Join Size Bounds using l_p-Norms on Degree Sequences
Summary: Extends information-theoretic join-size bounds with l_p-norms of degree sequences, yielding tighter estimates for acyclic and cyclic queries. Includes a matching evaluation algorithm; bounds are exponential-time computable and provably tight when degrees are simple. (summarized by gpt-5-nano on Feb 09 2026)
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Authors
- 1. Mahmoud Abo Khamis (RelationalAI)
- 2. Vasileios Nakos (RelationalAI)
- 3. Dan Olteanu (University of Zurich)
- 4. Dan Suciu (University of Washington)
BibTeX Citation
@inproceedings{khamis_pods24,
address = {New York, NY, USA},
series = {{PODS} '24},
title = {{Join Size Bounds using l\_p-Norms on Degree Sequences}},
url = {https://dl.acm.org/doi/10.1145/3651597},
doi = {10.1145/3651597},
booktitle = {Proceedings of the {ACM} {SIGMOD} Symposium on {Principles} of {Database} {Systems}},
publisher = {Association for Computing Machinery},
author = {Khamis, Mahmoud Abo and Nakos, Vasileios and Olteanu, Dan and Suciu, Dan},
year = {2024}
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