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https://issues.apache.org/jira/browse/KAFKA-4469?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15709573#comment-15709573
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Jason Gustafson commented on KAFKA-4469:
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[~ijuma] suggests that the inefficiency is not necessarily in the list copy
itself, but the fact that we remove one at a time from the head of the array
list, which causes all of the elements to be shifted each time. In the patch
above, I've used {{List.subList}}, which avoids the need for copying and
mutation of the original list.
> Consumer throughput regression caused by decrease in max.poll.records
> ---------------------------------------------------------------------
>
> Key: KAFKA-4469
> URL: https://issues.apache.org/jira/browse/KAFKA-4469
> Project: Kafka
> Issue Type: Bug
> Affects Versions: 0.10.1.0
> Reporter: Jason Gustafson
> Assignee: Jason Gustafson
> Fix For: 0.10.1.1
>
>
> There appears to be a small performance regression in 0.10.1.0 from previous
> versions. I tracked it back to KAFKA-3888. As part of KIP-62, we decreased
> the value of {{max.poll.records}} from {{Integer.MAX_VALUE}} to 500. Based on
> some performance testing, this results in about a 5% decrease in throughput.
> This depends on the fetch and message sizes. My test used message size of 1K
> with the default fetch size, and the default {{max.poll.records}} of 500.
> The main cause of the regression seems to be an unneeded list copy in
> {{Fetcher}}. Basically when we have more records than we need to satisfy
> {{max.poll.records}}, then we copy the fetched records into a new list. When
> I modified the code to use a sub-list, which does not need a copy, the
> performance is much closer to that of 0.10.0 (within 1% or so with lots of
> qualification since there are many unexplored parameters). The remaining
> performance gap could be explained by sub-optimal pipelining as a result of
> KAFKA-4007 (this is likely part of the story anyway based on some rough
> testing).
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