Question

I am confronted with a problem where I have a massive list of information (287,843 items) that must be sorted for display. Which is more efficient, to use a self-organizing red-black binary tree to keep them sorted or to build an array and then sort? My keys are strings, if that helps. This algorithm should make use of multiple processor cores.

Thank you!

Answer 1

This really depends on the particulars of your setup. If you have a multicore machine, you can probably sort the strings extremely quickly by using a parallel version of quicksort, in which each recursive call is executed in parallel with each other call. With many cores, this can take the already fast quicksort and make it substantially faster. Other sorting algorithms like merge sort can also be parallelized, though parallel quicksort has the advantage of requiring less extra memory. Since you know that you’re sorting strings, you may also want to look into parallel radix sort, which could potentially be extremely fast.

Most binary search trees cannot easily be multithreaded, because rebalance operations often require changing multiple parts of the tree at once, so a balanced red/black tree may not be the best approach here. However, you may want to look into a concurrent skiplist, which is a data structure that can be made to work efficiently in parallel. There are some newer binary search trees designed for parallelism that sometimes outperform the skiplist (here is one such data structure), though I expect that there will be fewer existing implementations and discussion of these newer structures.

If the elements are not changing frequently or you only need sorted order once, then just sorting once with parallel quicksort is probably the best bet. If the elements are changing frequently, then a concurrent data structure like the parallel skiplist will probably be a better bet.

Hope this helps!