MTDB: an LSM-tree-based key-value store using a multi-tree structure to improve read performance

Traditional LSM-tree-based key-value storage systems face significant read amplification issues due to the multi-level structure of LSM-tree, the unordered SSTable files in Level 0, and the lack of an in-memory index structure for key-value pairs. We observed that, under the influence of workloads w...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:The Journal of supercomputing 2024-11, Vol.80 (16), p.23995-24025
Hauptverfasser: Lin, Xinwei, Pan, Yubiao, Feng, Wenjuan, Zhang, Huizhen, Lin, Mingwei
Format: Artikel
Sprache:eng
Schlagworte:
Online-Zugang:Volltext
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
Beschreibung
Zusammenfassung:Traditional LSM-tree-based key-value storage systems face significant read amplification issues due to the multi-level structure of LSM-tree, the unordered SSTable files in Level 0, and the lack of an in-memory index structure for key-value pairs. We observed that, under the influence of workloads with locality features, key-value pairs exhibit a range-specific access intensity. Addressing the three reasons for LSM-tree read amplification, we have utilized the range-specific access intensity of workload to propose a multi-tree structure consisting of a B+ tree, a single-level hot tree, and an LSM-tree with partition-based Level 0. This aims to enhance the read performance of LSM-tree-based key-value storage systems. We designed the prototype, MTDB, based on LevelDB. The experimental results show that MTDB’s read performance is 1.62× to 2.02× that of LevelDB, and it approaches or exceeds the read performance of KVell and Bourbon while reducing memory overhead by 58.85%–86%.
ISSN:0920-8542
1573-0484
DOI:10.1007/s11227-024-06382-5