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Mayank Shekhar Narula updated KAFKA-16226: ------------------------------------------ Attachment: Screenshot 2024-02-01 at 11.06.36.png > Java client: Performance regression in Trogdor benchmark with high partition > counts > ----------------------------------------------------------------------------------- > > Key: KAFKA-16226 > URL: https://issues.apache.org/jira/browse/KAFKA-16226 > Project: Kafka > Issue Type: Bug > Components: clients > Affects Versions: 3.7.0, 3.6.1 > Reporter: Mayank Shekhar Narula > Assignee: Mayank Shekhar Narula > Priority: Major > Labels: kip-951 > Fix For: 3.6.2, 3.8.0, 3.7.1 > > Attachments: Screenshot 2024-02-01 at 11.06.36.png > > > Background > https://issues.apache.org/jira/browse/KAFKA-15415 implemented optimisation in > java-client to skip backoff period if client knows of a newer leader, for > produce-batch being retried. > What changed > The implementation introduced a regression noticed on a trogdor-benchmark > running with high partition counts(36000!). > With regression, following metrics changed on the produce side. > # record-queue-time-avg: increased from 20ms to 30ms. > # request-latency-avg: increased from 50ms to 100ms. > How it happened > As can be seen from the original > [PR|[https://github.com/apache/kafka/pull/14384],] > RecordAccmulator.partitionReady() & drainBatchesForOneNode() started using > synchronised method Metadata.currentLeader(). This has led to increased > synchronization between KafkaProducer's application-thread that call send(), > and background-thread that actively send producer-batches to leaders. > See lock profiles that clearly show increased synchronisation in KAFKA-15415 > PR(highlighted in {color:#de350b}Red{color}) Vs baseline. Note the > synchronisation is much worse for paritionReady() in this benchmark as its > called for each partition, and it has 36k partitions! > Fix -- This message was sent by Atlassian Jira (v8.20.10#820010)