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LEO - DB2's LEarning Optimizer

Summary: LEO, DB2's LEarning Optimizer, uses a feedback loop to repair cardinality estimates by comparing forecasts with actuals at each QEP step. Online or offline, incremental or batched, it updates costs and statistics across operators (joins, DISTINCT, GROUP BY) with low overhead and large potential gains. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
8917
Venue
VLDB
Year
2001
Pagerank
0.00034385207
Overall Rank
100 | 99.32%
DOI
-

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@article{stillger_vldb01,
        title = {{LEO - DB2's LEarning Optimizer}},
        author = {Stillger, Michael and Lohman, Guy and Markl, Volker and Kandil, Mokhtar},
        journal = {PVLDB},
        series = {{VLDB} '01},
        year = {2001}
}

Incoming Citations (Sorted by Pagerank)

Showing 50 of 122 citing papers.

Rank Citing Paper Year Venue Pagerank
18 How Good Are Query Optimizers, Really? 2016 VLDB 0.00059284255
154 Neo: A Learned Query Optimizer 2019 VLDB 0.00028726181
159 CORDS: Automatic Discovery of Correlations and Soft Functional Dependencies 2004 SIGMOD 0.00028129426
257 The History of Histograms (abridged) 2003 VLDB 0.00023154793
378 Bao: Making Learned Query Optimization Practical 2021 SIGMOD 0.00019638121
401 Deep Unsupervised Cardinality Estimation 2020 VLDB 0.00019092557
492 Robust Query Processing through Progressive Optimization 2004 SIGMOD 0.0001756877
513 NeuroCard: One Cardinality Estimator for All Tables 2021 VLDB 0.00017190574
563 Plan-Structured Deep Neural Network Models for Query Performance Prediction 2019 VLDB 0.0001650812
664 Exploiting Statistics on Query Expressions for Optimization 2002 SIGMOD 0.00015167825
682 Robust Estimation of Resource Consumption for SQL Queries using Statistical Techniques 2012 VLDB 0.00015014887
694 Cardinality Estimation Done Right: Index-Based Join Sampling 2017 CIDR 0.00014911698
697 Selectivity Estimation for Range Predicates using Lightweight Models 2019 VLDB 0.00014888851
781 Self-tuning Database Technology and Information Services: from Wishful Thinking to Viable Engineering 2002 VLDB 0.00014085674
813 Adaptive Ordering of Pipelined Stream Filters 2004 SIGMOD 0.00013846487
984 Analyzing Plan Diagrams of Database Query Optimizers 2005 VLDB 0.00012825643
1,122 Cardinality Estimation in DBMS: A Comprehensive Benchmark Evaluation 2022 VLDB 0.0001209124
1,143 Toward a Progress Indicator for Database Queries 2004 SIGMOD 0.00011999403
1,170 QuickSel: Quick Selectivity Learning with Mixture Models 2020 SIGMOD 0.00011827259
1,256 Sampling-Based Query Re-Optimization 2016 SIGMOD 0.00011457194
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
1,468 Towards a Learning Optimizer for Shared Clouds 2019 VLDB 0.00010686496
1,562 Estimating Progress of Execution for SQL Queries 2004 SIGMOD 0.00010354429
1,604 The Picasso Database Query Optimizer Visualizer 2010 VLDB 0.00010230973
1,648 BHUNT: Automatic Discovery of Fuzzy Algebraic Constraints in Relational Data 2003 VLDB 0.00010120668
1,712 SkinnerDB: Regret-Bounded Query Evaluation via Reinforcement Learning 2019 SIGMOD 9.9492299e-05
1,815 SkinnerDB: Regret-Bounded Query Evaluation via Reinforcement Learning 2018 VLDB 9.6894541e-05
1,936 Consistently Estimating the Selectivity of Conjuncts of Predicates 2005 VLDB 9.4557372e-05
1,982 WeTune: Automatic Discovery and Verification of Query Rewrite Rules 2022 SIGMOD 9.3573897e-05
1,987 Plan Bouquets: Query Processing without Selectivity Estimation 2014 SIGMOD 9.3517129e-05
1,988 FLAT: Fast, Lightweight and Accurate Method for Cardinality Estimation 2021 VLDB 9.3501502e-05
2,121 SASH: A Self-Adaptive Histogram Set for Dynamically Changing Workloads 2003 VLDB 9.1402718e-05
2,157 A Black-Box Approach to Query Cardinality Estimation 2007 CIDR 9.0625592e-05
2,203 Estimating Join Selectivities using Bandwidth-Optimized Kernel Density Models 2017 VLDB 8.9610447e-05
2,269 GORDIAN: Efficient and Scalable Discovery of Composite Keys 2006 VLDB 8.8328424e-05
2,313 Active Learning for ML Enhanced Database Systems 2020 SIGMOD 8.762627e-05
2,589 Statistical Learning Techniques for Costing XML Queries 2005 VLDB 8.371643e-05
2,620 Fauce: Fast and Accurate Deep Ensembles with Uncertainty for Cardinality Estimation 2021 VLDB 8.3363963e-05
2,822 Cost Models for Big Data Query Processing: Learning, Retrofitting, and Our Findings 2020 SIGMOD 8.0898536e-05
2,892 Scalable and Adaptive Online Joins 2014 VLDB 7.9852178e-05
2,944 Query Optimizers: Time to Rethink the Contract? 2009 SIGMOD 7.9335187e-05
2,991 FactorJoin: A New Cardinality Estimation Framework for Join Queries 2023 SIGMOD 7.8880723e-05
2,997 Adapting to Source Properties in Processing Data Integration Queries 2004 SIGMOD 7.8745158e-05
3,051 Towards a Hands-Free Query Optimizer through Deep Learning 2019 CIDR 7.8121919e-05
3,086 A Unified Deep Model of Learning from both Data and Queries for Cardinality Estimation 2021 SIGMOD 7.7708642e-05
3,202 How to Fit when No One Size Fits 2013 CIDR 7.6409287e-05
3,309 Conditional Selectivity for Statistics on Query Expressions 2004 SIGMOD 7.5368417e-05
3,338 Robust Query Driven Cardinality Estimation under Changing Workloads 2023 VLDB 7.5068221e-05
3,426 Exact Cardinality Query Optimization for Optimizer Testing 2009 VLDB 7.4218997e-05
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Outgoing Citations (Sorted by Pagerank)

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