Please note that the content of this book primarily consists of articles available from Wikipedia or other free sources online. Pages: 41. Chapters: Hash table, HMAC, Collision, Rabin-Karp string search algorithm, Bloom filter, Cryptographic hash function, Universal hashing, Comparison of cryptographic hash functions, Extendible hashing, Cuckoo hashing, Hash join, Open addressing, Hash tree, Coalesced hashing, Java hashCode(), Hopscotch hashing, Linear hashing, Perfect hash function, Consistent hashing, SUHA, Koorde, Quadratic probing, Hash list, Hash consing, Linear probing, Index mapping, Double hashing, Dynamic perfect hashing, Hash array mapped trie, Primary clustering, Lazy deletion, 2-choice hashing, Dirhash, Stable hashing. Excerpt: In computer science, a hash table or hash map is a data structure that uses a hash function to map identifying values, known as keys (e.g., a person's name), to their associated values (e.g., their telephone number). Thus, a hash table implements an associative array. The hash function is used to transform the key into the index (the hash) of an array element (the slot or bucket) where the corresponding value is to be sought. Ideally, the hash function should map each possible key to a unique slot index, but this ideal is rarely achievable in practice (unless the hash keys are fixed; i.e. new entries are never added to the table after it is created). Instead, most hash table designs assume that hash collisions-different keys that map to the same hash value-will occur and must be accommodated in some way. In a well-dimensioned hash table, the average cost (number of instructions) for each lookup is independent of the number of elements stored in the table. Many hash table designs also allow arbitrary insertions and deletions of key-value pairs, at constant average (indeed, amortized) cost per operation. In many situations, hash tables turn out to be more efficient than search trees or any other table lookup structure. For this ...
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