Iterator Interface Extended LSM-tree-based KVSSD for Range Queries

Seungjin Lee, Chang-Gyu Lee, Donghyun Min, Inhyuk Park, Woosuk Chung, A. Sivasubramaniam, Youngjae Kim
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Abstract

Key-Value SSD (KVSSD) has shown great potential for several important classes of emerging data stores due to its high throughput and low latency. When designing a key-value store with range queries, an LSM-tree is considered a better choice than a hash table due to its key ordering. However, the design space for range queries in LSM-tree-based KVSSDs has yet to be explored, despite range queries being one of the most demanding features. In this paper, we investigate the design constraints in LSM-tree-based KVSSDs from the perspective of range queries and propose three design principles. Based on these principles, we present IterKVSSD, an Iterator interface extended LSM-tree-based KVSSD for range queries. We implement IterKVSSD on OpenSSD Cosmos+, and our evaluation shows that it increases range query throughput by up to 4.13× and 7.22× for random and sequential key distributions, respectively, compared to existing KVSSDs.
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用于范围查询的基于lsm树的扩展KVSSD迭代器接口
Key-Value SSD (KVSSD)由于其高吞吐量和低延迟,在一些重要的新兴数据存储类别中显示出巨大的潜力。在设计包含范围查询的键值存储时,由于其键顺序,lsm树被认为是比散列表更好的选择。然而,在基于lsm树的kvssd中,范围查询的设计空间还有待探索,尽管范围查询是最苛刻的功能之一。本文从范围查询的角度研究了基于lsm树的kvssd的设计约束,提出了三个设计原则。基于这些原则,我们提出了IterKVSSD,这是一个Iterator接口,扩展了基于lsm树的KVSSD,用于范围查询。我们在OpenSSD Cosmos+上实现了IterKVSSD,我们的评估表明,与现有的kvssd相比,对于随机和顺序密钥分布,IterKVSSD分别将范围查询吞吐量提高了4.13倍和7.22倍。
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