Computing Iceberg Queries Efficiently
Summary: Introduces low-memory, few-pass algorithms for iceberg aggregate queries, avoiding conventional sorting or hashing. Demonstrates substantial savings on multi-gigabyte Web data, exploiting the typically tiny set of above-threshold results. (summarized by gpt-5.6-luna on Jul 24 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Min Fang (Oracle Systems; Stanford University)
- 2. Narayanan Shivakumar (Stanford University)
- 3. Hector Garcia-Molina (Stanford University)
- 4. Rajeev Motwani (Stanford University)
- 5. Jeffrey D. Ullman (Stanford University)
BibTeX Citation
@article{fang_vldb98,
title = {{Computing Iceberg Queries Efficiently}},
author = {Fang, Min and Shivakumar, Narayanan and Garcia-Molina, Hector and Motwani, Rajeev and Ullman, Jeffrey D.},
journal = {PVLDB},
series = {{VLDB} '98},
pages = {299--310},
year = {1998}
}
Incoming Citations (Sorted by Pagerank)
Showing 35 of 35 citing papers.
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Outgoing Citations (Sorted by Pagerank)
Showing 2 of 2 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 240 | An Effective Hash-Based Algorithm for Mining Association Rules | 1995 | SIGMOD | 0.0002366381 |
| 704 | Dynamic Itemset Counting and Implication Rules for Market Basket Data | 1997 | SIGMOD | 0.00014837704 |
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