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Fauce: Fast and Accurate Deep Ensembles with Uncertainty for Cardinality Estimation

Summary: Fauce is a join cardinality estimator learning correlations across columns and tables with deep ensembles. It yields 10x faster inference and 1.3x–6.7x lower error on complex queries, and it is the first DL-based estimator to embed uncertainty. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
hc663871043e78cd6
Venue
VLDB
Year
2021
Pagerank
8.2589842e-05
Overall Rank
2,583 | 82.65%
DOI
10.14778/3476249.3476254
PDF
Download (CC BY-NC-ND 4.0)

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@article{liu_vldb21,
        title = {{Fauce: Fast and Accurate Deep Ensembles with Uncertainty for Cardinality Estimation}},
        author = {Liu, Jie and Dong, Wenqian and Zhou, Qingqing and Li, Dong},
        journal = {PVLDB},
        series = {{VLDB} '21},
        volume = {14},
        number = {11},
        pages = {1950--1963},
        doi = {10.14778/3476249.3476254},
        url = {https://doi.org/10.14778/3476249.3476254},
        year = {2021}
}

Incoming Citations (Sorted by Pagerank)

Showing 31 of 31 citing papers.

Rank Citing Paper Year Venue Pagerank
2,209 Lero: A Learning-to-Rank Query Optimizer 2023 VLDB 8.8360101e-05
2,342 Learned Cardinality Estimation: An In-depth Study 2022 SIGMOD 8.6074783e-05
2,686 Cost-based or Learning-based? A Hybrid Query Optimizer for Query Plan Selection 2022 VLDB 8.1300913e-05
2,844 FactorJoin: A New Cardinality Estimation Framework for Join Queries 2023 SIGMOD 7.9446987e-05
3,327 Robust Query Driven Cardinality Estimation under Changing Workloads 2023 VLDB 7.4233639e-05
4,299 ALECE: An Attention-based Learned Cardinality Estimator for SPJ Queries on Dynamic Workloads 2024 VLDB 6.6766173e-05
4,459 Lightweight and Accurate Cardinality Estimation by Neural Network Gaussian Process 2022 SIGMOD 6.5883555e-05
4,945 Debunking the Myth of Join Ordering: Toward Robust SQL Analytics 2025 SIGMOD 6.3418058e-05
5,062 Fine-Grained Modeling and Optimization for Intelligent Resource Management in Big Data Processing 2022 VLDB 6.2896995e-05
5,224 SafeBound: A Practical System for Generating Cardinality Bounds 2023 SIGMOD 6.2197808e-05
5,630 Sample-Efficient Cardinality Estimation Using Geometric Deep Learning 2024 VLDB 6.056758e-05
6,664 Speeding Up End-to-end Query Execution via Learning-based Progressive Cardinality Estimation 2023 SIGMOD 5.715134e-05
6,824 ASM: Harmonizing Autoregressive Model, Sampling, and Multi-dimensional Statistics Merging for Cardinality Estimation 2024 SIGMOD 5.670071e-05
7,021 Rethinking Learned Cost Models: Why Start from Scratch? 2023 SIGMOD 5.6168049e-05
8,009 A Spark Optimizer for Adaptive, Fine-Grained Parameter Tuning 2024 VLDB 5.4063491e-05
8,373 GenJoin: Conditional Generative Plan-to-Plan Query Optimizer that Learns from Subplan Hints 2026 SIGMOD 5.3427119e-05
9,010 ByteCard: Enhancing ByteDance’s Data Warehouse with Learned Cardinality Estimation 2024 SIGMOD 5.2371313e-05
9,028 Optimizing the cloud? Don't train models. Build oracles! 2024 CIDR 5.2330697e-05
9,381 Efficient and Effective Cardinality Estimation for Skyline Family 2023 SIGMOD 5.1843659e-05
9,556 Athena: An Effective Learning-based Framework for Query Optimizer Performance Improvement 2025 SIGMOD 5.1580326e-05
9,583 A Step Toward Deep Online Aggregation 2023 SIGMOD 5.154741e-05
9,705 Experimental Analysis of Large-scale Learnable Vector Storage Compression 2024 VLDB 5.1357625e-05
9,739 CAFE: Towards Compact, Adaptive, and Fast Embedding for Large-scale Recommendation Models 2024 SIGMOD 5.1325223e-05
9,900 Approximate Sketches 2024 SIGMOD 5.1110481e-05
9,962 Graph Transformers for Query Plan Representation: Potentials and Challenges 2025 VLDB 5.1014161e-05
10,222 PRICE: A Pretrained Model for Cross-Database Cardinality Estimation 2025 VLDB 5.0560976e-05
10,343 An Elephant Under The Microscope: Analyzing The Interaction Of Optimizer Components In PostgreSQL 2025 SIGMOD 5.0176429e-05
10,380 Coresets for Robust Query Optimization 2026 PODS 4.9769913e-05
10,690 Reqo: A Comprehensive Learning-Based Cost Model for Robust and Explainable Query Optimization 2026 SIGMOD 4.9769913e-05
10,812 BaCon: Efficient Batch Processing of Counting Queries 2026 VLDB 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 25 of 25 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
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
98 LEO - DB2's LEarning Optimizer 2001 VLDB 0.00034099838
318 DeepDB: Learn from Data, not from Queries! 2020 VLDB 0.00021166957
371 STHoles: A Multidimensional Workload-Aware Histogram 2001 SIGMOD 0.00019822444
406 Deep Unsupervised Cardinality Estimation 2020 VLDB 0.00019050182
510 NeuroCard: One Cardinality Estimator for All Tables 2021 VLDB 0.00017059914
688 Cardinality Estimation Done Right: Index-Based Join Sampling 2017 CIDR 0.00014749318
691 Selectivity Estimation for Range Predicates using Lightweight Models 2019 VLDB 0.00014737455
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
1,465 Pessimistic Cardinality Estimation: Tighter Upper Bounds for Intermediate Join Cardinalities 2019 SIGMOD 0.00010572023
1,488 Efficient Discovery of Approximate Dependencies 2018 VLDB 0.00010513265
1,495 An Efficient Bitmap Encoding Scheme for Selection Queries 1999 SIGMOD 0.00010493769
1,509 Self-Tuning, GPU-Accelerated Kernel Density Models for Multidimensional Selectivity Estimation 2015 SIGMOD 0.00010436933
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
2,002 FLAT: Fast, Lightweight and Accurate Method for Cardinality Estimation 2021 VLDB 9.2076835e-05
2,028 Database Learning: Toward a Database that Becomes Smarter Every Time 2017 SIGMOD 9.1584244e-05
2,217 Estimating Join Selectivities using Bandwidth-Optimized Kernel Density Models 2017 VLDB 8.8151982e-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
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