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ESTune: Bayesian Uncertainty-Guided Early Stopping for Database Configuration Tuning

Summary: ESTune accelerates database knob tuning by early-stopping clearly poor configurations, replacing full-workload evaluation with high-confidence performance estimates from partial runs. Core novelty: a hybrid Bayesian NN plus MAML few-shot/meta-learning to predict configuration performance uncertainty and preserve tuning quality. (summarized by gpt-5-mini on Apr 11 2026)

Paper ID
7666
Venue
SIGMOD
Year
2026
Pagerank
5.093636e-05
Overall Rank
10,453 | 28.29%
DOI
10.1145/3786649

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Authors

BibTeX Citation

@inproceedings{yue_sigmod26,
        title = {{ESTune: Bayesian Uncertainty-Guided Early Stopping for Database Configuration Tuning}},
        author = {Yue, Zhongwei and Zhu, Jun-Peng and Cai, Peng and Zhou, Xuan and Xu, Quanqing and Yang, Chuanhui},
        series = {{SIGMOD} '26},
        booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
        publisher = {Association for Computing Machinery},
        doi = {10.1145/3786649},
        url = {https://dl.acm.org/doi/10.1145/3786649},
        year = {2026}
}

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Outgoing Citations (Sorted by Pagerank)

Showing 18 of 18 cited papers.

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

Rank Cited Paper Year Venue Pagerank
86 Automatic Database Management System Tuning Through Large-scale Machine Learning 2017 SIGMOD 0.00035316107
226 OLTP-Bench: An Extensible Testbed for Benchmarking Relational Databases 2014 VLDB 0.00024027277
334 An End-to-End Automatic Cloud Database Tuning System Using Deep Reinforcement Learning 2019 SIGMOD 0.00020875082
498 QTune: A Query-Aware Database Tuning System with Deep Reinforcement Learning 2019 VLDB 0.00017440583
1,337 DB-BERT: A Database Tuning Tool that "Reads the Manual" 2022 SIGMOD 0.00011117488
1,344 An Inquiry into Machine Learning-based Automatic Configuration Tuning Services on Real-World Database Management Systems 2021 VLDB 0.00011094717
2,298 GPTuner: A Manual-Reading Database Tuning System via GPT-Guided Bayesian Optimization 2024 VLDB 8.7886538e-05
2,740 Facilitating Database Tuning with Hyper-Parameter Optimization: A Comprehensive Experimental Evaluation 2022 VLDB 8.1855759e-05
3,116 ResTune: Resource Oriented Tuning Boosted by Meta-Learning for Cloud Databases 2021 SIGMOD 7.7390737e-05
3,219 iBTune: Individualized Buffer Tuning for Large-scale Cloud Databases 2019 VLDB 7.6283153e-05
3,343 LlamaTune: Sample-Efficient DBMS Configuration Tuning 2022 VLDB 7.4983591e-05
3,346 CGPTuner: a Contextual Gaussian Process Bandit Approach for the Automatic Tuning of IT Configurations Under Varying Workload Conditions 2021 VLDB 7.4967834e-05
3,587 HUNTER: An Online Cloud Database Hybrid Tuning System for Personalized Requirements 2022 SIGMOD 7.2829345e-05
4,011 Towards Dynamic and Safe Configuration Tuning for Cloud Databases 2022 SIGMOD 6.959982e-05
4,788 iTuned: A Tool for Configuring and Visualizing Database Parameters 2010 SIGMOD 6.5079219e-05
5,171 An Efficient Transfer Learning Based Configuration Adviser for Database Tuning 2024 VLDB 6.3347618e-05
5,340 Machine Learning for Databases 2021 VLDB 6.2603359e-05
6,997 E2ETune: End-to-End Knob Tuning via Fine-tuned Generative Language Model 2025 VLDB 5.7300324e-05
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