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AI Meets AI: Leveraging Query Executions to Improve Index Recommendations

Summary: Replaces optimizer-cost plan comparison in index tuning with an ML classifier predicting cheaper plans across configs. Integrates with advanced tuners, delivering up to 5x fewer errors on benchmarks and real workloads, reducing cost regressions. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
hc46501f01faf95e4
Venue
SIGMOD
Year
2019
Pagerank
0.00011224914
Overall Rank
1,280 | 91.40%
DOI
10.1145/3299869.3324957

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@inproceedings{ding_sigmod19,
        title = {{AI Meets AI: Leveraging Query Executions to Improve Index Recommendations}},
        author = {Ding, Bailu and Das, Sudipto and Marcus, Ryan and Wu, Wentao and Chaudhuri, Surajit and Narasayya, Vivek R.},
        series = {{SIGMOD} '19},
        booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
        publisher = {Association for Computing Machinery},
        doi = {10.1145/3299869.3324957},
        url = {https://dl.acm.org/doi/10.1145/3299869.3324957},
        year = {2019}
}

Incoming Citations (Sorted by Pagerank)

Showing 50 of 59 citing papers.

Rank Citing Paper Year Venue Pagerank
361 Bao: Making Learned Query Optimization Practical 2021 SIGMOD 0.00020000855
1,245 DB-BERT: A Database Tuning Tool that "Reads the Manual" 2022 SIGMOD 0.0001136308
1,396 Magic mirror in my hand, which is the best in the land? An Experimental Evaluation of Index Selection Algorithms 2020 VLDB 0.00010788714
1,515 DSB: A Decision Support Benchmark for Workload-Driven and Traditional Database Systems 2021 VLDB 0.00010418766
1,516 Automatically Indexing Millions of Databases in Microsoft Azure SQL Database 2019 SIGMOD 0.00010398346
2,208 Magpie: Python at Speed and Scale using Cloud Backends 2021 CIDR 8.8445332e-05
2,209 Lero: A Learning-to-Rank Query Optimizer 2023 VLDB 8.8360101e-05
2,248 QueryFormer: A Tree Transformer Model for Query Plan Representation 2022 VLDB 8.7567205e-05
2,278 Active Learning for ML Enhanced Database Systems 2020 SIGMOD 8.7057608e-05
3,565 Auto-WLM: Machine Learning Enhanced Workload Management in Amazon Redshift 2023 SIGMOD 7.200937e-05
3,648 UDO: Universal Database Optimization using Reinforcement Learning 2021 VLDB 7.1366536e-05
3,948 Deploying a Steered Query Optimizer in Production at Microsoft 2022 SIGMOD 6.9051584e-05
4,191 Kepler: Robust Learning for Faster Parametric Query Optimization 2023 SIGMOD 6.7425275e-05
4,240 LEON: A New Framework for ML-Aided Query Optimization 2023 VLDB 6.7064546e-05
4,459 Lightweight and Accurate Cardinality Estimation by Neural Network Gaussian Process 2022 SIGMOD 6.5883555e-05
4,713 Learned Index Benefits: Machine Learning Based Index Performance Estimation 2022 VLDB 6.4543291e-05
4,743 Machine Learning for Databases 2021 VLDB 6.4379536e-05
4,970 Budget-aware Index Tuning with Reinforcement Learning 2022 SIGMOD 6.3319052e-05
5,129 Monotonic Cardinality Estimation of Similarity Selection: A Deep Learning Approach 2020 SIGMOD 6.2582129e-05
5,159 Facilitating SQL Query Composition and Analysis 2020 SIGMOD 6.2464819e-05
5,188 Database Workload Characterization with Query Plan Encoders 2022 VLDB 6.2346845e-05
5,216 Stage: Query Execution Time Prediction in Amazon Redshift 2024 SIGMOD 6.2218868e-05
5,438 Eraser: Eliminating Performance Regression on Learned Query Optimizer 2024 VLDB 6.1278045e-05
5,482 A Comparative Study and Component Analysis of Query Plan Representation Techniques in ML4DB Studies 2024 VLDB 6.1123461e-05
5,675 HMAB: Self-Driving Hierarchy of Bandits for Integrated Physical Database Design Tuning 2023 VLDB 6.0401656e-05
5,700 PilotScope: Steering Databases with Machine Learning Drivers 2024 VLDB 6.028998e-05
5,895 Yannakakis+: Practical Acyclic Query Evaluation with Theoretical Guarantees 2025 SIGMOD 5.9534254e-05
5,973 Towards instance-optimized data systems 2021 VLDB 5.9281867e-05
6,107 Breaking It Down: An In-depth Study of Index Advisors 2024 VLDB 5.8833461e-05
6,141 Expand your Training Limits! Generating Training Data for ML-based Data Management 2021 SIGMOD 5.8708409e-05
6,732 A Unified and Efficient Coordinating Framework for Autonomous DBMS Tuning 2023 SIGMOD 5.6921776e-05
6,758 Multi-Tenant Cloud Data Services: State-of-the-Art, Challenges and Opportunities 2022 SIGMOD 5.6877154e-05
7,219 Refactoring Index Tuning Process with Benefit Estimation 2024 VLDB 5.5808392e-05
7,238 RCRank: Multimodal Ranking of Root Causes of Slow Queries in Cloud Database Systems 2025 VLDB 5.5764098e-05
7,356 PerfGuard: Deploying ML-for-Systems without Performance Regressions, Almost! 2021 VLDB 5.5421826e-05
7,773 DBG-PT: A Large Language Model Assisted Query Performance Regression Debugger 2024 VLDB 5.4539148e-05
7,813 Machine Learning for Cloud Data Systems: the Progress so far and the Path Forward 2021 VLDB 5.4474823e-05
7,904 DISTILL: Low-Overhead Data-Driven Techniques for Filtering and Costing Indexes for Scalable Index Tuning 2022 VLDB 5.4277674e-05
7,981 The Holon Approach for Simultaneously Tuning Multiple Components in a Self-Driving Database Management System with Machine Learning via Synthesized Proto-Actions 2024 VLDB 5.4117272e-05
8,779 Automatic Indexing in Oracle 2025 VLDB 5.2781453e-05
9,677 Robustness of Updatable Learning-based Index Advisors against Poisoning Attack 2024 SIGMOD 5.1424302e-05
9,725 APQO: An Adaptive Framework for Parametric Query Optimization 2026 SIGMOD 5.1325223e-05
9,787 Optimizing Dataflow Systems for Scalable Interactive Visualization 2024 SIGMOD 5.1276108e-05
9,796 Wii: Dynamic Budget Reallocation In Index Tuning 2024 SIGMOD 5.1236285e-05
9,926 Waffle: In-memory Grid Index for Moving Objects with Reinforcement Learning-based Configuration Tuning System 2022 VLDB 5.1079647e-05
9,950 Wred: Workload Reduction for Scalable Index Tuning 2024 SIGMOD 5.102891e-05
9,962 Graph Transformers for Query Plan Representation: Potentials and Challenges 2025 VLDB 5.1014161e-05
10,293 AdaChain: A Learned Adaptive Blockchain 2023 VLDB 5.042478e-05
10,296 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 5.0407989e-05
10,424 Are Learned DBMS Components Robust to Workload Drift?: [Experiments & Analysis] 2026 SIGMOD 4.9769913e-05
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Outgoing Citations (Sorted by Pagerank)

Showing 34 of 34 cited papers.

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

Rank Cited Paper Year Venue Pagerank
15 How Good Are Query Optimizers, Really? 2016 VLDB 0.00061067652
40 The Case for Learned Index Structures 2018 SIGMOD 0.00046363107
78 Automatic Database Management System Tuning Through Large-scale Machine Learning 2017 SIGMOD 0.00036675568
98 LEO - DB2's LEarning Optimizer 2001 VLDB 0.00034099838
123 Schism: a Workload-Driven Approach to Database Replication and Partitioning 2010 VLDB 0.00030749898
151 An Efficient, Cost-Driven Index Selection Tool for Microsoft SQL Server 1997 VLDB 0.00028664776
187 DB2 Design Advisor: Integrated Automatic Physical Database Design 2004 VLDB 0.00025914764
195 Integrating Vertical and Horizontal Partitioning into Automated Physical Database Design 2004 SIGMOD 0.00025619089
224 Self-Driving Database Management Systems 2017 CIDR 0.00024011047
232 Adaptive Selectivity Estimation Using Query Feedback 1994 SIGMOD 0.0002378554
243 Automating Physical Database Design in a Parallel Database 2002 SIGMOD 0.00023349603
252 Database Cracking 2007 CIDR 0.00023101361
272 An Overview of Query Optimization in Relational Systems 1998 PODS 0.0002251422
378 AutoAdmin "What-if" Index Analysis Utility 1998 SIGMOD 0.00019541534
492 Database Tuning Advisor for Microsoft SQL Server 2005 2004 VLDB 0.00017406029
508 Adaptive Self-Tuning Memory in DB2 2006 VLDB 0.00017083245
529 Automatic SQL Tuning in Oracle 10g 2004 VLDB 0.00016859276
629 Performance Prediction for Concurrent Database Workloads 2011 SIGMOD 0.00015428007
682 Robust Estimation of Resource Consumption for SQL Queries using Statistical Techniques 2012 VLDB 0.00014814858
781 Self-tuning Database Technology and Information Services: from Wishful Thinking to Viable Engineering 2002 VLDB 0.00014019939
1,200 Bridging the Archipelago between Row-Stores and Column-Stores for Hybrid Workloads 2016 SIGMOD 0.00011559584
1,258 Sampling-Based Query Re-Optimization 2016 SIGMOD 0.00011308863
1,380 H2O: A Hands-free Adaptive Store 2014 SIGMOD 0.00010858313
1,516 Automatically Indexing Millions of Databases in Microsoft Azure SQL Database 2019 SIGMOD 0.00010398346
1,606 The Data Calculator*: Data Structure Design and Cost Synthesis from First Principles and Learned Cost Models 2018 SIGMOD 0.00010091937
1,815 CoPhy: A Scalable, Portable, and Interactive Index Advisor for Large Workloads 2011 VLDB 9.5756946e-05
1,837 Merging What's Cracked, Cracking What's Merged: Adaptive Indexing in Main-Memory Column-Stores 2011 VLDB 9.5315292e-05
2,438 Goal-Oriented Buffer Management Revisited* 1996 SIGMOD 8.4633712e-05
2,776 Automatic Physical Design Tuning: Workload as a Sequence 2006 SIGMOD 8.0278951e-05
2,890 Query Optimizers: Time to Rethink the Contract? 2009 SIGMOD 7.9010819e-05
3,597 Access Path Selection in Main-Memory Optimized Data Systems: Should I Scan or Should I Probe? 2017 SIGMOD 7.1759026e-05
4,692 Columnstore and B+ tree – Are Hybrid Physical Designs Important? 2018 SIGMOD 6.4656516e-05
5,475 A Pay-As-You-Go Framework for Query Execution Feedback 2008 VLDB 6.115573e-05
7,074 Plan Stitch: Harnessing the Best of Many Plans 2018 VLDB 5.604902e-05
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