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Fast and Simple Compact Hashing via Bucketing

Authors Dominik Köppl , Simon J. Puglisi , Rajeev Raman

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Author Details

Dominik Köppl
  • Department of Informatics, Kyushu University, Japan Society for Promotion of Science (JSPS), Fukuoka, Japan
Simon J. Puglisi
  • Helsinki Institute for Information Technology, Espoo, Finland
  • Department of Computer Science, University of Helsinki, Finland
Rajeev Raman
  • School of Informatics, University of Leicester, United Kingdom

Funding

  • Köppl, Dominik: JSPS KAKENHI Grant Number JP18F18120.
  • Puglisi, Simon J.: Academy of Finland Grant 319454.

Acknowledgements

We thank Marvin Löbel for the implementations of the Bonsai tables with the additional support of a sparse table layout.

Cite AsGet BibTex

Dominik Köppl, Simon J. Puglisi, and Rajeev Raman. Fast and Simple Compact Hashing via Bucketing. In 18th International Symposium on Experimental Algorithms (SEA 2020). Leibniz International Proceedings in Informatics (LIPIcs), Volume 160, pp. 7:1-7:14, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2020)
https://doi.org/10.4230/LIPIcs.SEA.2020.7

Abstract

Compact hash tables store a set S of n key-value pairs, where the keys are from the universe U = {0,…,u-1}, and the values are v-bit integers, in close to B(u, n) + nv bits of space, where {b(u, n)} = log₂ binom(u,n) is the information-theoretic lower bound for representing the set of keys in S, and support operations insert, delete and lookup on S. Compact hash tables have received significant attention in recent years, and approaches dating back to Cleary [IEEE T. Comput, 1984], as well as more recent ones have been implemented and used in a number of applications. However, the wins on space usage of these approaches are outweighed by their slowness relative to conventional hash tables. In this paper, we demonstrate that compact hash tables based upon a simple idea of bucketing practically outperform existing compact hash table implementations in terms of memory usage and construction time, and existing fast hash table implementations in terms of memory usage (and sometimes also in terms of construction time). A related notion is that of a compact Hash ID map, which stores a set Ŝ of n keys from U, and implicitly associates each key in Ŝ with a unique value (its ID), chosen by the data structure itself, which is an integer of magnitude O(n), and supports inserts and lookups on Ŝ, while using close to B(u,n) bits. One of our approaches is suitable for use as a compact Hash ID map.

Subject Classification

ACM Subject Classification
  • Theory of computation → Sorting and searching
Keywords
  • compact hashing
  • hash table
  • separate chaining

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References

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