LINE: A Learned Index with Group-Enhanced Leaves and Cache-Optimized Inner Tree
Summary: LINE combines linear-model group-enhanced leaves with in-group hashing for locally hard distributions and a cache-aware PLA-built inner tree for global skew. Group-wise SMO migration reduces worst-case tail latency, delivering up to 5.8× improvement. (summarized by gpt-5.6-luna on Jul 26 2026)
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Authors
- 1. Leying Chen (Chinese Academy of Sciences; University of Chinese Academy of Sciences)
- 2. Shimin Chen (Chinese Academy of Sciences; University of Chinese Academy of Sciences)
BibTeX Citation
@inproceedings{chen_sigmod26,
title = {{LINE: A Learned Index with Group-Enhanced Leaves and Cache-Optimized Inner Tree}},
author = {Chen, Leying and Chen, Shimin},
series = {{SIGMOD} '26},
booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
publisher = {Association for Computing Machinery},
doi = {10.1145/3802080},
url = {https://dl.acm.org/doi/10.1145/3802080},
year = {2026}
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