Ok, my next thought would be that your young generation is perhaps too
big? I'm sure you've probably tried choking it down and letting GC run
more often against a smaller young heap?

If GC times for young gen are getting longer, something has to be
changing. Finalizers? Weak/SoftReferences? You say you're not getting
to the point of CMS running, but a large young gen can still take a
long time to collect. Do less more often?

On Wed, May 5, 2010 at 9:25 AM, Matt Fowles <[email protected]> wrote:
> Charles~
>
> I settled on that after having run experiments varying the survivor
> ratio and tenuring threshold.  In the end, I discovered that >99.9% of
> the young garbage got caught with this and each extra young gen run
> only reclaimed about 1% of the previously surviving objects.  So it
> seemed like the trade off just wasn't winning me anything.
>
> Matt
>
> On Tue, May 4, 2010 at 6:50 PM, Charles Oliver Nutter
> <[email protected]> wrote:
>> Why are you using -XX:MaxTenuringThreshold=0? That's basically forcing
>> all objects that survive one collection to immediately be promoted,
>> even if they just happen to be a slightly longer-lived young object.
>> Using 0 seems like a bad idea.
>>
>> On Tue, May 4, 2010 at 4:46 PM, Matt Fowles <[email protected]> wrote:
>>> All~
>>>
>>> I have a large app that produces ~4g of garbage every minute and am
>>> trying to reduce the size of gc outliers.  About 99% of this data is
>>> garbage, but almost anything that survives one collection survives for
>>> an indeterminately long amount of time.  We are currently using the
>>> following VM and options
>>>
>>>
>>> java version "1.6.0_16"
>>> Java(TM) SE Runtime Environment (build 1.6.0_16-b01)
>>> Java HotSpot(TM) 64-Bit Server VM (build 14.2-b01, mixed mode)
>>>
>>> -verbose:gc
>>> -Xms32g -Xmx32g -Xmn4g
>>> -XX:+UseParNewGC
>>> -XX:ParallelGCThreads=4
>>> -XX:+UseConcMarkSweepGC
>>> -XX:ParallelCMSThreads=4
>>> -XX:MaxTenuringThreshold=0
>>> -XX:SurvivorRatio=20000
>>> -XX:CMSInitiatingOccupancyFraction=60
>>> -XX:+UseCMSInitiatingOccupancyOnly
>>> -XX:+CMSParallelRemarkEnabled
>>> -XX:MaxGCPauseMillis=50
>>> -Xloggc:gc.log
>>>
>>>
>>>
>>> As you can see from the GC log, we never actually reach the point
>>> where the CMS kicks in (after app startup).  But our young gens seem
>>> to take increasingly long to collect as time goes by.
>>>
>>> One of the major metrics we have for measuring this system is latency
>>> as measured from connected clients and as measured internally.  You
>>> can see an attached graph of latency vs time for the clients.  It is
>>> not surprising the the internal latency (green and labeled 'sb') is
>>> not as large as the network latency.  I assume this is in part because
>>> VM safe points are less likely to occur within our internal timing
>>> markers.  But, one can easily see how the external latency
>>> measurements (blue and labeled 'network') display the same steady
>>> increase in times.
>>>
>>> My hope is to be able to tweak young gen size and trade off GC
>>> frequency with pause length; however, the steadily increasing GC times
>>> are proving to persist regardless of the size that I make the young
>>> generation.
>>>
>>> Has anyone seen this sort of behavior before?  Are there more switches
>>> that I should try running with?
>>>
>>> Obviously, I am working to profile the app and reduce the garbage load
>>> in parallel.  But if I still see this sort of problem, it is only a
>>> question of how long must the app run before I see unacceptable
>>> latency spikes.
>>>
>>> Matt
>>>
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>>
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