[jira] [Resolved] (KAFKA-5868) Kafka Consumer Rebalancing takes too long

["Sophie Blee-Goldman (Jira)" <ji...@apache.org>]

     [ https://issues.apache.org/jira/browse/KAFKA-5868?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]

Sophie Blee-Goldman resolved KAFKA-5868.
----------------------------------------
    Fix Version/s: 2.5.0
       Resolution: Fixed

> Kafka Consumer Rebalancing takes too long
> -----------------------------------------
>
>                 Key: KAFKA-5868
>                 URL: https://issues.apache.org/jira/browse/KAFKA-5868
>             Project: Kafka
>          Issue Type: Bug
>          Components: streams
>    Affects Versions: 0.10.2.0, 0.10.2.1, 0.11.0.0
>            Reporter: Nandish Kotadia
>            Priority: Major
>             Fix For: 2.5.0
>
>
> up vote
> 0
> down vote
> favorite
> 1
> I have a Kafka Streams Application which takes data from few topics and joins the data and puts it in another topic.
> *Kafka Configuration: *
> * 5 kafka brokers
> * Kafka Topics - 15 partitions and 3 replication factor.
> Few millions of records are consumed/produced every hour. Whenever I take any kafka broker down, it goes into rebalancing and it takes approx. 30 minutes or sometimes even more for rebalancing. Also it kills many of my Kafka Streams processes.
> *Note: My Kafka Streams processes are running on the same machine as of Kafka Broker.*
> Anyone has any idea how to solve rebalancing issue in kafka consumer? Also, many times it throws exception while rebalancing.
> This is stopping us from going live in production environment with this setup. Any help would be appreciated.
> _Caused by: org.apache.kafka.clients.consumer.CommitFailedException: ?
> Commit cannot be completed since the group has already rebalanced and assigned the partitions to another member. This means that the time between subsequent calls to poll() was longer than the configured max.poll.interval.ms, which typically implies that the poll loop is spending too much time message processing. You can address this either by increasing the session timeout or by reducing the maximum size of batches returned in poll() with max.poll.records.
> at org.apache.kafka.clients.consumer.internals.ConsumerCoordinator.sendOffsetCommitRequest(ConsumerCoordinator.java:725)
> at org.apache.kafka.clients.consumer.internals.ConsumerCoordinator.commitOffsetsSync(ConsumerCoordinator.java:604)
> at org.apache.kafka.clients.consumer.KafkaConsumer.commitSync(KafkaConsumer.java:1173)
> at org.apache.kafka.streams.processor.internals.StreamTask.commitOffsets(StreamTask.java:307)
> at org.apache.kafka.streams.processor.internals.StreamTask.access$000(StreamTask.java:49)
> at org.apache.kafka.streams.processor.internals.StreamTask$1.run(StreamTask.java:268)
> at org.apache.kafka.streams.processor.internals.StreamsMetricsImpl.measureLatencyNs(StreamsMetricsImpl.java:187)
> at org.apache.kafka.streams.processor.internals.StreamTask.commitImpl(StreamTask.java:259)
> at org.apache.kafka.streams.processor.internals.StreamTask.suspend(StreamTask.java:362)
> at org.apache.kafka.streams.processor.internals.StreamTask.suspend(StreamTask.java:346)
> at org.apache.kafka.streams.processor.internals.StreamThread$3.apply(StreamThread.java:1118)
> at org.apache.kafka.streams.processor.internals.StreamThread.performOnStreamTasks(StreamThread.java:1448)
> at org.apache.kafka.streams.processor.internals.StreamThread.suspendTasksAndState(StreamThread.java:1110)_
> *Kafka Streams Config: *
> * bootstrap.servers=kafka-1:9092,kafka-2:9092,kafka-3:9092,kafka-4:9092,kafka-5:9092
> * max.poll.records = 100
> * request.timeout.ms=40000
> ConsumerConfig it internally creates is:
>     auto.commit.interval.ms = 5000
>     auto.offset.reset = earliest
>     bootstrap.servers = [kafka-1:9092, kafka-2:9092, kafka-3:9092, kafka-4:9092, kafka-5:9092]
>     check.crcs = true
>     client.id = conversion-live-StreamThread-1-restore-consumer
>     connections.max.idle.ms = 540000
>     enable.auto.commit = false
>     exclude.internal.topics = true
>     fetch.max.bytes = 52428800
>     fetch.max.wait.ms = 500
>     fetch.min.bytes = 1
>     group.id = 
>     heartbeat.interval.ms = 3000
>     interceptor.classes = null
>     internal.leave.group.on.close = false
>     isolation.level = read_uncommitted
>     key.deserializer = class org.apache.kafka.common.serialization.ByteArrayDeserializer
>     max.partition.fetch.bytes = 1048576
>     max.poll.interval.ms = 2147483647
>     max.poll.records = 100
>     metadata.max.age.ms = 300000
>     metric.reporters = []
>     metrics.num.samples = 2
>     metrics.recording.level = INFO
>     metrics.sample.window.ms = 30000
>     partition.assignment.strategy = [class org.apache.kafka.clients.consumer.RangeAssignor]
>     receive.buffer.bytes = 65536
>     reconnect.backoff.max.ms = 1000
>     reconnect.backoff.ms = 50
>     request.timeout.ms = 40000
>     retry.backoff.ms = 100
>     sasl.jaas.config = null
>     sasl.kerberos.kinit.cmd = /usr/bin/kinit
>     sasl.kerberos.min.time.before.relogin = 60000
>     sasl.kerberos.service.name = null
>     sasl.kerberos.ticket.renew.jitter = 0.05
>     sasl.kerberos.ticket.renew.window.factor = 0.8
>     sasl.mechanism = GSSAPI
>     security.protocol = PLAINTEXT
>     send.buffer.bytes = 131072
>     session.timeout.ms = 10000
>     ssl.cipher.suites = null
>     ssl.enabled.protocols = [TLSv1.2, TLSv1.1, TLSv1]
>     ssl.endpoint.identification.algorithm = null
>     ssl.key.password = null
>     ssl.keymanager.algorithm = SunX509
>     ssl.keystore.location = null
>     ssl.keystore.password = null
>     ssl.keystore.type = JKS
>     ssl.protocol = TLS
>     ssl.provider = null
>     ssl.secure.random.implementation = null
>     ssl.trustmanager.algorithm = PKIX
>     ssl.truststore.location = null
>     ssl.truststore.password = null
>     ssl.truststore.type = JKS
>     value.deserializer = class org.apache.kafka.common.serialization.ByteArrayDeserializer



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