Disclaimer: I'm the author of django-treebeard > I am glad to hear that the naive way could possibly fit my 3-levels > tree, or at least that it deserves a try. I'll have some benchmarks as > you suggest.
You can look at the treebeard benchmarks in http://django-treebeard.googlecode.com/svn/docs/index.html#module-tbbench I'll take as an example the results of reading branches in postgresql 8.3 in unordered trees: - Nested sets: 5840ms - Materialized Path: 7132ms - Adjacency List: 50682ms So as you can see, your approach (adjacency list) is by far the slowest. The only advantage of the adjacency list model is for trees that are mostly write-only, look at the benchmark results for insertions in an ordered tree with transactions (the optimal use for AL trees): - Nested sets: 10941ms - Materialized path: 3942ms - Adjacency List: 896ms 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 -tabo --~--~---------~--~----~------------~-------~--~----~ 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 -~----------~----~----~----~------~----~------~--~---
