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)
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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}
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Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 78 | Automatic Database Management System Tuning Through Large-scale Machine Learning | 2017 | SIGMOD | 0.00036675568 |
| 224 | Self-Driving Database Management Systems | 2017 | CIDR | 0.00024011047 |
| 322 | Tuning Database Configuration Parameters with iTuned | 2009 | VLDB | 0.00021034201 |
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