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Wii: Dynamic Budget Reallocation In Index Tuning

Summary: Wii addresses budgeted index tuning by dynamically reallocating what-if calls away from QCPs whose optimizer costs can be safely derived, avoiding spurious expensive evaluations. Lightweight and plug-in compatible with existing enumeration methods, it improves final configurations by spending budget where cost derivation is less accurate. (summarized by gpt-5.4-mini on May 24 2026)

Paper ID
7007
Venue
SIGMOD
Year
2024
Pagerank
5.2436464e-05
Overall Rank
9,615 | 34.04%
DOI
10.1145/3654985

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@inproceedings{wang_sigmod24,
        title = {{Wii: Dynamic Budget Reallocation In Index Tuning}},
        author = {Wang, Xiaoying and Wu, Wentao and Wang, Chi and Narasayya, Vivek and Chaudhuri, Surajit},
        series = {{SIGMOD} '24},
        booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
        publisher = {Association for Computing Machinery},
        doi = {10.1145/3654985},
        url = {https://dl.acm.org/doi/10.1145/3654985},
        year = {2024}
}

Incoming Citations (Sorted by Pagerank)

Showing 5 of 5 citing papers.

Rank Citing Paper Year Venue Pagerank
8,984 Hit the Gym: Accelerating Query Execution to Efficiently Bootstrap Behavior Models for Self-Driving Database Management Systems 2024 VLDB 5.3395569e-05
10,277 On Self-Designing Learned Indexes 2026 SIGMOD 5.093636e-05
10,413 Understanding and Detecting Query Performance Regression in Practical Index Tuning: [Experiments & Analysis] 2026 SIGMOD 5.093636e-05
10,494 RIB: Robust Learning-based Index Benefit Estimation 2026 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 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
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
387 AutoAdmin "What-if" Index Analysis Utility 1998 SIGMOD 0.00019442332
465 An End-to-End Learning-based Cost Estimator 2020 VLDB 0.0001803934
563 Plan-Structured Deep Neural Network Models for Query Performance Prediction 2019 VLDB 0.0001650812
682 Robust Estimation of Resource Consumption for SQL Queries using Statistical Techniques 2012 VLDB 0.00015014887
768 Automatic Physical Database Tuning: A Relaxation-based Approach 2005 SIGMOD 0.00014173242
1,256 Sampling-Based Query Re-Optimization 2016 SIGMOD 0.00011457194
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
1,997 Efficient Use of the Query Optimizer for Automated Physical Design 2007 VLDB 9.3378162e-05
2,355 QueryFormer: A Tree Transformer Model for Query Plan Representation 2022 VLDB 8.7022189e-05
2,822 Cost Models for Big Data Query Processing: Learning, Retrofitting, and Our Findings 2020 SIGMOD 8.0898536e-05
2,844 Zero-Shot Cost Models for Out-of-the-box Learned Cost Prediction 2022 VLDB 8.0608767e-05
3,482 Towards Predicting Query Execution Time for Concurrent and Dynamic Database Workloads 2013 VLDB 7.3751635e-05
4,550 Index Interactions in Physical Design Tuning: Modeling, Analysis, and Applications 2009 VLDB 6.635765e-05
4,643 Learned Index Benefits: Machine Learning Based Index Performance Estimation 2022 VLDB 6.5907466e-05
5,073 Database Workload Characterization with Query Plan Encoders 2022 VLDB 6.3751266e-05
5,091 Budget-aware Index Tuning with Reinforcement Learning 2022 SIGMOD 6.3669569e-05
5,537 Uncertainty Aware Query Execution Time Prediction 2014 VLDB 6.1820087e-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
10,082 Wred: Workload Reduction for Scalable Index Tuning 2024 SIGMOD 5.1587525e-05
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