Optimizing Database Joins

Cost Models and Benchmarking for CPU and GPU Systems

Master Thesis (2024)
Author(s)

M. Matušovič (TU Delft - Electrical Engineering, Mathematics and Computer Science)

Contributor(s)

Rihan Hai – Mentor (TU Delft - Web Information Systems)

Christoph Lofi – Graduation committee member (TU Delft - Web Information Systems)

Jérémie Decouchant – Graduation committee member (TU Delft - Data-Intensive Systems)

W. Sun – Coach (TU Delft - Web Information Systems)

Faculty
Electrical Engineering, Mathematics and Computer Science
More Info
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Publication Year
2024
Language
English
Graduation Date
25-04-2024
Awarding Institution
Delft University of Technology
Programme
Computer Science | Software Technology
Faculty
Electrical Engineering, Mathematics and Computer Science
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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.

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