ARCube: Supporting Ranking Aggregate Queries in Partially Materialized Data Cubes
Summary: ARCube introduces a unified partial-cube structure for ranking aggregates in partially materialized data cubes. A candidate generation/verification framework uses guiding cells with a pruning rule (prune a guiding cell, prune descendants) and a chunked, memory-bounded execution to verify many candidates; yields order-of-magnitude speedups and broader ranking-aggregate support over prior work. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Tianyi Wu (University of Illinois Urbana-Champaign)
- 2. Dong Xin (Microsoft; University of Illinois Urbana-Champaign)
- 3. Jiawei Han (University of Illinois Urbana-Champaign)
BibTeX Citation
@inproceedings{wu_sigmod08,
title = {{ARCube: Supporting Ranking Aggregate Queries in Partially Materialized Data Cubes}},
author = {Wu, Tianyi and Xin, Dong and Han, Jiawei},
series = {{SIGMOD} '08},
booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
publisher = {Association for Computing Machinery},
doi = {10.1145/1376616.1376627},
url = {https://dl.acm.org/doi/10.1145/1376616.1376627},
year = {2008}
}
Incoming Citations (Sorted by Pagerank)
Showing 3 of 3 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 3,132 | Extracting Top-K Insights from Multi-dimensional Data | 2017 | SIGMOD | 7.7246394e-05 |
| 3,521 | Promotion Analysis in Multi-Dimensional Space | 2009 | VLDB | 7.3501396e-05 |
| 3,930 | Data Canopy: Accelerating Exploratory Statistical Analysis | 2017 | SIGMOD | 7.0102082e-05 |
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Outgoing Citations (Sorted by Pagerank)
Showing 23 of 23 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
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