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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
3641
Venue
SIGMOD
Year
2005
Pagerank
5.3482537e-05
Overall Rank
5,736 | 60.10%
DOI
-

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Incoming Citations (Sorted by Pagerank)

Showing 6 of 6 citing papers.

Rank Citing Paper Year Venue Pagerank
4,335 Optimization of Analytic Window Functions 2012 VLDB 6.2790346e-05
6,736 CURE for Cubes: Cubing Using a ROLAP Engine 2006 VLDB 4.9459588e-05
9,175 Efficient Exploration of Interesting Aggregates in RDF Graphs 2021 SIGMOD 4.383548e-05
9,850 COMPARE: Accelerating Groupwise Comparison in Relational Databases for Data Analytics 2021 VLDB 4.2721228e-05
11,411 High-dimensional Data Cubes 2022 VLDB 4.1945683e-05
12,520 Composite Subset Measures 2006 VLDB 4.1945683e-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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