Good catch, thanks. I'm guessing that pending_ms is the time a request stays
on hold before execution? I couldn't find it documented anywhere. If so,
then the question is: why would a request be in a pending state? Is it
waiting for an instance to be free?

This might also be related to my other thread about the task queue not
scaling up [1].

Thanks,
Waleed

[1]
http://groups.google.com/group/google-appengine/browse_thread/thread/f8d1c6f39ad2af27/c989b852d1011cd6




On Tue, Jun 21, 2011 at 3:33 PM, Nicholas Verne <[email protected]> wrote:

> One other note:
>
> In a large number of cases, if you the pending_ms (when it exists) to
> your measurement, you come close to the ms value you circled at the
> top.
>
> Nick Verne
>
> On Wed, Jun 22, 2011 at 8:18 AM, Nicholas Verne <[email protected]> wrote:
> > Waleed,
> >
> > I'm going to have to ask one of the other infrastructure engineers
> > about the log lines. The value you have circled (18386ms) is not
> > always greater than the cpu_ms. I'm not sure what this value
> > indicates.
> >
> > Nick Verne
> >
> > On Wed, Jun 22, 2011 at 6:27 AM, Waleed Abdulla <[email protected]>
> wrote:
> >> Nicholas,
> >>     I implemented the change you suggested (making task_t0) a global
> >> variable, but that didn't change the calculations. I'm attaching another
> >> screen shot. There is a big difference between the actual processing
> time
> >> and the time reported in the logs. It doesn't happen in all tasks, but
> it's
> >> often enough that it's slowing down my application considerably and
> causing
> >> a lot of user complaints.
> >>     I also calculated the total time to load the module (including time
> for
> >> imports). It doesn't seem to take much time (sub 1 second), and it
> happens
> >> only once right after I deploy a new version. So that is not an issue.
> >>     I've set the processing rate, bucket size, and max concurrency on
> the
> >> task queue to high numbers (much higher than I need).
> >>     Any explanation for why this is happening?
> >> Waleed
> >>
> >>
> >>
> >> On Mon, Jun 20, 2011 at 6:54 PM, Brandon Wirtz <[email protected]>
> wrote:
> >>>
> >>> Use a fetch from one thread to another.
> >>>
> >>> Echo Time
> >>> Fetch
> >>>        Echo Time
> >>>        Do something
> >>>        Echo Time
> >>> Echo Fetch
> >>>
> >>> Now you have a timeline of everything except the latency from User to
> >>> Appengine.
> >>>
> >>>
> >>> -----Original Message-----
> >>> From: [email protected]
> >>> [mailto:[email protected]] On Behalf Of Nicholas Verne
> >>> Sent: Monday, June 20, 2011 6:03 PM
> >>> To: [email protected]
> >>> Subject: Re: [google-appengine] Why a big difference between execution
> >>> time
> >>> and response time?
> >>>
> >>> Yes, that's true. If you try this:
> >>>
> >>> task_t0 = None
> >>>
> >>> ...
> >>>
> >>>
> >>> def main(argv):
> >>>  global task_t0
> >>>  task_t0 = time.time()
> >>>
> >>> You'll get a measurement per request as early as we can make it. For
> >>> warming
> >>> requests, it might still be worth measuring the import time
> >>>
> >>> import time
> >>> import_start = time.time()
> >>> ... other imports
> >>> import_duration = time.time() - import_start
> >>>
> >>> The import_duration global should persist and tell you how long this
> >>> instance's imports took to process. Subsequent requests on that
> instance
> >>> don't do the imports.
> >>>
> >>> Nick Verne
> >>>
> >>> On Tue, Jun 21, 2011 at 10:49 AM, Waleed Abdulla <[email protected]>
> wrote:
> >>> >> A more useful measurement might be to set task_t0 as a global
> >>> >> variable at the top of your file, with only the import of "time"
> >>> >> preceding it
> >>> >
> >>> > Wouldn't that cause the 2nd, 3rd, ...nth requests to the same handler
> >>> > to show wrong values? I see why setting task_t0 at the top of the
> file
> >>> > would apply if it was the first request that causes the handler to be
> >>> > loaded. But this is happening on an ongoing basis for all requests,
> >>> > not only the first for that handler.
> >>> >
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