BBHash is a simple library for building minimal perfect hash function. It is designed to handle large scale datasets. The function is just a little bit larger than other state-of-the-art libraries, it takes approximately 3 bits / elements (compared to 2.62 bits/elem for the emphf lib), but construction is faster and does not require additional memory.
It is easy to include in other projects (just include a single .h file) and has no dependencies.
A preprint paper is available on arXiv: https://arxiv.org/abs/1702.03154
Here is a simple example showing how to build and query a mphf with input keys in a std::vector<u_int64_t> . BBHash is mainly designed for de-duplicated input. Keys can be read from a disk file, or from some user-defined iterator.
#include "BooPHF.h"
//tells bbhash to use included hash function working on u_int64_t input keys :
typedef boomphf::SingleHashFunctor<u_int64_t> hasher_t;
typedef boomphf::mphf< u_int64_t, hasher_t > boophf_t;
std::vector<u_int64_t> input_keys;
//
... fill the input_keys vector
//build the mphf
boophf_t * bphf = new boomphf::mphf<u_int64_t,hasher_t>(input_keys.size(),input_keys,nthreads);
//query the mphf :
uint64_t idx = bphf->lookup(input_keys[0]);
The master branch works with Plain Old Data types only (POD). To work with other types, use the "alltypes" branch (it runs slighlty slower). The alltypes branch includes a sample code with strings. The "internal_hash" branch allows to work with types that do not support copy or assignment operators, at the expense of using 128bits/key in I/O operations regardless of the actual key size. Thus, if your keys are 64 bits integers, "internal_hash" will do twice more I/Os. But if your keys are longer than 128 bits, then "internal_hash" branch will be faster than the master branch.
A sample usage is provided in file example.cpp, compile and run with: ( params are nb_elements nb_threads)
make
./example 100000000 1
File Bootest.cpp contains more options, use ./Bootest with -check to check correctness of the hash function, and -bench to benchmark lookup performance.
Here is a sample output :
./Bootest 100000000 8 1.0 -check -bench
key file generated
Construct a BooPHF with 100000000 elements
for info, total work write each : 3.718 total work inram from level 8 : 9.408 total work raw : 25.000
[Building BooPHF] 100 % elapsed: 0 min 10 sec remaining: 0 min 0 sec
BooPHF constructed perfect hash for 100000000 keys in 10.25s
Bitarray 305808384 bits (100.00 %) (array + ranks )
Last level hash 0 bits (0.00 %) (nb in last level hash 0)
boophf bits/elem : 3.058084
--- boophf working correctly ---
bench lookups sample size 10000000
BBhash bench lookups average 243.84 ns +- stddev 13.01 % (fingerprint 4999580507664480)
Guillaume Rizk, Antoine Limasset, Rayan Chikhi