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: 0.0001801482
Overall Rank: 453 | 96.97%
DOI: 10.14778/3368289.3368296
PDF: Download (CC BY-NC-ND 4.0)

Incoming Non-self Citations Over Time

Authors

1. Ji Sun (Tsinghua University)
2. Guoliang Li (Tsinghua University)

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 109 citing papers.

Rank	Citing Paper	Year	Venue	Pagerank
5,982	Towards instance-optimized data systems	2021	VLDB	5.9096991e-05
6,113	Expand your Training Limits! Generating Training Data for ML-based Data Management	2021	SIGMOD	5.8662826e-05
6,121	Breaking It Down: An In-depth Study of Index Advisors	2024	VLDB	5.863893e-05
6,158	Rethinking Learned Cost Models: Why Start from Scratch?	2023	SIGMOD	5.8518237e-05
6,402	A Unified Transferable Model for ML-Enhanced DBMS	2022	CIDR	5.7800842e-05
6,672	Speeding Up End-to-end Query Execution via Learning-based Progressive Cardinality Estimation	2023	SIGMOD	5.6975871e-05
6,725	Simple Adaptive Query Processing vs. Learned Query Optimizers: Observations and Analysis	2023	VLDB	5.6826988e-05
6,812	dbET: Execution Time Distribution-based Plan Selection	2023	SIGMOD	5.6597129e-05
6,840	ASM: Harmonizing Autoregressive Model, Sampling, and Multi-dimensional Statistics Merging for Cardinality Estimation	2024	SIGMOD	5.6513231e-05
7,238	Refactoring Index Tuning Process with Benefit Estimation	2024	VLDB	5.5624225e-05
7,257	RCRank: Multimodal Ranking of Root Causes of Slow Queries in Cloud Database Systems	2025	VLDB	5.5579707e-05
7,363	Blueprinting the Cloud: Unifying and Automatically Optimizing Cloud Data Infrastructures with BRAD	2024	VLDB	5.5279826e-05
7,388	Towards Foundation Database Models	2025	CIDR	5.5211011e-05
7,483	T3: Accurate and Fast Performance Prediction for Relational Database Systems With Compiled Decision Trees	2025	SIGMOD	5.5007125e-05
7,517	DBMind: A Self-Driving Platform in openGauss	2021	VLDB	5.4895762e-05
7,561	Learned Offline Query Planning via Bayesian Optimization	2025	SIGMOD	5.4784915e-05
7,925	CAMAL: Optimizing LSM-trees via Active Learning	2024	SIGMOD	5.4086685e-05
7,975	Robust Query Processing: Mission Possible	2020	VLDB	5.3985544e-05
8,188	Efficient Query Re-optimization with Judicious Subquery Selections	2023	SIGMOD	5.3649397e-05
8,225	Grep: A Graph Learning Based Database Partitioning System	2023	SIGMOD	5.3583852e-05
8,297	Consistent and Flexible Selectivity Estimation for High-Dimensional Data	2021	SIGMOD	5.3438874e-05
8,550	ROME: Robust Query Optimization via Parallel Multi-Plan Execution	2024	SIGMOD	5.3030089e-05
8,657	LIMAO: A Framework for Lifelong Modular Learned Query Optimization	2025	VLDB	5.2790784e-05
8,685	ShadowAQP: Efficient Approximate Group-by and Join Query via Attribute-oriented Sample Size Allocation and Data Generation	2023	VLDB	5.2730954e-05
8,989	Conformal Prediction for Verifiable Learned Query Optimization	2025	VLDB	5.2304457e-05
9,011	Improving DBMS Scheduling Decisions with Accurate Performance Prediction on Concurrent Queries	2025	VLDB	5.2238303e-05
9,031	ByteCard: Enhancing ByteDance’s Data Warehouse with Learned Cardinality Estimation	2024	SIGMOD	5.219814e-05
9,143	Check Out the Big Brain on BRAD: Simplifying Cloud Data Processing with Learned Automated Data Meshes	2023	VLDB	5.2074327e-05
9,213	FEBench: A Benchmark for Real-Time Relational Data Feature Extraction	2023	VLDB	5.1926696e-05
9,583	Athena: An Effective Learning-based Framework for Query Optimizer Performance Improvement	2025	SIGMOD	5.140977e-05
9,655	Db2une: Tuning Under Pressure via Deep Learning	2024	VLDB	5.1307018e-05
9,681	Are Joins over LSM-trees Ready? Take RocksDB as an Example	2025	VLDB	5.1258854e-05
9,753	A Practical Theory of Generalization in Selectivity Learning	2025	VLDB	5.1159926e-05
9,756	APQO: An Adaptive Framework for Parametric Query Optimization	2026	SIGMOD	5.115551e-05
9,829	Wii: Dynamic Budget Reallocation In Index Tuning	2024	SIGMOD	5.1066866e-05
9,837	NeuSO: Neural Optimizer for Subgraph Queries	2026	SIGMOD	5.1064323e-05
9,952	Cardinality Estimation for Similarity Search on High-Dimensional Data Objects: The Impact of Reference Objects	2025	VLDB	5.0910746e-05
9,995	Graph Transformers for Query Plan Representation: Potentials and Challenges	2025	VLDB	5.0845476e-05
10,070	Cardinality Estimation of LIKE Predicate Queries using Deep Learning	2025	SIGMOD	5.0733319e-05
10,258	DBMS Fitting: Why should we learn what we already know?	2020	CIDR	5.0391159e-05
10,391	DQSim: Does the Task Assignment Slow Down Your Distributed Database System?	2027	SIGMOD	4.9605343e-05
10,392	E-LQO: A Comprehensive Energy Evaluation Framework for Learned Query Optimization	2027	SIGMOD	4.9605343e-05
10,393	EASE: Resource-aware Query Scheduling across Heterogeneous Cloud Compute Services	2027	SIGMOD	4.9605343e-05
10,490	Are Learned DBMS Components Robust to Workload Drift?: [Experiments & Analysis]	2026	SIGMOD	4.9605343e-05
10,500	Bridging the Gap: Cardinality Estimation for Semantic Queries on Unstructured Data	2026	SIGMOD	4.9605343e-05
10,608	Rainbow: Risk-aware Index Benefit Estimation Facing Out Of Distribution Workloads	2026	SIGMOD	4.9605343e-05
10,676	Understanding and Detecting Query Performance Regression in Practical Index Tuning: [Experiments & Analysis]	2026	SIGMOD	4.9605343e-05
10,745	Qualitative Join Discovery in Data Lakes using Examples	2026	SIGMOD	4.9605343e-05
10,751	Reqo: A Comprehensive Learning-Based Cost Model for Robust and Explainable Query Optimization	2026	SIGMOD	4.9605343e-05
10,764	Practical Parameterized Query Optimization via Efficient Plan Reuse and List-wise Ranking	2026	SIGMOD	4.9605343e-05

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
15	How Good Are Query Optimizers, Really?	2016	VLDB	0.00061463175
79	Practical Selectivity Estimation through Adaptive Sampling	1990	SIGMOD	0.00036394222
84	Learned Cardinalities: Estimating Correlated Joins with Deep Learning	2019	CIDR	0.00035920657
142	Neo: A Learned Query Optimizer	2019	VLDB	0.00029114937
254	The History of Histograms (abridged)	2003	VLDB	0.00022999992
309	An End-to-End Automatic Cloud Database Tuning System Using Deep Reinforcement Learning	2019	SIGMOD	0.0002143249
411	QTune: A Query-Aware Database Tuning System with Deep Reinforcement Learning	2019	VLDB	0.0001874043
545	Plan-Structured Deep Neural Network Models for Query Performance Prediction	2019	VLDB	0.0001657599
676	Robust Estimation of Resource Consumption for SQL Queries using Statistical Techniques	2012	VLDB	0.00014838681
689	Cardinality Estimation Done Right: Index-Based Join Sampling	2017	CIDR	0.00014725904
1,261	Sampling-Based Query Re-Optimization	2016	SIGMOD	0.00011289724
2,174	A Black-Box Approach to Query Cardinality Estimation	2007	CIDR	8.9067128e-05
2,614	Statistical Learning Techniques for Costing XML Queries	2005	VLDB	8.2023561e-05

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