多种存储环境下压缩数据库的缓存优化

摘要

近年来,各行业数据量增速提升,对承担数据存储任务的数据库系统进行性能优化的需求也越来越强烈.利用关系型数据库I/O密集型、服务器CPU相对空闲的特点,在数据库中引入数据压缩技术,节省了数据存储空间和I/O传输带宽.但当今主流数据库系统的压缩技术都是针对传统的存储和运行环境设计,并未考虑固态硬盘(SSD)等新型存储设备和云数据库等虚拟化运行环境对系统性能的影响,因此,以数据库压缩系统在不同存储环境的缓存优化作为切入点,对系统整体性能的影响进行分析,给出了数据库压缩系统性能的分析模型,并以MySQL为例进行具体分析,给出了对应的缓存优化措施.在内核虚拟机(KVM)和MySQL数据库测试平台上的性能评估结果表明,所提出的优化方法使得系统性能最高有超过40％的提升,在某些配置下获得了优于物理机的性能.%In recent years,the amount of data in various industries grows rapidly,which results in the increasing of optimization demands in database storage system.Relational databases are I/O-intensive,take use of relatively free CPU time,data compression technology could save data storage space and I/O bandwidth.However,the compression features of current database systems were designed for traditional storage and computing environments,without considering the impact of virtualized environments or the use of Solid State Drive (SSD) on system performance.To optimize the cache performance of database compression system,a database compression system performance model.was proposed,and the impact on the I/O performance of various system environments was analyzed.Take the open source database MySQL as an example,the corresponding cache optimization methods were given based on analysis.Evaluation results on Kernel-based Virtual Machine (KVM) and MySQL database show that the optimized version has an increase of more than 40％ in performance under some configurations,even close to superior physical machine performance.