Tight Bounds for Monotone Minimal Perfect Hashing

Author: Sepehr Assadi, Martin Farach-Colton, William Kuszmaul.
Conference: The 34th Annual ACM-SIAM Symposium on Discrete Algorithms (SODA'23).
This paper resolved a long standing open question of Belazzougui, Boldi, Pagh, Vigna [BBPV09] on size of monotone minimal perfect hash functions.
Abstract: The monotone minimal perfect hash function (MMPHF) problem is the following indexing problem. Given a set S = {s1, . . . , sn} of n distinct keys from a universe U of size u, create a data structure D that answers the following query: Rank(q) ={rank of q in S q ∈ S and arbitrary answer otherwise}.

Solutions to the MMPHF problem are in widespread use in both theory and practice. The best upper bound known for the problem encodes D in O(n log log log u) bits and per- forms queries in O(log u) time. It has been an open problem to either improve the space upper bound or to show that this somewhat odd looking bound is tight.

In this paper, we show the latter: any data structure (deterministic or randomized) for monotone minimal perfect hashing of any collection of n elements from a universe of size u requires Ω(n · log log log u) expected bits to answer every query correctly. We achieve our lower bound by defining a graph G where the nodes are the possible (u choose n) inputs and where two nodes are adjacent if they cannot share the same D. The size of D is then lower bounded by the log of the chromatic number of G. Finally, we show that the fractional chromatic number (and hence the chromatic number) of G is lower bounded by 2^Ω(n log log log u).
Full version: [arXiv]
Streaming video: [YouTube] (Sepehr @ DIMACS Workshop on Lower Bounds and Frontiers in Data Structures)