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https://issues.apache.org/jira/browse/KAFKA-374?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=13530674#comment-13530674
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Jay Kreps commented on KAFKA-374:
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Hey Scott, currently the implementation of the consumer is that there is a
background thread that fetches data and populates a queue of data chunks which
are handed off to the user's iterators. A single consumer client can feed many
iterators in (potentially) many threads. The goal of this design was
specifically to support a large thread pool of processors while still
maintaining ordered consumption on a per-partition basis. So although a
background thread would be one way to increase parallelism I think it is
actually the harder one to reason about since now there are multiple thread
pools to tune. I think just increasing the number of user threads/iterators is
probably the best approach.
> Move to java CRC32 implementation
> ---------------------------------
>
> Key: KAFKA-374
> URL: https://issues.apache.org/jira/browse/KAFKA-374
> Project: Kafka
> Issue Type: New Feature
> Components: core
> Affects Versions: 0.8
> Reporter: Jay Kreps
> Priority: Minor
> Labels: newbie
> Attachments: KAFKA-374-draft.patch, KAFKA-374.patch
>
>
> We keep a per-record crc32. This is fairly cheap algorithm, but the java
> implementation uses JNI and it seems to be a bit expensive for small records.
> I have seen this before in Kafka profiles, and I noticed it on another
> application I was working on. Basically with small records the native
> implementation can only checksum < 100MB/sec. Hadoop has done some analysis
> of this and replaced it with a Java implementation that is 2x faster for
> large values and 5-10x faster for small values. Details are here HADOOP-6148.
> We should do a quick read/write benchmark on log and message set iteration
> and see if this improves things.
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