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QuickSel: Quick Selectivity Learning with Mixture Models

Summary: QuickSel introduces a selectivity-learning framework that replaces histograms with a mixture model for query-driven estimation. It refines the model in milliseconds per batch, beating ISOMER/STHoles in speed and achieving higher accuracy for a fixed space. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
h41eaf43e6f416b46
Venue
SIGMOD
Year
2020
Pagerank
0.00011777105
Overall Rank
1,156 | 92.23%
DOI
10.1145/3318464.3389727

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@inproceedings{park_sigmod20,
        title = {{QuickSel: Quick Selectivity Learning with Mixture Models}},
        author = {Park, Yongjoo and Zhong, Shucheng and Mozafari, Barzan},
        series = {{SIGMOD} '20},
        booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
        publisher = {Association for Computing Machinery},
        doi = {10.1145/3318464.3389727},
        url = {https://dl.acm.org/doi/10.1145/3318464.3389727},
        year = {2020}
}

Incoming Citations (Sorted by Pagerank)

Showing 38 of 38 citing papers.

Rank Citing Paper Year Venue Pagerank
145 Neo: A Learned Query Optimizer 2019 VLDB 0.0002908188
362 Bao: Making Learned Query Optimization Practical 2021 SIGMOD 0.00019989474
406 Deep Unsupervised Cardinality Estimation 2020 VLDB 0.00019045544
512 NeuroCard: One Cardinality Estimator for All Tables 2021 VLDB 0.00017050173
868 Learning Multi-dimensional Indexes 2020 SIGMOD 0.00013354403
1,064 Are We Ready For Learned Cardinality Estimation? 2021 VLDB 0.00012202282
1,734 Flow-Loss: Learning Cardinality Estimates That Matter 2021 VLDB 9.7545773e-05
2,250 QueryFormer: A Tree Transformer Model for Query Plan Representation 2022 VLDB 8.7533306e-05
2,342 Learned Cardinality Estimation: An In-depth Study 2022 SIGMOD 8.6060437e-05
2,522 Learned Cardinality Estimation: A Design Space Exploration and A Comparative Evaluation 2022 VLDB 8.3477168e-05
2,908 AI Meets Database: AI4DB and DB4AI 2021 SIGMOD 7.8742664e-05
3,052 A Unified Deep Model of Learning from both Data and Queries for Cardinality Estimation 2021 SIGMOD 7.7052471e-05
3,210 Efficiently Approximating Selectivity Functions using Low Overhead Regression Models 2020 VLDB 7.5363533e-05
3,327 Robust Query Driven Cardinality Estimation under Changing Workloads 2023 VLDB 7.4207879e-05
3,645 UDO: Universal Database Optimization using Reinforcement Learning 2021 VLDB 7.1397796e-05
3,682 openGauss: An Autonomous Database System 2021 VLDB 7.1013922e-05
3,978 Efficient Deep Learning Pipelines for Accurate Cost Estimations Over Large Scale Query Workload 2021 SIGMOD 6.8807882e-05
4,688 Learned Cardinality Estimation for Similarity Queries 2021 SIGMOD 6.4697463e-05
4,741 Machine Learning for Databases 2021 VLDB 6.4410027e-05
4,950 Debunking the Myth of Join Ordering: Toward Robust SQL Analytics 2025 SIGMOD 6.3421691e-05
5,357 Can Large Language Models Predict Data Correlations from Column Names? 2023 VLDB 6.1619918e-05
5,831 Joins on Samples: A Theoretical Guide for Practitioners 2020 VLDB 5.9782109e-05
5,974 Towards instance-optimized data systems 2021 VLDB 5.9305575e-05
6,818 ASM: Harmonizing Autoregressive Model, Sampling, and Multi-dimensional Statistics Merging for Cardinality Estimation 2024 SIGMOD 5.672718e-05
7,332 Selectivity Functions of Range Queries are Learnable* 2022 SIGMOD 5.5499953e-05
8,164 Efficient Query Re-optimization with Judicious Subquery Selections 2023 SIGMOD 5.3852872e-05
8,258 The Case for NLP-Enhanced Database Tuning: Towards Tuning Tools that “Read the Manual” 2021 VLDB 5.3671363e-05
8,276 Consistent and Flexible Selectivity Estimation for High-Dimensional Data 2021 SIGMOD 5.3641556e-05
8,332 Learned Offline Query Planning via Bayesian Optimization 2025 SIGMOD 5.3528188e-05
8,524 ROME: Robust Query Optimization via Parallel Multi-Plan Execution 2024 SIGMOD 5.3231221e-05
8,879 Spatial Query Optimization With Learning 2024 VLDB 5.2568354e-05
9,575 A Step Toward Deep Online Aggregation 2023 SIGMOD 5.1571823e-05
9,718 A Practical Theory of Generalization in Selectivity Learning 2025 VLDB 5.1353964e-05
9,976 Selectivity Estimation for Queries Containing Predicates over Set-Valued Attributes 2023 SIGMOD 5.1031384e-05
10,294 Data-Agnostic Cardinality Learning from Imperfect Workloads 2025 VLDB 5.0431863e-05
10,336 An Elephant Under The Microscope: Analyzing The Interaction Of Optimizer Components In PostgreSQL 2025 SIGMOD 5.0200193e-05
10,412 Are Learned DBMS Components Robust to Workload Drift?: [Experiments & Analysis] 2026 SIGMOD 4.9793485e-05
10,802 BaCon: Efficient Batch Processing of Counting Queries 2026 VLDB 4.9793485e-05
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Outgoing Citations (Sorted by Pagerank)

Showing 48 of 48 cited papers.

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

Rank Cited Paper Year Venue Pagerank
1 Access Path Selection in a Relational Database Management System 1979 SIGMOD 0.0023947656
40 The Case for Learned Index Structures 2018 SIGMOD 0.00046284649
78 Automatic Database Management System Tuning Through Large-scale Machine Learning 2017 SIGMOD 0.00036684414
79 Practical Selectivity Estimation through Adaptive Sampling 1990 SIGMOD 0.00036487763
85 Learned Cardinalities: Estimating Correlated Joins with Deep Learning 2019 CIDR 0.00035864347
98 LEO - DB2's LEarning Optimizer 2001 VLDB 0.00034106982
121 Boosting the Accuracy of Differentially Private Histograms Through Consistency 2010 VLDB 0.00031089378
145 Neo: A Learned Query Optimizer 2019 VLDB 0.0002908188
160 CORDS: Automatic Discovery of Correlations and Soft Functional Dependencies 2004 SIGMOD 0.00027837289
232 Adaptive Selectivity Estimation Using Query Feedback 1994 SIGMOD 0.00023792809
275 Optimal Histograms with Quality Guarantees 1998 VLDB 0.00022413521
286 Selectivity Estimation using Probabilistic Models 2001 SIGMOD 0.0002211981
371 STHoles: A Multidimensional Workload-Aware Histogram 2001 SIGMOD 0.00019829769
454 Self-tuning Histograms: Building Histograms Without Looking at Data 1999 SIGMOD 0.00017962189
460 Query-based Workload Forecasting for Self-Driving Database Management Systems 2018 SIGMOD 0.00017842695
555 SageDB: A Learned Database System 2019 CIDR 0.00016506678
625 Optimizing Linear Counting Queries Under Differential Privacy 2010 PODS 0.00015478765
692 Selectivity Estimation for Range Predicates using Lightweight Models 2019 VLDB 0.00014741011
701 Independence is Good: Dependency-Based Histogram Synopses for High-Dimensional Data 2001 SIGMOD 0.00014680907
742 Dynamic Multidimensional Histograms 2002 SIGMOD 0.0001431602
866 Approximating Multi-Dimensional Aggregate Range Queries Over Real Attributes 2000 SIGMOD 0.00013381261
919 Estimating the Selectivity of XML Path Expressions for Internet Scale Applications 2001 VLDB 0.00013083677
956 Selectivity Estimation and Query Optimization in Large Databases with Highly Skewed Distributions of Column Values 1988 VLDB 0.00012865801
1,461 Substring Selectivity Estimation 1999 PODS 0.00010583833
1,465 Pessimistic Cardinality Estimation: Tighter Upper Bounds for Intermediate Join Cardinalities 2019 SIGMOD 0.00010576304
1,467 On the Relative Cost of Sampling for Join Selectivity Estimation 1994 PODS 0.00010567959
1,508 Self-Tuning, GPU-Accelerated Kernel Density Models for Multidimensional Selectivity Estimation 2015 SIGMOD 0.00010440205
1,687 Global Optimization of Histograms 2001 SIGMOD 9.8655879e-05
1,929 Consistently Estimating the Selectivity of Conjuncts of Predicates 2005 VLDB 9.3546057e-05
2,027 Database Learning: Toward a Database that Becomes Smarter Every Time 2017 SIGMOD 9.1618139e-05
2,140 SASH: A Self-Adaptive Histogram Set for Dynamically Changing Workloads 2003 VLDB 8.9682092e-05
3,005 Multiple Join Size Estimation by Virtual Domains (extended abstract) 1993 PODS 7.7621043e-05
3,269 Multi-Dimensional Substring Selectivity Estimation 1999 VLDB 7.4756338e-05
3,419 Revisiting Reuse for Approximate Query Processing 2017 VLDB 7.3190065e-05
3,599 Access Path Selection in Main-Memory Optimized Data Systems: Should I Scan or Should I Probe? 2017 SIGMOD 7.1773938e-05
3,644 Optimal Histograms for Hierarchical Range Queries (Extended Abstract) 2000 PODS 7.1399991e-05
3,851 Graph-Based Synopses for Relational Selectivity Estimation 2006 SIGMOD 6.9785886e-05
4,933 A Comparison of Selectivity Estimators for Range Queries on Metric Attributes 1999 SIGMOD 6.3474817e-05
5,004 Fast Algorithms For Hierarchical Range Histogram Construction 2002 PODS 6.3186165e-05
5,199 Exact Cardinality Query Optimization with Bounded Execution Cost 2019 SIGMOD 6.2327836e-05
5,652 Building Wavelet Histograms on Large Data in MapReduce 2012 VLDB 6.0515502e-05
5,815 Exploiting Ordered Dictionaries to Efficiently Construct Histograms with Q-Error Guarantees in SAP HANA 2014 SIGMOD 5.9844993e-05
5,973 Understanding Cardinality Estimation using Entropy Maximization 2010 PODS 5.9306716e-05
7,561 Selectivity Estimation on Streaming Spatio-Textual Data Using Local Correlations 2015 VLDB 5.4958573e-05
7,633 Consistent Histograms In The Presence of Distinct Value Counts 2009 VLDB 5.4792473e-05
8,576 Histograms as a Side Effect of Data Movement for Big Data 2014 SIGMOD 5.3111243e-05
8,592 Differentially Private Hierarchical Count-of-Counts Histograms 2018 VLDB 5.3069959e-05
9,992 Multiscale Histograms: Summarizing Topological Relations in Large Spatial Datasets 2003 VLDB 5.099523e-05
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Semantically Similar Papers

# Overall Rank Paper Year Venue
1 2,354 Hashed Samples: Selectivity Estimators For Set Similarity Selection Queries 2008 VLDB
2 8,276 Consistent and Flexible Selectivity Estimation for High-Dimensional Data 2021 SIGMOD
3 286 Selectivity Estimation using Probabilistic Models 2001 SIGMOD
4 1,542 Improved Selectivity Estimation by Combining Knowledge from Sampling and Synopses 2018 VLDB
5 169 Wavelet-Based Histograms for Selectivity Estimation 1998 SIGMOD
6 1,508 Self-Tuning, GPU-Accelerated Kernel Density Models for Multidimensional Selectivity Estimation 2015 SIGMOD
7 1,580 Deep Learning Models for Selectivity Estimation of Multi-Attribute Queries 2020 SIGMOD
8 9,333 Deep Query Optimization 2019 SIGMOD
9 692 Selectivity Estimation for Range Predicates using Lightweight Models 2019 VLDB
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