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An End-to-End Learning-based Cost Estimator

Summary: An end-to-end tree-structured estimator jointly predicts query cardinality and execution cost, encoding both query predicates and physical operators. Pattern-based string embeddings improve generalization to predicate values without enumerating them, while handling complex query structures. (summarized by gpt-5.6-luna on Jul 24 2026)

Paper ID
12379
Venue
VLDB
Year
2020
Pagerank
0.0001803934
Overall Rank
465 | 96.82%
DOI
10.14778/3368289.3368296

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@article{sun_vldb20,
        title = {{An End-to-End Learning-based Cost Estimator}},
        author = {Sun, Ji and Li, Guoliang},
        journal = {PVLDB},
        series = {{VLDB} '20},
        volume = {13},
        number = {3},
        pages = {307--319},
        doi = {10.14778/3368289.3368296},
        url = {https://doi.org/10.14778/3368289.3368296},
        year = {2020}
}

Incoming Citations (Sorted by Pagerank)

Showing 50 of 106 citing papers.

Rank Citing Paper Year Venue Pagerank
323 DeepDB: Learn from Data, not from Queries! 2020 VLDB 0.00021264788
378 Bao: Making Learned Query Optimization Practical 2021 SIGMOD 0.00019638121
498 QTune: A Query-Aware Database Tuning System with Deep Reinforcement Learning 2019 VLDB 0.00017440583
513 NeuroCard: One Cardinality Estimator for All Tables 2021 VLDB 0.00017190574
1,061 Are We Ready For Learned Cardinality Estimation? 2021 VLDB 0.00012369764
1,122 Cardinality Estimation in DBMS: A Comprehensive Benchmark Evaluation 2022 VLDB 0.0001209124
1,241 Balsa: Learning a Query Optimizer Without Expert Demonstrations 2022 SIGMOD 0.00011521639
1,573 Deep Learning Models for Selectivity Estimation of Multi-Attribute Queries 2020 SIGMOD 0.00010328171
1,876 Flow-Loss: Learning Cardinality Estimates That Matter 2021 VLDB 9.5717543e-05
2,355 QueryFormer: A Tree Transformer Model for Query Plan Representation 2022 VLDB 8.7022189e-05
2,420 Lero: A Learning-to-Rank Query Optimizer 2023 VLDB 8.605257e-05
2,452 A Learned Query Rewrite System using Monte Carlo Tree Search 2022 VLDB 8.5584e-05
2,499 Learning a Partitioning Advisor for Cloud Databases 2020 SIGMOD 8.4993549e-05
2,543 Learned Cardinality Estimation: An In-depth Study 2022 SIGMOD 8.4445934e-05
2,723 Learned Cardinality Estimation: A Design Space Exploration and A Comparative Evaluation 2022 VLDB 8.2049453e-05
2,731 Neural Subgraph Counting with Wasserstein Estimator 2022 SIGMOD 8.1959181e-05
2,762 Cost-based or Learning-based? A Hybrid Query Optimizer for Query Plan Selection 2022 VLDB 8.1539867e-05
2,812 Query Performance Prediction for Concurrent Queries using Graph Embedding 2020 VLDB 8.0979597e-05
2,844 Zero-Shot Cost Models for Out-of-the-box Learned Cost Prediction 2022 VLDB 8.0608767e-05
2,888 AI Meets Database: AI4DB and DB4AI 2021 SIGMOD 7.9941489e-05
2,991 FactorJoin: A New Cardinality Estimation Framework for Join Queries 2023 SIGMOD 7.8880723e-05
3,086 A Unified Deep Model of Learning from both Data and Queries for Cardinality Estimation 2021 SIGMOD 7.7708642e-05
3,283 A Learned Sketch for Subgraph Counting 2021 SIGMOD 7.56675e-05
3,516 LOGER: A Learned Optimizer towards Generating Efficient and Robust Query Execution Plans 2023 VLDB 7.3524442e-05
3,545 Astrid: Accurate Selectivity Estimation for String Predicates using Deep Learning 2021 VLDB 7.3249967e-05
3,662 openGauss: An Autonomous Database System 2021 VLDB 7.2166682e-05
3,688 FACE: A Normalizing Flow based Cardinality Estimator 2022 VLDB 7.201795e-05
3,953 Efficient Deep Learning Pipelines for Accurate Cost Estimations Over Large Scale Query Workload 2021 SIGMOD 6.996368e-05
3,961 MB2: Decomposed Behavior Modeling for Self-Driving Database Management Systems 2021 SIGMOD 6.987575e-05
4,011 Towards Dynamic and Safe Configuration Tuning for Cloud Databases 2022 SIGMOD 6.959982e-05
4,073 Stable Learned Bloom Filters for Data Streams 2020 VLDB 6.9242783e-05
4,368 Lightweight and Accurate Cardinality Estimation by Neural Network Gaussian Process 2022 SIGMOD 6.7393882e-05
4,434 LEON: A New Framework for ML-Aided Query Optimization 2023 VLDB 6.7079088e-05
4,468 One Model to Rule them All: Towards Zero-Shot Learning for Databases 2022 CIDR 6.6819041e-05
4,603 The Art of Balance: A RateupDB Experience of Building a CPU/GPU Hybrid Database Product 2021 VLDB 6.6105578e-05
4,617 Learned Cardinality Estimation for Similarity Queries 2021 SIGMOD 6.604437e-05
4,643 Learned Index Benefits: Machine Learning Based Index Performance Estimation 2022 VLDB 6.5907466e-05
4,671 PreQR: Pre-training Representation for SQL Understanding 2022 SIGMOD 6.5732787e-05
4,789 Learned Approximate Query Processing: Make it Light, Accurate and Fast 2021 CIDR 6.5072039e-05
5,011 Monotonic Cardinality Estimation of Similarity Selection: A Deep Learning Approach 2020 SIGMOD 6.4020848e-05
5,073 Database Workload Characterization with Query Plan Encoders 2022 VLDB 6.3751266e-05
5,107 Stage: Query Execution Time Prediction in Amazon Redshift 2024 SIGMOD 6.3623786e-05
5,277 FASTgres: Making Learned Query Optimizer Hinting Effective 2023 VLDB 6.2859099e-05
5,340 Machine Learning for Databases 2021 VLDB 6.2603359e-05
5,388 Fine-Grained Modeling and Optimization for Intelligent Resource Management in Big Data Processing 2022 VLDB 6.2362811e-05
5,573 Eraser: Eliminating Performance Regression on Learned Query Optimizer 2024 VLDB 6.1682747e-05
5,712 Sample-Efficient Cardinality Estimation Using Geometric Deep Learning 2024 VLDB 6.1123894e-05
5,767 A Comparative Study and Component Analysis of Query Plan Representation Techniques in ML4DB Studies 2024 VLDB 6.0945741e-05
5,974 Towards instance-optimized data systems 2021 VLDB 6.0230488e-05
6,024 Expand your Training Limits! Generating Training Data for ML-based Data Management 2021 SIGMOD 6.0031118e-05
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Outgoing Citations (Sorted by Pagerank)

Showing 13 of 13 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
76 Practical Selectivity Estimation through Adaptive Sampling 1990 SIGMOD 0.00037054261
84 Learned Cardinalities: Estimating Correlated Joins with Deep Learning 2019 CIDR 0.00035838391
154 Neo: A Learned Query Optimizer 2019 VLDB 0.00028726181
257 The History of Histograms (abridged) 2003 VLDB 0.00023154793
334 An End-to-End Automatic Cloud Database Tuning System Using Deep Reinforcement Learning 2019 SIGMOD 0.00020875082
498 QTune: A Query-Aware Database Tuning System with Deep Reinforcement Learning 2019 VLDB 0.00017440583
563 Plan-Structured Deep Neural Network Models for Query Performance Prediction 2019 VLDB 0.0001650812
682 Robust Estimation of Resource Consumption for SQL Queries using Statistical Techniques 2012 VLDB 0.00015014887
694 Cardinality Estimation Done Right: Index-Based Join Sampling 2017 CIDR 0.00014911698
1,256 Sampling-Based Query Re-Optimization 2016 SIGMOD 0.00011457194
2,157 A Black-Box Approach to Query Cardinality Estimation 2007 CIDR 9.0625592e-05
2,589 Statistical Learning Techniques for Costing XML Queries 2005 VLDB 8.371643e-05
Previous Page 1 / 1 Next

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