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https://issues.apache.org/jira/browse/KAFKA-16277?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=17935039#comment-17935039
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Gangadharan commented on KAFKA-16277:
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[~credpath-seek] thanks for info. When you say that consumer group would scale
up to 7/8/9, was the even distribution guaranteed then? Because I see that
though initial distribution is attempted to be round robin inside the
AbstractStickyAssignor, when it eventually retains the partitions with minimum
quota, the distribution is not guaranteed.
Is it that even distribution cannot be achieved alongside stickiness? Do you is
it a bug that should be corrected using the cooperative sticky assignor?
> CooperativeStickyAssignor does not spread topics evenly among consumer group
> ----------------------------------------------------------------------------
>
> Key: KAFKA-16277
> URL: https://issues.apache.org/jira/browse/KAFKA-16277
> Project: Kafka
> Issue Type: Bug
> Components: clients, consumer
> Reporter: Cameron Redpath
> Assignee: Cameron Redpath
> Priority: Major
> Fix For: 3.8.0, 3.7.1
>
> Attachments: image-2024-02-19-13-00-28-306.png
>
>
> Consider the following scenario:
> `topic-1`: 12 partitions
> `topic-2`: 12 partitions
>
> Of note, `topic-1` gets approximately 10 times more messages through it than
> `topic-2`.
>
> Both of these topics are consumed by a single application, single consumer
> group, which scales under load. Each member of the consumer group subscribes
> to both topics. The `partition.assignment.strategy` being used is
> `org.apache.kafka.clients.consumer.CooperativeStickyAssignor`. The
> application may start with one consumer. It consumes all partitions from both
> topics.
>
> The problem begins when the application scales up to two consumers. What is
> seen is that all partitions from `topic-1` go to one consumer, and all
> partitions from `topic-2` go to the other consumer. In the case with one
> topic receiving more messages than the other, this results in a very
> imbalanced group where one consumer is receiving 10x the traffic of the other
> due to partition assignment.
>
> This is the issue being seen in our cluster at the moment. See this graph of
> the number of messages being processed by each consumer as the group scales
> from one to four consumers:
> !image-2024-02-19-13-00-28-306.png|width=537,height=612!
> Things to note from this graphic:
> * With two consumers, the partitions for a topic all go to a single consumer
> each
> * With three consumers, the partitions for a topic are split between two
> consumers each
> * With four consumers, the partitions for a topic are split between three
> consumers each
> * The total number of messages being processed by each consumer in the group
> is very imbalanced throughout the entire period
>
> With regard to the number of _partitions_ being assigned to each consumer,
> the group is balanced. However, the assignment appears to be biased so that
> partitions from the same topic go to the same consumer. In our scenario, this
> leads to very undesirable partition assignment.
>
> I question if the behaviour of the assignor should be revised, so that each
> topic has its partitions maximally spread across all available members of the
> consumer group. In the above scenario, this would result in much more even
> distribution of load. The behaviour would then be:
> * With two consumers, 6 partitions from each topic go to each consumer
> * With three consumers, 4 partitions from each topic go to each consumer
> * With four consumers, 3 partitions from each topic go to each consumer
>
> Of note, we only saw this behaviour after migrating to the
> `CooperativeStickyAssignor`. It was not an issue with the default partition
> assignment strategy.
>
> It is possible this may be intended behaviour. In which case, what is the
> preferred workaround for our scenario? Our current workaround if we decide to
> go ahead with the update to `CooperativeStickyAssignor` may be to limit our
> consumers so they only subscribe to one topic, and have two consumer threads
> per instance of the application.
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