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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
0.00035876108
Overall Rank
85 | 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 184 citing papers.

Rank Citing Paper Year Venue Pagerank
144 Neo: A Learned Query Optimizer 2019 VLDB 0.00029090793
318 DeepDB: Learn from Data, not from Queries! 2020 VLDB 0.00021166957
361 Bao: Making Learned Query Optimization Practical 2021 SIGMOD 0.00020000855
406 Deep Unsupervised Cardinality Estimation 2020 VLDB 0.00019050182
422 ALEX: An Updatable Adaptive Learned Index 2020 SIGMOD 0.00018488849
462 An End-to-End Learning-based Cost Estimator 2020 VLDB 0.00017836105
510 NeuroCard: One Cardinality Estimator for All Tables 2021 VLDB 0.00017059914
555 SageDB: A Learned Database System 2019 CIDR 0.0001650754
560 Plan-Structured Deep Neural Network Models for Query Performance Prediction 2019 VLDB 0.00016408613
691 Selectivity Estimation for Range Predicates using Lightweight Models 2019 VLDB 0.00014737455
981 Cardinality Estimation in DBMS: A Comprehensive Benchmark Evaluation 2022 VLDB 0.00012713454
1,065 Are We Ready For Learned Cardinality Estimation? 2021 VLDB 0.00012202293
1,155 QuickSel: Quick Selectivity Learning with Mixture Models 2020 SIGMOD 0.00011777046
1,195 Balsa: Learning a Query Optimizer Without Expert Demonstrations 2022 SIGMOD 0.00011574218
1,515 DSB: A Decision Support Benchmark for Workload-Driven and Traditional Database Systems 2021 VLDB 0.00010418766
1,580 Deep Learning Models for Selectivity Estimation of Multi-Attribute Queries 2020 SIGMOD 0.00010177136
1,735 Flow-Loss: Learning Cardinality Estimates That Matter 2021 VLDB 9.7566604e-05
1,890 WeTune: Automatic Discovery and Verification of Query Rewrite Rules 2022 SIGMOD 9.4234723e-05
1,975 CodexDB: Synthesizing Code for Query Processing from Natural Language Instructions using GPT-3 Codex 2022 VLDB 9.2801545e-05
2,002 FLAT: Fast, Lightweight and Accurate Method for Cardinality Estimation 2021 VLDB 9.2076835e-05
2,209 Lero: A Learning-to-Rank Query Optimizer 2023 VLDB 8.8360101e-05
2,237 Designing Succinct Secondary Indexing Mechanism by Exploiting Column Correlations 2019 SIGMOD 8.7738349e-05
2,248 QueryFormer: A Tree Transformer Model for Query Plan Representation 2022 VLDB 8.7567205e-05
2,342 Learned Cardinality Estimation: An In-depth Study 2022 SIGMOD 8.6074783e-05
2,393 A Learned Query Rewrite System using Monte Carlo Tree Search 2022 VLDB 8.5298464e-05
2,476 Learning a Partitioning Advisor for Cloud Databases 2020 SIGMOD 8.407183e-05
2,518 Learned Cardinality Estimation: A Design Space Exploration and A Comparative Evaluation 2022 VLDB 8.3532841e-05
2,583 Fauce: Fast and Accurate Deep Ensembles with Uncertainty for Cardinality Estimation 2021 VLDB 8.2589842e-05
2,686 Cost-based or Learning-based? A Hybrid Query Optimizer for Query Plan Selection 2022 VLDB 8.1300913e-05
2,765 Instance-Optimized Data Layouts for Cloud Analytics Workloads 2021 SIGMOD 8.0401855e-05
2,833 Cost Models for Big Data Query Processing: Learning, Retrofitting, and Our Findings 2020 SIGMOD 7.9539771e-05
2,844 FactorJoin: A New Cardinality Estimation Framework for Join Queries 2023 SIGMOD 7.9446987e-05
2,879 Zero-Shot Cost Models for Out-of-the-box Learned Cost Prediction 2022 VLDB 7.9126862e-05
2,963 Proving Query Equivalence Using Linear Integer Arithmetic 2023 SIGMOD 7.8035846e-05
3,053 A Unified Deep Model of Learning from both Data and Queries for Cardinality Estimation 2021 SIGMOD 7.7041081e-05
3,092 Correlation Sketches for Approximate Join-Correlation Queries 2021 SIGMOD 7.6548729e-05
3,161 A Learned Sketch for Subgraph Counting 2021 SIGMOD 7.5771609e-05
3,208 Efficiently Approximating Selectivity Functions using Low Overhead Regression Models 2020 VLDB 7.5355264e-05
3,272 Estimating Cardinalities with Deep Sketches 2019 SIGMOD 7.4711788e-05
3,563 Astrid: Accurate Selectivity Estimation for String Predicates using Deep Learning 2021 VLDB 7.2023194e-05
3,565 Auto-WLM: Machine Learning Enhanced Workload Management in Amazon Redshift 2023 SIGMOD 7.200937e-05
3,648 UDO: Universal Database Optimization using Reinforcement Learning 2021 VLDB 7.1366536e-05
3,680 openGauss: An Autonomous Database System 2021 VLDB 7.1016555e-05
3,708 The Case for a Learned Sorting Algorithm 2020 SIGMOD 7.0781032e-05
3,710 CARMI: A Cache-Aware Learned Index with a Cost-based Construction Algorithm 2022 VLDB 7.0775695e-05
3,742 FACE: A Normalizing Flow based Cardinality Estimator 2022 VLDB 7.0564546e-05
3,900 SQLStorm: Taking Database Benchmarking into the LLM Era 2025 VLDB 6.9320915e-05
3,964 MB2: Decomposed Behavior Modeling for Self-Driving Database Management Systems 2021 SIGMOD 6.889374e-05
3,979 Efficient Deep Learning Pipelines for Accurate Cost Estimations Over Large Scale Query Workload 2021 SIGMOD 6.8791817e-05
3,983 Simplicity Done Right for Join Ordering 2021 CIDR 6.8722161e-05
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Outgoing Citations (Sorted by Pagerank)

Showing 14 of 14 cited papers.

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