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An Efficient Transfer Learning Based Configuration Adviser for Database Tuning

Summary: OpAdviser uses transfer learning to infer search-space geometries (important knobs and effective ranges) from historical tuning tasks and constructs compact, task-adaptive search spaces. A pairwise ranking model selects the best optimizer per task, yielding ~3.4x fewer runs and 9.2% higher throughput versus SOTA. (summarized by gpt-5-mini on Feb 09 2026)

Paper ID
13733
Venue
VLDB
Year
2024
Pagerank
5.183652e-05
Overall Rank
6,151 | 57.21%
DOI
10.14778/3632093.3632114

Incoming Non-self Citations Over Time

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Incoming Citations (Sorted by Pagerank)

Showing 13 of 13 citing papers.

Rank Citing Paper Year Venue Pagerank
8,020 The Holon Approach for Simultaneously Tuning Multiple Components in a Self-Driving Database Management System with Machine Learning via Synthesized Proto-Actions 2024 VLDB 4.6040862e-05
8,186 E2ETune: End-to-End Knob Tuning via Fine-tuned Generative Language Model 2025 VLDB 4.5651684e-05
9,006 Hit the Gym: Accelerating Query Execution to Efficiently Bootstrap Behavior Models for Self-Driving Database Management Systems 2024 VLDB 4.4101482e-05
9,956 SCompression: Enhancing Database Knob Tuning Efficiency Through Slice-Based OLTP Workload Compression 2025 VLDB 4.2373024e-05
10,047 AgentTune: An Agent-Based Large Language Model Framework for Database Knob Tuning 2026 SIGMOD 4.1945683e-05
10,093 MCTuner: Spatial Decomposition-Enhanced Database Tuning via LLM-Guided Exploration 2026 SIGMOD 4.1945683e-05
10,164 ESTune: Bayesian Uncertainty-Guided Early Stopping for Database Configuration Tuning 2026 SIGMOD 4.1945683e-05
10,217 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 4.1945683e-05
10,247 Why Database Manuals Are Not Enough: Efficient and Reliable Configuration Tuning for DBMSs via Code-Driven LLM Agents 2026 VLDB 4.1945683e-05
10,328 Libra: One-Shot Parameter Sensitivity Estimation for Transfer Learning in Database Performance Prediction 2026 VLDB 4.1945683e-05
10,534 AdaNDV: Adaptive Number of Distinct Value Estimation via Learning to Select and Fuse Estimators 2025 VLDB 4.1945683e-05
10,658 LLMLog: Advanced Log Template Generation via LLM-driven Multi-Round Annotation 2025 VLDB 4.1945683e-05
10,859 Graph Transformers for Query Plan Representation: Potentials and Challenges 2025 VLDB 4.1945683e-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
71 How Good Are Query Optimizers, Really? 2016 VLDB 0.00059038975
183 Automatic Database Management System Tuning Through Large-scale Machine Learning 2017 SIGMOD 0.00036721403
340 OLTP-Bench: An Extensible Testbed for Benchmarking Relational Databases 2014 VLDB 0.00026841628
424 Tuning Database Configuration Parameters with iTuned 2009 VLDB 0.00023616398
514 An End-to-End Automatic Cloud Database Tuning System Using Deep Reinforcement Learning 2019 SIGMOD 0.0002124895
661 Database Tuning Advisor for Microsoft SQL Server 2005 2004 VLDB 0.00018481174
663 Adaptive Self-Tuning Memory in DB2 2006 VLDB 0.00018469455
716 Query-based Workload Forecasting for Self-Driving Database Management Systems 2018 SIGMOD 0.00017723171
782 QTune: A Query-Aware Database Tuning System with Deep Reinforcement Learning 2019 VLDB 0.00016729063
846 Self-tuning Database Technology and Information Services: from Wishful Thinking to Viable Engineering 2002 VLDB 0.00015997985
1,407 DB-BERT: A Database Tuning Tool that "Reads the Manual" 2022 SIGMOD 0.00012146739
1,827 An Inquiry into Machine Learning-based Automatic Configuration Tuning Services on Real-World Database Management Systems 2021 VLDB 0.00010390548
1,902 Black or White? How to Develop an AutoTuner for Memory-based Analytics 2020 SIGMOD 0.00010157713
3,522 ResTune: Resource Oriented Tuning Boosted by Meta-Learning for Cloud Databases 2021 SIGMOD 7.0096727e-05
3,538 Database Tuning: principles, experiments, and troubleshooting techniques 2002 SIGMOD 6.995825e-05
3,812 Facilitating Database Tuning with Hyper-Parameter Optimization: A Comprehensive Experimental Evaluation 2022 VLDB 6.7373184e-05
4,265 CGPTuner: a Contextual Gaussian Process Bandit Approach for the Automatic Tuning of IT Configurations Under Varying Workload Conditions 2021 VLDB 6.3097793e-05
4,380 LlamaTune: Sample-Efficient DBMS Configuration Tuning 2022 VLDB 6.2396606e-05
4,399 HUNTER: An Online Cloud Database Hybrid Tuning System for Personalized Requirements 2022 SIGMOD 6.2225151e-05
4,842 Towards Dynamic and Safe Configuration Tuning for Cloud Databases 2022 SIGMOD 5.8826802e-05
4,868 DBPA: A Benchmark for Transactional Database Performance Anomalies 2023 SIGMOD 5.8629636e-05
6,379 A Unified and Efficient Coordinating Framework for Autonomous DBMS Tuning 2023 SIGMOD 5.0909479e-05
6,520 Foundations of Automated Database Tuning 2006 VLDB 5.0307595e-05
6,871 Towards General and Efficient Online Tuning for Spark 2023 VLDB 4.8997004e-05
7,862 Database Tuning 1992 VLDB 4.6330193e-05
9,733 ContTune: Continuous Tuning by Conservative Bayesian Optimization for Distributed Stream Data Processing Systems 2023 VLDB 4.2942813e-05
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Semantically Similar Papers

Overall Rank Paper Year Venue Pagerank
514 An End-to-End Automatic Cloud Database Tuning System Using Deep Reinforcement Learning 2019 SIGMOD 0.0002124895
4,380 LlamaTune: Sample-Efficient DBMS Configuration Tuning 2022 VLDB 6.2396606e-05
1,827 An Inquiry into Machine Learning-based Automatic Configuration Tuning Services on Real-World Database Management Systems 2021 VLDB 0.00010390548
3,812 Facilitating Database Tuning with Hyper-Parameter Optimization: A Comprehensive Experimental Evaluation 2022 VLDB 6.7373184e-05
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