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Efficient Computation of Multiple Group By Queries

Summary: Many Group By queries on wide warehouse data; hardness of the problem motivates cross-query sharing techniques for efficient computation. Empirical results show substantial speedups versus commercial DBs for data-quality analysis. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
3703
Venue
SIGMOD
Year
2005
Pagerank
6.2070458e-05
Overall Rank
5,470 | 62.48%
DOI
10.1145/1066157.1066188

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@inproceedings{chen_sigmod05,
        title = {{Efficient Computation of Multiple Group By Queries}},
        author = {Chen, Zhimin and Narasayya, Vivek},
        series = {{SIGMOD} '05},
        booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
        publisher = {Association for Computing Machinery},
        doi = {10.1145/1066157.1066188},
        url = {https://dl.acm.org/doi/10.1145/1066157.1066188},
        year = {2005}
}

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6,658 CURE for Cubes: Cubing Using a ROLAP Engine 2006 VLDB 5.8104851e-05
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11,609 High-dimensional Data Cubes 2022 VLDB 5.093636e-05
12,713 Composite Subset Measures 2006 VLDB 5.093636e-05
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Outgoing Citations (Sorted by Pagerank)

Showing 14 of 14 cited papers.

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

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