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https://issues.apache.org/jira/browse/KAFKA-21241?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=18139291#comment-18139291
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이선민 commented on KAFKA-21241:
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[~muralibasani] [~schofielaj] Following up on the October 20 measurements: 
those covered only the assignor, so coordinator and broker capacity remain open 
questions.

I'd propose starting with a share-group heartbeat microbenchmark, using 1,000 
members as a baseline and scaling to the 20–30k-member use case in this ticket. 
The first step would measure steady-state processing cost within the 
coordinator shard; a follow-up would measure assignment-record counts and 
serialized bytes across join/leave and subsequent reassignment.

I can put together an initial benchmark, using the shard-level setup in 
https://github.com/apache/kafka/pull/24101 as a reference.

Would this be the most useful next step for the KIP, or would you prefer 
broker-side ShareSessionCache memory measurements first, varying active 
sessions and cached partitions per session?

If there's already a KIP draft, I'd be happy to align the measurements with its 
scope.

> Increase the number of consumers in the share consumer group
> ------------------------------------------------------------
>
>                 Key: KAFKA-21241
>                 URL: https://issues.apache.org/jira/browse/KAFKA-21241
>             Project: Kafka
>          Issue Type: Improvement
>            Reporter: Prakhar Kulshrestha
>            Priority: Major
>         Attachments: MapBench.java, WorkingSetBench.java, 
> assignor-gc-G1.json, assignor-gc-Parallel.json, assignor-sweep-pretouch.json, 
> hashmap-isolated.json, notes.txt, working-set.json
>
>
> Currently the max  number of consumers in a share consumer group is default 
> to 200 and max to 1000.  In bigger platforms where batch processing along 
> with slow consumer use cases limiting to just 1000 consumer is very 
> restrictive.{*}{*}
> One of the scenario is a batch processing of millions of records and having 
> to parallel process 20-30k records in parallel using spring kafka concurrency 
> feature would mean we would need at least 20-30k consumers in a consumer 
> groups with around 1k pods. Current 1000 limit just let it have ~60pods.
> Request this to be reevaluated and increase the number of consumers that a 
> share group can have.
> *group.share.max.size*



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