DBScholar

Back to papers

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
h65c46788cb871bbe
Venue
VLDB
Year
2020
Pagerank
0.00017829982
Overall Rank
461 | 96.91%
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
318 DeepDB: Learn from Data, not from Queries! 2020 VLDB 0.00021167555
362 Bao: Making Learned Query Optimization Practical 2021 SIGMOD 0.00019989474
437 QTune: A Query-Aware Database Tuning System with Deep Reinforcement Learning 2019 VLDB 0.00018315867
512 NeuroCard: One Cardinality Estimator for All Tables 2021 VLDB 0.00017050173
982 Cardinality Estimation in DBMS: A Comprehensive Benchmark Evaluation 2022 VLDB 0.00012714044
1,064 Are We Ready For Learned Cardinality Estimation? 2021 VLDB 0.00012202282
1,199 Balsa: Learning a Query Optimizer Without Expert Demonstrations 2022 SIGMOD 0.00011563985
1,580 Deep Learning Models for Selectivity Estimation of Multi-Attribute Queries 2020 SIGMOD 0.00010180835
1,734 Flow-Loss: Learning Cardinality Estimates That Matter 2021 VLDB 9.7545773e-05
2,210 Lero: A Learning-to-Rank Query Optimizer 2023 VLDB 8.8257742e-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
2,395 A Learned Query Rewrite System using Monte Carlo Tree Search 2022 VLDB 8.5281914e-05
2,478 Learning a Partitioning Advisor for Cloud Databases 2020 SIGMOD 8.4079121e-05
2,522 Learned Cardinality Estimation: A Design Space Exploration and A Comparative Evaluation 2022 VLDB 8.3477168e-05
2,634 Neural Subgraph Counting with Wasserstein Estimator 2022 SIGMOD 8.1993804e-05
2,690 Cost-based or Learning-based? A Hybrid Query Optimizer for Query Plan Selection 2022 VLDB 8.1258173e-05
2,842 Query Performance Prediction for Concurrent Queries using Graph Embedding 2020 VLDB 7.949193e-05
2,846 FactorJoin: A New Cardinality Estimation Framework for Join Queries 2023 SIGMOD 7.9453616e-05
2,885 Zero-Shot Cost Models for Out-of-the-box Learned Cost Prediction 2022 VLDB 7.9094988e-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
3,160 A Learned Sketch for Subgraph Counting 2021 SIGMOD 7.5807496e-05
3,487 LOGER: A Learned Optimizer towards Generating Efficient and Robust Query Execution Plans 2023 VLDB 7.263041e-05
3,562 Astrid: Accurate Selectivity Estimation for String Predicates using Deep Learning 2021 VLDB 7.2046519e-05
3,682 openGauss: An Autonomous Database System 2021 VLDB 7.1013922e-05
3,703 Stable Learned Bloom Filters for Data Streams 2020 VLDB 7.0842566e-05
3,741 FACE: A Normalizing Flow based Cardinality Estimator 2022 VLDB 7.0594076e-05
3,965 MB2: Decomposed Behavior Modeling for Self-Driving Database Management Systems 2021 SIGMOD 6.8918628e-05
3,978 Efficient Deep Learning Pipelines for Accurate Cost Estimations Over Large Scale Query Workload 2021 SIGMOD 6.8807882e-05
4,079 Towards Dynamic and Safe Configuration Tuning for Cloud Databases 2022 SIGMOD 6.818264e-05
4,137 The Art of Balance: A RateupDB Experience of Building a CPU/GPU Hybrid Database Product 2021 VLDB 6.7861661e-05
4,258 LEON: A New Framework for ML-Aided Query Optimization 2023 VLDB 6.6994722e-05
4,457 Lightweight and Accurate Cardinality Estimation by Neural Network Gaussian Process 2022 SIGMOD 6.5913732e-05
4,538 One Model to Rule them All: Towards Zero-Shot Learning for Databases 2022 CIDR 6.553705e-05
4,688 Learned Cardinality Estimation for Similarity Queries 2021 SIGMOD 6.4697463e-05
4,707 PreQR: Pre-training Representation for SQL Understanding 2022 SIGMOD 6.4587914e-05
4,711 Learned Index Benefits: Machine Learning Based Index Performance Estimation 2022 VLDB 6.4573842e-05
4,741 Machine Learning for Databases 2021 VLDB 6.4410027e-05
4,781 Learned Approximate Query Processing: Make it Light, Accurate and Fast 2021 CIDR 6.4162085e-05
5,058 Fine-Grained Modeling and Optimization for Intelligent Resource Management in Big Data Processing 2022 VLDB 6.2926774e-05
5,126 Monotonic Cardinality Estimation of Similarity Selection: A Deep Learning Approach 2020 SIGMOD 6.261175e-05
5,194 Database Workload Characterization with Query Plan Encoders 2022 VLDB 6.2353557e-05
5,214 Stage: Query Execution Time Prediction in Amazon Redshift 2024 SIGMOD 6.2248104e-05
5,241 FASTgres: Making Learned Query Optimizer Hinting Effective 2023 VLDB 6.2154384e-05
5,456 Eraser: Eliminating Performance Regression on Learned Query Optimizer 2024 VLDB 6.1239873e-05
5,481 A Comparative Study and Component Analysis of Query Plan Representation Techniques in ML4DB Studies 2024 VLDB 6.1125124e-05
5,649 Sample-Efficient Cardinality Estimation Using Geometric Deep Learning 2024 VLDB 6.052326e-05
5,683 How Good are Learned Cost Models, Really? Insights from Query Optimization Tasks 2025 SIGMOD 6.0392183e-05
5,865 Modeling Shifting Workloads for Learned Database Systems 2024 SIGMOD 5.9659203e-05
Previous Page 1 / 3 Next

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.

Previous Page 1 / 1 Next

Semantically Similar Papers