Sample-based Distinct Cardinality Estimation for Multiple Attributes in Multi-Dataset Queries
Summary: Introduces MAMD, a stored-sample method for distinct-count estimation over multiple attributes and joined datasets, with or without selections. Demonstrates moderately low error, low storage and compilation cost on TPC-H/IMDB, including scalability. (summarized by gpt-5.6-luna on Jul 24 2026)
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Authors
- 1. Mehnaz Tabassum Mahin (University of California Riverside)
- 2. Michael J. Carey (University of California Irvine)
- 3. Vassilis J. Tsotras (University of California Riverside)
BibTeX Citation
@article{mahin_vldb26,
title = {{Sample-based Distinct Cardinality Estimation for Multiple Attributes in Multi-Dataset Queries}},
author = {Mahin, Mehnaz Tabassum and Carey, Michael J. and Tsotras, Vassilis J.},
journal = {PVLDB},
series = {{VLDB} '26},
volume = {19},
number = {6},
pages = {1115--1127},
doi = {10.14778/3797919.3797922},
url = {https://doi.org/10.14778/3797919.3797922},
year = {2026}
}
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