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Not to be confused with Hash list or Hash tree. Ideally, the hash function will assign each key to a unique bucket, but most hash table designs employ an imperfect hash function, which might cause hash collisions where the hash function generates the same index for more than one key. Such collisions must be accommodated in some way. In many situations, hash tables turn out to be on average more efficient than search trees or any other table lookup structure. In the case that the array size is a power of two, the remainder operation is reduced to masking, which improves speed, but can increase problems with a poor hash function.
Then a new larger table is allocated, mIT Computer Science and Artificial Intelligence Laboratory. Hash tables in general exhibit poor locality of reference, rather than the current number. Another way to decrease the cost of table resizing is to choose a hash function in such a way that the hashes of most values do not change when the table is resized. Usually erasing the old item that is currently stored in the table and overwriting it with the new item, and inserted into the new table.
A good hash function and implementation algorithm are essential for good hash table performance, but may be difficult to achieve. A basic requirement is that the function should provide a uniform distribution of hash values. A non-uniform distribution increases the number of collisions and the cost of resolving them. Uniformity is sometimes difficult to ensure by design, but may be evaluated empirically using statistical tests, e. The distribution needs to be uniform only for table sizes that occur in the application.