Efficient Rank Join with Aggregation Constraints
Summary: Aggregation constraints enrich rank-join semantics, enabling user preferences in top-k queries. The paper develops deterministic and probabilistic algorithms that push constraints into rank-join rather than post-filtering, beating naive pipelines. (summarized by gpt-5-nano on Feb 09 2026)
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Authors
- 1. Min Xie (University of British Columbia)
- 2. Laks V.S. Lakshmanan (University of British Columbia)
- 3. Peter T. Wood (Birkbeck, University of London)
BibTeX Citation
@article{xie_vldb11,
title = {{Efficient Rank Join with Aggregation Constraints}},
author = {Xie, Min and Lakshmanan, Laks V.S. and Wood, Peter T.},
journal = {PVLDB},
series = {{VLDB} '11},
volume = {4},
number = {11},
pages = {1201--1212},
doi = {10.14778/3402707.3402754},
url = {https://doi.org/10.14778/3402707.3402754},
year = {2011}
}
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