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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
8727
Venue
VLDB
Year
2001
Pagerank
0.00036970794
Overall Rank
181 | 98.75%
DOI
-

Incoming Non-self Citations Over Time

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Incoming Citations (Sorted by Pagerank)

Showing 50 of 122 citing papers.

Rank Citing Paper Year Venue Pagerank
71 How Good Are Query Optimizers, Really? 2016 VLDB 0.00059446482
224 CORDS: Automatic Discovery of Correlations and Soft Functional Dependencies 2004 SIGMOD 0.00032743209
325 The History of Histograms (abridged) 2003 VLDB 0.00027398081
329 Neo: A Learned Query Optimizer 2019 VLDB 0.00027301488
634 Bao: Making Learned Query Optimization Practical 2021 SIGMOD 0.00018844568
650 Robust Query Processing through Progressive Optimization 2004 SIGMOD 0.0001865144
752 Deep Unsupervised Cardinality Estimation 2020 VLDB 0.00017138049
786 Exploiting Statistics on Query Expressions for Optimization 2002 SIGMOD 0.00016624743
841 Self-tuning Database Technology and Information Services: from Wishful Thinking to Viable Engineering 2002 VLDB 0.00015987128
876 Plan-Structured Deep Neural Network Models for Query Performance Prediction 2019 VLDB 0.00015660534
905 NeuroCard: One Cardinality Estimator for All Tables 2021 VLDB 0.00015423174
1,017 Robust Estimation of Resource Consumption for SQL Queries using Statistical Techniques 2012 VLDB 0.00014627121
1,041 Adaptive Ordering of Pipelined Stream Filters 2004 SIGMOD 0.00014470785
1,064 Analyzing Plan Diagrams of Database Query Optimizers 2005 VLDB 0.00014348262
1,104 Cardinality Estimation Done Right: Index-Based Join Sampling 2017 CIDR 0.0001398479
1,229 Toward a Progress Indicator for Database Queries 2004 SIGMOD 0.00013153898
1,239 Selectivity Estimation for Range Predicates using Lightweight Models 2019 VLDB 0.00013091459
1,297 The Picasso Database Query Optimizer Visualizer 2010 VLDB 0.00012732768
1,443 Compressing SQL Workloads 2002 SIGMOD 0.00011944621
1,509 Estimating Progress of Execution for SQL Queries 2004 SIGMOD 0.0001158945
1,638 Cardinality Estimation in DBMS: A Comprehensive Benchmark Evaluation 2022 VLDB 0.00011050093
1,727 QuickSel: Quick Selectivity Learning with Mixture Models 2020 SIGMOD 0.00010731889
1,756 Sampling-Based Query Re-Optimization 2016 SIGMOD 0.00010659753
1,856 AI Meets AI: Leveraging Query Executions to Improve Index Recommendations 2019 SIGMOD 0.00010319105
1,976 BHUNT: Automatic Discovery of Fuzzy Algebraic Constraints in Relational Data 2003 VLDB 9.8784644e-05
2,080 Towards a Learning Optimizer for Shared Clouds 2019 VLDB 9.5954034e-05
2,136 SASH: A Self-Adaptive Histogram Set for Dynamically Changing Workloads 2003 VLDB 9.4668797e-05
2,154 SkinnerDB: Regret-Bounded Query Evaluation via Reinforcement Learning 2018 VLDB 9.4176683e-05
2,222 SkinnerDB: Regret-Bounded Query Evaluation via Reinforcement Learning 2019 SIGMOD 9.2598438e-05
2,359 Consistently Estimating the Selectivity of Conjuncts of Predicates 2005 VLDB 8.967267e-05
2,551 GORDIAN: Efficient and Scalable Discovery of Composite Keys 2006 VLDB 8.5553153e-05
2,595 WeTune: Automatic Discovery and Verification of Query Rewrite Rules 2022 SIGMOD 8.4725961e-05
2,632 Plan Bouquets: Query Processing without Selectivity Estimation 2014 SIGMOD 8.4153283e-05
2,667 Statistical Learning Techniques for Costing XML Queries 2005 VLDB 8.3444649e-05
2,671 A Black-Box Approach to Query Cardinality Estimation 2007 CIDR 8.3385014e-05
2,769 FLAT: Fast, Lightweight and Accurate Method for Cardinality Estimation 2021 VLDB 8.1512848e-05
2,971 Estimating Join Selectivities using Bandwidth-Optimized Kernel Density Models 2017 VLDB 7.7935535e-05
3,040 How to Fit when No One Size Fits 2013 CIDR 7.6672864e-05
3,144 Active Learning for ML Enhanced Database Systems 2020 SIGMOD 7.4844943e-05
3,331 Adapting to Source Properties in Processing Data Integration Queries 2004 SIGMOD 7.2094696e-05
3,384 Scalable and Adaptive Online Joins 2014 VLDB 7.153329e-05
3,402 Query Optimizers: Time to Rethink the Contract? 2009 SIGMOD 7.134261e-05
3,492 Fauce: Fast and Accurate Deep Ensembles with Uncertainty for Cardinality Estimation 2021 VLDB 7.0435484e-05
3,623 Cost Models for Big Data Query Processing: Learning, Retrofitting, and Our Findings 2020 SIGMOD 6.9017341e-05
3,656 Conditional Selectivity for Statistics on Query Expressions 2004 SIGMOD 6.8712579e-05
3,658 Towards a Hands-Free Query Optimizer through Deep Learning 2019 CIDR 6.8700949e-05
3,699 Lazy, Adaptive RID-List Intersection, and Its Application to Index Anding 2007 SIGMOD 6.827026e-05
3,924 A Unified Deep Model of Learning from both Data and Queries for Cardinality Estimation 2021 SIGMOD 6.6227223e-05
3,943 Exact Cardinality Query Optimization for Optimizer Testing 2009 VLDB 6.6067351e-05
3,966 Apache Hive: From MapReduce to Enterprise-grade Big Data Warehousing 2019 SIGMOD 6.5782437e-05
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Outgoing Citations (Sorted by Pagerank)

Showing 11 of 11 cited papers.

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

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Semantically Similar Papers

Overall Rank Paper Year Venue Pagerank
1,268 Proactive Re-Optimization 2005 SIGMOD 0.00012914584
1,756 Sampling-Based Query Re-Optimization 2016 SIGMOD 0.00010659753
7,326 Lemo: A Cache-Enhanced Learned Optimizer for Concurrent Queries 2023 SIGMOD 4.7563708e-05
329 Neo: A Learned Query Optimizer 2019 VLDB 0.00027301488
7,220 Speeding Up End-to-end Query Execution via Learning-based Progressive Cardinality Estimation 2023 SIGMOD 4.7926382e-05
11,352 DeepO: A Learned Query Optimizer 2022 SIGMOD 4.1905499e-05
5,339 LEON: A New Framework for ML-Aided Query Optimization 2023 VLDB 5.5596755e-05
10,225 LIO: A lightweight and interpretable query optimizer based on an evolutionary forest 2026 VLDB 4.1905499e-05
3,345 Lero: A Learning-to-Rank Query Optimizer 2023 VLDB 7.1908499e-05
8,118 Learning Table Access Cardinalities with LEO 2002 SIGMOD 4.5783775e-05