Optimizing Database Joins
Cost Models and Benchmarking for CPU and GPU Systems
M. Matušovič (TU Delft - Electrical Engineering, Mathematics and Computer Science)
R. Hai – Mentor (TU Delft - Web Information Systems)
C. Lofi – Graduation committee member (TU Delft - Web Information Systems)
Jérémie Decouchant – Graduation committee member (TU Delft - Data-Intensive Systems)
Wenbo Sun – Coach (TU Delft - Web Information Systems)
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Abstract
Optimizing SQL query execution through effective cost models is a critical challenge in database management systems (DBMS). This thesis introduces a modular benchmarking system for cost models, with a pluggable architecture for both cost models and execution engines, enabling comprehensive benchmarking across various scenarios. Accompanied by a detailed methodology for the empirical measurement of cost model performance across different execution engines, a standardized approach is established, ensuring consistent and reproducible benchmarks. Furthermore, as a showcase of the developed system's capabilities, an analysis of key features influencing join-order optimization performance in both CPU and GPU systems is presented. This analysis demonstrates the system's utility in developing more effective cost models and optimizers. These contributions pave the way for future research in DBMS optimization, providing a research platform for the accelerated development of new cost models.