Year: 2024
Type: conference-paper
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$O\left({\log \,\log {\varepsilon ^{ - 1}}} \right)$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$\Omega \left({\log \,log{\varepsilon ^{ - 1}}} \right)$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$\geq 1-\varepsilon$at all times, we can support$O(1)$queries and$O\left({\log \,\log {\varepsilon ^{ - 1}}} \right)$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.
Institutions: Stony Brook University, Carnegie Mellon University
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
Funder: National Science Foundation
OpenAlex ID: W4404848173