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FLAT: Fast, Lightweight and Accurate Method for Cardinality Estimation

Summary: FLAT introduces FSPN, an adaptive graphical model combining independent and conditional factorization to capture attribute correlations. It delivers fast near-linear probability computation, compact models, incremental updates, and highly accurate single-table and join cardinalities. (summarized by gpt-5.6-luna on Jul 24 2026)

Paper ID
12525
Venue
VLDB
Year
2021
Pagerank
9.3501502e-05
Overall Rank
1,988 | 86.37%
DOI
10.14778/3461535.3461539

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@article{zhu_vldb21,
        title = {{FLAT: Fast, Lightweight and Accurate Method for Cardinality Estimation}},
        author = {Zhu, Rong and Wu, Ziniu and Han, Yuxing and Zeng, Kai and Pfadler, Andreas and Qian, Zhengping and Zhou, Jingren and Cui, Bin},
        journal = {PVLDB},
        series = {{VLDB} '21},
        volume = {14},
        number = {9},
        pages = {1489--1502},
        doi = {10.14778/3461535.3461539},
        url = {https://doi.org/10.14778/3461535.3461539},
        year = {2021}
}

Incoming Citations (Sorted by Pagerank)

Showing 1 of 51 citing papers.

Rank Citing Paper Year Venue Pagerank
11,160 Sub-optimal Join Order Identification with L1-error 2024 SIGMOD 5.093636e-05
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Outgoing Citations (Sorted by Pagerank)

Showing 27 of 27 cited papers.

Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.

Rank Cited Paper Year Venue Pagerank
1 Access Path Selection in a Relational Database Management System 1979 SIGMOD 0.0024089429
18 How Good Are Query Optimizers, Really? 2016 VLDB 0.00059284255
24 Spark SQL: Relational Data Processing in Spark 2015 SIGMOD 0.00054865648
43 The Case for Learned Index Structures 2018 SIGMOD 0.00046060254
84 Learned Cardinalities: Estimating Correlated Joins with Deep Learning 2019 CIDR 0.00035838391
86 Automatic Database Management System Tuning Through Large-scale Machine Learning 2017 SIGMOD 0.00035316107
89 On the Propagation of Errors in the Size of Join Results 1991 SIGMOD 0.00035031529
100 LEO - DB2's LEarning Optimizer 2001 VLDB 0.00034385207
101 Selectivity Estimation Without the Attribute Value Independence Assumption 1997 VLDB 0.00034376651
154 Neo: A Learned Query Optimizer 2019 VLDB 0.00028726181
280 Selectivity Estimation using Probabilistic Models 2001 SIGMOD 0.00022454217
323 DeepDB: Learn from Data, not from Queries! 2020 VLDB 0.00021264788
365 STHoles: A Multidimensional Workload-Aware Histogram 2001 SIGMOD 0.00020041735
401 Deep Unsupervised Cardinality Estimation 2020 VLDB 0.00019092557
513 NeuroCard: One Cardinality Estimator for All Tables 2021 VLDB 0.00017190574
692 Independence is Good: Dependency-Based Histogram Synopses for High-Dimensional Data 2001 SIGMOD 0.00014919816
694 Cardinality Estimation Done Right: Index-Based Join Sampling 2017 CIDR 0.00014911698
697 Selectivity Estimation for Range Predicates using Lightweight Models 2019 VLDB 0.00014888851
802 Random Sampling over Joins Revisited 2018 SIGMOD 0.00013907725
850 Approximating Multi-Dimensional Aggregate Range Queries Over Real Attributes 2000 SIGMOD 0.00013619394
873 Learning Multi-dimensional Indexes 2020 SIGMOD 0.00013481915
1,061 Are We Ready For Learned Cardinality Estimation? 2021 VLDB 0.00012369764
1,071 Lightweight Graphical Models for Selectivity Estimation Without Independence Assumptions 2011 VLDB 0.00012322342
1,468 Towards a Learning Optimizer for Shared Clouds 2019 VLDB 0.00010686496
1,503 Self-Tuning, GPU-Accelerated Kernel Density Models for Multidimensional Selectivity Estimation 2015 SIGMOD 0.000105564
1,995 Database Learning: Toward a Database that Becomes Smarter Every Time 2017 SIGMOD 9.3403665e-05
2,203 Estimating Join Selectivities using Bandwidth-Optimized Kernel Density Models 2017 VLDB 8.9610447e-05
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