Cardinality Estimation Using Sample Views with Quality Assurance
Summary: Proposes a general cardinality estimator that blends random sampling with materialized views for complex predicates, correlations, and UDFs. Uses execution feedback with data-change controls to keep estimates valid, demonstrated on a SQL Server prototype. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Per-Ake Larson (Microsoft)
- 2. Wolfgang Lehner (Microsoft; Technical University of Dresden)
- 3. Jingren Zhou (Microsoft)
- 4. Peter Zabback (Microsoft)
BibTeX Citation
@inproceedings{larson_sigmod07,
title = {{Cardinality Estimation Using Sample Views with Quality Assurance}},
author = {Larson, Per-Ake and Lehner, Wolfgang and Zhou, Jingren and Zabback, Peter},
series = {{SIGMOD} '07},
booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
publisher = {Association for Computing Machinery},
doi = {10.1145/1247480.1247502},
url = {https://dl.acm.org/doi/10.1145/1247480.1247502},
year = {2007}
}
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