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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.
A hash table uses a hash function to compute an index, also called a hash code, into an array of buckets or slots, from which the desired value can be found. During lookup, the key is hashed and the resulting hash indicates where the corresponding value is stored. A map implemented by a hash table is called a hash map.
The most frequently used general-purpose implementation of an associative array is with a hash table: an array combined with a hash function that separates each key into a separate "bucket" of the array. The basic idea behind a hash table is that accessing an element of an array via its index is a simple, constant-time operation.
The output is a hash code used to index a hash table holding the data or records, or pointers to them. A hash function may be considered to perform three functions: Convert variable-length keys into fixed-length (usually machine-word -length or less) values, by folding them by words or other units using a parity-preserving operator like ADD or XOR,
For any fixed set of keys, using a universal family guarantees the following properties.. For any fixed in , the expected number of keys in the bin () is /.When implementing hash tables by chaining, this number is proportional to the expected running time of an operation involving the key (for example a query, insertion or deletion).
Linear probing is a component of open addressing schemes for using a hash table to solve the dictionary problem.In the dictionary problem, a data structure should maintain a collection of key–value pairs subject to operations that insert or delete pairs from the collection or that search for the value associated with a given key.
Ultimately the resulting performance of a concurrent hash table depends on a variety of factors based upon its desired application. When choosing the implementation, it is important to determine the necessary amount of generality, contention handling strategies and some thoughts on whether the size of the desired table can be determined in ...
Few hash table algorithms support worst-case O(1) lookup time (constant lookup time even in the worst case). The few that do include: perfect hashing; dynamic perfect hashing; cuckoo hashing; hopscotch hashing; and extendible hashing. [13]: 42–69 A simple alternative to perfect hashing, which also allows dynamic updates, is cuckoo hashing ...