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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.
In the table below, the column "ISO 8859-1" shows how the file signature appears when interpreted as text in the common ISO 8859-1 encoding, with unprintable characters represented as the control code abbreviation or symbol, or codepage 1252 character where available, or a box otherwise. In some cases the space character is shown as ␠.
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,
It is also well suited for implementing a concurrent hash table. Hopscotch hashing was introduced by Maurice Herlihy, Nir Shavit and Moran Tzafrir in 2008. [1] The name is derived from the sequence of hops that characterize the table's insertion algorithm (see Hopscotch for the children's game). The algorithm uses a single array of n buckets.
Often, an additional hash of the hash list itself (a top hash, also called root hash or master hash) is used.Before downloading a file on a p2p network, in most cases the top hash is acquired from a trusted source, for instance a friend or a web site that is known to have good recommendations of files to download.
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 ...
For a user's action to trigger the execution of server-side code, for example, a developer working with classic ASP must explicitly cause the user's browser to make a request back to the webserver. Server-side scripts are completely processed by the servers instead of clients.
The term "consistent hashing" was introduced by David Karger et al. at MIT for use in distributed caching, particularly for the web. [4] This academic paper from 1997 in Symposium on Theory of Computing introduced the term "consistent hashing" as a way of distributing requests among a changing population of web servers. [5]