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Sharing Aggregate Computation for Distributed Queries

Summary: Cross-query sharing for distributed aggregations via a data–query incidence matrix; recovers a compact set of shared plans. SUM/COUNT/AVERAGE optimal; MIN/MAX NP-hard set-basis; offers heuristics and a dynamic distributed architecture. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
3937
Venue
SIGMOD
Year
2007
Pagerank
5.2323504e-05
Overall Rank
9,718 | 33.33%
DOI
10.1145/1247480.1247535

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@inproceedings{huebsch_sigmod07,
        title = {{Sharing Aggregate Computation for Distributed Queries}},
        author = {Huebsch, Ryan and Garofalakis, Minos and Hellerstein, Joseph M. and Stoica, Ion},
        series = {{SIGMOD} '07},
        booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
        publisher = {Association for Computing Machinery},
        doi = {10.1145/1247480.1247535},
        url = {https://dl.acm.org/doi/10.1145/1247480.1247535},
        year = {2007}
}

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Rank Citing Paper Year Venue Pagerank
9,425 Ranking Distributed Probabilistic Data 2009 SIGMOD 5.2711481e-05
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