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Projection-Compliant Database Generation

Summary: Adds projection cardinalities (Distinct/Union/Group By) to declarative data generation, modeling multidimensional cardinality unions and cross-subspace dependencies missing from prior work. PiGen uses projection-subspace division with LP encodings, symmetric refinement, and workload decomposition to enable on-demand, scalable, accurate projections. (summarized by gpt-5-mini on Feb 09 2026)

Paper ID
13157
Venue
VLDB
Year
2022
Pagerank
5.1842045e-05
Overall Rank
9,985 | 31.50%
DOI
10.14778/3510397.3510398

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@article{sanghi_vldb22,
        title = {{Projection-Compliant Database Generation}},
        author = {Sanghi, Anupam and Ahmed, Shadab and Haritsa, Jayant R.},
        journal = {PVLDB},
        series = {{VLDB} '22},
        volume = {15},
        number = {5},
        pages = {998--1010},
        doi = {10.14778/3510397.3510398},
        url = {https://doi.org/10.14778/3510397.3510398},
        year = {2022}
}

Incoming Citations (Sorted by Pagerank)

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Rank Citing Paper Year Venue Pagerank
9,536 Database Gyms 2023 CIDR 5.2529727e-05
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Outgoing Citations (Sorted by Pagerank)

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