WeTune: Automatic Discovery and Verification of Query Rewrite Rules
Summary: WeTune automatically discovers rewrite rules by enumerating relational plans up to a size, proposing equivalent rewrites. SMT-based verifier checks equivalence under enumerated constraints; on GitHub-app SQL, 247 queries are optimized beyond standard DBs. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Zhaoguo Wang (Chinese Ministry of Education; Shanghai Jiao Tong University)
- 2. Zhou Zhou (Chinese Ministry of Education; Shanghai Jiao Tong University)
- 3. Yicun Yang (Chinese Ministry of Education; Shanghai Jiao Tong University)
- 4. Haoran Ding (Chinese Ministry of Education; Shanghai Jiao Tong University)
- 5. Gansen Hu (Chinese Ministry of Education; Shanghai Jiao Tong University)
- 6. Ding Ding (New York University)
- 7. Chuzhe Tang (Chinese Ministry of Education; Shanghai Jiao Tong University)
- 8. Haibo Chen (Chinese Ministry of Education; Shanghai Jiao Tong University)
- 9. Jinyang Li (New York University)
BibTeX Citation
@inproceedings{wang_sigmod22,
title = {{WeTune: Automatic Discovery and Verification of Query Rewrite Rules}},
author = {Wang, Zhaoguo and Zhou, Zhou and Yang, Yicun and Ding, Haoran and Hu, Gansen and Ding, Ding and Tang, Chuzhe and Chen, Haibo and Li, Jinyang},
series = {{SIGMOD} '22},
booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
publisher = {Association for Computing Machinery},
doi = {10.1145/3514221.3526125},
url = {https://dl.acm.org/doi/10.1145/3514221.3526125},
year = {2022}
}
Incoming Citations (Sorted by Pagerank)
Showing 24 of 24 citing papers.
Previous
Page 1 / 1
Next
Outgoing Citations (Sorted by Pagerank)
Showing 20 of 20 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
Previous
Page 1 / 1
Next
Semantically Similar Papers
| # | Overall Rank | Paper | Year | Venue |
|---|---|---|---|---|
| 1 | 2,553 | LLM-R^2: A Large Language Model Enhanced Rule-based Rewrite System for Boosting Query Efficiency | 2025 | VLDB |
| 2 | 4,909 | QueryBooster: Improving SQL Performance Using Middleware Services for Human-Centered Query Rewriting | 2023 | VLDB |
| 3 | 13,310 | OmniTune: A Universal Framework for Query Refinement via LLMs | 2025 | SIGMOD |
| 4 | 2,298 | GPTuner: A Manual-Reading Database Tuning System via GPT-Guided Bayesian Optimization | 2024 | VLDB |
| 5 | 8,453 | A Learned Query Rewrite System | 2023 | VLDB |
| 6 | 4,363 | GenRewrite: Query Rewriting via Large Language Models | 2026 | SIGMOD |
| 7 | 498 | QTune: A Query-Aware Database Tuning System with Deep Reinforcement Learning | 2019 | VLDB |
| 8 | 11,326 | Demonstration of the VeriEQL Equivalence Checker for Complex SQL Queries | 2024 | VLDB |
| 9 | 3,003 | Configuration-Parametric Query Optimization for Physical Design Tuning | 2008 | SIGMOD |
| 10 | 10,139 | Leveraging Query Optimizers to Verify the Soundness of LLM-based Query Rewrites for Real-World Workloads, and More! | 2026 | CIDR |