[jira] [Resolved] (KAFKA-4469) Consumer throughput regression caused by inefficient list removal and copy

["Jason Gustafson (JIRA)" <ji...@apache.org>]

     [ https://issues.apache.org/jira/browse/KAFKA-4469?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]

Jason Gustafson resolved KAFKA-4469.
------------------------------------
    Resolution: Fixed

Issue resolved by pull request 2190
[https://github.com/apache/kafka/pull/2190]

> Consumer throughput regression caused by inefficient list removal and copy
> --------------------------------------------------------------------------
>
>                 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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