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CliffGuard: A Principled Framework for Finding Robust Database Designs
Summary: CliffGuard applies robust optimization to select physical designs (indices, materialized views) under workload uncertainty. Users set risk tolerance to trade nominal optimality for robustness, yielding predictable performance amid workload shifts.
(summarized by gpt-5-nano on Feb 09 2026)
Paper ID
h5459bd145610be67
Venue
SIGMOD
Year
2015
Pagerank
6.1645235e-05
Overall Rank
5,324 | 64.32%
DOI
10.1145/2723372.2749454
Incoming Non-self Citations Over Time
BibTeX Citation
@inproceedings{mozafari_sigmod15,
title = {{CliffGuard: A Principled Framework for Finding Robust Database Designs}},
author = {Mozafari, Barzan and Goh, Eugene Zhen Ye and Yoon, Dong Young},
series = {{SIGMOD} '15},
booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
publisher = {Association for Computing Machinery},
doi = {10.1145/2723372.2749454},
url = {https://dl.acm.org/doi/10.1145/2723372.2749454},
year = {2015}
}
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