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https://issues.apache.org/jira/browse/KAFKA-12664?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=17320763#comment-17320763
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Daniel Urban commented on KAFKA-12664:
--------------------------------------
MM2 spins up a Connect worker *per replication flow*. (The number of Connect
workers are affected by the target clusters you provided for MM2 - if you did
not do it explicitly, all clusters are targeted).
This setting:
dc3.group.id=mm2-dc3
Causes the Connect worker responsible for the dc1->dc3, and the worker
responsible for dc2->dc3 join the same connect group. This causes a collision,
likely to lead to those rebalances.
> Mirrormaker 2.0 infinite rebalance loop when dealing with more than 2
> clusters in standalone mode
> -------------------------------------------------------------------------------------------------
>
> Key: KAFKA-12664
> URL: https://issues.apache.org/jira/browse/KAFKA-12664
> Project: Kafka
> Issue Type: Bug
> Components: mirrormaker
> Affects Versions: 2.5.0, 2.4.1, 2.6.0, 2.7.0
> Reporter: Edward Vaisman
> Priority: Major
> Attachments: connect.log.tar.gz, docker-compose-multi.yml,
> mm2.properties
>
>
> Hi Folks, I came across this issue when trying to aggregate data from two
> separate data centres into one data centre.
> In the configuration below, you can see I am trying to replicate a topic from
> dc1 (named test_topic_dc1) to dc3 as well as replicate a topic from dc2
> (test_topic_dc2) to dc3.
> However, when I try to replicate both topics from those datacenters at the
> same time I notice that connect gets stuck in a rebalance loop (see
> attachment for logs)
> [^connect.log.tar.gz]
> excerpt of connect.log
> {code:java}
> 2021-04-13 17:03:06,360] INFO [Worker clientId=connect-3, groupId=mm2-dc2]
> Successfully synced group in generation Generation{generationId=347,
> memberId='connect-3-c59342c3-ca62-41cc-964c-41a0f98351c0',
> protocol='sessioned'}
> (org.apache.kafka.clients.consumer.internals.AbstractCoordinator:756)[2021-04-13
> 17:03:06,360] INFO [Worker clientId=connect-4, groupId=mm2-dc2] Rebalance
> started
> (org.apache.kafka.connect.runtime.distributed.WorkerCoordinator:225)[2021-04-13
> 17:03:06,362] INFO [Worker clientId=connect-4, groupId=mm2-dc2] (Re-)joining
> group
> (org.apache.kafka.clients.consumer.internals.AbstractCoordinator:540)[2021-04-13
> 17:03:06,368] INFO [Worker clientId=connect-2, groupId=mm2-dc3] Rebalance
> started
> (org.apache.kafka.connect.runtime.distributed.WorkerCoordinator:225)[2021-04-13
> 17:03:06,369] INFO [Worker clientId=connect-2, groupId=mm2-dc3] (Re-)joining
> group
> (org.apache.kafka.clients.consumer.internals.AbstractCoordinator:540)[2021-04-13
> 17:03:06,370] INFO [Worker clientId=connect-3, groupId=mm2-dc2] Joined group
> at generation 347 with protocol version 2 and got assignment:
> Assignment{error=1, leader='connect-3-c59342c3-ca62-41cc-964c-41a0f98351c0',
> leaderUrl='NOTUSED/dc1', offset=13, connectorIds=[MirrorSourceConnector],
> taskIds=[], revokedConnectorIds=[], revokedTaskIds=[], delay=0} with
> rebalance delay: 0
> (org.apache.kafka.connect.runtime.distributed.DistributedHerder:1688)
> {code}
> To replicate the issue here is what I used:
> [^mm2.properties]
> {code:java}
> clusters = dc1, dc2, dc3
> dc1.bootstrap.servers = kafka-dc1:19092
> dc2.bootstrap.servers = kafka-dc2:19093
> dc3.bootstrap.servers = kafka-dc3:19094
> dc1.group.id=mm2-dc1
> dc2.group.id=mm2-dc2
> dc3.group.id=mm2-dc3
> replication.factor=1
> checkpoints.topic.replication.factor=1
> heartbeats.topic.replication.factor=1
> offset-syncs.topic.replication.factor=1
> offset.storage.replication.factor=1
> status.storage.replication.factor=1
> config.storage.replication.factor=1
> dc1->dc3.enabled = true
> dc1->dc3.topics = test_topic_dc1
> dc2->dc3.enabled = true
> dc2->dc3.topics = test_topic_dc2
> dc3->dc2 = falsedc3->dc1 = false
> {code}
> This [^docker-compose-multi.yml] file to create local kafka clusters
> (dc1,dc2,dc3)
> (I set docker to use 6 cpus, 8gb mem, swap 2gb)
> I then ran an interactive shell to run mirror maker within the same
> docker-compose network (change network to match yours)
> {code:java}
> docker run --network kafka-examples_default -it wurstmeister/kafka:latest bash
> # Upload mm2 properties on server
> /opt/kafka/bin/connect-mirror-maker.sh mm2.properties{code}
> Kafkacat commands to produce to dc1, dc2
> {code:java}
> kafkacat -b localhost:9092 -t test_topic_dc1 -P
> Hello World from DC1!{code}
> {code:java}
> kafkacat -b localhost:9093 -t test_topic_dc2 -P
> Hello World from DC2{code}
> I then tried to remove one of the datacenters to confirm if it was a
> configuration problem, however mirror maker ran successfully with the below
> configuration
> mm2.properties
> {code:java}
> clusters = dc2, dc3
> dc2.bootstrap.servers = kafka-dc2:19093
> dc3.bootstrap.servers = kafka-dc3:19094
> dc2.group.id=mm2-dc2
> dc3.group.id=mm2-dc3
> replication.factor=1
> checkpoints.topic.replication.factor=1
> heartbeats.topic.replication.factor=1
> offset-syncs.topic.replication.factor=1
> offset.storage.replication.factor=1
> status.storage.replication.factor=1
> config.storage.replication.factor=1
> dc2->dc3.enabled = true
> dc2->dc3.topics = test_topic_dc2
> {code}
> Any help would be appreciated!
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