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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
12887
Venue
VLDB
Year
2022
Pagerank
5.5523652e-05
Overall Rank
7,750 | 46.83%
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 11 of 11 citing papers.

Rank Citing Paper Year Venue Pagerank
6,327 Breaking It Down: An In-depth Study of Index Advisors 2024 VLDB 5.9124005e-05
7,076 Refactoring Index Tuning Process with Benefit Estimation 2024 VLDB 5.7098893e-05
7,846 The Holon Approach for Simultaneously Tuning Multiple Components in a Self-Driving Database Management System with Machine Learning via Synthesized Proto-Actions 2024 VLDB 5.5331459e-05
8,984 Hit the Gym: Accelerating Query Execution to Efficiently Bootstrap Behavior Models for Self-Driving Database Management Systems 2024 VLDB 5.3395569e-05
9,615 Wii: Dynamic Budget Reallocation In Index Tuning 2024 SIGMOD 5.2436464e-05
10,082 Wred: Workload Reduction for Scalable Index Tuning 2024 SIGMOD 5.1587525e-05
10,327 Rainbow: Risk-aware Index Benefit Estimation Facing Out Of Distribution Workloads 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
10,506 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 5.093636e-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 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
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
501 Database Tuning Advisor for Microsoft SQL Server 2005 2004 VLDB 0.0001738508
697 Selectivity Estimation for Range Predicates using Lightweight Models 2019 VLDB 0.00014888851
768 Automatic Physical Database Tuning: A Relaxation-based Approach 2005 SIGMOD 0.00014173242
984 Analyzing Plan Diagrams of Database Query Optimizers 2005 VLDB 0.00012825643
1,266 Compressing SQL Workloads 2002 SIGMOD 0.00011412078
1,279 AI Meets AI: Leveraging Query Executions to Improve Index Recommendations 2019 SIGMOD 0.00011361878
1,321 Parametric Query Optimization for Linear and Piecewise Linear Cost Functions 2002 VLDB 0.00011162369
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
1,548 Automatically Indexing Millions of Databases in Microsoft Azure SQL Database 2019 SIGMOD 0.00010392475
1,771 Plan Selection based on Query Clustering 2002 VLDB 9.7942089e-05
1,997 Efficient Use of the Query Optimizer for Automated Physical Design 2007 VLDB 9.3378162e-05
2,364 To Tune or not to Tune? A Lightweight Physical Design Alerter 2006 VLDB 8.6869645e-05
2,822 Cost Models for Big Data Query Processing: Learning, Retrofitting, and Our Findings 2020 SIGMOD 8.0898536e-05
3,162 Efficiently Approximating Selectivity Functions using Low Overhead Regression Models 2020 VLDB 7.6785856e-05
4,084 Comprehensive and Efficient Workload Compression 2021 VLDB 6.9151691e-05
5,091 Budget-aware Index Tuning with Reinforcement Learning 2022 SIGMOD 6.3669569e-05
5,869 ISUM: Efficiently Compressing Large and Complex Workloads for Scalable Index Tuning 2022 SIGMOD 6.0610922e-05
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