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 <nve...@google.com> 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 <wal...@ninua.com> 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 <drak...@digerat.com> 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: google-appengine@googlegroups.com
>>> [mailto:google-appengine@googlegroups.com] On Behalf Of Nicholas Verne
>>> Sent: Monday, June 20, 2011 6:03 PM
>>> To: google-appengine@googlegroups.com
>>> 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 <wal...@ninua.com> 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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