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In the programming language C++, unordered associative containers are a group of class templates in the C++ Standard Library that implement hash table variants. Being templates , they can be used to store arbitrary elements, such as integers or custom classes.
In a well-dimensioned hash table, the average time complexity for each lookup is independent of the number of elements stored in the table. Many hash table designs also allow arbitrary insertions and deletions of key–value pairs, at amortized constant average cost per operation. [4] [5] [6] Hashing is an example of a space-time tradeoff.
similar to a set, multiset, map, or multimap, respectively, but implemented using a hash table; keys are not ordered, but a hash function must exist for the key type. These types were left out of the C++ standard; similar containers were standardized in C++11, but with different names (unordered_set and unordered_map). Other types of containers ...
This technique is simple and fast, with each dictionary operation taking constant time. However, the space requirement for this structure is the size of the entire keyspace, making it impractical unless the keyspace is small. [5] The two major approaches for implementing dictionaries are a hash table or a search tree. [3] [4] [5] [6]
A hash array mapped trie [1] (HAMT) is an implementation of an associative array that combines the characteristics of a hash table and an array mapped trie. [1] It is a refined version of the more general notion of a hash tree.
Linear hashing (LH) is a dynamic data structure which implements a hash table and grows or shrinks one bucket at a time. It was invented by Witold Litwin in 1980. [1] [2] It has been analyzed by Baeza-Yates and Soza-Pollman. [3]
A concurrent hash table or concurrent hash map is an implementation of hash tables allowing concurrent access by multiple threads using a hash function. [ 1 ] [ 2 ] Concurrent hash tables represent a key concurrent data structure for use in concurrent computing which allow multiple threads to more efficiently cooperate for a computation among ...
Clients C 1 and C 4 independently pick the same random subset of four sites {S 2, S 5, S 6, S 10} from among the twelve options S 1, S 2, ..., S 12, for placing replicas or shares of object O. Rendezvous or highest random weight (HRW) hashing [ 1 ] [ 2 ] is an algorithm that allows clients to achieve distributed agreement on a set of k ...