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Facilitating Database Tuning with Hyper-Parameter Optimization: A Comprehensive Experimental Evaluation

Summary: Comprehensive evaluation of DB configuration tuning methods across modules, showing hyper-parameter optimization can boost tuning performance. Proposes an efficient surrogate-based unified benchmark to minimize evaluation cost and identify best algorithms per module. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
h5e0e7bcafe6e6277
Venue
VLDB
Year
2022
Pagerank
8.0343719e-05
Overall Rank
2,770 | 81.39%
DOI
10.14778/3538598.3538604
PDF
Download (CC BY-NC-ND 4.0)

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@article{zhang_vldb22,
        title = {{Facilitating Database Tuning with Hyper-Parameter Optimization: A Comprehensive Experimental Evaluation}},
        author = {Zhang, Xinyi and Chang, Zhuo and Li, Yang and Wu, Hong and Tan, Jian and Li, Feifei and Cui, Bin},
        journal = {PVLDB},
        series = {{VLDB} '22},
        volume = {15},
        number = {9},
        pages = {1808--1821},
        doi = {10.14778/3538598.3538604},
        url = {https://doi.org/10.14778/3538598.3538604},
        year = {2022}
}

Incoming Citations (Sorted by Pagerank)

Showing 34 of 34 citing papers.

Rank Citing Paper Year Venue Pagerank
2,227 GPTuner: A Manual-Reading Database Tuning System via GPT-Guided Bayesian Optimization 2024 VLDB 8.8007923e-05
3,052 LlamaTune: Sample-Efficient DBMS Configuration Tuning 2022 VLDB 7.704739e-05
4,113 Automatic Database Configuration Debugging using Retrieval-Augmented Language Models 2025 SIGMOD 6.7964307e-05
4,677 AutoSteer: Learned Query Optimization for Any SQL Database 2023 VLDB 6.4721041e-05
5,080 DBPA: A Benchmark for Transactional Database Performance Anomalies 2023 SIGMOD 6.2830313e-05
5,284 An Efficient Transfer Learning Based Configuration Adviser for Database Tuning 2024 VLDB 6.1963031e-05
5,700 PilotScope: Steering Databases with Machine Learning Drivers 2024 VLDB 6.028998e-05
6,453 Towards General and Efficient Online Tuning for Spark 2023 VLDB 5.7790502e-05
6,732 A Unified and Efficient Coordinating Framework for Autonomous DBMS Tuning 2023 SIGMOD 5.6921776e-05
7,072 E2ETune: End-to-End Knob Tuning via Fine-tuned Generative Language Model 2025 VLDB 5.6053987e-05
7,546 Learned Offline Query Planning via Bayesian Optimization 2025 SIGMOD 5.4966669e-05
7,981 The Holon Approach for Simultaneously Tuning Multiple Components in a Self-Driving Database Management System with Machine Learning via Synthesized Proto-Actions 2024 VLDB 5.4117272e-05
8,283 Hyper-Tune: Towards Efficient Hyper-parameter Tuning at Scale 2022 VLDB 5.3613692e-05
9,031 Rockhopper: A Robust Optimizer for Spark Configuration Tuning in Production Environment 2025 SIGMOD 5.2323895e-05
9,728 Shapley Value Estimation Based on Differential Matrix 2025 SIGMOD 5.1325223e-05
9,911 AgentTune: An Agent-Based Large Language Model Framework for Database Knob Tuning 2026 SIGMOD 5.1079647e-05
10,089 ContTune: Continuous Tuning by Conservative Bayesian Optimization for Distributed Stream Data Processing Systems 2023 VLDB 5.0806786e-05
10,296 This is Going to Sound Crazy, But What If We Used Large Language Models to Boost Automatic Database Tuning Algorithms By Leveraging Prior History? We Will Find Better Configurations More Quickly Than Retraining From Scratch! 2026 SIGMOD 5.0407989e-05
10,297 Why Database Manuals Are Not Enough: Efficient and Reliable Configuration Tuning for DBMSs via Code-Driven LLM Agents 2026 VLDB 5.0407989e-05
10,340 SCompression: Enhancing Database Knob Tuning Efficiency Through Slice-Based OLTP Workload Compression 2025 VLDB 5.0257853e-05
10,426 ASSS: Adaptive Stratified Sampling for Shapley-like Values 2026 SIGMOD 4.9769913e-05
10,477 HAMMER: An Automatic RAG Tuning System via Hierarchical Memory-Guided Monte Carlo Tree Search 2026 SIGMOD 4.9769913e-05
10,591 MCTuner: Spatial Decomposition-Enhanced Database Tuning via LLM-Guided Exploration 2026 SIGMOD 4.9769913e-05
10,652 ESTune: Bayesian Uncertainty-Guided Early Stopping for Database Configuration Tuning 2026 SIGMOD 4.9769913e-05
10,739 Scarf: Self-Adaptive Tuning via Multi-Objective Reinforcement Learning for Apache Flink 2026 VLDB 4.9769913e-05
10,751 OBELISK: Efficient Offline Query Planning with Bayesian Optimization-Informed Language Model Reasoning 2026 VLDB 4.9769913e-05
10,757 LakeHelm: Zero-Shot Lakehouse Advisor for Joint Engine-Format Selection and Configuration 2026 VLDB 4.9769913e-05
10,896 MFTune: An Efficient Multi-fidelity Framework for Spark SQL Configuration Tuning 2026 VLDB 4.9769913e-05
11,055 DOT: Dynamic Knob Selection and Online Sampling for Automated Database Tuning 2026 VLDB 4.9769913e-05
11,081 Libra: One-Shot Parameter Sensitivity Estimation for Transfer Learning in Database Performance Prediction 2026 VLDB 4.9769913e-05
11,112 Centrum: Model-based Database Auto-tuning with Minimal Distributional Assumptions 2025 SIGMOD 4.9769913e-05
11,243 A Systematic Study on Early Stopping Metrics in HPO and the Implications of Uncertainty 2025 VLDB 4.9769913e-05
11,295 AQETuner: Reliable Query-level Configuration Tuning for Analytical Query Engines 2025 VLDB 4.9769913e-05
11,436 AXE: A Task Decomposition Approach to Learned LSM Tuning 2025 VLDB 4.9769913e-05
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Outgoing Citations (Sorted by Pagerank)

Showing 21 of 21 cited papers.

Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.

Rank Cited Paper Year Venue Pagerank
15 How Good Are Query Optimizers, Really? 2016 VLDB 0.00061067652
78 Automatic Database Management System Tuning Through Large-scale Machine Learning 2017 SIGMOD 0.00036675568
235 OLTP-Bench: An Extensible Testbed for Benchmarking Relational Databases 2014 VLDB 0.00023689995
314 An End-to-End Automatic Cloud Database Tuning System Using Deep Reinforcement Learning 2019 SIGMOD 0.00021276452
322 Tuning Database Configuration Parameters with iTuned 2009 VLDB 0.00021034201
437 QTune: A Query-Aware Database Tuning System with Deep Reinforcement Learning 2019 VLDB 0.00018310278
461 Query-based Workload Forecasting for Self-Driving Database Management Systems 2018 SIGMOD 0.00017841988
492 Database Tuning Advisor for Microsoft SQL Server 2005 2004 VLDB 0.00017406029
508 Adaptive Self-Tuning Memory in DB2 2006 VLDB 0.00017083245
781 Self-tuning Database Technology and Information Services: from Wishful Thinking to Viable Engineering 2002 VLDB 0.00014019939
1,289 An Inquiry into Machine Learning-based Automatic Configuration Tuning Services on Real-World Database Management Systems 2021 VLDB 0.00011159167
1,699 Black or White? How to Develop an AutoTuner for Memory-based Analytics 2020 SIGMOD 9.8403606e-05
2,721 ResTune: Resource Oriented Tuning Boosted by Meta-Learning for Cloud Databases 2021 SIGMOD 8.0931221e-05
3,032 iBTune: Individualized Buffer Tuning for Large-scale Cloud Databases 2019 VLDB 7.7317595e-05
3,159 CGPTuner: a Contextual Gaussian Process Bandit Approach for the Automatic Tuning of IT Configurations Under Varying Workload Conditions 2021 VLDB 7.5797912e-05
3,332 VolcanoML: Speeding up End-to-End AutoML via Scalable Search Space Decomposition 2021 VLDB 7.4130985e-05
3,352 Database Tuning: principles, experiments, and troubleshooting techniques 2002 SIGMOD 7.3871134e-05
3,588 Make Your Database System Dream of Electric Sheep: Towards Self-Driving Operation 2021 VLDB 7.1841858e-05
4,080 Towards Dynamic and Safe Configuration Tuning for Cloud Databases 2022 SIGMOD 6.8151596e-05
6,254 Foundations of Automated Database Tuning 2006 VLDB 5.8328094e-05
7,794 Database Tuning 1992 VLDB 5.4505168e-05
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