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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.
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 ...
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. [3] [4] [5] Hashing is an example of a space-time tradeoff.
However, hash tables have a much better average-case time complexity than self-balancing binary search trees of O(1), and their worst-case performance is highly unlikely when a good hash function is used. A self-balancing binary search tree can be used to implement the buckets for a hash table that uses separate chaining.
For example, if the input is 123 456 789 and the hash table size 10 000, then squaring the key produces 15 241 578 750 190 521, so the hash code is taken as the middle 4 digits of the 17-digit number (ignoring the high digit) 8750. The mid-squares method produces a reasonable hash code if there is not a lot of leading or trailing zeros in the key.
C++'s Standard Template Library provides the multimap container for the sorted multimap using a self-balancing binary search tree, [1] and SGI's STL extension provides the hash_multimap container, which implements a multimap using a hash table. [2] As of C++11, the Standard Template Library provides the unordered_multimap for the unordered ...
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 ...
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).