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https://issues.apache.org/jira/browse/KAFKA-3554?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16063452#comment-16063452
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Chen He commented on KAFKA-3554:
--------------------------------

Thank you for the quick reply [~becket_qin]. This work is really valuable. It 
provides us a tool that can exploit kafka system's capacity. For example, we 
can get lowest latency by only use 1 thread, at the same time, by increasing 
thread, we can find what is the maximum throughput for a kafka cluster. 

Only one question, I did applied this patch to latest kafka and comparing 
results with old ProducerPerformance.java file. I found out, if we set ack=all 
with snappy compression, with 100M record(100B each), it does not work as well 
as old PproducerPerformance.java file. 

> Generate actual data with specific compression ratio and add multi-thread 
> support in the ProducerPerformance tool.
> ------------------------------------------------------------------------------------------------------------------
>
>                 Key: KAFKA-3554
>                 URL: https://issues.apache.org/jira/browse/KAFKA-3554
>             Project: Kafka
>          Issue Type: Improvement
>    Affects Versions: 0.9.0.1
>            Reporter: Jiangjie Qin
>            Assignee: Jiangjie Qin
>             Fix For: 0.11.1.0
>
>
> Currently the ProducerPerformance always generate the payload with same 
> bytes. This does not quite well to test the compressed data because the 
> payload is extremely compressible no matter how big the payload is.
> We can make some changes to make it more useful for compressed messages. 
> Currently I am generating the payload containing integer from a given range. 
> By adjusting the range of the integers, we can get different compression 
> ratios. 
> API wise, we can either let user to specify the integer range or the expected 
> compression ratio (we will do some probing to get the corresponding range for 
> the users)
> Besides that, in many cases, it is useful to have multiple producer threads 
> when the producer threads themselves are bottleneck. Admittedly people can 
> run multiple ProducerPerformance to achieve similar result, but it is still 
> different from the real case when people actually use the producer.



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