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Learned Cardinalities: Estimating Correlated Joins with Deep Learning

Summary: Proposes MSCN, a multi-set convolutional network that encodes relational query plans with set semantics to learn cardinalities and capture join-crossing correlations. Combines deep learning with sampling to handle zero-sample cases, yielding much better estimates on real-world data. (summarized by gpt-5-mini on Feb 09 2026)

Paper ID
hac0e2fce2cb9474d
Venue
CIDR
Year
2019
Pagerank
0.00035864347
Overall Rank
85 | 99.44%
DOI
-

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@inproceedings{kipf_cidr19,
        address = {Amsterdam, Netherlands},
        series = {{CIDR} '19},
        title = {{Learned Cardinalities: Estimating Correlated Joins with Deep Learning}},
        booktitle = {Proceedings of the {Conference} on {Innovative} {Data} {Systems} {Research}},
        author = {Kipf, Andreas and Kipf, Thomas and Radke, Bernhard and Leis, Viktor and Boncz, Peter and Kemper, Alfons},
        year = {2019}
}

Incoming Citations (Sorted by Pagerank)

Showing 50 of 184 citing papers.

Rank Citing Paper Year Venue Pagerank
7,236 RCRank: Multimodal Ranking of Root Causes of Slow Queries in Cloud Database Systems 2025 VLDB 5.5790509e-05
7,332 Selectivity Functions of Range Queries are Learnable* 2022 SIGMOD 5.5499953e-05
7,341 Scalable Multi-Query Execution using Reinforcement Learning 2021 SIGMOD 5.5481233e-05
7,363 PerfGuard: Deploying ML-for-Systems without Performance Regressions, Almost! 2021 VLDB 5.5418564e-05
7,385 Towards Foundation Database Models 2025 CIDR 5.5385053e-05
7,410 POLAR: Adaptive and Non-invasive Join Order Selection via Plans of Least Resistance 2024 VLDB 5.5342768e-05
7,417 Cardinality Estimation of Approximate Substring Queries using Deep Learning 2022 VLDB 5.5327978e-05
7,429 Learning to be a Statistician: Learned Estimator for Number of Distinct Values 2022 VLDB 5.5300853e-05
7,460 T3: Accurate and Fast Performance Prediction for Relational Database Systems With Compiled Decision Trees 2025 SIGMOD 5.5215755e-05
7,822 Bespoke OLAP: Synthesizing Workload-Specific One-size-fits-one Database Engines 2026 VLDB 5.4461624e-05
7,907 A Practical Approach to Groupjoin and Nested Aggregates 2021 VLDB 5.4287568e-05
7,954 Robust Query Processing: Mission Possible 2020 VLDB 5.4190023e-05
8,164 Efficient Query Re-optimization with Judicious Subquery Selections 2023 SIGMOD 5.3852872e-05
8,258 The Case for NLP-Enhanced Database Tuning: Towards Tuning Tools that “Read the Manual” 2021 VLDB 5.3671363e-05
8,276 Consistent and Flexible Selectivity Estimation for High-Dimensional Data 2021 SIGMOD 5.3641556e-05
8,332 Learned Offline Query Planning via Bayesian Optimization 2025 SIGMOD 5.3528188e-05
8,389 PARQO: Penalty-Aware Robust Plan Selection in Query Optimization 2024 VLDB 5.3413016e-05
8,403 The Case for Learned In-Memory Joins 2023 VLDB 5.3389852e-05
8,524 ROME: Robust Query Optimization via Parallel Multi-Plan Execution 2024 SIGMOD 5.3231221e-05
8,532 AirIndex: Versatile Index Tuning Through Data and Storage 2023 SIGMOD 5.3217474e-05
8,580 Conditional Cuckoo Filters 2021 SIGMOD 5.3100462e-05
8,659 ShadowAQP: Efficient Approximate Group-by and Join Query via Attribute-oriented Sample Size Allocation and Data Generation 2023 VLDB 5.2930951e-05
8,800 PACE: Poisoning Attacks on Learned Cardinality Estimation 2024 SIGMOD 5.2742531e-05
8,850 SkinnerMT: Parallelizing for Efficiency and Robustness in Adaptive Query Processing on Multicore Platforms 2023 VLDB 5.2645282e-05
8,946 HAP: An Efficient Hamming Space Index Based on Augmented Pigeonhole Principle 2022 SIGMOD 5.2532874e-05
8,947 Machine Unlearning in Learned Databases: An Experimental Analysis 2024 SIGMOD 5.2532248e-05
9,012 ByteCard: Enhancing ByteDance’s Data Warehouse with Learned Cardinality Estimation 2024 SIGMOD 5.2375369e-05
9,173 Towards Enhancing Database Education: Natural Language Generation Meets Query Execution Plans 2021 SIGMOD 5.2135302e-05
9,209 NeuroSketch: Fast and Approximate Evaluation of Range Aggregate Queries with Neural Networks 2023 SIGMOD 5.2061781e-05
9,300 GenJoin: Conditional Generative Plan-to-Plan Query Optimizer that Learns from Subplan Hints 2026 SIGMOD 5.1987909e-05
9,358 Phoebe: A Learning-based Checkpoint Optimizer 2021 VLDB 5.1869771e-05
9,372 Efficient and Effective Cardinality Estimation for Skyline Family 2023 SIGMOD 5.1868213e-05
9,546 Athena: An Effective Learning-based Framework for Query Optimizer Performance Improvement 2025 SIGMOD 5.1604755e-05
9,610 LIMAO: A Framework for Lifelong Modular Learned Query Optimization 2025 VLDB 5.1526493e-05
9,632 Small Selectivities Matter: Lifting the Burden of Empty Samples 2021 SIGMOD 5.1472849e-05
9,641 CEDA: Learned Cardinality Estimation with Domain Adaptation 2023 VLDB 5.1456789e-05
9,670 Low Rank Learning for Offline Query Optimization 2025 SIGMOD 5.1452097e-05
9,718 A Practical Theory of Generalization in Selectivity Learning 2025 VLDB 5.1353964e-05
9,797 NeuSO: Neural Optimizer for Subgraph Queries 2026 SIGMOD 5.1257999e-05
9,893 Approximate Sketches 2024 SIGMOD 5.1134687e-05
9,910 Cardinality Estimation for Similarity Search on High-Dimensional Data Objects: The Impact of Reference Objects 2025 VLDB 5.1103839e-05
9,954 Conformal Prediction for Verifiable Learned Query Optimization 2025 VLDB 5.1038322e-05
9,956 Graph Transformers for Query Plan Representation: Potentials and Challenges 2025 VLDB 5.1038322e-05
9,976 Selectivity Estimation for Queries Containing Predicates over Set-Valued Attributes 2023 SIGMOD 5.1031384e-05
10,027 Cardinality Estimation of LIKE Predicate Queries using Deep Learning 2025 SIGMOD 5.0925739e-05
10,057 SPACE: Cardinality Estimation for Path Queries Using Cardinality-Aware Sequence-based Learning 2025 SIGMOD 5.0875952e-05
10,103 Still Asking: How Good Are Query Optimizers, Really? 2025 VLDB 5.0789354e-05
10,148 Improving DBMS Scheduling Decisions with Accurate Performance Prediction on Concurrent Queries 2025 VLDB 5.0715586e-05
10,156 Generating Application-Specific Data Layouts for In-memory Databases 2019 VLDB 5.0707546e-05
10,184 Path-centric Cardinality Estimation for Subgraph Matching 2025 VLDB 5.0651993e-05
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Outgoing Citations (Sorted by Pagerank)

Showing 14 of 14 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 0.00061066921
40 The Case for Learned Index Structures 2018 SIGMOD 0.00046284649
78 Automatic Database Management System Tuning Through Large-scale Machine Learning 2017 SIGMOD 0.00036684414
103 Selectivity Estimation Without the Attribute Value Independence Assumption 1997 VLDB 0.00033894985
386 Preventing Bad Plans by Bounding the Impact of Cardinality Estimation Errors 2009 VLDB 0.00019444411
682 Robust Estimation of Resource Consumption for SQL Queries using Statistical Techniques 2012 VLDB 0.0001481781
688 Cardinality Estimation Done Right: Index-Based Join Sampling 2017 CIDR 0.00014753664
750 Join Size Estimation Subject to Filter Conditions 2015 VLDB 0.00014265196
1,186 Adaptive Optimization of Very Large Join Queries 2018 SIGMOD 0.0001160797
1,257 Sampling-Based Query Re-Optimization 2016 SIGMOD 0.00011310561
1,542 Improved Selectivity Estimation by Combining Knowledge from Sampling and Synopses 2018 VLDB 0.00010308631
1,678 Two-Level Sampling for Join Size Estimation 2017 SIGMOD 9.9088372e-05
2,172 A Black-Box Approach to Query Cardinality Estimation 2007 CIDR 8.9214171e-05
2,303 Selectivity Estimation in Extensible Databases - A Neural Network Approach 1998 VLDB 8.6708797e-05
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Semantically Similar Papers

# Overall Rank Paper Year Venue
1 406 Deep Unsupervised Cardinality Estimation 2020 VLDB
2 1,064 Are We Ready For Learned Cardinality Estimation? 2021 VLDB
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4 7,417 Cardinality Estimation of Approximate Substring Queries using Deep Learning 2022 VLDB
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6 10,027 Cardinality Estimation of LIKE Predicate Queries using Deep Learning 2025 SIGMOD
7 2,342 Learned Cardinality Estimation: An In-depth Study 2022 SIGMOD
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