Thanks for the suggestion - that hasn't improved matters, and in fact makes the 
CPU ramp-up quicker (60% CPU after 1 hour). This implies it is something to do 
with the batching mechanism.

Unfortunately, that code is quite complex, and so hard for us to work out 
exactly what is going on. We'll try and get a stand-alone testcase

Simon

From: Roshan Naik <[email protected]>
Sent: 16 April 2018 10:06
To: [email protected]
Subject: Re: Storm using all the CPU in disruptor-flush-task-pool

Strange indeed. However since you have slow throughput scenario you could try 
to see if setting the disruptor batch size to 1 works around the issue.


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On Monday, April 16, 2018, 1:50 AM, Simon Cooper 
<[email protected]<mailto:[email protected]>> wrote:

Hi,



We've been encountering a problem for some time now, where the storm CPU usage 
is continually going up, until it's using all the CPU on the system. This is 
despite the topology not really doing much - 1-2 tuples a second. We first 
noticed it on 1.1.0, but it has continued after upgrading to 1.2.1.



We've isolated the problem to the disruptor-flush-task-pool. Changing the size 
of the pool doesn't really seem to change things; after a couple of days of 
'idling', those threads are working all the time inside 
DisruptorQueue.ThreadLocalBatcher and DisruptorQueue.Flusher, checking 
_overflow.isEmpty() and running _batchers.values().iterator()



Has anyone else seen similar problems? Is there likely to be a slow-burning 
task proliferation issue inside DisruptorQueue?



Thanks,

SimonC
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