I hadn't described the details be there is not much to the work around and pretty application specific.
The summary is that I moved some application level filtering that was being done in python code on the results into the query so less results are returned. This saves a great deal of memory in my cases and speeds up the system dramatically. Once I understood that there wasn't really a memory leak, I just optimized what was already there to use less memory. -Allen On Wed, Feb 25, 2009 at 6:59 PM, Peter Hansen <pe...@engcorp.com> wrote: > > Allen Bierbaum wrote: >> On Tue, Feb 24, 2009 at 4:44 AM, Chris Miles <miles.ch...@gmail.com> wrote: >>> On Feb 22, 6:08 am, Allen Bierbaum <abierb...@gmail.com> wrote: >>> Python 2.5 and later will free up garbage collected memory, handing it >>> back to the system. Previous versions of Python would never free up >>> memory (hence never shrink in size). >>> >>> Are you using Python 2.4? >> >> I am using Python 2.5. But now that I understand the issue better I >> have come up with a workaround. The biggest issue was that I didn't >> understand what I should be seeing as far as memory usage. > > Although your workaround may not be generally useful, it would still be > nice for posterity (i.e. those searching through this thread in future) > if you could summarize how you've actually addressed this issue to your > satisfaction, however crude or unusual that might be. Thanks. :) > > -- > Peter Hansen > > > > --~--~---------~--~----~------------~-------~--~----~ You received this message because you are subscribed to the Google Groups "sqlalchemy" group. To post to this group, send email to sqlalchemy@googlegroups.com To unsubscribe from this group, send email to sqlalchemy+unsubscr...@googlegroups.com For more options, visit this group at http://groups.google.com/group/sqlalchemy?hl=en -~----------~----~----~----~------~----~------~--~---
