApis.scala:175) > at kafka.server.KafkaRequestHandler.run(KafkaRequestHandler.scala:75) > at java.lang.Thread.run(java.base@11.0.17/Thread.java:829) {code} > * > ** Also there were bunch of logs that writing producer snapshots took > hundreds of milliseconds. > *** > {code:java} > ... > [2023-05-01 11:08:36,689] INFO [ProducerStateManager partition=xxx-4] Wrote > producer snapshot at offset 1748817854 with 8 producer ids in 809 ms. > (kafka.log.ProducerStateManager) > [2023-05-01 11:08:37,319] INFO [ProducerStateManager partition=yyy-34] Wrote > producer snapshot at offset 247996937813 with 0 producer ids in 547 ms. > (kafka.log.ProducerStateManager) > [2023-05-01 11:08:38,887] INFO [ProducerStateManager partition=zzz-9] Wrote > producer snapshot at offset 226222355404 with 0 producer ids in 576 ms. > (kafka.log.ProducerStateManager) > ... {code} > * From the analysis, we summarized the issue as below: > * > ** 1. Disk write latency got worse due to the replica reassignment > *** We already use replication quota, and lowering the quota further may not > be acceptable for too long assignment duration > ** 2. ProducerStateManager#takeSnapshot started to take time due to fsync > latency > *** This is done at every log segment roll. > *** In our case, the broker hosts high load partitions so log roll is > occurring very frequently. > ** 3. During ProducerStateManager#takeSnapshot is doing fsync, all > subsequent produce requests to the partition is blocked due to Log#lock > ** 4. During produce requests waiting the lock, they consume request handler > threads time so it's accounted as thread-time utilization and caused > throttling > * Suggestion: > ** We didn't see this phenomenon when we used Kafka 2.4.1. > *** ProducerState fsync was introduced in 2.8.0 by this: > https://issues.apache.org/jira/browse/KAFKA-9892 > ** The reason why ProducerState needs to be fsync is not well described in > above ticket though, we think fsync is not really necessary here. Because: > * > ** > *** If ProducerState snapshot file was not written to the disk after power > failure, it will be just rebuilt from logs. > *** Also, even if ProducerState snapshot was corrupted after power failure, > it will be rebuilt from logs thanks to CRC -- This message was sent by Atlassian Jira (v8.20.10#820010)