Locally Uniform Hashing
Ioana O. Bercea, Lorenzo Beretta, Jonas Klausen, Jakob B{\ae}k Tejs, Houen, Mikkel Thorup

TL;DR
This paper introduces tornado tabulation hashing, a practical and fast hashing method with strong theoretical guarantees that performs nearly as well as fully-random hash functions in various algorithms.
Contribution
The paper presents tornado tabulation hashing, a new simple, fast hash function with provable local randomness properties applicable to multiple algorithms.
Findings
Performs almost as well as fully-random hashing in diverse algorithms.
Provides an efficient method for achieving fully-random hashing on fixed key sets.
Enables more efficient implementations of existing hashing techniques.
Abstract
Hashing is a common technique used in data processing, with a strong impact on the time and resources spent on computation. Hashing also affects the applicability of theoretical results that often assume access to (unrealistic) uniform/fully-random hash functions. In this paper, we are concerned with designing hash functions that are practical and come with strong theoretical guarantees on their performance. To this end, we present tornado tabulation hashing, which is simple, fast, and exhibits a certain full, local randomness property that provably makes diverse algorithms perform almost as if (abstract) fully-random hashing was used. For example, this includes classic linear probing, the widely used HyperLogLog algorithm of Flajolet, Fusy, Gandouet, Meunier [AOFA 97] for counting distinct elements, and the one-permutation hashing of Li, Owen, and Zhang [NIPS 12] for large-scale…
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Taxonomy
TopicsAlgorithms and Data Compression · Advanced Image and Video Retrieval Techniques · Cryptography and Data Security
