i had that exact problem.
I resolved it by cutting down the amount of processing from one process to
tons of them.
You can break all the mini calculations into mini tasks running asyc side by
side and get the work done at the same time or even shorter.
If tasks isnt the solution for you try the mapper class, google for it. it
lets you catch the HardDeadlineExceededError and save your current job
location and restart again at the same position.
quick tip from what i've learned. google gives you extra few seconds before
they break your process with HardDeadlineExceededError, its not something
static but its around 2-3 seconds, you can do alot when you hit that. do
try: catch on that and test it.
For large datastore uploads and so on use the bulkloader tool.
-
Cheers,
def AlonCarmel(request)
import simplejson as json
contact = {}
contant['email'] = '[email protected]'
contact['twitter'] = '@aloncarmel'
contact['web'] = 'http://aloncarmel.me'
contact['phone'] = '+972-54-4860380'
return HttpResponse(json.dumps(contact))
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On Thu, Jul 29, 2010 at 8:29 AM, Lu <[email protected]> wrote:
> Hi,
>
> My application throws 'HardDeadlineExceededError' exception and i know
> the reason is that google only allows at most 30 secs to give
> response. However, I am doing large amounts of processing on the
> server side and I cannot manage to give feedback under 30 secs.
>
> Is there any mechanism that can throw some whatever stuff back to
> client every 30 secs and meanwhile still do the processing on the
> server side?
>
> Thanks,
> Lu
>
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