Tight Bounds for Classical Open Addressing

Michael A. Bender, William Kuszmaul, Renfei Zhou
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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.
经典开放式寻址的严格界限
我们引入了一种称为彩虹散列(rainbow hashing)的经典开放寻址哈希表,它支持高达 1 - \varepsilon$ 的负载因子,同时还支持 $O(1)$ 的预期时间查询,以及 $O(\log \log \varepsilon^{-1})$ 的预期时间插入和删除。我们进一步证明,这种权衡曲线是最优的:任何支持负载系数为 1 -\varepsilon$ 的经典开放式散列表每次操作都必须花费 $\Omega(\log \log \varepsilon^{-1})$ 的预期时间。最后,我们将彩虹散列扩展到散列表随时间动态调整大小的情况。令人惊讶的是,增加动态调整大小并不会带来任何时间成本--即使在任何时候都保持 $\ge1 - \varepsilon$ 的负载系数,我们也能支持 $O(1)$ 查询和 $O(\log \log\varepsilon^{-1})$ 更新。在我们的工作之前,同时实现所有插入、删除和查询的任何时间界限为 $o(\varepsilon^{-1})$,仍然是一个悬而未决的问题。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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