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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
5766
Venue
SIGMOD
Year
2019
Pagerank
0.00010315245
Overall Rank
1,855 | 87.10%
DOI
10.1145/3299869.3324957

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Showing 7 of 57 citing papers.

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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
71 How Good Are Query Optimizers, Really? 2016 VLDB 0.00059038975
102 The Case for Learned Index Structures 2018 SIGMOD 0.00049545203
182 LEO - DB2's LEarning Optimizer 2001 VLDB 0.00036962631
183 Automatic Database Management System Tuning Through Large-scale Machine Learning 2017 SIGMOD 0.00036721403
209 Schism: a Workload-Driven Approach to Database Replication and Partitioning 2010 VLDB 0.00034468292
237 An Efficient, Cost-Driven Index Selection Tool for Microsoft SQL Server 1997 VLDB 0.00031726304
252 Adaptive Selectivity Estimation Using Query Feedback 1994 SIGMOD 0.00030632263
258 DB2 Design Advisor: Integrated Automatic Physical Database Design 2004 VLDB 0.0003022091
285 Automating Physical Database Design in a Parallel Database 2002 SIGMOD 0.0002899128
286 Integrating Vertical and Horizontal Partitioning into Automated Physical Database Design 2004 SIGMOD 0.00028990057
359 Self-Driving Database Management Systems 2017 CIDR 0.0002592783
408 Database Cracking 2007 CIDR 0.00023953844
454 An Overview of Query Optimization in Relational Systems 1998 PODS 0.00022734812
496 Automatic SQL Tuning in Oracle 10g 2004 VLDB 0.00021728655
516 AutoAdmin "What-if" Index Analysis Utility 1998 SIGMOD 0.00021196031
661 Database Tuning Advisor for Microsoft SQL Server 2005 2004 VLDB 0.00018481174
663 Adaptive Self-Tuning Memory in DB2 2006 VLDB 0.00018469455
718 Performance Prediction for Concurrent Database Workloads 2011 SIGMOD 0.0001763106
846 Self-tuning Database Technology and Information Services: from Wishful Thinking to Viable Engineering 2002 VLDB 0.00015997985
1,019 Robust Estimation of Resource Consumption for SQL Queries using Statistical Techniques 2012 VLDB 0.00014625603
1,700 Bridging the Archipelago between Row-Stores and Column-Stores for Hybrid Workloads 2016 SIGMOD 0.00010858865
1,758 Sampling-Based Query Re-Optimization 2016 SIGMOD 0.00010655546
1,807 H2O: A Hands-free Adaptive Store 2014 SIGMOD 0.00010487796
2,047 Automatically Indexing Millions of Databases in Microsoft Azure SQL Database 2019 SIGMOD 9.6920209e-05
2,157 The Data Calculator*: Data Structure Design and Cost Synthesis from First Principles and Learned Cost Models 2018 SIGMOD 9.416022e-05
2,363 Merging What’s Cracked, Cracking What’s Merged: Adaptive Indexing in Main-Memory Column-Stores 2011 VLDB 8.9580928e-05
2,470 CoPhy: A Scalable, Portable, and Interactive Index Advisor for Large Workloads 2011 VLDB 8.7333019e-05
2,624 Goal-Oriented Buffer Management Revisited* 1996 SIGMOD 8.4332581e-05
2,828 Automatic Physical Design Tuning: Workload as a Sequence 2006 SIGMOD 8.0548516e-05
3,408 Query Optimizers: Time to Rethink the Contract? 2009 SIGMOD 7.1288167e-05
4,161 Access Path Selection in Main-Memory Optimized Data Systems: Should I Scan or Should I Probe? 2017 SIGMOD 6.3938006e-05
5,113 Columnstore and B+ tree – Are Hybrid Physical Designs Important? 2018 SIGMOD 5.687445e-05
5,668 A Pay-As-You-Go Framework for Query Execution Feedback 2008 VLDB 5.3806337e-05
7,776 Plan Stitch: Harnessing the Best of Many Plans 2018 VLDB 4.6537231e-05
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