On Apr 21, 3:36 pm, Scott David Daniels <scott.dani...@acm.org> wrote: > Philip Semanchuk wrote: > > ... If you're doing a mass insert to populate a blank table it also often > > helps to postpone index creation until after the table is populated.... > > I forget the name of the SQL Server bulk loader, but for large loads, I > used to populate a fresh table with the bulk data, then do UPDATEs and > INSERTs to get the data spread out into the main tables. You (the OP) > might try a scheme like that. > > --Scott David Daniels > scott.dani...@acm.org
Hmm..I think I'm going to move my question over to a SQL forum because this is starting to feel like a SQL, rather than a python issue to me. Three times now after letting the system "rest" where I go off an do other things and then run my script it completes in 10 seconds. If I drop tables and start fresh immediately after that it takes 35 seconds. If I drop the tables and wait an hour and then run the script it'll finish in 10 seconds again. That makes me think it's a SQL config or optimization issue more than a python issue. oh and the times I listed above were totals from the start of execution so the string.join() was taking 0.047 seconds to run. It was taking 9 seconds to get my data from the com object and format it but the join was quite fast. -- http://mail.python.org/mailman/listinfo/python-list
