Apache-2.0 licensed and maintained by Karl Ostmo
This version can be pinned in stack with:perfect-hash-generator-1.0.0@sha256:0a0c71a4ff572db04b49e8d0083472f9b2395276f066419f0b6eaa5bce75a69a,5516

Module documentation for 1.0.0

A perfect hash function for a set S is a hash function that maps distinct elements in S to a set of integers, with no collisions. A minimal perfect hash function is a perfect hash function that maps n keys to n consecutive integers, e.g. the numbers from 0 to n-1.

In contrast with the PerfectHash package, which is a binding to a C-based library, this package is a fully-native Haskell implementation.

It is intended primarily for generating C code for embedded applications (compare to gperf). The output of this tool is a pair of arrays that can be included in generated C code for allocation-free hash tables.

Though conceivably this data structure could be used directly in Haskell applications as a read-only hash table, it is not recommened, as lookups are about 10x slower than HashMap.

This implementation was adapted from Steve Hanov's Blog.

Usage

The library is written generically to hash both strings and raw integers according to the FNV-1a algorithm. Integers are split by octets before hashing.

import Data.PerfectHash.Construction (createMinimalPerfectHash)
import qualified Data.Map as Map

tuples = [
   (1000, 1)
 , (5555, 2)
 , (9876, 3)
 ]

lookup_table = createMinimalPerfectHash $ Map.fromList tuples

Generation of C code based on the arrays in lookup_table is left as an exercise to the reader. Algorithm documentation in the Data.PerfectHash.Hashing and Data.PerfectHash.Lookup modules will be helpful.

Demo

See the hash-perfectly-strings-demo and hash-perfectly-ints-demo, as well as the test suite, for working examples.

$ stack build
$ stack exec hash-perfectly-strings-demo

Changes

0.2.0.1 (Feb. 2018)

  • Fixed a foldr vs. foldl bug with algorithmic implications

1.0.0 (June 2022)

  • Changed input type from HashMap to Map
  • Removed superfluous internal map lookups by threading values alongside keys throughout the algorithm
  • Used newtypes internally for algorithmic clarity