I think it is pretty standard practice, and it can be quite fast when
implemented correctly.

Check out Brett Slatkin's IO talk:
http://code.google.com/events/io/2010/sessions/high-throughput-data-pipelines-appengine.html

And the 'mapper' implementation:
http://code.google.com/p/appengine-mapreduce/


Robert




On Mon, Jul 12, 2010 at 8:13 PM, Phil McDonnell
<phil.a.mcdonn...@gmail.com> wrote:
> I see how this is possible, but it feels very clunky.  Is this standard
> practice?
> Thanks,
> Phil
>
> On Mon, Jul 12, 2010 at 7:09 PM, Pieter Coucke <pieter.cou...@onthoo.com>
> wrote:
>>
>> For a similar problem I use a task A which fetches 10 entities, creates
>> subtasks B for them and then creates a new task A with the datastore cursor
>> as a parameter so this task can continue creating subtasks.
>>
>>
>>
>> On Mon, Jul 12, 2010 at 1:31 AM, Phil McDonnell
>> <phil.a.mcdonn...@gmail.com> wrote:
>>>
>>> I know there are a number of different frameworks and mechanisms to
>>> process data offline on GAE.  I need to have a daily job that scans one of
>>> my datastore tables and computes an updated profile for all my users.  What
>>> would be the best mechanism to do this?  Are task queues appropriate?
>>>  Should I be using some sort of mapreduce?  If I should use some sort of
>>> mapreduce framework, how does that integrate with GAE?  My user base right
>>> now is small, but I intend to scale this.
>>> Thanks,
>>> Phil
>>>
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>>
>>
>> --
>> Pieter Coucke
>> Onthoo BVBA
>> http://www.onthoo.com
>> http://www.koopjeszoeker.be
>>
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