1 citations · 1 across the 4 of their papers we have counts for
4 papers
IDSTune: A Multi-Agent Collaborative Framework for Integrated Database System Tuning
Yiyan Li, Guanli Liu, Renata Borovica-Gajic +6
Database tuning is critical for achieving high performance in modern database management systems (DBMSs). Existing methods typically optimize a single component---knobs, indexes, o…
FD-RAG: Federated Dual-System Retrieval-Augmented Generation
Tianhao Gao, Kai Yang, Yiyang Li
Retrieval-augmented generation (RAG) has emerged as a paradigm for grounding large language models in external knowledge, yet most existing RAG systems assume centralized knowledge…
Is Large Language Model Good at Database Knob Tuning? A Comprehensive Experimental Evaluation
Yiyan Li, Haoyang Li, Zhao Pu +6
Knob tuning plays a crucial role in optimizing databases by adjusting knobs to enhance database performance. However, traditional tuning methods often follow a Try-Collect-Adjust a…
E2ETune: End-to-End Knob Tuning via Fine-tuned Generative Language Model
Xinmei Huang, Haoyang Li, Jing Zhang +7
Database knob tuning is a significant challenge for database administrators, as it involves tuning a large number of configuration knobs with continuous or discrete values to achie…