基于LSM-Tree的键值存储系统的读写性能优化  

Read and Write Performance Optimization of Storage System Based on LSM-tree Key Value

作　　者：程浩津 胡乃平[1] CHENG Haojin;HU Naiping(College of Information Science and Technology,Qingdao University of Science&Technology,Qingdao 266061,China)

机构地区：[1]青岛科技大学信息科学技术学院,山东青岛266061

出　　处：《计算机测量与控制》2024年第6期262-268,275,共8页Computer Measurement &Control

摘　　要：在写密集型工作环境中,日志结构合并树(LSM-Tree)已逐渐成为主流存储系统,LSM-Tree存在读操作速度慢、写操作成本高、范围查询操作效率低等问题;针对这些问题,为提升LSM-Tree的性能进行了研究,提出了一种基于LSM-Tree的键值存储系统的读写性能优化策略,通过键值分离策略设计vTree结构,并提出层内归并与消极的层间合并相结合的方法,以及范围查询优化合并的策略,从而优化系统的范围查询性能,在LSM-Tree和vTree采用不同的压缩结构,以实现系统读写性能的提升;实验结果表明,与RocksDB相比读性能提升30%,与RocksDB-vTree相比范围查询性能提升10%。In a write-intensive work environment,log-structured-merge(LSM-Tree)has gradually become a mainstream storage system,there are problems in LSM-tree such as slow read operation speed,high cost of write operation,and low efficiency of range query operation,etc.In view of these problems,this paper presents a study to improve the performance of LSM-tree,and optimize the read and write performance of key-value storage system based on LSM-tree,and proposes a read and write performance optimization strategy for LSM-tree-based key-value storage system,designs the vTree structure through the key-value separation strategy,and presents the combination of layer merging and negative inter layer merging,as well as the strategy of range query-optimized merging,so as to optimize the range query performance of the system,and adopt different compression structures in the LSM-tree and vTree to improve the system's read and write performance;the experimental results show that the read performance is improved by 30%compared with the RocksDB system,and the range query performance is improved by 10%compared with the RocksDB-vTree system.

关 键 词：读性能 LSM-Tree 消极的层间合并 范围查询优化合并 范围查询 

分 类 号：TP391.1[自动化与计算机技术—计算机应用技术]