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[3] [4] [5] Hashing is an example of a space-time tradeoff. If memory is infinite, the entire key can be used directly as an index to locate its value with a single memory access. On the other hand, if infinite time is available, values can be stored without regard for their keys, and a binary search or linear search can be used to retrieve the ...
Object pooling can offer a significant performance boost in situations where the cost of initializing a class instance is high and the rate of instantiation and destruction of a class is high – in this case objects can frequently be reused, and each reuse saves a significant amount of time.
Keys are unique identifiers which map to particular values, which in turn can be anything from addresses, to documents, to arbitrary data. [2] Responsibility for maintaining the mapping from keys to values is distributed among the nodes, in such a way that a change in the set of participants causes a minimal amount of disruption.
Values are primarily retrieved using the indexer (which throws an exception if the key does not exist) and the TryGetValue method, which has an output parameter for the sought value and a Boolean return-value indicating whether the key was found.
SipHash computes a 64-bit message authentication code from a variable-length message and 128-bit secret key. It was designed to be efficient even for short inputs, with performance comparable to non-cryptographic hash functions, such as CityHash; [4]: 496 [2] this can be used to prevent denial-of-service attacks against hash tables ("hash flooding"), [5] or to authenticate network packets.
find the value (if any) that is bound to a given key. The argument to this operation is the key, and the value is returned from the operation. If no value is found, some lookup functions raise an exception, while others return a default value (such as zero, null, or a specific value passed to the constructor).
A universal hashing scheme is a randomized algorithm that selects a hash function h among a family of such functions, in such a way that the probability of a collision of any two distinct keys is 1/m, where m is the number of distinct hash values desired—independently of the two keys. Universal hashing ensures (in a probabilistic sense) that ...
Haskell implementation is available as a package [9] and on GitHub. [10] Standalone Java implementations are available on GitHub for Java 17, Java 11 and Java 8 [11] as well for Java 6. [12] CL-CTRIE is a Common Lisp implementation available on GitHub. [13] An insert-only Ctrie variant has been used for tabling in Prolog programs. [14]