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Lightweight and Accurate Cardinality Estimation by Neural Network Gaussian Process

Summary: Lightweight, uncertainty-aware cardinality estimation via Neural Network Gaussian Process (NNGP); trained in seconds with calibrated predictions. Bayesian deep learning; NNGP yields a universal nonparametric model (GP limit), robust to workload shift. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
hc237c873688e6adc
Venue
SIGMOD
Year
2022
Pagerank
6.5883555e-05
Overall Rank
4,459 | 70.04%
DOI
10.1145/3514221.3526156

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@inproceedings{zhao_sigmod22,
        title = {{Lightweight and Accurate Cardinality Estimation by Neural Network Gaussian Process}},
        author = {Zhao, Kangfei and Yu, Jeffrey Xu and He, Zongyan and Li, Rui and Zhang, Hao},
        series = {{SIGMOD} '22},
        booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
        publisher = {Association for Computing Machinery},
        doi = {10.1145/3514221.3526156},
        url = {https://dl.acm.org/doi/10.1145/3514221.3526156},
        year = {2022}
}

Incoming Citations (Sorted by Pagerank)

Showing 10 of 10 citing papers.

Rank Citing Paper Year Venue Pagerank
4,299 ALECE: An Attention-based Learned Cardinality Estimator for SPJ Queries on Dynamic Workloads 2024 VLDB 6.6766173e-05
6,472 Cardinality Estimation over Knowledge Graphs with Embeddings and Graph Neural Networks 2024 SIGMOD 5.7716301e-05
6,780 Missing Data Imputation with Uncertainty-Driven Network 2024 SIGMOD 5.6826037e-05
8,888 Spatial Query Optimization With Learning 2024 VLDB 5.2543468e-05
9,381 Efficient and Effective Cardinality Estimation for Skyline Family 2023 SIGMOD 5.1843659e-05
10,222 PRICE: A Pretrained Model for Cross-Database Cardinality Estimation 2025 VLDB 5.0560976e-05
10,424 Are Learned DBMS Components Robust to Workload Drift?: [Experiments & Analysis] 2026 SIGMOD 4.9769913e-05
10,543 Rainbow: Risk-aware Index Benefit Estimation Facing Out Of Distribution Workloads 2026 SIGMOD 4.9769913e-05
10,690 Reqo: A Comprehensive Learning-Based Cost Model for Robust and Explainable Query Optimization 2026 SIGMOD 4.9769913e-05
11,265 ACE: A Cardinality Estimator for Set-Valued Queries 2025 VLDB 4.9769913e-05
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Outgoing Citations (Sorted by Pagerank)

Showing 36 of 36 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 0.00061067652
37 Improved Histograms for Selectivity Estimation of Range Predicates 1996 SIGMOD 0.0004772731
40 The Case for Learned Index Structures 2018 SIGMOD 0.00046363107
78 Automatic Database Management System Tuning Through Large-scale Machine Learning 2017 SIGMOD 0.00036675568
85 Learned Cardinalities: Estimating Correlated Joins with Deep Learning 2019 CIDR 0.00035876108
103 Selectivity Estimation Without the Attribute Value Independence Assumption 1997 VLDB 0.00033884854
135 Ripple Joins for Online Aggregation 1999 SIGMOD 0.00029858107
144 Neo: A Learned Query Optimizer 2019 VLDB 0.00029090793
286 Selectivity Estimation using Probabilistic Models 2001 SIGMOD 0.00022112534
314 An End-to-End Automatic Cloud Database Tuning System Using Deep Reinforcement Learning 2019 SIGMOD 0.00021276452
318 DeepDB: Learn from Data, not from Queries! 2020 VLDB 0.00021166957
322 Tuning Database Configuration Parameters with iTuned 2009 VLDB 0.00021034201
335 The Aqua Approximate Query Answering System 1999 SIGMOD 0.000206533
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
596 Wander Join: Online Aggregation via Random Walks 2016 SIGMOD 0.00015782051
691 Selectivity Estimation for Range Predicates using Lightweight Models 2019 VLDB 0.00014737455
795 Random Sampling over Joins Revisited 2018 SIGMOD 0.00013934719
869 Learning Multi-dimensional Indexes 2020 SIGMOD 0.00013363241
1,058 Lightweight Graphical Models for Selectivity Estimation Without Independence Assumptions 2011 VLDB 0.00012224038
1,065 Are We Ready For Learned Cardinality Estimation? 2021 VLDB 0.00012202293
1,280 AI Meets AI: Leveraging Query Executions to Improve Index Recommendations 2019 SIGMOD 0.00011224914
1,428 Knowing When You’re Wrong: Building Fast and Reliable Approximate Query Processing Systems 2014 SIGMOD 0.0001069161
1,465 Pessimistic Cardinality Estimation: Tighter Upper Bounds for Intermediate Join Cardinalities 2019 SIGMOD 0.00010572023
1,580 Deep Learning Models for Selectivity Estimation of Multi-Attribute Queries 2020 SIGMOD 0.00010177136
1,699 Black or White? How to Develop an AutoTuner for Memory-based Analytics 2020 SIGMOD 9.8403606e-05
1,828 DBEst: Revisiting Approximate Query Processing Engines with Machine Learning Models 2019 SIGMOD 9.547768e-05
2,217 Estimating Join Selectivities using Bandwidth-Optimized Kernel Density Models 2017 VLDB 8.8151982e-05
2,583 Fauce: Fast and Accurate Deep Ensembles with Uncertainty for Cardinality Estimation 2021 VLDB 8.2589842e-05
2,837 Query Performance Prediction for Concurrent Queries using Graph Embedding 2020 VLDB 7.9495917e-05
3,161 A Learned Sketch for Subgraph Counting 2021 SIGMOD 7.5771609e-05
3,198 CDFShop: Exploring and Optimizing Learned Index Structures 2020 SIGMOD 7.5422544e-05
3,208 Efficiently Approximating Selectivity Functions using Low Overhead Regression Models 2020 VLDB 7.5355264e-05
4,458 Application Driven Graph Partitioning 2020 SIGMOD 6.5890319e-05
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