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In computer science, a hash table is a data structure that implements an associative array, also called a dictionary or simply map; an associative array is an abstract data type that maps keys to values. [3] 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 ...
Some collections maintain a linear ordering of items – with access to one or both ends. The data structure implementing such a collection need not be linear. For example, a priority queue is often implemented as a heap, which is a kind of tree. Notable linear collections include: list; stack; queue; priority queue; double-ended queue
Collection implementations in pre-JDK 1.2 versions of the Java platform included few data structure classes, but did not contain a collections framework. [4] The standard methods for grouping Java objects were via the array, the Vector, and the Hashtable classes, which unfortunately were not easy to extend, and did not implement a standard member interface.
An invocation of gethash actually returns two values: the value or substitute value for the key and a boolean indicator, returning T if the hash table contains the key and NIL to signal its absence. ( multiple-value-bind ( value contains-key ) ( gethash "Sally Smart" phone-book ) ( if contains-key ( format T "~&The associated value is: ~s ...
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.
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.
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 ...
It is a similar idea to the separate chaining methods, although it does not technically involve the chained lists. In this case, instead of chained lists, the hash values are represented in a contiguous list of items. This is better suited for string hash tables and the use for numeric values is still unknown. [10]