SHA: QoS-Aware Software and Hardware Auto-Tuning for Database Systems  

作　　者：李进 陈全 唐晓新 过敏意 Jin Li;Quan Chen;Xiao-Xin Tang;Min-Yi Guo(Department of Computer Science,Shanghai Jiao Tong University,Shanghai 200240,China;Department of Computer Science and Technology,Shanghai University of Finance and Economics,Shanghai 200433,China)

机构地区：[1]Department of Computer Science,Shanghai Jiao Tong University,Shanghai 200240,China [2]Department of Computer Science and Technology,Shanghai University of Finance and Economics,Shanghai 200433,China

出　　处：《Journal of Computer Science & Technology》2024年第2期369-383,共15页计算机科学技术学报（英文版）

基　　金：sponsored by the National Natural Science Foundation of China under Grant Nos.62022057,61832006,61632017,and 61872240.

摘　　要：While databases are widely-used in commercial user-facing services that have stringent quality-of-service(QoS)requirement,it is crucial to ensure their good performance and minimize the hardware usage at the same time.Our investigation shows that the optimal DBMS(database management system)software configuration varies for different user request patterns(i.e.,workloads)and hardware configurations.It is challenging to identify the optimal software and hardware configurations for a database workload,because DBMSs have hundreds of tunable knobs,the effect of tuning a knob depends on other knobs,and the dependency relationship changes under different hardware configurations.In this paper,we propose SHA,a software and hardware auto-tuning system for DBMSs.SHA is comprised of a scaling-based performance predictor,a reinforcement learning(RL)based software tuner,and a QoS-aware resource reallocator.The performance predictor predicts its optimal performance with different hardware configurations and identifies the minimum amount of resources for satisfying its performance requirement.The software tuner fine-tunes the DBMS software knobs to optimize the performance of the workload.The resource reallocator assigns the saved resources to other applications to improve resource utilization without incurring QoS violation of the database workload.Experimental results show that SHA improves the performance of database workloads by 9.9%on average compared with a state-of-the-art solution when the hardware configuration is fixed,and improves 43.2%of resource utilization while ensuring the QoS.

关 键 词：AUTO-TUNING database configuration joint tuning UTILIZATION quality-of-service(QoS) 

分 类 号：TP311.13[自动化与计算机技术—计算机软件与理论]