TY - GEN
T1 - Iterator Interface Extended LSM-tree-based KVSSD for Range Queries
AU - Lee, Seungjin
AU - Lee, Chang Gyu
AU - Min, Donghyun
AU - Park, Inhyuk
AU - Chung, Woosuk
AU - Sivasubramaniam, Anand
AU - Kim, Youngjae
N1 - Publisher Copyright:
© 2023 ACM.
PY - 2023/6/5
Y1 - 2023/6/5
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=85166004664&partnerID=8YFLogxK
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U2 - 10.1145/3579370.3594775
DO - 10.1145/3579370.3594775
M3 - Conference contribution
AN - SCOPUS:85166004664
T3 - Proceedings of the 16th ACM International Conference on Systems and Storage, SYSTOR 2023
SP - 60
EP - 70
BT - Proceedings of the 16th ACM International Conference on Systems and Storage, SYSTOR 2023
PB - Association for Computing Machinery, Inc
T2 - 16th ACM International Conference on Systems and Storage, SYSTOR 2023
Y2 - 5 June 2023 through 7 June 2023
ER -