Improved Selectivity Estimation by Combining Knowledge from Sampling and Synopses
Summary: Novel approach to fuse synopses (histograms) and sampling for conjunctive-query selectivity estimation. It extracts mutually consistent statistics from both sources, then computes an admissible combined estimate and benchmarks its accuracy and tradeoffs against state-of-the-art methods. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Magnus Müller (University of Mannheim)
- 2. Guido Moerkotte (University of Mannheim)
- 3. Oliver Kolb (University of Mannheim)
BibTeX Citation
@article{muller_vldb18,
title = {{Improved Selectivity Estimation by Combining Knowledge from Sampling and Synopses}},
author = {Müller, Magnus and Moerkotte, Guido and Kolb, Oliver},
journal = {PVLDB},
series = {{VLDB} '18},
volume = {11},
number = {9},
pages = {1016--1028},
doi = {10.14778/3213880.3213882},
url = {https://doi.org/10.14778/3213880.3213882},
year = {2018}
}
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|---|---|---|---|---|
| 1 | 76 | Practical Selectivity Estimation through Adaptive Sampling | 1990 | SIGMOD |
| 2 | 1,186 | Fixed-Precision Estimation of Join Selectivity | 1993 | PODS |
| 3 | 35 | Improved Histograms for Selectivity Estimation of Range Predicates | 1996 | SIGMOD |
| 4 | 2,308 | Hashed Samples: Selectivity Estimators For Set Similarity Selection Queries | 2008 | VLDB |
| 5 | 9,455 | Small Selectivities Matter: Lifting the Burden of Empty Samples | 2021 | SIGMOD |
| 6 | 7,388 | Synopses for Query Optimization: A Space-Complexity Perspective | 2004 | PODS |
| 7 | 3,788 | Graph-Based Synopses for Relational Selectivity Estimation | 2006 | SIGMOD |
| 8 | 3,162 | Efficiently Approximating Selectivity Functions using Low Overhead Regression Models | 2020 | VLDB |
| 9 | 280 | Selectivity Estimation using Probabilistic Models | 2001 | SIGMOD |
| 10 | 3,309 | Conditional Selectivity for Statistics on Query Expressions | 2004 | SIGMOD |