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Groups > comp.lang.python > #45822
| Date | 2013-05-23 17:41 +0100 |
|---|---|
| From | duncan smith <buzzard@invalid.invalid> |
| Newsgroups | comp.lang.python |
| Subject | Re: Ordered dictionaries compared |
| References | <mailman.1989.1369279892.3114.python-list@python.org> |
| Message-ID | <519e46c0$0$26690$862e30e2@ngroups.net> (permalink) |
On 23/05/13 04:31, Dan Stromberg wrote: > > What kind of ordered dictionaries? Sorted by key. > > I've redone the previous comparison, this time with a better red-black > tree implementation courtesy of Duncan G. Smith. > > The comparison is at > http://stromberg.dnsalias.org/~strombrg/python-tree-and-heap-comparison/just-trees/ > > The Red-Black tree gave a much better showing this time, but it gave > just one 2nd place on one workload-interpreter - still kinda > lackluster. It took 1st place 0 times. > > A quick test of my Red Black Tree and Treap (Python 2.7). >>> def test_trees(data, randomize=True): cpy = data[:] # for deletion if randomize: random.shuffle(data) random.shuffle(cpy) t = binary_trees.RedBlackTree() start = time.time() for datum in data: t.insert(datum) print 'Red Black Tree insertion %s' % (time.time() - start) start = time.time() for datum in data: t.find(datum) print 'Red Black Tree find %s' % (time.time() - start) start = time.time() for datum in cpy: t.delete(datum) print 'Red Black Tree deletion %s' % (time.time() - start) t = binary_trees.Treap() start = time.time() for datum in data: t.insert(datum) print print 'Treap insertion %s' % (time.time() - start) start = time.time() for datum in data: t.find(datum) print 'Treap find %s' % (time.time() - start) start = time.time() for datum in cpy: t.delete(datum) print 'Treap deletion %s' % (time.time() - start) >>> test_trees(range(100000)) Red Black Tree insertion 5.42807197571 Red Black Tree find 1.58799219131 Red Black Tree deletion 3.87580800056 Treap insertion 6.79647684097 Treap find 2.11693120003 Treap deletion 4.61243915558 >>> >>> test_trees(range(100000), False) Red Black Tree insertion 6.29647898674 Red Black Tree find 1.157143116 Red Black Tree deletion 2.74785804749 Treap insertion 3.87288999557 Treap find 1.48776102066 Treap deletion 1.88962197304 >>> RBT is quicker than Treap for insertion with randomized data, but slower with ordered data. Randomized data will tend to minimize the number of tree rotations needed to keep the RBT balanced, whilst the Treap will be performing rotations to maintain the heap property in an already reasonably well balanced tree. With ordered data the RBT will have to work harder to keep the tree balanced, whilst the Treap will be able to maintain the heap property with fewer rotations. No surprise that find() is generally quicker for RBTs, they tend to be better balanced. Deletion is a bit more confusing. I suppose deletion from a better balanced tree will tend to be quicker, but deletion from a treap constructed from ordered data is (for some reason) quickest of all. All these operations require a call to find(), and that is generally going to be quicker for RBTs. Treaps tend to require fewer subsequent rotations, but they have variable worth (in terms of rebalancing). Looks like RBTs are better than treaps if they are being populated with randomly ordered data, but not if they are being populated with ordered data. RBTs are better for use cases that are heavy on finds. Both types of tree appear to be better balanced (on the basis of the find results) if populated from ordered data. Treaps appear to perform better on insertion, find and deletion when populated from ordered data. Duncan
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Ordered dictionaries compared Dan Stromberg <drsalists@gmail.com> - 2013-05-22 20:31 -0700
Re: Ordered dictionaries compared duncan smith <buzzard@invalid.invalid> - 2013-05-23 17:41 +0100
Re: Ordered dictionaries compared Dan Stromberg <drsalists@gmail.com> - 2013-05-23 10:44 -0700
Re: Ordered dictionaries compared duncan smith <buzzard@invalid.invalid> - 2013-05-24 00:57 +0100
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