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Engineering Minimal k-Perfect Hash Functions

Authors Stefan Hermann , Sebastian Kirmayer , Hans-Peter Lehmann , Peter Sanders , Stefan Walzer

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ACM Subject Classification
  • Theory of computation → Data compression
  • Theory of computation → Bloom filters and hashing
  • Information systems → Point lookups
Keywords
  • Compressed Data Structures
  • Perfect Hashing

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Abstract

Given a set S of n keys, a k-perfect hash function (kPHF) is a data structure that maps the keys to the first m integers, where each output integer can be hit by at most k input keys. When m = ⌈n/k⌉, the resulting function is called a minimal k-perfect hash function (MkPHF). Applications of kPHFs can be found in external memory data structures or to create efficient 1-perfect hash functions, which in turn have a wide range of applications from databases to bioinformatics.
Several papers from the 1980s look at external memory data structures with small internal memory indexes. However, actual k-perfect hash functions are surprisingly rare, and the area has not seen a lot of research recently. At the same time, recent research in 1-perfect hashing shows that there is a lack of efficient kPHFs. In this paper, we revive the area of k-perfect hashing, presenting four new constructions. Our implementations simultaneously dominate older approaches in space consumption, construction time, and query time. We see this paper as a possible starting point of an active line of research, similar to the area of 1-perfect hashing.

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Stefan Hermann, Sebastian Kirmayer, Hans-Peter Lehmann, Peter Sanders, and Stefan Walzer. Engineering Minimal k-Perfect Hash Functions. In 33rd Annual European Symposium on Algorithms (ESA 2025). Leibniz International Proceedings in Informatics (LIPIcs), Volume 351, pp. 99:1-99:18, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025) https://doi.org/10.4230/LIPIcs.ESA.2025.99

Author Details

Stefan Hermann
  • Karlsruhe Institute of Technology, Germany
Sebastian Kirmayer
  • Karlsruhe Institute of Technology, Germany
Hans-Peter Lehmann
  • Karlsruhe Institute of Technology, Germany
Peter Sanders
  • Karlsruhe Institute of Technology, Germany
Stefan Walzer
  • Karlsruhe Institute of Technology, Germany

Funding

This project has received funding from the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation programme (grant agreement No. 882500). This work was also supported by funding from the pilot program Core Informatics at KIT (KiKIT) of the Helmholtz Association (HGF).

Acknowledgements

This paper is based on and has text overlaps with the bachelor’s thesis of Sebastian Kirmayer [Kirmayer, 2024].

Supplementary Materials

References

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