Le lundi 11 janvier 2010 à 15:55 -0800, diana a écrit : > And now for a question about a completely different app (no sharding, > very simple). I haven't got a sufficient response from the pylons > group, so I'm trying here. > > The question: > > http://groups.google.com/group/pylons-discuss/browse_thread/thread/cb48d0ea2b084159
Well if you only want to count entries, use Query.count(), not Query.all(). It will be much more efficient, both on the DB side and on the Python side. Even if you use the entries one by one but don't need to keep them in memory afterwards, just use the iterative form (`for row in query: ...`). Regardless, you are fetching 90000 objects and witnessing a 160MB increase in memory. This gives approximately 1.7KB per objects. Depending on the size and complexity of each row this is not necessarily surprising. Python will generally not be as memory-efficient as hand-tailored structures written in C, since there is a lot of genericity and flexibility in most Python datatypes. Objects in general can be quite big, because they are based on dictionaries (dict objects) which are themselves big. As for releasing memory, try to call gc.collect() after you have released the last reference to the result set. I'd be a bit surprised if SQLAlchemy created reference cycles, though -- and would be inclined to consider it a bug ;-)
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