Cardinality Estimation Done Right: Index-Based Join Sampling
Summary: Index-based join sampling: a main-memory cardinality estimator that uses existing indexes to sample join results and produce accurate multi-table cardinalities. Low, configurable sampling overhead substantially improves estimates and end-to-end plan quality and integrates easily into existing systems. (summarized by gpt-5-mini on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Viktor Leis (Technical University of Munich)
- 2. Bernhard Radke (Technical University of Munich)
- 3. Andrey Gubichev (Google; Technical University of Munich)
- 4. Alfons Kemper (Technical University of Munich)
- 5. Thomas Neumann (Technical University of Munich)
BibTeX Citation
@inproceedings{leis_cidr17,
address = {Amsterdam, Netherlands},
series = {{CIDR} '17},
title = {{Cardinality Estimation Done Right: Index-Based Join Sampling}},
booktitle = {Proceedings of the {Conference} on {Innovative} {Data} {Systems} {Research}},
author = {Leis, Viktor and Radke, Bernhard and Gubichev, Andrey and Kemper, Alfons and Neumann, Thomas},
year = {2017}
}Incoming Citations (Sorted by Pagerank)
Showing 4 of 54 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 11,592 | Agile-Ant: Self-managing Distributed Cache Management for Cost Optimization of Big Data Applications | 2024 | VLDB | 4.9793485e-05 |
| 11,848 | Juggler: Autonomous Cost Optimization and Performance Prediction of Big Data Applications | 2022 | SIGMOD | 4.9793485e-05 |
| 11,951 | Index-Based Join Size Estimation Using Adaptive Sampling | 2021 | SIGMOD | 4.9793485e-05 |
| 12,202 | Tighter Upper Bounds for Join Cardinality Estimates | 2018 | SIGMOD | 4.9793485e-05 |
Outgoing Citations (Sorted by Pagerank)
Showing 20 of 20 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
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