Least Expected Cost Query Optimization: What Can We Expect?
Summary: Evaluates least-expected-cost planning versus optimizing for a 'typical' parameter; carefully chosen typical values often suffice for expected runtime. But expected-cost minimization encodes a linear utility of runtime (ratios) and can be suboptimal; least-expected-cost optimization yields significant gains under several alternative cost/utility models. (summarized by gpt-5-mini on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Francis Chu (Cornell University)
- 2. Joseph Halpern (Cornell University)
- 3. Johannes Gehrke (Cornell University)
BibTeX Citation
@inproceedings{chu_pods02,
address = {New York, NY, USA},
series = {{PODS} '02},
title = {{Least Expected Cost Query Optimization: What Can We Expect?}},
url = {https://dl.acm.org/doi/10.1145/543613.543651},
doi = {10.1145/543613.543651},
booktitle = {Proceedings of the {ACM} {SIGMOD} Symposium on {Principles} of {Database} {Systems}},
publisher = {Association for Computing Machinery},
author = {Chu, Francis and Halpern, Joseph and Gehrke, Johannes},
year = {2002}
}
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