PLRTune: Importance Pre-Sampling and LLM-Guided Reinforcement Learning for Automatic Database Tuning (opens in new tab)
Configuration tuning is critical to database performance, yet automatic database tuning remains challenging due to high-dimensional knob spaces, substantial online tuning cost, unreliable textual hints derived from Large Language Models (LLMs) or community documents, and the difficulty of exploiting the remaining optimization room after initialization. Hence, we propose PLRTune, a staged database tuning system that leverages workload-specific do...
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