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Concept
Cuckoo hashing
Résumé
Cuckoo hashing is a scheme in computer programming for resolving hash collisions of values of hash functions in a table, with worst-case constant lookup time. The name derives from the behavior of some species of cuckoo, where the cuckoo chick pushes the other eggs or young out of the nest when it hatches in a variation of the behavior referred to as brood parasitism; analogously, inserting a new key into a cuckoo hashing table may push an older key to a different location in the table.
Cuckoo hashing was first described by Rasmus Pagh and Flemming Friche Rodler in a 2001 conference paper. The paper was awarded the European Symposium on Algorithms Test-of-Time award in 2020.
Cuckoo hashing is a form of open addressing in which each non-empty cell of a hash table contains a key or key–value pair. A hash function is used to determine the location for each key, and its presence in the table (or the value associated with it) can be found by examining that cell of the table. However, open addressing suffers from collisions, which happens when more than one key is mapped to the same cell.
The basic idea of cuckoo hashing is to resolve collisions by using two hash functions instead of only one. This provides two possible locations in the hash table for each key. In one of the commonly used variants of the algorithm, the hash table is split into two smaller tables of equal size, and each hash function provides an index into one of these two tables. It is also possible for both hash functions to provide indexes into a single table.
Cuckoo hashing uses two hash tables, and . Assuming is the length of each table, the hash functions for the two tables is defined as, and where be the key and be the set whose keys are stored in of or of . The lookup operation is as follows:
The logical or () denotes that, the value of the key is found in either or , which is in worst case.
Deletion is performed in since there isn't involvement of probing—not considering the cost of shrinking operation if table is too sparse.
Source officielle
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