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https://issues.apache.org/jira/browse/KAFKA-687?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=13548604#comment-13548604
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Jay Kreps commented on KAFKA-687:
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This is a very good point, and not one I had considered.
It is probably not a trivial change because right now I think the election is
done for each topic independently.
We have in mind in the next major release after 0.8 (0.9, presumably) to move
this co-ordination to the server, which would be a good time to fix this. We
could either do this balancing exactly or else just randomize the start index
(which would be almost as good if you had many topics.
> Rebalance algorithm should consider partitions from all topics
> --------------------------------------------------------------
>
> Key: KAFKA-687
> URL: https://issues.apache.org/jira/browse/KAFKA-687
> Project: Kafka
> Issue Type: Improvement
> Affects Versions: 0.8.1
> Reporter: Pablo Barrera
>
> The current rebalance step, as stated in the original Kafka paper [1], splits
> the partitions per topic between all the consumers. So if you have 100 topics
> with 2 partitions each and 10 consumers only two consumers will be used. That
> is, for each topic all partitions will be listed and shared between the
> consumers in the consumer group in order (not randomly).
> If the consumer group is reading from several topics at the same time it
> makes sense to split all the partitions from all topics between all the
> consumer. Following the example, we will have 200 partitions in total, 20 per
> consumer, using the 10 consumers.
> The load per topic could be different and the division should consider this.
> However even a random division should be better than the current algorithm
> while reading from several topics and should harm reading from a few topics
> with several partitions.
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