Multiple Join Size Estimation by Virtual Domains (extended abstract)
Summary: Introduces "virtual domains" to estimate sizes of intermediate relations for complex multi-equijoin expressions, avoiding the unrealistic underestimates caused by attribute-independence assumptions while requiring little database statistics. Presents an exact model plus a lightweight, fast approximation tailored for optimizer search over many alternative plans. (summarized by gpt-5-mini on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Allen Van Gelder (University of California Santa Cruz)
BibTeX Citation
@inproceedings{gelder_pods93,
address = {New York, NY, USA},
series = {{PODS} '93},
title = {{Multiple Join Size Estimation by Virtual Domains (extended abstract)}},
url = {https://dl.acm.org/doi/10.1145/153850.153872},
doi = {10.1145/153850.153872},
booktitle = {Proceedings of the {ACM} {SIGMOD} Symposium on {Principles} of {Database} {Systems}},
publisher = {Association for Computing Machinery},
author = {Van Gelder, Allen},
year = {1993}
}
Incoming Citations (Sorted by Pagerank)
Showing 6 of 6 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 100 | LEO - DB2's LEarning Optimizer | 2001 | VLDB | 0.00034385207 |
| 492 | Robust Query Processing through Progressive Optimization | 2004 | SIGMOD | 0.0001756877 |
| 1,061 | Are We Ready For Learned Cardinality Estimation? | 2021 | VLDB | 0.00012369764 |
| 1,170 | QuickSel: Quick Selectivity Learning with Mixture Models | 2020 | SIGMOD | 0.00011827259 |
| 1,936 | Consistently Estimating the Selectivity of Conjuncts of Predicates | 2005 | VLDB | 9.4557372e-05 |
| 3,086 | A Unified Deep Model of Learning from both Data and Queries for Cardinality Estimation | 2021 | SIGMOD | 7.7708642e-05 |
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Outgoing Citations (Sorted by Pagerank)
Showing 12 of 12 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
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