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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
0.00035920657
Overall Rank
84 | 99.44%
DOI
-
PDF
Download (CC BY 3.0)

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 185 citing papers.

Rank Citing Paper Year Venue Pagerank
4,063 The Art of Balance: A RateupDB Experience of Building a CPU/GPU Hybrid Database Product 2021 VLDB 6.812902e-05
4,101 Towards Dynamic and Safe Configuration Tuning for Cloud Databases 2022 SIGMOD 6.7930727e-05
4,202 Kepler: Robust Learning for Faster Parametric Query Optimization 2023 SIGMOD 6.7258607e-05
4,302 A Method for Optimizing Opaque Filter Queries 2020 SIGMOD 6.6614501e-05
4,315 ALECE: An Attention-based Learned Cardinality Estimator for SPJ Queries on Dynamic Workloads 2024 VLDB 6.6545412e-05
4,459 Warper: Efficiently Adapting Learned Cardinality Estimators to Data and Workload Drifts 2022 SIGMOD 6.5757572e-05
4,479 Lightweight and Accurate Cardinality Estimation by Neural Network Gaussian Process 2022 SIGMOD 6.5665703e-05
4,549 One Model to Rule them All: Towards Zero-Shot Learning for Databases 2022 CIDR 6.5328866e-05
4,641 How Good are Learned Cost Models, Really? Insights from Query Optimization Tasks 2025 SIGMOD 6.4739208e-05
4,683 AutoSteer: Learned Query Optimization for Any SQL Database 2023 VLDB 6.4545989e-05
4,703 Learned Cardinality Estimation for Similarity Queries 2021 SIGMOD 6.4458272e-05
4,720 PreQR: Pre-training Representation for SQL Understanding 2022 SIGMOD 6.4353798e-05
4,726 Learned Index Benefits: Machine Learning Based Index Performance Estimation 2022 VLDB 6.4329878e-05
4,765 Machine Learning for Databases 2021 VLDB 6.4166895e-05
4,792 Learned Approximate Query Processing: Make it Light, Accurate and Fast 2021 CIDR 6.4010108e-05
4,797 LSched: A Workload-Aware Learned Query Scheduler for Analytical Database Systems 2022 SIGMOD 6.3978116e-05
4,882 LpBound: Pessimistic Cardinality Estimation using ℓp-Norms of Degree Sequences 2025 SIGMOD 6.3565046e-05
4,915 Can Learned Models Replace Hash Functions? 2023 VLDB 6.3452789e-05
4,971 Debunking the Myth of Join Ordering: Toward Robust SQL Analytics 2025 SIGMOD 6.3209003e-05
5,029 COMPASS: Online Sketch-based Query Optimization for In-Memory Databases 2021 SIGMOD 6.2952031e-05
5,044 Analyzing the Impact of Cardinality Estimation on Execution Plans in Microsoft SQL Server 2023 VLDB 6.2888728e-05
5,075 SafeBound: A Practical System for Generating Cardinality Bounds 2023 SIGMOD 6.2721634e-05
5,126 Steering Query Optimizers: A Practical Take on Big Data Workloads 2021 SIGMOD 6.2493606e-05
5,153 Monotonic Cardinality Estimation of Similarity Selection: A Deep Learning Approach 2020 SIGMOD 6.2375324e-05
5,237 SAM: Database Generation from Query Workloads with Supervised Autoregressive Models 2022 SIGMOD 6.2027113e-05
5,245 FASTgres: Making Learned Query Optimizer Hinting Effective 2023 VLDB 6.1995935e-05
5,453 Eraser: Eliminating Performance Regression on Learned Query Optimizer 2024 VLDB 6.1077838e-05
5,457 Sample-Efficient Cardinality Estimation Using Geometric Deep Learning 2024 VLDB 6.1058928e-05
5,484 A Comparative Study and Component Analysis of Query Plan Representation Techniques in ML4DB Studies 2024 VLDB 6.0980944e-05
5,687 HMAB: Self-Driving Hierarchy of Bandits for Integrated Physical Database Design Tuning 2023 VLDB 6.0201937e-05
5,713 PilotScope: Steering Databases with Machine Learning Drivers 2024 VLDB 6.0090633e-05
5,728 Detect, Distill and Update: Learned DB Systems Facing Out of Distribution Data 2023 SIGMOD 5.9979958e-05
5,837 Pre-training Summarization Models of Structured Datasets for Cardinality Estimation 2022 VLDB 5.9600736e-05
5,841 Joins on Samples: A Theoretical Guide for Practitioners 2020 VLDB 5.9569427e-05
5,854 Modeling Shifting Workloads for Learned Database Systems 2024 SIGMOD 5.9520525e-05
5,926 Quantum-Inspired Digital Annealing for Join Ordering 2024 VLDB 5.9282142e-05
5,982 Towards instance-optimized data systems 2021 VLDB 5.9096991e-05
6,095 From Auto-tuning One Size Fits All to Self-designed and Learned Data-intensive Systems 2019 SIGMOD 5.8706416e-05
6,113 Expand your Training Limits! Generating Training Data for ML-based Data Management 2021 SIGMOD 5.8662826e-05
6,121 Breaking It Down: An In-depth Study of Index Advisors 2024 VLDB 5.863893e-05
6,158 Rethinking Learned Cost Models: Why Start from Scratch? 2023 SIGMOD 5.8518237e-05
6,402 A Unified Transferable Model for ML-Enhanced DBMS 2022 CIDR 5.7800842e-05
6,485 Cardinality Estimation over Knowledge Graphs with Embeddings and Graph Neural Networks 2024 SIGMOD 5.7525455e-05
6,672 Speeding Up End-to-end Query Execution via Learning-based Progressive Cardinality Estimation 2023 SIGMOD 5.6975871e-05
6,725 Simple Adaptive Query Processing vs. Learned Query Optimizers: Observations and Analysis 2023 VLDB 5.6826988e-05
6,768 Multi-Tenant Cloud Data Services: State-of-the-Art, Challenges and Opportunities 2022 SIGMOD 5.6693759e-05
6,812 dbET: Execution Time Distribution-based Plan Selection 2023 SIGMOD 5.6597129e-05
6,840 ASM: Harmonizing Autoregressive Model, Sampling, and Multi-dimensional Statistics Merging for Cardinality Estimation 2024 SIGMOD 5.6513231e-05
6,906 LPLM: A Neural Language Model for Cardinality Estimation of LIKE-Queries 2024 SIGMOD 5.634971e-05
7,175 Learning to Sample: Counting with Complex Queries 2020 VLDB 5.5779755e-05
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Outgoing Citations (Sorted by Pagerank)

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