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CGPTuner: a Contextual Gaussian Process Bandit Approach for the Automatic Tuning of IT Configurations Under Varying Workload Conditions
Summary: CGPTuner uses a contextual GP bandit to auto-tune DBMS and IT-stack configurations under changing workloads. It learns online without prior knowledge bases, adapts to Cassandra and MongoDB, and keeps memory lean while latency stays low under load.
(summarized by gpt-5-nano on Feb 09 2026)
- Paper ID
- 12330
- Venue
- VLDB
- Year
- 2021
- Pagerank
- 6.3297728e-05
- Overall Rank
- 4,235 | 70.57%
- DOI
-
10.14778/3457390.3457404
Incoming Non-self Citations Over Time
Incoming Citations (Sorted by Pagerank)
Showing 17 of 17 citing papers.
| Rank |
Citing Paper |
Year |
Venue |
Pagerank |
| 3,105 |
GPTuner: A Manual-Reading Database Tuning System via GPT-Guided Bayesian Optimization |
2024 |
VLDB |
7.5567226e-05 |
| 3,655 |
Facilitating Database Tuning with Hyper-Parameter Optimization: A Comprehensive Experimental Evaluation |
2022 |
VLDB |
6.8723042e-05 |
| 4,180 |
LlamaTune: Sample-Efficient DBMS Configuration Tuning |
2022 |
VLDB |
6.3725334e-05 |
| 4,216 |
Make Your Database System Dream of Electric Sheep: Towards Self-Driving Operation |
2021 |
VLDB |
6.3448176e-05 |
| 5,834 |
An Efficient Transfer Learning Based Configuration Adviser for Database Tuning |
2024 |
VLDB |
5.3082111e-05 |
| 6,376 |
A Unified and Efficient Coordinating Framework for Autonomous DBMS Tuning |
2023 |
SIGMOD |
5.0861082e-05 |
| 7,676 |
E2ETune: End-to-End Knob Tuning via Fine-tuned Generative Language Model |
2025 |
VLDB |
4.6770108e-05 |
| 8,003 |
The Holon Approach for Simultaneously Tuning Multiple Components in a Self-Driving Database Management System with Machine Learning via Synthesized Proto-Actions |
2024 |
VLDB |
4.6049527e-05 |
| 8,660 |
Learned Offline Query Planning via Bayesian Optimization |
2025 |
SIGMOD |
4.4680058e-05 |
| 9,605 |
Waffle: In-memory Grid Index for Moving Objects with Reinforcement Learning-based Configuration Tuning System |
2022 |
VLDB |
4.3136057e-05 |
| 9,732 |
ContTune: Continuous Tuning by Conservative Bayesian Optimization for Distributed Stream Data Processing Systems |
2023 |
VLDB |
4.2901665e-05 |
| 10,093 |
MCTuner: Spatial Decomposition-Enhanced Database Tuning via LLM-Guided Exploration |
2026 |
SIGMOD |
4.1905499e-05 |
| 10,164 |
ESTune: Bayesian Uncertainty-Guided Early Stopping for Database Configuration Tuning |
2026 |
SIGMOD |
4.1905499e-05 |
| 10,247 |
Why Database Manuals Are Not Enough: Efficient and Reliable Configuration Tuning for DBMSs via Code-Driven LLM Agents |
2026 |
VLDB |
4.1905499e-05 |
| 10,382 |
Centrum: Model-based Database Auto-tuning with Minimal Distributional Assumptions |
2025 |
SIGMOD |
4.1905499e-05 |
| 10,641 |
AQETuner: Reliable Query-level Configuration Tuning for Analytical Query Engines |
2025 |
VLDB |
4.1905499e-05 |
| 11,227 |
Auto-Tuning with Reinforcement Learning for Permissioned Blockchain Systems |
2023 |
VLDB |
4.1905499e-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.
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