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Are We Ready For Learned Cardinality Estimation?

Summary: Assess readiness of learned cardinality estimators for production; static workloads yield gains, but training/inference costs are high. Dynamic updates hurt accuracy; sensitivity to correlation, skew, and domain shifts; emphasizes cost control and trustworthiness. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
12539
Venue
VLDB
Year
2021
Pagerank
0.00012369764
Overall Rank
1,061 | 92.73%
DOI
10.14778/3461535.3461552

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@article{wang_vldb21,
        title = {{Are We Ready For Learned Cardinality Estimation?}},
        author = {Wang, Xiaoying and Qu, Changbo and Wu, Weiyuan and Wang, Jiannan and Zhou, Qingqing},
        journal = {PVLDB},
        series = {{VLDB} '21},
        volume = {14},
        number = {9},
        pages = {1640--1654},
        doi = {10.14778/3461535.3461552},
        url = {https://doi.org/10.14778/3461535.3461552},
        year = {2021}
}

Incoming Citations (Sorted by Pagerank)

Showing 10 of 60 citing papers.

Rank Citing Paper Year Venue Pagerank
10,413 Understanding and Detecting Query Performance Regression in Practical Index Tuning: [Experiments & Analysis] 2026 SIGMOD 5.093636e-05
10,438 CorrBound: Cardinality Estimation Accounting for Inter- and Intra-relation Correlations 2026 SIGMOD 5.093636e-05
10,486 Qualitative Join Discovery in Data Lakes using Examples 2026 SIGMOD 5.093636e-05
10,508 Practical Parameterized Query Optimization via Efficient Plan Reuse and List-wise Ranking 2026 SIGMOD 5.093636e-05
10,515 Sample-based Distinct Cardinality Estimation for Multiple Attributes in Multi-Dataset Queries 2026 VLDB 5.093636e-05
10,529 Robust Predicate Transfer with Dynamic Execution 2026 VLDB 5.093636e-05
10,760 FAAQP: Fast and Accurate Approximate Query Processing based on Bitmap-augmented Sum-Product Network 2025 SIGMOD 5.093636e-05
10,945 The Accuracy of Cardinality Estimators: Unraveling the Evaluation Result Conundrum 2025 VLDB 5.093636e-05
11,160 Sub-optimal Join Order Identification with L1-error 2024 SIGMOD 5.093636e-05
11,290 Presto’s History-based Query Optimizer 2024 VLDB 5.093636e-05
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Outgoing Citations (Sorted by Pagerank)

Showing 50 of 52 cited papers.

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

Rank Cited Paper Year Venue Pagerank
18 How Good Are Query Optimizers, Really? 2016 VLDB 0.00059284255
35 Improved Histograms for Selectivity Estimation of Range Predicates 1996 SIGMOD 0.00048481081
36 Accurate Estimation Of The Number Of Tuples Satisfying A Condition 1984 SIGMOD 0.00048351457
43 The Case for Learned Index Structures 2018 SIGMOD 0.00046060254
76 Practical Selectivity Estimation through Adaptive Sampling 1990 SIGMOD 0.00037054261
84 Learned Cardinalities: Estimating Correlated Joins with Deep Learning 2019 CIDR 0.00035838391
101 Selectivity Estimation Without the Attribute Value Independence Assumption 1997 VLDB 0.00034376651
118 Equi-Depth Histograms For Estimating Selectivity Factors For Multi-Dimensional Queries 1988 SIGMOD 0.00031922279
154 Neo: A Learned Query Optimizer 2019 VLDB 0.00028726181
168 Wavelet-Based Histograms for Selectivity Estimation 1998 SIGMOD 0.00027541029
222 Adaptive Selectivity Estimation Using Query Feedback 1994 SIGMOD 0.00024193708
280 Selectivity Estimation using Probabilistic Models 2001 SIGMOD 0.00022454217
323 DeepDB: Learn from Data, not from Queries! 2020 VLDB 0.00021264788
334 An End-to-End Automatic Cloud Database Tuning System Using Deep Reinforcement Learning 2019 SIGMOD 0.00020875082
365 STHoles: A Multidimensional Workload-Aware Histogram 2001 SIGMOD 0.00020041735
388 Preventing Bad Plans by Bounding the Impact of Cardinality Estimation Errors 2009 VLDB 0.00019410042
401 Deep Unsupervised Cardinality Estimation 2020 VLDB 0.00019092557
445 Apache Calcite: A Foundational Framework for Optimized Query Processing Over Heterogeneous Data Sources 2018 SIGMOD 0.00018336751
448 Self-tuning Histograms: Building Histograms Without Looking at Data 1999 SIGMOD 0.00018292618
465 An End-to-End Learning-based Cost Estimator 2020 VLDB 0.0001803934
513 NeuroCard: One Cardinality Estimator for All Tables 2021 VLDB 0.00017190574
593 Wander Join: Online Aggregation via Random Walks 2016 SIGMOD 0.00016027871
692 Independence is Good: Dependency-Based Histogram Synopses for High-Dimensional Data 2001 SIGMOD 0.00014919816
694 Cardinality Estimation Done Right: Index-Based Join Sampling 2017 CIDR 0.00014911698
697 Selectivity Estimation for Range Predicates using Lightweight Models 2019 VLDB 0.00014888851
772 VerdictDB: Universalizing Approximate Query Processing 2018 SIGMOD 0.00014147905
850 Approximating Multi-Dimensional Aggregate Range Queries Over Real Attributes 2000 SIGMOD 0.00013619394
1,071 Lightweight Graphical Models for Selectivity Estimation Without Independence Assumptions 2011 VLDB 0.00012322342
1,170 QuickSel: Quick Selectivity Learning with Mixture Models 2020 SIGMOD 0.00011827259
1,256 Sampling-Based Query Re-Optimization 2016 SIGMOD 0.00011457194
1,499 Pessimistic Cardinality Estimation: Tighter Upper Bounds for Intermediate Join Cardinalities 2019 SIGMOD 0.00010564536
1,503 Self-Tuning, GPU-Accelerated Kernel Density Models for Multidimensional Selectivity Estimation 2015 SIGMOD 0.000105564
1,516 Cardinality Estimation: An Experimental Survey 2018 VLDB 0.00010520885
1,536 Improved Selectivity Estimation by Combining Knowledge from Sampling and Synopses 2018 VLDB 0.00010460864
1,573 Deep Learning Models for Selectivity Estimation of Multi-Attribute Queries 2020 SIGMOD 0.00010328171
1,621 Orca: A Modular Query Optimizer Architecture for Big Data 2014 SIGMOD 0.00010203114
1,668 Global Optimization of Histograms 2001 SIGMOD 0.00010057026
1,712 SkinnerDB: Regret-Bounded Query Evaluation via Reinforcement Learning 2019 SIGMOD 9.9492299e-05
1,799 DBEst: Revisiting Approximate Query Processing Engines with Machine Learning Models 2019 SIGMOD 9.7326398e-05
1,936 Consistently Estimating the Selectivity of Conjuncts of Predicates 2005 VLDB 9.4557372e-05
2,121 SASH: A Self-Adaptive Histogram Set for Dynamically Changing Workloads 2003 VLDB 9.1402718e-05
2,203 Estimating Join Selectivities using Bandwidth-Optimized Kernel Density Models 2017 VLDB 8.9610447e-05
2,281 Selectivity Estimation in Extensible Databases - A Neural Network Approach 1998 VLDB 8.8129279e-05
2,493 Applying the Golden Rule of Sampling for Query Estimation 2001 SIGMOD 8.5070756e-05
2,984 Multiple Join Size Estimation by Virtual Domains (extended abstract) 1993 PODS 7.8920597e-05
3,162 Efficiently Approximating Selectivity Functions using Low Overhead Regression Models 2020 VLDB 7.6785856e-05
3,219 iBTune: Individualized Buffer Tuning for Large-scale Cloud Databases 2019 VLDB 7.6283153e-05
3,366 AQP++: Connecting Approximate Query Processing With Aggregate Precomputation for Interactive Analytics 2018 SIGMOD 7.4748604e-05
3,605 Computation Reuse in Analytics Job Service at Microsoft 2018 SIGMOD 7.2640711e-05
3,865 The Case for a Learned Sorting Algorithm 2020 SIGMOD 7.0621718e-05
Previous Page 1 / 2 Next

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