Optimal median of medians selection - 3 element blocks vs 5 element blocks?
I'm working on a quicksort-variant implementation based on the Select algorithm for choosing a good pivot element. Conventional wisdom seems to be to divide the array into 5-element blocks, take the median of each, and then recursively apply the same blocking approach to the resulting medians to get a "median of medians".
What's confusing me is the choice of 5-element blocks rather than 3-element blocks. With 5-element blocks, it seems to me that you perform n/4 = n/5 + n/25 + n/125 + n/625 + ... median-of-5 operations, whereas with 3-element blocks, you perform n/2 = n/3 + n/9 + n/27 + n/81 + ... median-of-3 operations. Being that each median-of-5 is 6 comparisons, and each median-of-3 is 2 comparisons, that results in 3*n/2 comparisons using median-of-5 and n comparisons using median-of-3.
Can anyone explain this discrepancy, and what the motivation for using 5-element blocks could be? I'm not familiar with usual practices for applying these algorithms, so maybe there's some way you can cut out some steps and still get "close enough" to the median to ensure a good pivot, and that approach works better with 5-element blocks?
Answer
The reason is that by choosing blocks of 3, we might lose the guarantee of having an O(n) time algorithm.
For blocks of 5, the time complexity is
T(n) = T(n/5) + T(7n/10) + O(n)
For blocks of 3, it comes out to be
T(n) = T(n/3) + T(2n/3) + O(n)
Check this out: http://www.cs.berkeley.edu/~luca/w4231/fall99/slides/l3.pdf