Shifting Hash Table: An Efficient Hash Table with Delicate Summary

Jie Jiang, Yibo Yan, Mengyu Zhang, Binchao Yin, Yumeng Jiang, Tong Yang, Xiaoming Li, Tengjiao Wang
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Abstract

Hash tables have been broadly used in many security applications. These applications require fast query speed and high memory efficiency. However, the query speed degrades when hash collisions happen. The design goal of this paper is to achieve high load factor as well as fast query at the same time. In this paper, we propose a novel hashing scheme, namely the Shifting Hash Table (SHT), which consists of two parts. The first part is an enhanced version of the Bloom filter checking which subtable(s) may contain the incoming items, and the second part contains a cuckoo hashing based hash table which stores the key-value pairs. The key technique of this paper is that we divide items into two categories: at-home and abroad. We only insert the second kind of items (abroad) into the Bloom filter, thus the memory usage of the filter is significantly reduced. We conducted extensive experiments and the results show that SHT significantly outperforms the state-of-the-art. Specifically, SHT can query an item using on average less than 1.05 bucket probes and even using 1 bit per entry in the fast memory, and achieve a high load factor which is 95% at the same time.
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移动哈希表:一个具有精致摘要的高效哈希表
哈希表在许多安全应用中得到了广泛的应用。这些应用程序需要快速的查询速度和高内存效率。但是,当发生哈希冲突时,查询速度会降低。本文的设计目标是在实现高负载系数的同时实现快速查询。在本文中,我们提出了一种新的哈希方案,即移位哈希表(SHT),它由两部分组成。第一部分是Bloom过滤器的增强版本,检查哪些子表可能包含传入的项目,第二部分包含基于布谷鸟哈希的哈希表,该哈希表存储键值对。本文的关键技术是我们将项目分为两类:国内和国外。我们只将第二类项目(国外)插入到Bloom过滤器中,因此过滤器的内存使用显著减少。我们进行了大量的实验,结果表明,SHT明显优于最先进的技术。具体来说,SHT可以使用平均少于1.05个桶探测来查询一个项目,甚至在快速内存中每个条目使用1位,同时实现高达95%的高负载系数。
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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