Fast Computation of Sparse Datacubes
Summary: Introduces a novel, scalable algorithm for fast sparse datacubes with many CUBE BY attributes. In-memory data uses multiple sorts with no I/O beyond input and output; out-of-core uses divide-and-conquer to sub-datacubes, with I/O cost linear in the number of CUBE BY attributes. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Kenneth A. Ross (Columbia University)
- 2. Divesh Srivastava (AT&T)
BibTeX Citation
@article{ross_vldb97,
title = {{Fast Computation of Sparse Datacubes}},
author = {Ross, Kenneth A. and Srivastava, Divesh},
journal = {PVLDB},
series = {{VLDB} '97},
year = {1997}
}
Incoming Citations (Sorted by Pagerank)
Showing 21 of 21 citing papers.
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Outgoing Citations (Sorted by Pagerank)
Showing 3 of 3 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 11 | Implementing Data Cubes Efficiently | 1996 | SIGMOD | 0.00071822821 |
| 207 | On the Computation of Multidimensional Aggregates | 1996 | VLDB | 0.00025088003 |
| 324 | An Array-Based Algorithm for Simultaneous Multidimensional Aggregates | 1997 | SIGMOD | 0.00021200835 |
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