CGPTuner: a Contextual Gaussian Process Bandit Approach for the Automatic Tuning of IT Configurations Under Varying Workload Conditions

Summary: CGPTuner uses a contextual Gaussian-process bandit to jointly tune DBMS, JVM, OS, and hardware parameters without historical knowledge. It adapts configurations to workload changes and transfers across Cassandra and MongoDB, balancing response time against memory. (summarized by gpt-5.6-luna on Jul 21 2026)

Paper ID: 12517
Venue: VLDB
Year: 2021
Pagerank: 7.4967834e-05
Overall Rank: 3,346 | 77.05%
DOI: 10.14778/3457390.3457404

Incoming Non-self Citations Over Time

Authors

1. Stefano Cereda (Politecnico di Milano)
2. Stefano Valladares (Politecnico di Milano)
3. Paolo Cremonesi (Politecnico di Milano)
4. Stefano Doni (Akamas)

BibTeX Citation

@article{cereda_vldb21,
        title = {{CGPTuner: a Contextual Gaussian Process Bandit Approach for the Automatic Tuning of IT Configurations Under Varying Workload Conditions}},
        author = {Cereda, Stefano and Valladares, Stefano and Cremonesi, Paolo and Doni, Stefano},
        journal = {PVLDB},
        series = {{VLDB} '21},
        volume = {14},
        number = {8},
        pages = {1401--1413},
        doi = {10.14778/3457390.3457404},
        url = {https://doi.org/10.14778/3457390.3457404},
        year = {2021}
}

Incoming Citations (Sorted by Pagerank)

Showing 18 of 18 citing papers.

Rank	Citing Paper	Year	Venue	Pagerank
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
3,343	LlamaTune: Sample-Efficient DBMS Configuration Tuning	2022	VLDB	7.4983591e-05
3,586	Make Your Database System Dream of Electric Sheep: Towards Self-Driving Operation	2021	VLDB	7.2834069e-05
5,171	An Efficient Transfer Learning Based Configuration Adviser for Database Tuning	2024	VLDB	6.3347618e-05
6,600	A Unified and Efficient Coordinating Framework for Autonomous DBMS Tuning	2023	SIGMOD	5.8250114e-05
6,997	E2ETune: End-to-End Knob Tuning via Fine-tuned Generative Language Model	2025	VLDB	5.7300324e-05
7,846	The Holon Approach for Simultaneously Tuning Multiple Components in a Self-Driving Database Management System with Machine Learning via Synthesized Proto-Actions	2024	VLDB	5.5331459e-05
8,163	Learned Offline Query Planning via Bayesian Optimization	2025	SIGMOD	5.4751517e-05
9,739	Waffle: In-memory Grid Index for Moving Objects with Reinforcement Learning-based Configuration Tuning System	2022	VLDB	5.227679e-05
9,898	ContTune: Continuous Tuning by Conservative Bayesian Optimization for Distributed Stream Data Processing Systems	2023	VLDB	5.1997534e-05
10,253	HAMMER: An Automatic RAG Tuning System via Hierarchical Memory-Guided Monte Carlo Tree Search	2026	SIGMOD	5.093636e-05
10,384	MCTuner: Spatial Decomposition-Enhanced Database Tuning via LLM-Guided Exploration	2026	SIGMOD	5.093636e-05
10,453	ESTune: Bayesian Uncertainty-Guided Early Stopping for Database Configuration Tuning	2026	SIGMOD	5.093636e-05
10,535	Why Database Manuals Are Not Enough: Efficient and Reliable Configuration Tuning for DBMSs via Code-Driven LLM Agents	2026	VLDB	5.093636e-05
10,660	Centrum: Model-based Database Auto-tuning with Minimal Distributional Assumptions	2025	SIGMOD	5.093636e-05
10,886	AQETuner: Reliable Query-level Configuration Tuning for Analytical Query Engines	2025	VLDB	5.093636e-05
11,426	Auto-Tuning with Reinforcement Learning for Permissioned Blockchain Systems	2023	VLDB	5.093636e-05

Outgoing Citations (Sorted by Pagerank)

Showing 3 of 3 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
234	Self-Driving Database Management Systems	2017	CIDR	0.00023810722
347	Tuning Database Configuration Parameters with iTuned	2009	VLDB	0.00020651582

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2	11,613	Budget-Conscious Fine-Grained Configuration Optimization for Spatio-Temporal Applications	2022	VLDB
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