LEAP: A Low-cost Spark SQL Query Optimizer using Pairwise Comparison
Summary: LEAP is the first learned optimizer tailored to Spark SQL, avoiding unsupported physical-operator enumeration. It uses estimation-free pairwise plan comparisons and progressive, pruned enumeration, cutting native-optimizer execution time by up to 54%. (summarized by gpt-5.6-luna on Jul 24 2026)
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Authors
- 1. Junhao Ye (Zhejiang University)
- 2. Jiahui Li (Zhejiang University)
- 3. Lu Chen (Zhejiang University)
- 4. Yuren Mao (Zhejiang Key Laboratory of Big Data Intelligent Computing; Zhejiang University)
- 5. Yunjun Gao (Zhejiang Key Laboratory of Big Data Intelligent Computing; Zhejiang University)
- 6. Tianyi Li (Aalborg University)
BibTeX Citation
@article{ye_vldb25,
title = {{LEAP: A Low-cost Spark SQL Query Optimizer using Pairwise Comparison}},
author = {Ye, Junhao and Li, Jiahui and Chen, Lu and Mao, Yuren and Gao, Yunjun and Li, Tianyi},
journal = {PVLDB},
series = {{VLDB} '25},
volume = {18},
number = {3},
pages = {675--687},
doi = {10.14778/3712221.3712234},
url = {https://doi.org/10.14778/3712221.3712234},
year = {2025}
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