Lightweight Graphical Models for Selectivity Estimation Without Independence Assumptions
Summary: Proposes a selectivity model that drops independence assumptions and factorizes joint distribution into 2D factors via graphical models. Implemented in PostgreSQL with optimizations, achieving order-of-magnitude gains in selectivity within tens-of-ms. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Kostas Tzoumas (Aalborg University)
- 2. Amol Deshpande (University of Maryland)
- 3. Christian S. Jensen (Aarhus University)
BibTeX Citation
@article{tzoumas_vldb11,
title = {{Lightweight Graphical Models for Selectivity Estimation Without Independence Assumptions}},
author = {Tzoumas, Kostas and Deshpande, Amol and Jensen, Christian S.},
journal = {PVLDB},
series = {{VLDB} '11},
volume = {4},
number = {11},
pages = {852--863},
doi = {10.14778/3402707.3402724},
url = {https://doi.org/10.14778/3402707.3402724},
year = {2011}
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