Hi Peter, On Fri, Sep 11, 2009 at 2:18 AM, Peter Liu <tinyee...@gmail.com> wrote:
> > I see similar results. The total api cpu time is much higher then > actual time spent on the actual call. I use a profiling api delegate > that logs every api call duration, and the total api cpu reported on > admin console is usually at least 2 times higher. > This is because an API call may involve multiple machines. A batch put, for example, can include operations on multiple tabletservers, which are all executed simultaneously. -Nick Johnson > > On Sep 9, 2:05 pm, Lec <lec...@gmail.com> wrote: > > I cannot confirm what it was like previous to 1.2.5 release, but I > > think I am seeing something similar. Although with task queues my > > workers do data processing then store the data in datastore, i am NOT > > seeingcpuproblems with workers. I only see problems with the > > datastore in the main threads where i do not use workers. Did anyone > > have this kind of experience? > > > > L > > > > On Sep 9, 3:54 am, herbie <4whi...@o2.co.uk> wrote: > > > > > It seems I'm not the only one. I was starting to think I was imagining > > > it! Thanks for supporting this thread. > > > Would anyone fro Google like to comment? > > > > > On Sep 8, 11:01 pm, Robert Kluin <robert.kl...@gmail.com> wrote: > > > > > > I have some code that is now using moreCPUas well. > > > > > > Previously: > > > > 1530cpu_ms 616api_cpu_ms > > > > 1404cpu_ms 995api_cpu_ms > > > > 1104cpu_ms 695api_cpu_ms > > > > > > Now: > > > > 4619cpu_ms 4133api_cpu_ms > > > > 4619cpu_ms 4133api_cpu_ms (yes, it is exactly the same) > > > > > > That is unchanged code. Same exact data. > > > > > > Robert > > > > > > On Tue, Sep 8, 2009 at 3:23 PM, bFlood <bflood...@gmail.com> wrote: > > > > > > > I just ran a batch delete using the Task queue. It grabs the next > 50 > > > > > keys for a Kind and then calls db.delete(keys), so fairly simple > > > > > stuff. here's some example results in the log: > > > > > > > 865ms 1032cpu_ms 952api_cpu_ms > > > > > 1058ms 1040cpu_ms 952api_cpu_ms > > > > > 947ms 49947cpu_ms 49869api_cpu_ms <--??? > > > > > 1425ms 1035cpu_ms 952api_cpu_ms > > > > > 1674ms 41181cpu_ms 41094api_cpu_ms > > > > > > > any thoughts? something seems wrong to me > > > > > > > cheers > > > > > brian > > > > > > > On Sep 8, 8:56 am, bFlood <bflood...@gmail.com> wrote: > > > > > > ok, I was able to check over my code again and even with rolling > back > > > > > > small changes, the largeCPUincreases are still there. at this > point, > > > > > > I have to agree with herbie's findings as well. It would be nice > if > > > > > > Google could weigh in on this troubling issue > > > > > > > > cheers > > > > > > brian > > > > > > > > On Sep 8, 4:51 am, herbie <4whi...@o2.co.uk> wrote: > > > > > > > > > On Sep 8, 12:07 am, Stephen <sdea...@gmail.com> wrote: > > > > > > > > > > OK, but because api_cpu_ms is 96% of the total, then cpu_ms > is also > > > > > > > > almost 3x higher? The spike is showing up in the cpu_ms? > > > > > > > > > Yes in total the cpu_ms has gone up by nearly 3x too. > > > > > > > > > But as I understand it cpu_ms is the totalcpuusage for the > request > > > > > > > and api_cpu_ms is thecpuusage by GAE api calls. So the > difference > > > > > > > between the two is thecpuusage of my non api code. This > difference > > > > > > > hasn’t increased because the code hasn’t changed. > > > > > > > > > But yes, the newhighvalue for api_cpu_ms directly affects my > quota > > > > > > > because it makes the vast majority of cpu_ms. So we do pay for > > > > > > > api_cpu_ms ! So for example if Google makes a change to > db.put() > > > > > > > (or any api call) so that it uses morecpu, we will be billed > for > > > > > > > morecpuusage even if our code hasn’t changed. > > > > > > > > > As my code/ indexes hasn’t changed and the api_cpu_ms has shot > up the > > > > > > > obvious conclusion is that an api/datastore change has caused > it? > > > > > > > > > But there may be another ‘good’ reason for it, which I can’t > think > > > > > > > of, but as I’m going to have to pay for the increase in > api_cpu_ms, > > > > > > > I would really appreciate it if someone at Google could help. > > > > > > > > > On Sep 8, 12:07 am, Stephen <sdea...@gmail.com> wrote: > > > > > > > > > > On Sep 7, 8:57 pm, herbie <4whi...@o2.co.uk> wrote: > > > > > > > > > > > On Sep 7, 6:50 pm, Stephen <sdea...@gmail.com> wrote: > > > > > > > > > > > > What about cpu_ms, is that also higher for requests which > write > > > > > to the > > > > > > > > > > data store? > > > > > > > > > > > No, not in relation to api_cpu_ms. For the request that > does the > > > > > most > > > > > > > > > writing to the datastore api_cpu_ms accounts for 96% of the > total > > > > > > > > > cpu_ms value!. The so request handler does not much more > than > > > > > create > > > > > > > > > new entities in the datastore. > > > > > > > > > > OK, but because api_cpu_ms is 96% of the total, then cpu_ms > is also > > > > > > > > almost 3x higher? The spike is showing up in the cpu_ms? > > > > > > > > > > cpu_ms is billed for, so if you have billing enabled you are > being > > > > > > > > overcharged. > > > > > > > > > > You could try asking for a refund here: > > > > > > > > http://code.google.com/support/bin/request.py?contact_type=AppEngineB... > > > > -- Nick Johnson, Developer Programs Engineer, App Engine --~--~---------~--~----~------------~-------~--~----~ You received this message because you are subscribed to the Google Groups "Google App Engine" group. 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