A Comparative Study of Database Knob-Tuning Approaches
| Název práce v češtině: | A Comparative Study of Database Knob-Tuning Approaches |
|---|---|
| Název v anglickém jazyce: | A Comparative Study of Database Knob-Tuning Approaches |
| Klíčová slova: | database management systems|knob tuning|machine learning|multi-model data |
| Klíčová slova anglicky: | database management systems|knob tuning|machine learning|multi-model data |
| Akademický rok vypsání: | 2024/2025 |
| Typ práce: | diplomová práce |
| Jazyk práce: | angličtina |
| Ústav: | Katedra softwarového inženýrství (32-KSI) |
| Vedoucí / školitel: | doc. RNDr. Irena Holubová, Ph.D. |
| Řešitel: |
| Zásady pro vypracování |
| Databases have hundreds of knobs and require the database administrators to tune the knobs to adapt them to different scenarios. Since it is a complex task, the database community utilises learning-based techniques. The thesis aims to perform both statical and experimental comparisons of knob-tuning approaches, primarily those based on machine learning approaches. The thesis will also summarise findings and open problems, especially in the context of multi-model data management and other current trends in database management systems. |
| Seznam odborné literatury |
| Xuanhe Zhou, Chengliang Chai, Guoliang Li, Ji Sun: Database Meets Artificial Intelligence: A Survey (Extended Abstract). ICDE 2023: 3901-3902
Ji Zhang, Yu Liu, Ke Zhou, Guoliang Li, Zhili Xiao, Bin Cheng, Jiashu Xing, Yangtao Wang, Tianheng Cheng, Li Liu, Minwei Ran, Zekang Li: An End-to-End Automatic Cloud Database Tuning System Using Deep Reinforcement Learning. SIGMOD Conference 2019: 415-432 Dana Van Aken, Andrew Pavlo, Geoffrey J. Gordon, Bohan Zhang: Automatic Database Management System Tuning Through Large-scale Machine Learning. SIGMOD Conference 2017: 1009-1024 Guoliang Li, Xuanhe Zhou, Shifu Li, Bo Gao: QTune: A Query-Aware Database Tuning System with Deep Reinforcement Learning. Proc. VLDB Endow. 12(12): 2118-2130 (2019) |