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DxHash: A Scalable Consistent Hash Based on the Pseudo-Random Sequence
arXiv - CS - Networking and Internet Architecture Pub Date : 2021-07-16 , DOI: arxiv-2107.07930
Chaos Dong, Fang Wang

Consistent hasing has played a fundamental role as a data router and a load balancer in various fields, such as distributed database, cloud infrastructure, and peer-to-peer network. However, the existing consistent hashing schemes can't meet the requirements simultaneously, including full consistency, scalability, small memory footprint, low update time and low query complexity. Thus, We propose DxHash, a scalable consistent hashing algorithm based on the pseudo-random sequence. For the scenario of distributed storage, there are two optimizations based on DXHash are proposed. First, the Weighted DxHash can adjust the workloads on arbitrary nodes. Second, the Asymmetric Replica Strategy (ARS) is combining the replica strategy in distributed storage with the scaleup process to improve the availability of the system and reduce the remapping rate. The evaluation indicates that compared with the state-of-art works, DxHash achieves significant improvements on the 5 requirements. Even with 50% failure ratio, DxHash still can complete 16.5 million queries per second. What's more, the two optimizations both achieve their own results.

中文翻译:

DxHash:基于伪随机序列的可扩展一致性哈希

Consistent hasing 在分布式数据库、云基础设施和点对点网络等各个领域作为数据路由器和负载均衡器发挥了基础性作用。然而,现有的一致性哈希方案不能同时满足要求,包括完全一致性、可扩展性、内存占用小、更新时间短和查询复杂度低。因此,我们提出了 DxHash,一种基于伪随机序列的可扩展一致性哈希算法。针对分布式存储的场景,提出了两种基于DXHash的优化方案。首先,Weighted DxHash 可以调整任意节点上的工作负载。其次,非对称副本策略(ARS)是将分布式存储中的副本策略与Scaleup过程相结合,以提高系统的可用性并降低重映射率。评估表明,与 state-of-art 作品相比,DxHash 在 5 个要求上实现了显着改进。即使有 50% 的失败率,DxHash 仍然可以每秒完成 1650 万次查询。更何况这两种优化都达到了各自的效果。
更新日期:2021-07-19
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