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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
6.1971399e-05
Overall Rank
5,286 | 64.47%
DOI
10.14778/3632093.3632114

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
7,070 E2ETune: End-to-End Knob Tuning via Fine-tuned Generative Language Model 2025 VLDB 5.6080535e-05
7,977 The Holon Approach for Simultaneously Tuning Multiple Components in a Self-Driving Database Management System with Machine Learning via Synthesized Proto-Actions 2024 VLDB 5.4142519e-05
9,133 Hit the Gym: Accelerating Query Execution to Efficiently Bootstrap Behavior Models for Self-Driving Database Management Systems 2024 VLDB 5.2229655e-05
9,904 AgentTune: An Agent-Based Large Language Model Framework for Database Knob Tuning 2026 SIGMOD 5.1103839e-05
9,956 Graph Transformers for Query Plan Representation: Potentials and Challenges 2025 VLDB 5.1038322e-05
10,290 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 5.0431863e-05
10,291 Why Database Manuals Are Not Enough: Efficient and Reliable Configuration Tuning for DBMSs via Code-Driven LLM Agents 2026 VLDB 5.0431863e-05
10,333 SCompression: Enhancing Database Knob Tuning Efficiency Through Slice-Based OLTP Workload Compression 2025 VLDB 5.0281656e-05
10,580 MCTuner: Spatial Decomposition-Enhanced Database Tuning via LLM-Guided Exploration 2026 SIGMOD 4.9793485e-05
10,641 ESTune: Bayesian Uncertainty-Guided Early Stopping for Database Configuration Tuning 2026 SIGMOD 4.9793485e-05
10,747 LakeHelm: Zero-Shot Lakehouse Advisor for Joint Engine-Format Selection and Configuration 2026 VLDB 4.9793485e-05
10,887 MFTune: An Efficient Multi-fidelity Framework for Spark SQL Configuration Tuning 2026 VLDB 4.9793485e-05
11,072 Libra: One-Shot Parameter Sensitivity Estimation for Transfer Learning in Database Performance Prediction 2026 VLDB 4.9793485e-05
11,219 AdaNDV: Adaptive Number of Distinct Value Estimation via Learning to Select and Fuse Estimators 2025 VLDB 4.9793485e-05
11,303 LLMLog: Advanced Log Template Generation via LLM-driven Multi-Round Annotation 2025 VLDB 4.9793485e-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 0.00061066921
78 Automatic Database Management System Tuning Through Large-scale Machine Learning 2017 SIGMOD 0.00036684414
235 OLTP-Bench: An Extensible Testbed for Benchmarking Relational Databases 2014 VLDB 0.00023697028
314 An End-to-End Automatic Cloud Database Tuning System Using Deep Reinforcement Learning 2019 SIGMOD 0.00021282642
322 Tuning Database Configuration Parameters with iTuned 2009 VLDB 0.00021041865
437 QTune: A Query-Aware Database Tuning System with Deep Reinforcement Learning 2019 VLDB 0.00018315867
460 Query-based Workload Forecasting for Self-Driving Database Management Systems 2018 SIGMOD 0.00017842695
491 Database Tuning Advisor for Microsoft SQL Server 2005 2004 VLDB 0.00017413042
508 Adaptive Self-Tuning Memory in DB2 2006 VLDB 0.00017089907
780 Self-tuning Database Technology and Information Services: from Wishful Thinking to Viable Engineering 2002 VLDB 0.00014025444
1,250 DB-BERT: A Database Tuning Tool that "Reads the Manual" 2022 SIGMOD 0.00011339256
1,289 An Inquiry into Machine Learning-based Automatic Configuration Tuning Services on Real-World Database Management Systems 2021 VLDB 0.00011162479
1,699 Black or White? How to Develop an AutoTuner for Memory-based Analytics 2020 SIGMOD 9.8445322e-05
2,720 ResTune: Resource Oriented Tuning Boosted by Meta-Learning for Cloud Databases 2021 SIGMOD 8.0966919e-05
2,772 Facilitating Database Tuning with Hyper-Parameter Optimization: A Comprehensive Experimental Evaluation 2022 VLDB 8.035288e-05
3,051 LlamaTune: Sample-Efficient DBMS Configuration Tuning 2022 VLDB 7.7055931e-05
3,158 CGPTuner: a Contextual Gaussian Process Bandit Approach for the Automatic Tuning of IT Configurations Under Varying Workload Conditions 2021 VLDB 7.5811757e-05
3,352 Database Tuning: principles, experiments, and troubleshooting techniques 2002 SIGMOD 7.3904295e-05
3,486 HUNTER: An Online Cloud Database Hybrid Tuning System for Personalized Requirements 2022 SIGMOD 7.2636102e-05
4,079 Towards Dynamic and Safe Configuration Tuning for Cloud Databases 2022 SIGMOD 6.818264e-05
5,077 DBPA: A Benchmark for Transactional Database Performance Anomalies 2023 SIGMOD 6.2858696e-05
6,251 Foundations of Automated Database Tuning 2006 VLDB 5.8354449e-05
6,450 Towards General and Efficient Online Tuning for Spark 2023 VLDB 5.7817872e-05
6,726 A Unified and Efficient Coordinating Framework for Autonomous DBMS Tuning 2023 SIGMOD 5.6948731e-05
7,786 Database Tuning 1992 VLDB 5.4529722e-05
10,084 ContTune: Continuous Tuning by Conservative Bayesian Optimization for Distributed Stream Data Processing Systems 2023 VLDB 5.0830849e-05
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# Overall Rank Paper Year Venue
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2 1,289 An Inquiry into Machine Learning-based Automatic Configuration Tuning Services on Real-World Database Management Systems 2021 VLDB
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