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https://issues.apache.org/jira/browse/STORM-297?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14020894#comment-14020894
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ASF GitHub Bot commented on STORM-297:
--------------------------------------

Github user clockfly commented on the pull request:

    https://github.com/apache/incubator-storm/pull/103#issuecomment-45416875
  
    fixed.
    
    The failed case is under namespace: backtype.storm.messaging-test
    
    root cause:
    The test failure is caused by the bug of local topology simulation. funtion 
complete-topology will asume topology is finished after all spout return, but 
it is not always true, the downstream bolts may be still working.
    
    direct cause:
    complete-topology->all spout finish -> shutdown the topology->shutdown 
worker->shutdown netty client -> bolt still not finished -> bolt try to send 
mesage to netty client -> client already shutdown -> throw runtime exception.
    
    the fix is to add a config to allow this topology to wait a longer time to 
be killed.


> 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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