A Judy array is a data structure that has high performance, low memory usage and implements an associative array. Unlike normal arrays, Judy arrays may be sparse, that is, they may have large ranges of unassigned indices.
In computer science and software engineering, a Judy array is a data structure that has high performance, low memory usage and implements an associative array. Unlike normal arrays, Judy arrays may be sparse, that is, they may have large ranges of unassigned indices. They can be used for storing and looking up values using integer or string keys. The key benefits of using a Judy array is its scalability, high performance, memory efficiency and ease of use.
Judy arrays are both speed- and memory-efficient[clarification needed], with no tuning or configuration required and therefore they can sometime replace common in-memory dictionary implementations (like red-black trees or hash tables) and work better with very large data sets[dubious – discuss][citation needed].
Roughly speaking, Judy arrays are highly-optimised 256-ary radix trees. To make memory consumption small, Judy arrays use over 20 different compression techniques to compress trie nodes.
The Judy array was invented by Douglas Baskins and named after his sister.
Wikipedia: http://en.wikipedia.org/wiki/Judy_array
