Looking for an edge with the classic Quicksort algorithm
Smart Sort
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If you wanted to assign a flavor to the Quicksort algorithm, it would be sweet and sour. Sweet, because it is very elegant; sour, because typical implementations sometimes leave more questions than they answer.
The Quicksort sorting algorithm has been around for 60 years, and, if implemented properly, it is still the fastest option for many sorting tasks. According to the description on Wikipedia, a well designed Quicksort is "…somewhat faster than Merge sort and about two or three times faster than Heapsort."
Many Linux users today have studied Quicksort at some point in the past, through a computer science class or other training scenario, but unless you are working as a professional programmer, chances are it has been a few years since you have taken the time to ponder the elegant Quicksort algorithm. Still, sorting goes on all the time on Linux networks. You don't have to be a full-time app developer to conjure up an occasional script to rank results or order a set of values extracted from a log file. This article explores some of the nuances of the classic Quicksort.
Quicksort ABC
The Quicksort [1] algorithm originated with Tony Hoare [2], who first developed it in 1959 and published it in 1961. Quicksort is what is known as a divide-and-conquer algorithm. One element in the array is chosen to be the pivot element. All elements smaller than the pivot element are then grouped in a sub-array before it, and all elements larger than the pivot element are placed in a sub-array after it. This process is then repeated with the sub-arrays: a pivot element is chosen, with smaller elements placed in a sub-array before and larger elements placed in a sub-array after. After a finite number of steps, the size of the sub-arrays becomes one, and at that point, the whole array has been sorted.
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