Join Order Selection with Deep Reinforcement Learning: Fundamentals, Techniques, and Challenges
Summary: Tutorial surveys deep-RL join-order selection, relating approaches and contrasting their strengths with traditional optimization. Two open-source demonstrations and a synthesis of challenges highlight directions toward practical, experience-driven query optimization. (summarized by gpt-5.6-luna on Jul 24 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Zhengtong Yan (University of Helsinki)
- 2. Valter Uotila (University of Helsinki)
- 3. Jiaheng Lu (University of Helsinki)
BibTeX Citation
@article{yan_vldb23,
title = {{Join Order Selection with Deep Reinforcement Learning: Fundamentals, Techniques, and Challenges}},
author = {Yan, Zhengtong and Uotila, Valter and Lu, Jiaheng},
journal = {PVLDB},
series = {{VLDB} '23},
volume = {16},
number = {12},
pages = {3882--3885},
doi = {10.14778/3611540.3611576},
url = {https://doi.org/10.14778/3611540.3611576},
year = {2023}
}
Incoming Citations (Sorted by Pagerank)
Showing 6 of 6 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 8,879 | Spatial Query Optimization With Learning | 2024 | VLDB | 5.2568354e-05 |
| 9,073 | Machine Learning for Graph Data Management and Query Processing | 2025 | VLDB | 5.2283159e-05 |
| 9,720 | APQO: An Adaptive Framework for Parametric Query Optimization | 2026 | SIGMOD | 5.1349531e-05 |
| 10,741 | OBELISK: Efficient Offline Query Planning with Bayesian Optimization-Informed Language Model Reasoning | 2026 | VLDB | 4.9793485e-05 |
| 10,832 | ReSequel: Robust LLM-assisted Query Rewriting and Optimization using Templatization and Sampling | 2026 | VLDB | 4.9793485e-05 |
| 11,175 | AJOSC: Adaptive Join Order Selection for Continuous Queries | 2025 | SIGMOD | 4.9793485e-05 |
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Outgoing Citations (Sorted by Pagerank)
Showing 16 of 16 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
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Semantically Similar Papers
| # | Overall Rank | Paper | Year | Venue |
|---|---|---|---|---|
| 1 | 3,797 | Query Simplification: Graceful Degradation for Join-Order Optimization | 2009 | SIGMOD |
| 2 | 1,603 | SkinnerDB: Regret-Bounded Query Evaluation via Reinforcement Learning | 2019 | SIGMOD |
| 3 | 1,186 | Adaptive Optimization of Very Large Join Queries | 2018 | SIGMOD |
| 4 | 3,487 | LOGER: A Learned Optimizer towards Generating Efficient and Robust Query Execution Plans | 2023 | VLDB |
| 5 | 12,209 | Improving Join Reorderability with Compensation Operators | 2018 | SIGMOD |
| 6 | 4,741 | Machine Learning for Databases | 2021 | VLDB |
| 7 | 3,060 | Towards a Hands-Free Query Optimizer through Deep Learning | 2019 | CIDR |
| 8 | 8,039 | Efficiently Computing Join Orders with Heuristic Search | 2023 | SIGMOD |
| 9 | 7,367 | ADOPT: Adaptively Optimizing Attribute Orders for Worst-Case Optimal Join Algorithms via Reinforcement Learning | 2023 | VLDB |
| 10 | 11,806 | Demonstrating ADOPT: Adaptively Optimizing Attribute Orders for Worst-Case Optimal Joins via Reinforcement Learning | 2023 | VLDB |