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Interesting article, but without actual numbers it's hard to tell whether the change made any difference in performance.


That's what mathematics is for ... you just need the growth rate.

O(lg lg N) is a smaller growth rate than O(lg N).

Of course, for smaller datasets it doesn't matter.

In fact if you do sorting, for small datasets (that are mostly sorted) a bubble-sort is better than quick-sort, since it doesn't involve random disk accesses and it might even require fewer steps.

I would be curious if this method for searching would apply to sorting (e.g. sorting done in O(N lg lg N)) ... since I remember that sorting done with comparisons can't be better than O(N lg N) (the height of a binary search tree is lg N ... and I think the demonstration was based on that).

So to get back on-topic ... it really depends on the size of your data.




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