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E = MC^3: Managing Uncertain Enterprise Data in a Cluster-Computing Environment

Summary: Extends MCDB to a MapReduce cluster for scalable Monte Carlo analytics over uncertain enterprise data. Introduces distributed seed-generation algorithms, maps MCDB plans to MapReduce over nested data, and supports non-relational storage, with scalable performance. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
4200
Venue
SIGMOD
Year
2009
Pagerank
5.3215443e-05
Overall Rank
9,114 | 37.48%
DOI
10.1145/1559845.1559893

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@inproceedings{xu_sigmod09,
        title = {{E = MC\^{}3: Managing Uncertain Enterprise Data in a Cluster-Computing Environment}},
        author = {Xu, Fei and Beyer, Kevin and Ercegovac, Vuk and Haas, Peter J. and Shekita, Eugene J.},
        series = {{SIGMOD} '09},
        booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
        publisher = {Association for Computing Machinery},
        doi = {10.1145/1559845.1559893},
        url = {https://dl.acm.org/doi/10.1145/1559845.1559893},
        year = {2009}
}

Incoming Citations (Sorted by Pagerank)

Showing 2 of 2 citing papers.

Rank Citing Paper Year Venue Pagerank
5,286 Data is Dead… Without What-If Models 2011 VLDB 6.282151e-05
8,192 Jigsaw: Efficient Optimization Over Uncertain Enterprise Data 2011 SIGMOD 5.4698006e-05
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Outgoing Citations (Sorted by Pagerank)

Showing 7 of 7 cited papers.

Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.

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