Hello, I have an application which looks lke this
Star: id, etc Band:id, etc LightCurve: id, star fkey(Star), band fkey(Band) Postgres is the backend..8.2.3 Every Star basically has multiple light curves (brightness vs time plots) in different spectral bands. Now, there are about 1/2 a billion stars i want to add. Having the foreign keys really slows things down, even when i set transactions to happen with the manual transactions decorator every 3000 stars or so. The timing goes thus: first 15623 6mins 21:31 next 21681 14 mins 21:45 next 29262 31 mins 22.16 next 36158 57 mins 23.13 which seems to indicate that as more stars get created, fkey lookups are taking longer and longer. Also, django generates additional indexes such as: "maindb_lightcurve_star_id" btree (star_id), which i presume is done to allow for extremely quick 'backwords' queries such as starinstance.lcot_set.all() My questions are (a) these additional indexes..do they affect performance on the inserts...it would seem so.. (b) i can do fkeys later by having explicit integers for the ids, then changing the model. Identically i can do the indexes later too. But syncdb wont pick this up, right? However, with a changed model, will everthing just work? Any other ideas for large scale insert efficiency? --~--~---------~--~----~------------~-------~--~----~ You received this message because you are subscribed to the Google Groups "Django users" group. To post to this group, send email to [email protected] 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 -~----------~----~----~----~------~----~------~--~---
