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ADOPT: Adaptively Optimizing Attribute Orders for Worst-Case Optimal Join Algorithms via Reinforcement Learning
Summary: Adaptive query engine for worst-case optimal joins that searches attribute-order space (not relation order) via episodic trials and reinforcement learning to balance exploration vs. exploitation. Novel data structure reuses processed input to avoid redundant work and converge quickly to near-optimal orders under skew/correlation.
(summarized by gpt-5-mini on Feb 09 2026)
- Paper ID
- 13123
- Venue
- VLDB
- Year
- 2023
- Pagerank
- 4.6030518e-05
- Overall Rank
- 8,026 | 44.17%
- DOI
-
10.14778/3611479.3611489
Incoming Non-self Citations Over Time
Incoming Citations (Sorted by Pagerank)
Showing 4 of 4 citing papers.
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 |
| 1 |
Access Path Selection in a Relational Database Management System |
1979 |
SIGMOD |
0.0040449103 |
| 44 |
The Design Of Postgres |
1986 |
SIGMOD |
0.00071838587 |
| 71 |
How Good Are Query Optimizers, Really? |
2016 |
VLDB |
0.00059038975 |
| 115 |
Eddies: Continuously Adaptive Query Processing |
2000 |
SIGMOD |
0.00046221215 |
| 333 |
Neo: A Learned Query Optimizer |
2019 |
VLDB |
0.00027206884 |
| 342 |
EmptyHeaded: A Relational Engine for Graph Processing |
2016 |
SIGMOD |
0.00026795977 |
| 613 |
Design and Implementation of the LogicBlox System |
2015 |
SIGMOD |
0.00019181325 |
| 640 |
Bao: Making Learned Query Optimization Practical |
2021 |
SIGMOD |
0.00018759152 |
| 782 |
QTune: A Query-Aware Database Tuning System with Deep Reinforcement Learning |
2019 |
VLDB |
0.00016729063 |
| 834 |
Learning Linear Regression Models over Factorized Joins |
2016 |
SIGMOD |
0.00016135159 |
| 1,259 |
Aggregation and Ordering in Factorised Databases |
2013 |
VLDB |
0.00012995821 |
| 1,407 |
DB-BERT: A Database Tuning Tool that "Reads the Manual" |
2022 |
SIGMOD |
0.00012146739 |
| 1,827 |
An Inquiry into Machine Learning-based Automatic Configuration Tuning Services on Real-World Database Management Systems |
2021 |
VLDB |
0.00010390548 |
| 2,219 |
SkinnerDB: Regret-Bounded Query Evaluation via Reinforcement Learning |
2019 |
SIGMOD |
9.2623533e-05 |
| 2,275 |
Adopting Worst-Case Optimal Joins in Relational Database Systems |
2020 |
VLDB |
9.1262202e-05 |
| 4,913 |
UDO: Universal Database Optimization using Reinforcement Learning |
2021 |
VLDB |
5.8316231e-05 |
| 5,530 |
Permutable Compiled Queries: Dynamically Adapting Compiled Queries without Recompiling |
2021 |
VLDB |
5.4554282e-05 |
| 5,686 |
Budget-aware Index Tuning with Reinforcement Learning |
2022 |
SIGMOD |
5.3712312e-05 |
| 8,180 |
Demonstrating UDO: A Unified Approach for Optimizing Transaction Code, Physical Design, and System Parameters via Reinforcement Learning |
2021 |
SIGMOD |
4.5663204e-05 |
| 8,395 |
GRainDB: A Relational-core Graph-Relational DBMS |
2022 |
CIDR |
4.5277896e-05 |
| 8,775 |
SkinnerMT: Parallelizing for Efficiency and Robustness in Adaptive Query Processing on Multicore Platforms |
2023 |
VLDB |
4.4553047e-05 |
| 11,298 |
Demonstrating ADOPT: Adaptively Optimizing Attribute Orders for Worst-Case Optimal Joins via Reinforcement Learning |
2023 |
VLDB |
4.1945683e-05 |
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| Overall Rank |
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R2O: A Dual-Layer Framework for Joint Rewriting and Ordering in Distributed Property Graph Query Optimization |
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VLDB |
9.4170209e-05 |
| 2,275 |
Adopting Worst-Case Optimal Joins in Relational Database Systems |
2020 |
VLDB |
9.1262202e-05 |
| 1,619 |
Adaptive Optimization of Very Large Join Queries |
2018 |
SIGMOD |
0.00011111678 |
| 7,011 |
Simple Adaptive Query Processing vs. Learned Query Optimizers: Observations and Analysis |
2023 |
VLDB |
4.8629458e-05 |
| 2,219 |
SkinnerDB: Regret-Bounded Query Evaluation via Reinforcement Learning |
2019 |
SIGMOD |
9.2623533e-05 |
| 6,862 |
Join Order Selection with Deep Reinforcement Learning: Fundamentals, Techniques, and Challenges |
2023 |
VLDB |
4.9051979e-05 |
| 11,298 |
Demonstrating ADOPT: Adaptively Optimizing Attribute Orders for Worst-Case Optimal Joins via Reinforcement Learning |
2023 |
VLDB |
4.1945683e-05 |