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A Unified Transferable Model for ML-Enhanced DBMS

Summary: MTMLF: unified transferable ML for DBMS, using multi-task training to capture cross-task signals and pretrain–fine-tune to distill meta-knowledge across databases, eliminating expensive per-DB retraining and large new-data needs. Demonstrated for query optimization. (summarized by gpt-5-mini on Feb 09 2026)

Paper ID
h6e4acac5a725167a
Venue
CIDR
Year
2022
Pagerank
5.7920805e-05
Overall Rank
6,416 | 56.87%
DOI
-

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@inproceedings{wu_cidr22,
        address = {Amsterdam, Netherlands},
        series = {{CIDR} '22},
        title = {{A Unified Transferable Model for ML-Enhanced DBMS}},
        booktitle = {Proceedings of the {Conference} on {Innovative} {Data} {Systems} {Research}},
        author = {Wu, Ziniu and Yu, Pei and Yang, Peilun and Zhu, Rong and Han, Yuxing and Li, Yaliang and Lian, Defu and Zeng, Kai and Zhou, Jingren},
        year = {2022}
}

Incoming Citations (Sorted by Pagerank)

Showing 13 of 13 citing papers.

Rank Citing Paper Year Venue Pagerank
982 Cardinality Estimation in DBMS: A Comprehensive Benchmark Evaluation 2022 VLDB 0.00012714044
2,846 FactorJoin: A New Cardinality Estimation Framework for Join Queries 2023 SIGMOD 7.9453616e-05
4,311 ALECE: An Attention-based Learned Cardinality Estimator for SPJ Queries on Dynamic Workloads 2024 VLDB 6.6727978e-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
5,716 Detect, Distill and Update: Learned DB Systems Facing Out of Distribution Data 2023 SIGMOD 6.0194657e-05
7,385 Towards Foundation Database Models 2025 CIDR 5.5385053e-05
7,864 Blueprinting the Cloud: Unifying and Automatically Optimizing Cloud Data Infrastructures with BRAD 2024 VLDB 5.4367919e-05
9,012 ByteCard: Enhancing ByteDance’s Data Warehouse with Learned Cardinality Estimation 2024 SIGMOD 5.2375369e-05
9,133 Hit the Gym: Accelerating Query Execution to Efficiently Bootstrap Behavior Models for Self-Driving Database Management Systems 2024 VLDB 5.2229655e-05
10,216 PRICE: A Pretrained Model for Cross-Database Cardinality Estimation 2025 VLDB 5.0584922e-05
10,924 TATA: An Efficient Framework for Task Transfer in Query Plan Representation 2026 VLDB 4.9793485e-05
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Outgoing Citations (Sorted by Pagerank)

Showing 22 of 22 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 0.00061066921
40 The Case for Learned Index Structures 2018 SIGMOD 0.00046284649
85 Learned Cardinalities: Estimating Correlated Joins with Deep Learning 2019 CIDR 0.00035864347
145 Neo: A Learned Query Optimizer 2019 VLDB 0.0002908188
314 An End-to-End Automatic Cloud Database Tuning System Using Deep Reinforcement Learning 2019 SIGMOD 0.00021282642
318 DeepDB: Learn from Data, not from Queries! 2020 VLDB 0.00021167555
377 TURL: Table Understanding through Representation Learning 2021 VLDB 0.00019570264
406 Deep Unsupervised Cardinality Estimation 2020 VLDB 0.00019045544
430 ALEX: An Updatable Adaptive Learned Index 2020 SIGMOD 0.00018409112
437 QTune: A Query-Aware Database Tuning System with Deep Reinforcement Learning 2019 VLDB 0.00018315867
461 An End-to-End Learning-based Cost Estimator 2020 VLDB 0.00017829982
512 NeuroCard: One Cardinality Estimator for All Tables 2021 VLDB 0.00017050173
560 Plan-Structured Deep Neural Network Models for Query Performance Prediction 2019 VLDB 0.00016403151
868 Learning Multi-dimensional Indexes 2020 SIGMOD 0.00013354403
982 Cardinality Estimation in DBMS: A Comprehensive Benchmark Evaluation 2022 VLDB 0.00012714044
1,191 Tsunami: A Learned Multi-dimensional Index for Correlated Data and Skewed Workloads 2021 VLDB 0.00011590153
1,734 Flow-Loss: Learning Cardinality Estimates That Matter 2021 VLDB 9.7545773e-05
2,004 FLAT: Fast, Lightweight and Accurate Method for Cardinality Estimation 2021 VLDB 9.2065719e-05
2,275 Active Learning for ML Enhanced Database Systems 2020 SIGMOD 8.7090584e-05
2,834 Cost Models for Big Data Query Processing: Learning, Retrofitting, and Our Findings 2020 SIGMOD 7.9560627e-05
2,981 WiSeDB: A Learning-based Workload Management Advisor for Cloud Databases 2016 VLDB 7.7851845e-05
5,199 Exact Cardinality Query Optimization with Bounded Execution Cost 2019 SIGMOD 6.2327836e-05
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