Fast and scalable minimal perfect hashing for massive key sets

Antoine Limasset 1 Guillaume Rizk 1 Rayan Chikhi 2 Pierre Peterlongo 1
1 GenScale - Scalable, Optimized and Parallel Algorithms for Genomics
Inria Rennes – Bretagne Atlantique , IRISA_D7 - GESTION DES DONNÉES ET DE LA CONNAISSANCE
2 BONSAI - Bioinformatics and Sequence Analysis
Université de Lille, Sciences et Technologies, Inria Lille - Nord Europe, CRIStAL - Centre de Recherche en Informatique, Signal et Automatique de Lille (CRIStAL) - UMR 9189, CNRS - Centre National de la Recherche Scientifique
Abstract : Minimal perfect hash functions provide space-efficient and collision-free hashing on static sets. Existing algorithms and implementations that build such functions have practical limitations on the number of input elements they can process, due to high construction time, RAM or external memory usage. We revisit a simple algorithm and show that it is highly competitive with the state of the art, especially in terms of construction time and memory usage. We provide a parallel C++ implementation called BBhash. It is capable of creating a minimal perfect hash function of 10^10 elements in less than 7 minutes using 8 threads and 5 GB of memory, and the resulting function uses 3.7 bits/element. To the best of our knowledge, this is also the first implementation that has been successfully tested on an input of cardinality 10^12. Source code: https://github.com/rizkg/BBHash
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  • HAL Id : hal-01566246, version 1
  • ARXIV : 1702.03154

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Antoine Limasset, Guillaume Rizk, Rayan Chikhi, Pierre Peterlongo. Fast and scalable minimal perfect hashing for massive key sets. 16th International Symposium on Experimental Algorithms, Jun 2017, London, United Kingdom. pp.1 - 11. ⟨hal-01566246⟩

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