[rabbitmq-discuss] Message sending/receiving overhead.
pavel.kogan at cortica.com
Wed Aug 14 16:40:44 BST 2013
Thanks for your reply. Sorry didn't answered before, I was on vacation.
Yes I am using prefetch = 100. I am using JAVA and .Net clients. I am not
sure about message size but it should not exceed 100kb.
What I saw in .Net client is that publishing message takes time - indeed
few milliseconds but my whole processing is also few milliseconds.
Moving publishing to separate thread with blocking collection interface
helped a lot. Now I am not sure about polling requests from queue ...
On Wed, Jul 31, 2013 at 7:59 PM, Laing, Michael
<michael.laing at nytimes.com>wrote:
> Hi Pavel,
> Have you experimented with prefetch?
> Which client are you using and which versions of rabbitmq and erlang.
> Message size is important too, of course.
> We use the python pika client in asynch mode and have consistent
> processing times (fetch/process/publish) under 5ms.
> In general, we have found event loop based approaches faster than threads,
> esp. on the small (cheap) machines we use in the cloud.
> Best regards,
> On Wed, Jul 31, 2013 at 6:16 PM, Pavel Kogan <pavel.kogan at cortica.com>wrote:
>> Hi all,
>> I have simple subscriber that receives message, process it in single
>> thread and publish response.
>> Processing must be done in single thread (logic limitations) but is very
>> fast (~5ms) so I expect to be able to process 200 requests per second.
>> However publishing response in line with processing slows the things as
>> network latency is considerable (even though it is internal 1Gbit network).
>> To resolve it I moved responses publishing to separate threads (via
>> internal concurrent queue) and it helped.
>> The question is about receiving overhead. Is there any pre-caching of
>> messages or I should also integrate internal concurrent queue for requests
>> Many Thanks,
>> rabbitmq-discuss mailing list
>> rabbitmq-discuss at lists.rabbitmq.com
> rabbitmq-discuss mailing list
> rabbitmq-discuss at lists.rabbitmq.com
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