Tight Bounds for Classical Open Addressing

TL;DR

This paper introduces rainbow hashing, a classical open-addressed hash table supporting high load factors and efficient operations, and proves its optimality, also extending it to dynamic resizing without additional time costs.

Contribution

The paper presents rainbow hashing, achieving near-optimal load factor and operation times, and extends it to dynamic resizing with no extra time overhead.

Findings

Supports load factor up to 1 - ε with O(1) queries

Supports insertions/deletions in O(log log ε^{-1}) expected time

Dynamic resizing maintains performance without additional costs

Abstract

We introduce a classical open-addressed hash table, called rainbow hashing, that supports a load factor of up to $1 - \varepsilon$, while also supporting $O(1)$ expected-time queries, and $O(\log \log \varepsilon^{-1})$ expected-time insertions and deletions. We further prove that this tradeoff curve is optimal: any classical open-addressed hash table that supports load factor $1 - \varepsilon$ must incur $\Omega(\log \log \varepsilon^{-1})$ expected time per operation. Finally, we extend rainbow hashing to the setting where the hash table is dynamically resized over time. Surprisingly, the addition of dynamic resizing does not come at any time cost -- even while maintaining a load factor of $\ge 1 - \varepsilon$ at all times, we can support $O(1)$ queries and $O(\log \log \varepsilon^{-1})$ updates. Prior to our work, achieving any time bounds of the form $o(\varepsilon^{-1})$ for all of insertions, deletions, and queries simultaneously remained an open question.