Malcolm Tredinnick wrote: > > On Mon, 2008-11-17 at 11:07 -0800, Gustavo Picón wrote: > [...] >> So the usual recommendation is: >> >> - if you're going to insert a lot more than you read, use adjacency >> list >> - if, as is the most common case, you're going to read your tree more >> than you insert nodes, use nested sets or materialized path > > Size matters, though. Your numbers are for a lot more than 500 nodes and > I'll repeat my earlier claim that for something that small you just > aren't going to lose a lot of performance (in fact, depending on what > you're doing with the data, you'll often gain speed) by doing a naive > select of almost everything (or everything restricted by parent name, > say) and then just working Python. You cut out a bunch of database level > comparisons at that point. > Sure, but ultimately the question then becomes "what data growth do you expect", since at some stage you can expect a DBMS-based solution to be required if volumes grow to the extent that a pure Python solution starts to seriously overload memory. This is not an attempt to negate your pragmatic approach, since I find pragmatism very Pythonic.
> Your benchmarks match what other people see with those various > implementation strategies, so they look believable (and the comparisons > between the various database engines look believable, too), so I think > they're good measures, but at various ends of the scale (and, let's be > serious here: 500 is small), alternative strategies work very well. > In RDBMS terms 500 is *tiny*, and handling the complexity in Python is a very viable strategy at that level unless the rows are 100kB apiece. > [...] regards Steve -- Steve Holden +1 571 484 6266 +1 800 494 3119 Holden Web LLC http://www.holdenweb.com/ --~--~---------~--~----~------------~-------~--~----~ 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 -~----------~----~----~----~------~----~------~--~---
