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)
Incoming Non-self Citations Over Time
Authors
- 1. Rong Zhu (Alibaba)
- 2. Ziniu Wu (Alibaba)
- 3. Yuxing Han (Alibaba)
- 4. Kai Zeng (Alibaba)
- 5. Andreas Pfadler (Alibaba)
- 6. Zhengping Qian (Alibaba)
- 7. Jingren Zhou (Alibaba)
- 8. Bin Cui (Peking University)
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 50 of 51 citing papers.
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.
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