Practical Parameterized Query Optimization via Efficient Plan Reuse and List-wise Ranking
Summary: PQO for repetitive analytical templates: PLARQ reuses a precomputed plan pool via similarity-based candidate retrieval, then applies a list-wise attention ranker. Practical PostgreSQL integration, no optimizer internals changes; large speedups over PostgreSQL and prior learned optimizers. (summarized by gpt-5.4-mini on Apr 11 2026)
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Authors
- 1. Hai Lan (University of Queensland)
- 2. Yang Yu (Wuhan University)
- 3. Zhifeng Bao (University of Queensland)
- 4. Zi Huang (University of Queensland)
- 5. Yuwei Peng (Wuhan University)
BibTeX Citation
@inproceedings{lan_sigmod26,
title = {{Practical Parameterized Query Optimization via Efficient Plan Reuse and List-wise Ranking}},
author = {Lan, Hai and Yu, Yang and Bao, Zhifeng and Huang, Zi and Peng, Yuwei},
series = {{SIGMOD} '26},
booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
publisher = {Association for Computing Machinery},
doi = {10.1145/3788254},
url = {https://dl.acm.org/doi/10.1145/3788254},
year = {2026}
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