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https://issues.apache.org/jira/browse/STORM-297?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14020441#comment-14020441
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ASF GitHub Bot commented on STORM-297:
--------------------------------------

Github user miguno commented on the pull request:

    https://github.com/apache/incubator-storm/pull/103#issuecomment-45389078
  
    +1
    
    > On 06.06.2014, at 19:00, "Robert (Bobby) Evans" 
<[email protected]> wrote:
    > 
    > @clockfly and everyone else I love the discussion that is happening here. 
I think the code is now at a point where we can merge it in (2 binding +1s), 
and continue the discussion and development on separate JIRAs. I tried to go 
through all of the comments and most of what is left is around possible 
improvements that are still remaining, but nothing blocking. If anyone 
disagrees or has issues they have seen, but not expressed yet please speak up. 
Otherwise I plan to merge this in later today.
    > 
    > —
    > Reply to this email directly or view it on GitHub.


> Storm Performance cannot be scaled up by adding more CPU cores
> --------------------------------------------------------------
>
>                 Key: STORM-297
>                 URL: https://issues.apache.org/jira/browse/STORM-297
>             Project: Apache Storm (Incubating)
>          Issue Type: Bug
>            Reporter: Sean Zhong
>              Labels: Performance, netty
>             Fix For: 0.9.2-incubating
>
>         Attachments: Storm_performance_fix.pdf, 
> storm_Netty_receiver_diagram.png, storm_conf.txt, 
> storm_performance_fix.patch, worker_throughput_without_storm-297.png
>
>
> We cannot scale up the performance by adding more CPU cores and increasing 
> parallelism.
> For a 2 layer topology Spout ---shuffle grouping--> bolt, when message size 
> is small (around 100 bytes), we can find in the below picture that neither 
> the CPU nor the network is saturated. When message size is 100 bytes, only 
> 40% of CPU is used, only 18% of network is used, although we have a high 
> parallelism (overall we have 144 executors)



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