Hi all,

Thank You for the response.

@Incure,

No I was not able to find out why/where the memory leak was happening.
I was unable to configure Apptrace for my application, it's missing
some dependencies, did not get a chance to figure out what!

I am guessing the issues might have been caused due to the 'string'
list properties in my model (although the number of items in the
string list were low) I have had to refactor the page to get the data
it needed differently, but this solution is not scalable, I am still
searching for a solution..

@Robert,

I am using Python. It truly is hard to find memory leaks in Python, I
tried using Apptrace but was not able to get it to work.

Functionally there is nothing much that my code does, it fetches all
items of a particular Model instance (around 500 records) serlializes
it into JSON and sends it back, the rest is done on the client.

http://code.google.com/p/apptrace/wiki/UsingApptrace

Thanks,
Arun.

On Feb 3, 11:18 am, Robert Kluin <robert.kl...@gmail.com> wrote:
> Hi Arun,
>   You don't say if you're using Python or Java.  For Python debugging
> memory usage is hard at best;  I'm not sure about Java.
>
>   In Python at least, every entity you load actually stores multiple
> copies of the data and it is decoded / encoded from protobufs many
> times.  So the end result is that your memory usage will be higher
> than what you expect.  Possibly by quite a bit depending on your data.
>
>   It is also possible that you've got other issues in your code
> leading to memory leaks.  That's harder to make general comments about
> though.
>
> Robert
>
> On Tue, Dec 27, 2011 at 11:58, Arun Shanker Prasad
>
>
>
>
>
>
>
> <arunshankerpra...@gmail.com> wrote:
> > Hi All,
>
> > Hope you had a wonderful holiday :)
>
> > I am experiencing an issue for the past couple of weeks, am getting
> > soft memory exceeded errors and the instance is being terminated..
> > This only started occuring recently.
>
> > The pages experiencing this error are mostly reporting kind of pages,
> > i.e pages that deal with a number of records that are fetched based on
> > filters selected by the user and use django.core.paginator.Paginator
> > to paginate over the result. I have a maximum of 700 records that are
> > fetched for these reports, according to datastore statistics in the
> > admin console the average size of the entities being fetched are 4KB.
>
> > Average Size of Entity:
> > 4 KBytes
>
> > Some of the properties are reference properties and I do use prefetch
> > logic to load these references as well, but most of them are also
> > small entities.
>
> > By my caclulations 158MB should be enough to handle a list of ~40448
> > records! I am not able to figure out why the request is using this
> > much memory.
>
> > I have tried eliminating most of the usual suspects (large string
> > concatination and so on), even tried deleting the large list after
> > they are processed and calling garbage collect, nothing seems to work.
> > Next step is to try and setup Apptrace for app engine.
>
> > Can anyone out there help me with this? Anyone else have any similar
> > issues? How did you manage to sort it out?
>
> > C 2011-12-27 10:03:54.089
> > Exceeded soft private memory limit with 157.648 MB after servicing 4
> > requests total
> > W 2011-12-27 10:03:54.090
> > While handling this request, the process that handled this request was
> > found to be using too much memory and was terminated. This is likely
> > to cause a new process to be used for the next request to your
> > application. If you see this message frequently, you may have a memory
> > leak in your application.
>
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