Random Sampling for Histogram Construction: How much is enough?
Summary: Optimal sampling bounds for equi-height histograms; region-sensitive error metric; adaptive page-level sampling leveraging value clustering. Distinct-value estimation is hard; practical estimator for optimizers; SQL Server 7.0 prototype confirms accuracy. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Surajit Chaudhuri (Microsoft)
- 2. Rajeev Motwani (Stanford University)
- 3. Vivek Narasayya (Microsoft)
BibTeX Citation
@inproceedings{chaudhuri_sigmod98,
title = {{Random Sampling for Histogram Construction: How much is enough?}},
author = {Chaudhuri, Surajit and Motwani, Rajeev and Narasayya, Vivek},
series = {{SIGMOD} '98},
booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
publisher = {Association for Computing Machinery},
doi = {10.1145/276304.276343},
url = {https://dl.acm.org/doi/10.1145/276304.276343},
year = {1998}
}
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