Learning to be a Statistician: Learned Estimator for Number of Distinct Values
Summary: Proposes a supervised-learning NDV estimator, replacing heuristic sample methods with a data-driven model. Trains on synthetic data for workload-agnostic deployment as a UDF, outperforming existing estimators on nine real datasets; code available. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Renzhi Wu (Georgia Institute of Technology)
- 2. Bolin Ding (Alibaba)
- 3. Xu Chu (Georgia Institute of Technology)
- 4. Zhewei Wei (Renmin University of China)
- 5. Xiening Dai (Alibaba)
- 6. Tao Guan (Alibaba)
- 7. Jingren Zhou (Alibaba)
BibTeX Citation
@article{wu_vldb22,
title = {{Learning to be a Statistician: Learned Estimator for Number of Distinct Values}},
author = {Wu, Renzhi and Ding, Bolin and Chu, Xu and Wei, Zhewei and Dai, Xiening and Guan, Tao and Zhou, Jingren},
journal = {PVLDB},
series = {{VLDB} '22},
volume = {15},
number = {2},
pages = {272--284},
doi = {10.14778/3489496.3489508},
url = {https://doi.org/10.14778/3489496.3489508},
year = {2022}
}
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