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Detect, Distill and Update: Learned DB Systems Facing Out of Distribution Data

Summary: DDUp is an updatability framework for learned DB components facing insertion-driven shifts, pairing OOD detection with efficient updates. It uses a test to flag OOD data and a distillation-based update to keep AQP, CE, DG accurate without retraining. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
6537
Venue
SIGMOD
Year
2023
Pagerank
4.9008421e-05
Overall Rank
6,860 | 52.33%
DOI
10.1145/3588713

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Showing 27 of 27 cited papers.

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

Rank Cited Paper Year Venue Pagerank
101 The Case for Learned Index Structures 2018 SIGMOD 0.00049778866
183 Automatic Database Management System Tuning Through Large-scale Machine Learning 2017 SIGMOD 0.00036859633
203 Learned Cardinalities: Estimating Correlated Joins with Deep Learning 2019 CIDR 0.00034868567
329 Neo: A Learned Query Optimizer 2019 VLDB 0.00027301488
510 An End-to-End Automatic Cloud Database Tuning System Using Deep Reinforcement Learning 2019 SIGMOD 0.00021420477
606 DeepDB: Learn from Data, not from Queries! 2020 VLDB 0.00019251186
634 Bao: Making Learned Query Optimization Practical 2021 SIGMOD 0.00018844568
752 Deep Unsupervised Cardinality Estimation 2020 VLDB 0.00017138049
779 QTune: A Query-Aware Database Tuning System with Deep Reinforcement Learning 2019 VLDB 0.00016719473
819 ALEX: An Updatable Adaptive Learned Index 2020 SIGMOD 0.00016237497
905 NeuroCard: One Cardinality Estimator for All Tables 2021 VLDB 0.00015423174
1,372 Random Sampling over Joins Revisited 2018 SIGMOD 0.0001233325
1,464 Learning Multi-dimensional Indexes 2020 SIGMOD 0.0001184772
1,699 Are We Ready For Learned Cardinality Estimation? 2021 VLDB 0.00010848882
1,887 Tsunami: A Learned Multi-dimensional Index for Correlated Data and Skewed Workloads 2021 VLDB 0.00010201938
2,364 Deep Learning Models for Selectivity Estimation of Multi-Attribute Queries 2020 SIGMOD 8.955077e-05
2,423 Data Synthesis based on Generative Adversarial Networks 2018 VLDB 8.8447357e-05
2,494 DBEst: Revisiting Approximate Query Processing Engines with Machine Learning Models 2019 SIGMOD 8.6457436e-05
2,769 FLAT: Fast, Lightweight and Accurate Method for Cardinality Estimation 2021 VLDB 8.1512848e-05
3,144 Active Learning for ML Enhanced Database Systems 2020 SIGMOD 7.4844943e-05
3,623 Cost Models for Big Data Query Processing: Learning, Retrofitting, and Our Findings 2020 SIGMOD 6.9017341e-05
3,691 Detecting Change in Data Streams 2004 VLDB 6.8345284e-05
4,800 Efficient Deep Learning Pipelines for Accurate Cost Estimations Over Large Scale Query Workload 2021 SIGMOD 5.9077188e-05
5,250 One Model to Rule them All: Towards Zero-Shot Learning for Databases 2022 CIDR 5.6007779e-05
5,799 Learned Approximate Query Processing: Make it Light, Accurate and Fast 2021 CIDR 5.3219666e-05
5,952 PGMJoins: Random Join Sampling with Graphical Models 2021 SIGMOD 5.2547498e-05
6,774 A Unified Transferable Model for ML-Enhanced DBMS 2022 CIDR 4.9253635e-05
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