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Refactoring Index Tuning Process with Benefit Estimation

Summary: RIBE refactors index tuning by removing redundant workload queries and using plan statistics with an attention-based model to estimate index benefits. It skips costly what-if calls without DBMS changes, delivering 1–2 orders of magnitude speedups and better tuning quality. (summarized by gpt-5.6-luna on Jul 24 2026)

Paper ID
13583
Venue
VLDB
Year
2024
Pagerank
5.7098893e-05
Overall Rank
7,076 | 51.46%
DOI
10.14778/3654621.3654622

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@article{yu_vldb24,
        title = {{Refactoring Index Tuning Process with Benefit Estimation}},
        author = {Yu, Tao and Zou, Zhaonian and Sun, Weihua and Yan, Yu},
        journal = {PVLDB},
        series = {{VLDB} '24},
        volume = {17},
        number = {7},
        pages = {1528--1541},
        doi = {10.14778/3654621.3654622},
        url = {https://doi.org/10.14778/3654621.3654622},
        year = {2024}
}

Incoming Citations (Sorted by Pagerank)

Showing 5 of 5 citing papers.

Rank Citing Paper Year Venue Pagerank
10,014 TxnSails: Achieving Serializable Transaction Scheduling with Self-Adaptive Isolation Level Selection 2025 VLDB 5.1770751e-05
10,327 Rainbow: Risk-aware Index Benefit Estimation Facing Out Of Distribution Workloads 2026 SIGMOD 5.093636e-05
10,494 RIB: Robust Learning-based Index Benefit Estimation 2026 SIGMOD 5.093636e-05
10,774 PLM4NDV: Minimizing Data Access for Number of Distinct Values Estimation with Pre-trained Language Models 2025 SIGMOD 5.093636e-05
10,815 Esc: An Early-Stopping Checker for Budget-aware Index Tuning 2025 VLDB 5.093636e-05
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Outgoing Citations (Sorted by Pagerank)

Showing 25 of 25 cited papers.

Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.

Rank Cited Paper Year Venue Pagerank
18 How Good Are Query Optimizers, Really? 2016 VLDB 0.00059284255
154 Neo: A Learned Query Optimizer 2019 VLDB 0.00028726181
156 An Efficient, Cost-Driven Index Selection Tool for Microsoft SQL Server 1997 VLDB 0.00028636811
323 DeepDB: Learn from Data, not from Queries! 2020 VLDB 0.00021264788
378 Bao: Making Learned Query Optimization Practical 2021 SIGMOD 0.00019638121
387 AutoAdmin "What-if" Index Analysis Utility 1998 SIGMOD 0.00019442332
465 An End-to-End Learning-based Cost Estimator 2020 VLDB 0.0001803934
513 NeuroCard: One Cardinality Estimator for All Tables 2021 VLDB 0.00017190574
563 Plan-Structured Deep Neural Network Models for Query Performance Prediction 2019 VLDB 0.0001650812
768 Automatic Physical Database Tuning: A Relaxation-based Approach 2005 SIGMOD 0.00014173242
1,061 Are We Ready For Learned Cardinality Estimation? 2021 VLDB 0.00012369764
1,279 AI Meets AI: Leveraging Query Executions to Improve Index Recommendations 2019 SIGMOD 0.00011361878
1,481 Magic mirror in my hand, which is the best in the land? An Experimental Evaluation of Index Selection Algorithms 2020 VLDB 0.00010644613
1,904 CoPhy: A Scalable, Portable, and Interactive Index Advisor for Large Workloads 2011 VLDB 9.5040429e-05
1,988 FLAT: Fast, Lightweight and Accurate Method for Cardinality Estimation 2021 VLDB 9.3501502e-05
2,355 QueryFormer: A Tree Transformer Model for Query Plan Representation 2022 VLDB 8.7022189e-05
2,812 Query Performance Prediction for Concurrent Queries using Graph Embedding 2020 VLDB 8.0979597e-05
3,338 Robust Query Driven Cardinality Estimation under Changing Workloads 2023 VLDB 7.5068221e-05
4,084 Comprehensive and Efficient Workload Compression 2021 VLDB 6.9151691e-05
4,643 Learned Index Benefits: Machine Learning Based Index Performance Estimation 2022 VLDB 6.5907466e-05
5,091 Budget-aware Index Tuning with Reinforcement Learning 2022 SIGMOD 6.3669569e-05
5,558 HMAB: Self-Driving Hierarchy of Bandits for Integrated Physical Database Design Tuning 2023 VLDB 6.1749098e-05
5,869 ISUM: Efficiently Compressing Large and Complex Workloads for Scalable Index Tuning 2022 SIGMOD 6.0610922e-05
7,750 DISTILL: Low-Overhead Data-Driven Techniques for Filtering and Costing Indexes for Scalable Index Tuning 2022 VLDB 5.5523652e-05
9,491 CEDA: Learned Cardinality Estimation with Domain Adaptation 2023 VLDB 5.2626014e-05
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# Overall Rank Paper Year Venue
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6 10,413 Understanding and Detecting Query Performance Regression in Practical Index Tuning: [Experiments & Analysis] 2026 SIGMOD
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