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An associative container uses an associative array, map, or dictionary, composed of key-value pairs, such that each key appears at most once in the container. The key is used to find the value, the object, if it is stored in the container. Associative containers are used in programming languages as class templates.
A hash variable is marked by a % sigil, to distinguish it from scalar, array, and other data types. A hash literal is a key-value list, with the preferred form using Perl's => token, which is semantically mostly identical to the comma and makes the key-value association clearer:
In computer science, an associative array, map, symbol table, or dictionary is an abstract data type that stores a collection of (key, value) pairs, such that each possible key appears at most once in the collection. In mathematical terms, an associative array is a function with finite domain. [1] It supports 'lookup', 'remove', and 'insert ...
An associative array stores a set of (key, value) pairs and allows insertion, deletion, and lookup (search), with the constraint of unique keys. In the hash table implementation of associative arrays, an array A {\displaystyle A} of length m {\displaystyle m} is partially filled with n {\displaystyle n} elements, where m ≥ n {\displaystyle m ...
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.
Lucene uses skip lists to search delta-encoded posting lists in logarithmic time. [citation needed] The "QMap" key/value dictionary (up to Qt 4) template class of Qt is implemented with skip lists. [13] Redis, an ANSI-C open-source persistent key/value store for Posix systems, uses skip lists in its implementation of ordered sets. [14]
For a trivial hash function lookup, the unsigned raw data value is used directly as an index to a one-dimensional table to extract a result. For small ranges, this can be amongst the fastest lookup, even exceeding binary search speed with zero branches and executing in constant time. [6]
In certain databases the key values may be points in some multi-dimensional space. For example, the key may be a geographic position ( latitude and longitude ) on the Earth . In that case, common kinds of queries are "find the record with a key closest to a given point v ", or "find all items whose key lies at a given distance from v ", or ...