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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)

Paper ID
11784
Venue
VLDB
Year
2018
Pagerank
0.00010460864
Overall Rank
1,536 | 89.47%
DOI
10.14778/3213880.3213882

Incoming Non-self Citations Over Time

Authors

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}
}

Incoming Citations (Sorted by Pagerank)

Showing 21 of 21 citing papers.

Rank Citing Paper Year Venue Pagerank
84 Learned Cardinalities: Estimating Correlated Joins with Deep Learning 2019 CIDR 0.00035838391
697 Selectivity Estimation for Range Predicates using Lightweight Models 2019 VLDB 0.00014888851
1,061 Are We Ready For Learned Cardinality Estimation? 2021 VLDB 0.00012369764
1,499 Pessimistic Cardinality Estimation: Tighter Upper Bounds for Intermediate Join Cardinalities 2019 SIGMOD 0.00010564536
1,573 Deep Learning Models for Selectivity Estimation of Multi-Attribute Queries 2020 SIGMOD 0.00010328171
2,355 QueryFormer: A Tree Transformer Model for Query Plan Representation 2022 VLDB 8.7022189e-05
2,940 G-CARE: A Framework for Performance Benchmarking of Cardinality Estimation Techniques for Subgraph Matching 2020 SIGMOD 7.9381573e-05
3,162 Efficiently Approximating Selectivity Functions using Low Overhead Regression Models 2020 VLDB 7.6785856e-05
3,215 Every Row Counts: Combining Sketches and Sampling for Accurate Group-By Result Estimates 2019 CIDR 7.6324234e-05
3,545 Astrid: Accurate Selectivity Estimation for String Predicates using Deep Learning 2021 VLDB 7.3249967e-05
3,959 Simplicity Done Right for Join Ordering 2021 CIDR 6.9879431e-05
4,205 Sample Debiasing in the Themis Open World Database System 2020 SIGMOD 6.8337021e-05
4,612 Warper: Efficiently Adapting Learned Cardinality Estimators to Data and Workload Drifts 2022 SIGMOD 6.6072026e-05
4,800 Scalable Reservoir Sampling on Many-Core CPUs 2019 SIGMOD 6.502434e-05
4,900 COMPASS: Online Sketch-based Query Optimization for In-Memory Databases 2021 SIGMOD 6.4534715e-05
5,010 Analyzing the Impact of Cardinality Estimation on Execution Plans in Microsoft SQL Server 2023 VLDB 6.4023732e-05
6,760 LPLM: A Neural Language Model for Cardinality Estimation of LIKE-Queries 2024 SIGMOD 5.7826781e-05
7,193 dbET: Execution Time Distribution-based Plan Selection 2023 SIGMOD 5.6770249e-05
7,351 PairwiseHist: Fast, Accurate and Space-Efficient Approximate Query Processing with Data Compression 2024 VLDB 5.6354898e-05
9,455 Small Selectivities Matter: Lifting the Burden of Empty Samples 2021 SIGMOD 5.2653318e-05
10,891 Cardinality Estimation for Having-Clauses 2025 VLDB 5.093636e-05
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Outgoing Citations (Sorted by Pagerank)

Showing 11 of 11 cited papers.

Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.

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