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Esc: An Early-Stopping Checker for Budget-aware Index Tuning

Summary: Identifies diminishing returns in budget-aware index tuning caused by expensive what-if optimizer calls and proposes early stopping via a user-specified tolerable-loss threshold that projects the impact of the remaining budget. Introduces Esc, a low-overhead checker that halts tuning when projected quality loss is below the threshold, drastically reducing what-if calls on benchmarks and real workloads with minimal or zero index-quality degradation. (summarized by gpt-5-mini on Feb 09 2026)

Paper ID
13797
Venue
VLDB
Year
2025
Pagerank
4.1905499e-05
Overall Rank
10,552 | 26.67%
DOI
10.14778/3718057.3718059

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

Rank Cited Paper Year Venue Pagerank
160 Automated Selection of Materialized Views and Indexes for SQL Databases 2000 VLDB 0.00040053897
237 An Efficient, Cost-Driven Index Selection Tool for Microsoft SQL Server 1997 VLDB 0.00031727601
329 Neo: A Learned Query Optimizer 2019 VLDB 0.00027301488
517 AutoAdmin "What-if" Index Analysis Utility 1998 SIGMOD 0.00021193179
804 An End-to-End Learning-based Cost Estimator 2020 VLDB 0.0001643674
876 Plan-Structured Deep Neural Network Models for Query Performance Prediction 2019 VLDB 0.00015660534
1,017 Robust Estimation of Resource Consumption for SQL Queries using Statistical Techniques 2012 VLDB 0.00014627121
1,018 Automatic Physical Database Tuning: A Relaxation-based Approach 2005 SIGMOD 0.00014626746
1,756 Sampling-Based Query Re-Optimization 2016 SIGMOD 0.00010659753
1,856 AI Meets AI: Leveraging Query Executions to Improve Index Recommendations 2019 SIGMOD 0.00010319105
2,022 Magic mirror in my hand, which is the best in the land? An Experimental Evaluation of Index Selection Algorithms 2020 VLDB 9.7623022e-05
2,467 CoPhy: A Scalable, Portable, and Interactive Index Advisor for Large Workloads 2011 VLDB 8.7264908e-05
2,479 Efficient Use of the Query Optimizer for Automated Physical Design 2007 VLDB 8.6836615e-05
3,167 QueryFormer: A Tree Transformer Model for Query Plan Representation 2022 VLDB 7.4561078e-05
3,623 Cost Models for Big Data Query Processing: Learning, Retrofitting, and Our Findings 2020 SIGMOD 6.9017341e-05
3,819 Zero-Shot Cost Models for Out-of-the-box Learned Cost Prediction 2022 VLDB 6.7267885e-05
4,075 Towards Predicting Query Execution Time for Concurrent and Dynamic Database Workloads 2013 VLDB 6.4699689e-05
5,055 Index Interactions in Physical Design Tuning: Modeling, Analysis, and Applications 2009 VLDB 5.72317e-05
5,343 Learned Index Benefits: Machine Learning Based Index Performance Estimation 2022 VLDB 5.5582234e-05
5,645 Database Workload Characterization with Query Plan Encoders 2022 VLDB 5.3928148e-05
5,673 Budget-aware Index Tuning with Reinforcement Learning 2022 SIGMOD 5.3789277e-05
5,925 HMAB: Self-Driving Hierarchy of Bandits for Integrated Physical Database Design Tuning 2023 VLDB 5.2669029e-05
6,277 Uncertainty Aware Query Execution Time Prediction 2014 VLDB 5.1260947e-05
6,364 ISUM: Efficiently Compressing Large and Complex Workloads for Scalable Index Tuning 2022 SIGMOD 5.0895007e-05
6,753 Breaking It Down: An In-depth Study of Index Advisors 2024 VLDB 4.9345582e-05
7,332 Refactoring Index Tuning Process with Benefit Estimation 2024 VLDB 4.7553758e-05
7,776 Plan Stitch: Harnessing the Best of Many Plans 2018 VLDB 4.6493147e-05
8,043 DISTILL: Low-Overhead Data-Driven Techniques for Filtering and Costing Indexes for Scalable Index Tuning 2022 VLDB 4.5954398e-05
9,930 Wred: Workload Reduction for Scalable Index Tuning 2024 SIGMOD 4.2469394e-05
9,931 Wii: Dynamic Budget Reallocation In Index Tuning 2024 SIGMOD 4.2469394e-05
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