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DISTILL: Low-Overhead Data-Driven Techniques for Filtering and Costing Indexes for Scalable Index Tuning

Summary: DISTILL enables index tuning via pattern-based pruning of spurious, rule-based indexes to cut optimizer calls. It learns cost models via workload similarity across configs to estimate costs for many candidates, enabling up to 12x faster tuning with high quality. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
h4212c5a19de93caa
Venue
VLDB
Year
2022
Pagerank
5.4303143e-05
Overall Rank
7,900 | 46.89%
DOI
10.14778/3547305.3547309

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@article{siddiqui_vldb22,
        title = {{DISTILL: Low-Overhead Data-Driven Techniques for Filtering and Costing Indexes for Scalable Index Tuning}},
        author = {Siddiqui, Tarique and Wu, Wentao and Narasayya, Vivek and Chaudhuri, Surajit},
        journal = {PVLDB},
        series = {{VLDB} '22},
        volume = {15},
        number = {10},
        pages = {2019--2031},
        doi = {10.14778/3547305.3547309},
        url = {https://doi.org/10.14778/3547305.3547309},
        year = {2022}
}

Incoming Citations (Sorted by Pagerank)

Showing 12 of 12 citing papers.

Rank Citing Paper Year Venue Pagerank
6,105 Breaking It Down: An In-depth Study of Index Advisors 2024 VLDB 5.8860941e-05
7,217 Refactoring Index Tuning Process with Benefit Estimation 2024 VLDB 5.5834823e-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
9,790 Wii: Dynamic Budget Reallocation In Index Tuning 2024 SIGMOD 5.1260323e-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
10,297 Wred: Workload Reduction for Scalable Index Tuning 2024 SIGMOD 5.0430432e-05
10,532 Rainbow: Risk-aware Index Benefit Estimation Facing Out Of Distribution Workloads 2026 SIGMOD 4.9793485e-05
10,604 Understanding and Detecting Query Performance Regression in Practical Index Tuning: [Experiments & Analysis] 2026 SIGMOD 4.9793485e-05
10,681 RIB: Robust Learning-based Index Benefit Estimation 2026 SIGMOD 4.9793485e-05
10,918 Evaluating the Practical Effectiveness of LLM-Driven Index Tuning on Microsoft SQL Server 2026 VLDB 4.9793485e-05
11,224 Esc: An Early-Stopping Checker for Budget-aware Index Tuning 2025 VLDB 4.9793485e-05
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Outgoing Citations (Sorted by Pagerank)

Showing 19 of 19 cited papers.

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

Rank Cited Paper Year Venue Pagerank
151 An Efficient, Cost-Driven Index Selection Tool for Microsoft SQL Server 1997 VLDB 0.00028672526
378 AutoAdmin "What-if" Index Analysis Utility 1998 SIGMOD 0.00019549382
491 Database Tuning Advisor for Microsoft SQL Server 2005 2004 VLDB 0.00017413042
692 Selectivity Estimation for Range Predicates using Lightweight Models 2019 VLDB 0.00014741011
751 Automatic Physical Database Tuning: A Relaxation-based Approach 2005 SIGMOD 0.0001425375
996 Analyzing Plan Diagrams of Database Query Optimizers 2005 VLDB 0.00012634603
1,242 Compressing SQL Workloads 2002 SIGMOD 0.00011373611
1,279 AI Meets AI: Leveraging Query Executions to Improve Index Recommendations 2019 SIGMOD 0.00011226878
1,298 Parametric Query Optimization for Linear and Piecewise Linear Cost Functions 2002 VLDB 0.00011120288
1,397 Magic mirror in my hand, which is the best in the land? An Experimental Evaluation of Index Selection Algorithms 2020 VLDB 0.00010789242
1,516 Automatically Indexing Millions of Databases in Microsoft Azure SQL Database 2019 SIGMOD 0.00010402594
1,789 Plan Selection based on Query Clustering 2002 VLDB 9.6293635e-05
2,023 Efficient Use of the Query Optimizer for Automated Physical Design 2007 VLDB 9.1669658e-05
2,373 To Tune or not to Tune? A Lightweight Physical Design Alerter 2006 VLDB 8.5606392e-05
2,834 Cost Models for Big Data Query Processing: Learning, Retrofitting, and Our Findings 2020 SIGMOD 7.9560627e-05
3,210 Efficiently Approximating Selectivity Functions using Low Overhead Regression Models 2020 VLDB 7.5363533e-05
3,815 Comprehensive and Efficient Workload Compression 2021 VLDB 7.0075744e-05
4,968 Budget-aware Index Tuning with Reinforcement Learning 2022 SIGMOD 6.3348803e-05
5,630 ISUM: Efficiently Compressing Large and Complex Workloads for Scalable Index Tuning 2022 SIGMOD 6.0582762e-05
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