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Jigsaw: Efficient Optimization Over Uncertain Enterprise Data

Summary: Jigsaw, a probabilistic database platform for simulating enterprise scenarios with parameterized VG-Functions. It employs fingerprints to detect cross-parameter output correlations, enabling reuse and up to 100× speedups in parameter-space search. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
4497
Venue
SIGMOD
Year
2011
Pagerank
5.4698006e-05
Overall Rank
8,192 | 43.80%
DOI
10.1145/1989323.1989410

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@inproceedings{kennedy_sigmod11,
        title = {{Jigsaw: Efficient Optimization Over Uncertain Enterprise Data}},
        author = {Kennedy, Oliver and Nath, Suman},
        series = {{SIGMOD} '11},
        booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
        publisher = {Association for Computing Machinery},
        doi = {10.1145/1989323.1989410},
        url = {https://dl.acm.org/doi/10.1145/1989323.1989410},
        year = {2011}
}

Incoming Citations (Sorted by Pagerank)

Showing 3 of 3 citing papers.

Rank Citing Paper Year Venue Pagerank
993 Simulation of Database-Valued Markov Chains Using SimSQL 2013 SIGMOD 0.00012789598
5,971 Lenses: An On-Demand Approach to ETL 2015 VLDB 6.0243066e-05
12,381 Fuzzy Prophet: Parameter Exploration in Uncertain Enterprise Scenarios 2011 SIGMOD 5.093636e-05
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Outgoing Citations (Sorted by Pagerank)

Showing 10 of 10 cited papers.

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

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