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An Efficient Transfer Learning Based Configuration Adviser for Database Tuning

Summary: OpAdviser transfers knowledge across tuning tasks to identify effective knob regions and adaptively construct compact search spaces. A pairwise model selects optimizers per task/iteration, yielding 9.2% higher throughput and ~3.4× fewer workload runs than state-of-the-art systems. (summarized by gpt-5.6-luna on Jul 24 2026)

Paper ID
h6caa7ae6852f3876
Venue
VLDB
Year
2024
Pagerank
6.1758143e-05
Overall Rank
5,304 | 64.45%
DOI
10.14778/3632093.3632114
PDF
Download (CC BY-NC-ND 4.0)

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@article{zhang_vldb24,
        title = {{An Efficient Transfer Learning Based Configuration Adviser for Database Tuning}},
        author = {Zhang, Xinyi and Wu, Hong and Li, Yang and Tang, Zhengju and Tan, Jian and Li, Feifei and Cui, Bin},
        journal = {PVLDB},
        series = {{VLDB} '24},
        volume = {17},
        number = {3},
        pages = {539--552},
        doi = {10.14778/3632093.3632114},
        url = {https://doi.org/10.14778/3632093.3632114},
        year = {2024}
}

Incoming Citations (Sorted by Pagerank)

Showing 15 of 15 citing papers.

Rank Citing Paper Year Venue Pagerank
7,092 E2ETune: End-to-End Knob Tuning via Fine-tuned Generative Language Model 2025 VLDB 5.5868637e-05
7,997 The Holon Approach for Simultaneously Tuning Multiple Components in a Self-Driving Database Management System with Machine Learning via Synthesized Proto-Actions 2024 VLDB 5.3938336e-05
9,154 Hit the Gym: Accelerating Query Execution to Efficiently Bootstrap Behavior Models for Self-Driving Database Management Systems 2024 VLDB 5.2050937e-05
9,946 AgentTune: An Agent-Based Large Language Model Framework for Database Knob Tuning 2026 SIGMOD 5.0910746e-05
9,995 Graph Transformers for Query Plan Representation: Potentials and Challenges 2025 VLDB 5.0845476e-05
10,323 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 5.0241309e-05
10,324 Why Database Manuals Are Not Enough: Efficient and Reliable Configuration Tuning for DBMSs via Code-Driven LLM Agents 2026 VLDB 5.0241309e-05
10,334 AdaNDV: Adaptive Number of Distinct Value Estimation via Learning to Select and Fuse Estimators 2025 VLDB 5.0225409e-05
10,366 SCompression: Enhancing Database Knob Tuning Efficiency Through Slice-Based OLTP Workload Compression 2025 VLDB 5.0091669e-05
10,653 MCTuner: Spatial Decomposition-Enhanced Database Tuning via LLM-Guided Exploration 2026 SIGMOD 4.9605343e-05
10,713 ESTune: Bayesian Uncertainty-Guided Early Stopping for Database Configuration Tuning 2026 SIGMOD 4.9605343e-05
10,818 LakeHelm: Zero-Shot Lakehouse Advisor for Joint Engine-Format Selection and Configuration 2026 VLDB 4.9605343e-05
10,957 MFTune: An Efficient Multi-fidelity Framework for Spark SQL Configuration Tuning 2026 VLDB 4.9605343e-05
11,142 Libra: One-Shot Parameter Sensitivity Estimation for Transfer Learning in Database Performance Prediction 2026 VLDB 4.9605343e-05
11,365 LLMLog: Advanced Log Template Generation via LLM-driven Multi-Round Annotation 2025 VLDB 4.9605343e-05
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Outgoing Citations (Sorted by Pagerank)

Showing 26 of 26 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 0.00061463175
74 Automatic Database Management System Tuning Through Large-scale Machine Learning 2017 SIGMOD 0.00037164008
236 OLTP-Bench: An Extensible Testbed for Benchmarking Relational Databases 2014 VLDB 0.00023639649
309 An End-to-End Automatic Cloud Database Tuning System Using Deep Reinforcement Learning 2019 SIGMOD 0.0002143249
313 Tuning Database Configuration Parameters with iTuned 2009 VLDB 0.00021288111
411 QTune: A Query-Aware Database Tuning System with Deep Reinforcement Learning 2019 VLDB 0.0001874043
458 Query-based Workload Forecasting for Self-Driving Database Management Systems 2018 SIGMOD 0.00017870238
493 Database Tuning Advisor for Microsoft SQL Server 2005 2004 VLDB 0.0001735831
496 Adaptive Self-Tuning Memory in DB2 2006 VLDB 0.00017347275
775 Self-tuning Database Technology and Information Services: from Wishful Thinking to Viable Engineering 2002 VLDB 0.00014062388
1,238 DB-BERT: A Database Tuning Tool that "Reads the Manual" 2022 SIGMOD 0.00011375179
1,294 An Inquiry into Machine Learning-based Automatic Configuration Tuning Services on Real-World Database Management Systems 2021 VLDB 0.00011129451
1,700 Black or White? How to Develop an AutoTuner for Memory-based Analytics 2020 SIGMOD 9.8224761e-05
2,572 ResTune: Resource Oriented Tuning Boosted by Meta-Learning for Cloud Databases 2021 SIGMOD 8.2581875e-05
2,779 Facilitating Database Tuning with Hyper-Parameter Optimization: A Comprehensive Experimental Evaluation 2022 VLDB 8.0085666e-05
3,057 LlamaTune: Sample-Efficient DBMS Configuration Tuning 2022 VLDB 7.6865211e-05
3,172 CGPTuner: a Contextual Gaussian Process Bandit Approach for the Automatic Tuning of IT Configurations Under Varying Workload Conditions 2021 VLDB 7.5556865e-05
3,356 Database Tuning: principles, experiments, and troubleshooting techniques 2002 SIGMOD 7.3653809e-05
3,486 HUNTER: An Online Cloud Database Hybrid Tuning System for Personalized Requirements 2022 SIGMOD 7.2428834e-05
4,101 Towards Dynamic and Safe Configuration Tuning for Cloud Databases 2022 SIGMOD 6.7930727e-05
5,098 DBPA: A Benchmark for Transactional Database Performance Anomalies 2023 SIGMOD 6.2631174e-05
6,265 Foundations of Automated Database Tuning 2006 VLDB 5.8135505e-05
6,464 Towards General and Efficient Online Tuning for Spark 2023 VLDB 5.759941e-05
6,752 A Unified and Efficient Coordinating Framework for Autonomous DBMS Tuning 2023 SIGMOD 5.6733557e-05
7,809 Database Tuning 1992 VLDB 5.432514e-05
10,123 ContTune: Continuous Tuning by Conservative Bayesian Optimization for Distributed Stream Data Processing Systems 2023 VLDB 5.0638787e-05
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