Applying the Golden Rule of Sampling for Query Estimation
Summary: Proposes a sampling method based on von Neumann's golden rule to estimate range-query size in databases. Randomly samples the frequency domain using the cumulative frequency distribution, with no prior distribution knowledge, delivering lower error than Min-Skew and wavelet baselines and scalable to higher dimensions. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Yi-Leh Wu (University of California Santa Barbara)
- 2. Divyakant Agrawal (University of California Santa Barbara)
- 3. Amr El Abbadi (University of California Santa Barbara)
BibTeX Citation
@inproceedings{wu_sigmod01,
title = {{Applying the Golden Rule of Sampling for Query Estimation}},
author = {Wu, Yi-Leh and Agrawal, Divyakant and Abbadi, Amr El},
series = {{SIGMOD} '01},
booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
publisher = {Association for Computing Machinery},
doi = {10.1145/375663.375724},
url = {https://dl.acm.org/doi/10.1145/375663.375724},
year = {2001}
}
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