Balancing Histogram Optimality and Practicality for Query Result Size Estimation
Summary: Trade-off between histogram optimality and practicality for estimating query result sizes. Proposes a practical histogram class: preserve exact frequencies for a few values, assume uniformity for the rest, and pick per relation the self-join-optimal histogram; theory and experiments show strong accuracy and tractable construction. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Yannis E. Ioannidis (University of Wisconsin)
- 2. Viswanath Poosala (University of Wisconsin)
BibTeX Citation
@inproceedings{ioannidis_sigmod95,
title = {{Balancing Histogram Optimality and Practicality for Query Result Size Estimation}},
author = {Ioannidis, Yannis E. and Poosala, Viswanath},
series = {{SIGMOD} '95},
booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
publisher = {Association for Computing Machinery},
doi = {10.1145/223784.223841},
url = {https://dl.acm.org/doi/10.1145/223784.223841},
year = {1995}
}
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