[jira] [Created] (KAFKA-4469) Consumer throughput regression caused by decrease in max.poll.records

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

Jason Gustafson created KAFKA-4469:
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             Summary: 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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