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Radix Sort, Part 2
(Up to Basic Computer Science : Lists and Arrays : Sorting Algorithms)

[Part 1] [Part 2]


Still, there are some tradeoffs for Radix Sort that can make it less preferable than other sorts.

The speed of Radix Sort largely depends on the inner basic operations, and if the operations are not efficient enough, Radix Sort can be slower than some other algorithms such as Quick Sort and Merge Sort. These operations include the insert and delete functions of the sublists and the process of isolating the digit you want.

In the example above, the numbers were all of equal length, but many times, this is not the case. If the numbers are not of the same length, then a test is needed to check for additional digits that need sorting. This can be one of the slowest parts of Radix Sort, and it is one of the hardest to make efficient.

Radix Sort can also take up more space than other sorting algorithms, since in addition to the array that will be sorted, you need to have a sublist for each of the possible digits or letters. If you are sorting pure English words, you will need at least 26 different sublists, and if you are sorting alphanumeric words or sentences, you will probably need more than 40 sublists in all!

Since Radix Sort depends on the digits or letters, Radix Sort is also much less flexible than other sorts. For every different type of data, Radix Sort needs to be rewritten, and if the sorting order changes, the sort needs to be rewritten again. In short, Radix Sort takes more time to write, and it is very difficult to write a general purpose Radix Sort that can handle all kinds of data.

For many programs that need a fast sort, Radix Sort is a good choice. Still, there are faster sorts, which is one reason why Radix Sort is not used as much as some other sorts.

If you would like to study a commented version of the actual source code, you can download one from our site:

Download from Source Code Repository: sorts/radix.h

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