Skip to content
/ emphf Public

An efficient external-memory algorithm for the construction of minimal perfect hash functions

License

Notifications You must be signed in to change notification settings

ot/emphf

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

3 Commits
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

Repository files navigation

emphf

emphf is a minimal perfect hashing library for large-scale key sets focused on speed and low memory usage. A minimal perfect hash function (MPHF) is a data structure that maps injectively a static set of strings of size n to the integer set [0, n-1]. The overall space usage of the MPHFs generated with emphf is 2.61 n bits plus a small constant factor.

The algorithms used in this library are described in the paper Cache-Oblivious Peeling of Random Hypergraphs by Djamal Belazzougui, Paolo Boldi, Giuseppe Ottaviano, Rossano Venturini, and Sebastiano Vigna.

All the algorithms implemented here construct a MPHF for a given key set using a standard scheme based on the Majewski–Wormald–Havas–Czech (MWHC) construction, that is based on finding a peeling order of a random 3-hypergraph.

  • compute_mphf_seq computes the peeling order using the standard in-memory linear-time peeling algorithm, implemented with the xor-trick described in the paper. This is the fastest MPHF construction implementation that we know of.

  • compute_mphf_scan_mmap computes the peeling order using the new algorithm proposed in the paper, using an mmapped temporary file for its data structure, thus in an external-memory setting.

  • compute_mphf_hem uses a technique described in F. C. Botelho, R. Pagh, and N. Ziviani, “Practical perfect hashing in nearly optimal space”, that splits the key sets in bucket that are small enough that the perfect hash function is easy to compute in memory for each bucket. While the construction is faster than by using compute_mphf_scan_mmap, the resulting data structure takes slightly more space and it is slightly slower.

compute_mphf_seq and compute_mphf_scan_mmap construct the same data structure, but the second should be used when the space needed to construct the MPHF does not fit in main memory. The obtained MPHF data structures can perform lookups significantly faster than other implementations using the same algorithm (see the paper for details).

The script test_all.py executes all the algorithms on a given file (or the standard UNIX dictionary if none is provided) and checks that the generated hash function is indeed minimal and perfect.

The project uses CMake. To build it on Unix systems it should be sufficient to do the following:

$ cmake .
$ make

About

An efficient external-memory algorithm for the construction of minimal perfect hash functions

Resources

License

Stars

Watchers

Forks

Packages

No packages published