I think you may need to consider looking outside the ORM for imports of that size. I was having trouble with only about 5 million rows, and got a reasonable speed up doing executemany. It was still slow though. I ended up redesigning to eliminate that table, but from what I read in trying to make it work a good approach would have been:
drop the indexes import the data and convert to raw sql statements and save those to a file do a bulk load of the file add the indexes If you have debug enabled you can take a look at django.db.connection.queries after a small import using your models to get an idea of how to build the sql statements. On a related note, I always seem to get bitten by forgetting to turn debug off when doing large imports. All of the sql statements are logged in debug mode, and things can get ugly quickly for large datasets. There might be better ways to do it, I'm no DB expert but since you hadn't gotten a reply in a few days maybe something is better than nothing. --~--~---------~--~----~------------~-------~--~----~ You received this message because you are subscribed to the Google Groups "Django users" group. To post to this group, send email to django-users@googlegroups.com To unsubscribe from this group, send email to [EMAIL PROTECTED] For more options, visit this group at http://groups.google.com/group/django-users?hl=en -~----------~----~----~----~------~----~------~--~---
