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I've had pretty good results with SQLAlchemy on large datasets, that
might be a painless way to solve the problem..
Ben
Jarek Zgoda wrote:
> Jacob Kaplan-Moss napisał(a):
>
Can you share any hints on how to reduce the memory usage in such
Jacob Kaplan-Moss napisał(a):
>>> Can you share any hints on how to reduce the memory usage in such
>>> situation? The underlying database structure is rather complicated and I
>>> would like to not do all queries manually.
>> At this level -- hundreds of thousands of objects per query -- I
On 1/30/08, James Bennett <[EMAIL PROTECTED]> wrote:
> On Jan 30, 2008 10:21 AM, Jarek Zgoda <[EMAIL PROTECTED]> wrote:
> > Can you share any hints on how to reduce the memory usage in such
> > situation? The underlying database structure is rather complicated and I
> > would like to not do all
On Jan 30, 2008 10:21 AM, Jarek Zgoda <[EMAIL PROTECTED]> wrote:
> Can you share any hints on how to reduce the memory usage in such
> situation? The underlying database structure is rather complicated and I
> would like to not do all queries manually.
At this level -- hundreds of thousands of
Hello, I'd like to get some hints on memory usage by python/django program.
I have standalone script that populates solr index with django
application data. The queryset I have to process has over 16
objects. No matter if I use iterator() or not, the script eats more and
more memory, finally
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