Hello Takashi,

Can you please point me how to acomplish this timeout in Java?

Thanks!

Em terça-feira, 22 de maio de 2012 19h19min44s UTC-3, Takashi Matsuo 
(Google) escreveu:
>
> Thanks for reporting guys! 
>
> Ideally, the memcache service should have steady latencies, but 
> unfortunately it is not as stable as HR datastore. Additionally, our 
> SLA is not covering the memcache service now. In general, we're 
> working hard for improving stability of our service. However, of 
> course we prioritize SLA-covered serviced first. 
>
> Thus, you may want to file a feature request for making the memcache 
> service covered by SLA. That way, others can show their 
> interests/business needs by staring it, and if there's many stars on 
> the issue, our engineering team will eventually prioritize providing 
> SLA-covered memcache service. 
>
> For the time being, you can put appropriate deadline on your memcache 
> call to prevent those kind of latency problems happening. Python 
> memcache Client class has some methods like get_multi_async and 
> set_multi_async that you can put a deadline(by specifying an rpc 
> object). 
>
> For more details, please see: 
>
> https://developers.google.com/appengine/docs/python/memcache/clientclass#Client_get_multi_async
>  
>
> -- Takashi 
>
> On Wed, May 23, 2012 at 6:36 AM, Rishi Arora <[email protected]> 
> wrote: 
> > Here's my appstats output for a specific request showing my problem is 
> > squarely related to memcache: 
> > 
> > 
> > 
> > 
> > On Tue, May 22, 2012 at 4:33 PM, Rishi Arora <[email protected]> 
>
> > wrote: 
> >> 
> >> Hmmm.  That means the problem isn't specific to memcache.  And that 
> means 
> >> it might take longer for Google to fix this, if indeed they determine 
> >> there's a problem. 
> >> 
> >> 
> >> On Tue, May 22, 2012 at 4:15 PM, Robert Morgan <[email protected]> 
> >> wrote: 
> >>> 
> >>> My graph is attached -- interesting, eh? 
> >>> I don't think we're using memcache in this instance. 
> >>> 
> >>> :R 
> >>> 
> >>> 
> >>> On Tue, May 22, 2012 at 2:04 PM, Rishi Arora <
> [email protected]> 
> >>> wrote: 
> >>>> 
> >>>> Here's what my milliseconds/request looks like, although the 
> #instances 
> >>>> follows a similar pattern, and translates directly into higher costs 
> (5x 
> >>>> normal usage today) 
> >>>> 
> >>>> 
> >>>> On Tue, May 22, 2012 at 4:01 PM, Rishi Arora <
> [email protected]> 
> >>>> wrote: 
> >>>>> 
> >>>>> Perhaps similar to what I'm seeing.  Although I was able to use the 
> >>>>> appstats tool to determine that the deadlines were being missed 
> specifically 
> >>>>> because of memcache API calls.  Perhaps you can determine from 
> appstats if 
> >>>>> its the same for you? 
> >>>>> 
> >>>>> If so, please star this issue that I logged: 
> >>>>> 
> >>>>> code.google.com/p/googleappengine/issues/detail?id=7554 
> >>>>> 
> >>>>> 
> >>>>> 
> >>>>> On Tue, May 22, 2012 at 2:02 PM, Robert Morgan <
> [email protected]> 
> >>>>> wrote: 
> >>>>>> 
> >>>>>> Beginning about 18 hours ago, the milliseconds/Request on one of 
> our 
> >>>>>> apps began to ramp and is now over 100 seconds for a trivial 
> response (which 
> >>>>>> historically takes 2 seconds). Our other apps are fine, and the AE 
> status 
> >>>>>> page is clear. 
> >>>>>> 
> >>>>>> It's an app that we use for development, it's been around for ages 
> and 
> >>>>>> still runs the Master-Slave datastore. Python. The ramping just 
> started -- 
> >>>>>> we had not deployed a new server version in about a week, and our 
> client 
> >>>>>> usage remains low and patterns haven't changed. 
> >>>>>> 
> >>>>>> I've poked at it trying to see if I can determine some threshold, 
> but 
> >>>>>> even a very simple return now fails due to DeadlineExceeded. 
> >>>>>> 
> >>>>>> This really feels like it's a system issue -- any ideas on what I 
> can 
> >>>>>> do next? 
> >>>>>> 
> >>>>>> Thanks, 
> >>>>>> :R 
> >>>>>> 
> >>>>>> -- 
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> >>>>> 
> >>>>> 
> >>>> 
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> >>> 
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> >> 
> >> 
> > 
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>
>
>
> -- 
> Takashi Matsuo | Developer Advocate | [email protected] 
>

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