Hash table

A hash table applies a hash function to a key and uses the result to select a bucket or candidate slot. Repeating the calculation narrows later lookup. Keys, values, hashing, and equality must remain consistent, since the representation of a key affects whether an existing logical record can be found again.

References: [1]

Distinct keys can produce the same hash result, creating a collision. Implementations may store several entries in one bucket or probe additional slots. Matching a hash identifies candidates, not necessarily the correct key. Concentrated collisions increase work, making collision handling a basic part of the structure rather than an exceptional repair procedure.

References: [2]

As entries accumulate, available capacity and bucket lengths change. Resizing can require relocating existing keys and create a larger individual operation. Growth policies help amortize that cost. Statements about average efficiency therefore depend on load, hashing quality, and assumptions about inputs, including whether adversarially chosen keys must be handled.

References: [1]

Hashing emphasizes equality lookup and generally does not preserve key order. Retrieving one key and retrieving an ordered range can favor different structures. PostgreSQL hash indexes support equality conditions, while B-tree indexes exploit ordering. Comparing these approaches begins with the operations required by the workload rather than one context-free speed measurement.

References: [2]