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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
6468
Venue
SIGMOD
Year
2022
Pagerank
6.1870601e-05
Overall Rank
4,431 | 69.21%
DOI
10.1145/3514221.3526156

Incoming Non-self Citations Over Time

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Incoming Citations (Sorted by Pagerank)

Showing 9 of 9 citing papers.

Rank Citing Paper Year Venue Pagerank
5,405 ALECE: An Attention-based Learned Cardinality Estimator for SPJ Queries on Dynamic Workloads 2024 VLDB 5.5243727e-05
6,601 Missing Data Imputation with Uncertainty-Driven Network 2024 SIGMOD 4.9924633e-05
6,715 Cardinality Estimation over Knowledge Graphs with Embeddings and Graph Neural Networks 2024 SIGMOD 4.9464666e-05
9,487 Spatial Query Optimization With Learning 2024 VLDB 4.3300131e-05
9,877 PRICE: A Pretrained Model for Cross-Database Cardinality Estimation 2025 VLDB 4.2615675e-05
10,032 Rainbow: Risk-aware Index Benefit Estimation Facing Out Of Distribution Workloads 2026 SIGMOD 4.1905499e-05
10,203 Reqo: A Comprehensive Learning-Based Cost Model for Robust and Explainable Query Optimization 2026 SIGMOD 4.1905499e-05
10,598 ACE: A Cardinality Estimator for Set-Valued Queries 2025 VLDB 4.1905499e-05
11,192 Efficient and Effective Cardinality Estimation for Skyline Family 2023 SIGMOD 4.1905499e-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
63 Improved Histograms for Selectivity Estimation of Range Predicates 1996 SIGMOD 0.00063595699
71 How Good Are Query Optimizers, Really? 2016 VLDB 0.00059446482
101 The Case for Learned Index Structures 2018 SIGMOD 0.00049778866
141 Selectivity Estimation Without the Attribute Value Independence Assumption 1997 VLDB 0.00041819767
183 Automatic Database Management System Tuning Through Large-scale Machine Learning 2017 SIGMOD 0.00036859633
203 Learned Cardinalities: Estimating Correlated Joins with Deep Learning 2019 CIDR 0.00034868567
216 Ripple Joins for Online Aggregation 1999 SIGMOD 0.00033560137
329 Neo: A Learned Query Optimizer 2019 VLDB 0.00027301488
373 Selectivity Estimation using Probabilistic Models 2001 SIGMOD 0.00025354685
423 Tuning Database Configuration Parameters with iTuned 2009 VLDB 0.00023628474
431 The Aqua Approximate Query Answering System 1999 SIGMOD 0.00023397171
510 An End-to-End Automatic Cloud Database Tuning System Using Deep Reinforcement Learning 2019 SIGMOD 0.00021420477
606 DeepDB: Learn from Data, not from Queries! 2020 VLDB 0.00019251186
752 Deep Unsupervised Cardinality Estimation 2020 VLDB 0.00017138049
804 An End-to-End Learning-based Cost Estimator 2020 VLDB 0.0001643674
819 ALEX: An Updatable Adaptive Learned Index 2020 SIGMOD 0.00016237497
905 NeuroCard: One Cardinality Estimator for All Tables 2021 VLDB 0.00015423174
941 Wander Join: Online Aggregation via Random Walks 2016 SIGMOD 0.00015147831
1,239 Selectivity Estimation for Range Predicates using Lightweight Models 2019 VLDB 0.00013091459
1,372 Random Sampling over Joins Revisited 2018 SIGMOD 0.0001233325
1,464 Learning Multi-dimensional Indexes 2020 SIGMOD 0.0001184772
1,536 Lightweight Graphical Models for Selectivity Estimation Without Independence Assumptions 2011 VLDB 0.00011458359
1,699 Are We Ready For Learned Cardinality Estimation? 2021 VLDB 0.00010848882
1,856 AI Meets AI: Leveraging Query Executions to Improve Index Recommendations 2019 SIGMOD 0.00010319105
1,867 Knowing When You’re Wrong: Building Fast and Reliable Approximate Query Processing Systems 2014 SIGMOD 0.00010264932
1,892 Black or White? How to Develop an AutoTuner for Memory-based Analytics 2020 SIGMOD 0.00010176219
2,143 Pessimistic Cardinality Estimation: Tighter Upper Bounds for Intermediate Join Cardinalities 2019 SIGMOD 9.4437798e-05
2,364 Deep Learning Models for Selectivity Estimation of Multi-Attribute Queries 2020 SIGMOD 8.955077e-05
2,494 DBEst: Revisiting Approximate Query Processing Engines with Machine Learning Models 2019 SIGMOD 8.6457436e-05
2,971 Estimating Join Selectivities using Bandwidth-Optimized Kernel Density Models 2017 VLDB 7.7935535e-05
3,492 Fauce: Fast and Accurate Deep Ensembles with Uncertainty for Cardinality Estimation 2021 VLDB 7.0435484e-05
3,580 Query Performance Prediction for Concurrent Queries using Graph Embedding 2020 VLDB 6.9460425e-05
3,781 A Learned Sketch for Subgraph Counting 2021 SIGMOD 6.7691344e-05
3,955 Efficiently Approximating Selectivity Functions using Low Overhead Regression Models 2020 VLDB 6.5895015e-05
4,069 CDFShop: Exploring and Optimizing Learned Index Structures 2020 SIGMOD 6.4744708e-05
4,868 Application Driven Graph Partitioning 2020 SIGMOD 5.8595544e-05
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Overall Rank Paper Year Venue Pagerank
1,699 Are We Ready For Learned Cardinality Estimation? 2021 VLDB 0.00010848882
905 NeuroCard: One Cardinality Estimator for All Tables 2021 VLDB 0.00015423174
752 Deep Unsupervised Cardinality Estimation 2020 VLDB 0.00017138049
7,473 Cardinality Estimation of Approximate Substring Queries using Deep Learning 2022 VLDB 4.7149077e-05
9,725 Cardinality Estimation of LIKE Predicate Queries using Deep Learning 2025 SIGMOD 4.290223e-05
4,413 Robust Query Driven Cardinality Estimation under Changing Workloads 2023 VLDB 6.1989918e-05
2,364 Deep Learning Models for Selectivity Estimation of Multi-Attribute Queries 2020 SIGMOD 8.955077e-05
7,220 Speeding Up End-to-end Query Execution via Learning-based Progressive Cardinality Estimation 2023 SIGMOD 4.7926382e-05
3,455 Learned Cardinality Estimation: A Design Space Exploration and A Comparative Evaluation 2022 VLDB 7.0760196e-05
6,382 Sample-Efficient Cardinality Estimation Using Geometric Deep Learning 2024 VLDB 5.0835686e-05