2015-11-04 17:12 GMT+01:00 Rainer Gerhards <[email protected]>:
> 2015-11-04 17:08 GMT+01:00 Joe Blow <[email protected]>:
>> I think i've spoken too soon.  The in memory queues are clearing extremely
>> well with these settings, but the DA stuff is still pretty sluggish (slowed
>> down to 50-100 EPS again).  I've looked at the box and the IO is around 10%
>> (12 disk array, which performs quite snappily), so i'm sincerely doubting
>> this is an IO issue.
>>
>> The huge feed in question uses around 4 workers before it has enough
>> workers to clear the queue as fast as it comes in (400k avg in the queue).
>> From my understanding that means that i've got 4 workers@50k bulk size
>> each, and at 200k EPS out (4 workers x 50k EPS) the in memory queue gets no
>> bigger.  Now this is where my knowledge ends.  I've set the low watermark
>> to 750k and high watermark to 1 million, with the thoughts that the low
>> watermark is below having all 8 workers full bore (8x100k) and the high
>> watermark is a 250k higher than that (slightly above all workers going full
>> bore).  If i'm staying below the low watermark, and still have "free"
>> workers, would those workers not try and empty the DA queue?  What would
>> help allocate more resources to clearing the DA queue?
>
> The DA queue always run on one worker, because you can't use more than
> one worker with purely sequential files.
>
> TBH I think your needs simply go above what the current system can
> provide. As David said, the queue subsystem could well deserve an
> overhaul, but this is a too-big task right now given what else is
> going on and there also has been no sponsor for any of that disk queue
> work in the past years, so it doesn't seem to have a too high priority
> either.

mhhh, I should mention a potential work-around: forget the DA queue.
Use failover actions. If the action fails, write log lines in native
format to a file. Then, use imfile to monitor that file. Together with
a smart design of the rulesets, you can probably get all you need out
of such a system. Unfortunately, I am even more swamped than usual, so
I cannot provide detail advised except than here pointing you to the
idea.

HTH
Rainer
>
> Rainer
>>
>> Thanks for the prompt responses.
>>
>> Cheers,
>>
>> JB
>>
>> On Wed, Nov 4, 2015 at 10:53 AM, Rainer Gerhards <[email protected]>
>> wrote:
>>
>>> 2015-11-04 16:44 GMT+01:00 Joe Blow <[email protected]>:
>>> > Ok i've played with some numbers.... this is what one of the massive
>>> queues
>>> > looks like now, and it *IS* dequeuing much faster (500 EPS from DA, 25k
>>> EPS
>>> > from in memory queue.
>>> >
>>> This may sound a bit strange, and I never tried it, but .. I wouldn't
>>> be surprised if it is actually faster if you put the queue files on a
>>> compressed directory. The idea behind that is that while this
>>> obviously eats CPU, it will probably save you a lot of real i/o
>>> because the data written to the disk queue can be greatly compressed.
>>>
>>> If you give it a try, please let us know the outcome.
>>>
>>> Rainer
>>>
>>> > Hopefully this helps some other people who have very massive, disk backed
>>> > queues...  Please feel free to comment on these values.
>>> >
>>> > action(type="omelasticsearch"
>>> >         name="rsys_HugeQ"
>>> >         server="10.10.10.10"
>>> >         serverport="9200"
>>> >         template="HugeQTemplate"
>>> >         asyncrepl="on"
>>> >         searchType="HugeType"
>>> >         searchIndex="HugeQindex"
>>> >         timeout="3m"
>>> >         dynSearchIndex="on"
>>> >         bulkmode="on"
>>> >         errorfile="HugeQ_err.log"
>>> >         queue.type="linkedlist"
>>> >         queue.filename="HugeQ.rsysq"
>>> >         queue.maxfilesize="2048m"
>>> >         queue.highwatermark="1000000"
>>> >         queue.lowwatermark="750000"
>>> >         queue.discardmark="499999999"
>>> >         queue.dequeueslowdown="100"
>>> >         queue.size="500000000"
>>> >         queue.saveonshutdown="on"
>>> >         queue.maxdiskspace="1000g"
>>> >         queue.dequeuebatchsize="50000"
>>> >         queue.workerthreads="8"
>>> >         queue.workerthreadminimummessages="100000"
>>> >         action.resumeretrycount="-1")stop}
>>> >
>>> > I'd love some feedback, but these numbers are working pretty well for
>>> these
>>> > massive feeds.
>>> >
>>> > Cheers,
>>> >
>>> > JB
>>> >
>>> > On Wed, Nov 4, 2015 at 10:26 AM, Radu Gheorghe <
>>> [email protected]>
>>> > wrote:
>>> >
>>> >> On Wed, Nov 4, 2015 at 5:19 PM, Joe Blow <[email protected]>
>>> wrote:
>>> >> > Radu - My checkpoint interval is set at 100k.  Are you suggesting
>>> this be
>>> >> > lowered? raised?
>>> >>
>>> >> It sounds like the higher the better, but if your problem is on how
>>> >> fast it can read... I think there's not much you can do - that seems
>>> >> to be a setting for writes. Also note David's comment on how it might
>>> >> only apply if syncing is enabled.
>>> >>
>>> >> On the read side I don't know what optimization you can do in the
>>> >> conf. Maybe you can test with various file sizes? (queue.maxfilesize -
>>> >> the default is 1MB so that might be too small) Though I wouldn't have
>>> >> high hopes, it sounds like recovery is much too slow even for reading
>>> >> 1MB files.
>>> >>
>>> >> Best regards,
>>> >> Radu
>>> >> --
>>> >> Performance Monitoring * Log Analytics * Search Analytics
>>> >> Solr & Elasticsearch Support * http://sematext.com/
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