60 citations · 112 across the 8 of their papers we have counts for
6 papers · 1 filter
From Blind Search to Memory-Aware Evolution: Efficient DBMS Tuning via Collaborative Diagnosis and Utility-Aware Retrieval
Zhaoyan Hong, Yishen Sun, Xinyi Zhang +7
Modern DBMSs expose multiple configurable components (e.g., knobs, query hints, and indexes) that jointly determine query performance. Multi-component tuning is challenging due to…
Why Database Manuals Are Not Enough: Efficient and Reliable Configuration Tuning for DBMSs via Code-Driven LLM Agents
Xinyi Zhang, Tiantian Chen, Zhentao Han +9
Modern database management systems (DBMSs) expose hundreds of configuration knobs that critically influence performance. Existing automated tuning methods either adopt a data-drive…
ContTune: Continuous Tuning by Conservative Bayesian Optimization for Distributed Stream Data Processing Systems
Jinqing Lian, Xinyi Zhang, Yingxia Shao +4
The past decade has seen rapid growth of distributed stream data processing systems. Under these systems, a stream application is realized as a Directed Acyclic Graph (DAG) of oper…
A Unified and Efficient Coordinating Framework for Autonomous DBMS Tuning
Xinyi Zhang, Zhuo Chang, Hong Wu +5
Recently using machine learning (ML) based techniques to optimize modern database management systems has attracted intensive interest from both industry and academia. With an objec…
Towards Dynamic and Safe Configuration Tuning for Cloud Databases
Xinyi Zhang, Hong Wu, Yang Li +3
Configuration knobs of database systems are essential to achieve high throughput and low latency. Recently, automatic tuning systems using machine learning methods (ML) have shown…
Facilitating Database Tuning with Hyper-Parameter Optimization: A Comprehensive Experimental Evaluation
Xinyi Zhang, Zhuo Chang, Yang Li +4
Recently, using automatic configuration tuning to improve the performance of modern database management systems (DBMSs) has attracted increasing interest from the database communit…