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An object is similar to a map—both let you set keys to values, retrieve those values, delete keys, and detect whether a value is stored at a key. For this reason (and because there were no built-in alternatives), objects historically have been used as maps.
Any existing mapping is overwritten. The arguments to this operation are the key and the value. Remove or delete remove a (,) pair from the collection, unmapping a given key from its value. The argument to this operation is the key. Lookup, find, or get find the value (if any) that is bound to a given key.
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.
Example of a web form with name-value pairs. A name–value pair, also called an attribute–value pair, key–value pair, or field–value pair, is a fundamental data representation in computing systems and applications. Designers often desire an open-ended data structure that allows for future extension without modifying existing code or data.
Scramble the bits of the key so that the resulting values are uniformly distributed over the keyspace, and; Map the key values into ones less than or equal to the size of the table. A good hash function satisfies two basic properties: it should be very fast to compute, and it should minimize duplication of output values .
STORE — Stores a (key, value) pair in one node. FIND_NODE — The recipient of the request will return the k nodes in its own buckets that are the closest ones to the requested key. FIND_VALUE — Same as FIND_NODE, but if the recipient of the request has the requested key in its store, it will return the corresponding value.
The sequence of values is then sorted and compressed using Golomb coding (or some other compression technique) to occupy a space close to (/) bits. To query the Bloom filter for a given key, it will suffice to check if its corresponding value is stored in the Bloom filter.
pull() { highest = list.get_first_element() foreach node in list { if highest.priority < node.priority { highest = node } } list.remove(highest) return highest } In another case, one can keep all the elements in a priority sorted list ( O (n) insertion sort time), whenever the highest-priority element is requested, the first one in the list can ...