Modern cloud database management systems face challenges in performance optimization due to numerous configurable parameters, necessitating automatic tuning techniques for effective management.
This paper surveys various automatic parameter tuning techniques, including Bayesian optimization, neural networks, reinforcement learning, and search-based methodologies, showcasing their applications in DBMS performance enhancement.
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