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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.
Although std::map is typically implemented using a self-balancing binary search tree, C++11 defines a second map called std::unordered_map, which has the algorithmic characteristics of a hash table. This is a common vendor extension to the Standard Template Library (STL) as well, usually called hash_map , available from such implementations as ...
A perfect hash function for the four names shown A minimal perfect hash function for the four names shown. In computer science, a perfect hash function h for a set S is a hash function that maps distinct elements in S to a set of m integers, with no collisions. In mathematical terms, it is an injective function.
The basic idea behind a hash table is that accessing an element of an array via its index is a simple, constant-time operation. Therefore, the average overhead of an operation for a hash table is only the computation of the key's hash, combined with accessing the corresponding bucket within the array.
A hash function is used to map each key into the cell of T where that key should be stored, typically scrambling the keys so that keys with similar values are not placed near each other in the table. A hash collision occurs when the hash function maps a key into a cell that is already occupied by a different key. Linear probing is a strategy ...
A map, sometimes referred to as a dictionary, consists of a key/value pair. The key is used to order the sequence, and the value is somehow associated with that key. For example, a map might contain keys representing every unique word in a text and values representing the number of times that word appears in the text.
Additionally, concurrent hash maps are provided which build upon the concurrent unordered map and further allow concurrent erasure and contain built-in locking. [13] growt provides concurrent growing hash tables for C++ on the basis of the so-called folklore implementation. Based on this non-growing implementation, a variety of different ...