R2O: A Dual-Layer Framework for Joint Rewriting and Ordering in Distributed Property Graph Query Optimization
Summary: R2O targets distributed property-graph pattern queries by jointly optimizing partition-aware rewriting and inter-partition join ordering. Uses a dual-layer GNN+RL framework to shrink intermediate results and communication, delivering 1–2 orders-of-magnitude speedups on billion-scale graphs. (summarized by gpt-5-mini on Apr 11 2026)
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BibTeX Citation
@inproceedings{shi_sigmod26,
title = {{R2O: A Dual-Layer Framework for Joint Rewriting and Ordering in Distributed Property Graph Query Optimization}},
author = {Shi, Min and Peng, Peng and Xiao, Xin and Zou, Lei and Li, Kenli and Zhou, Xu},
series = {{SIGMOD} '26},
booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
publisher = {Association for Computing Machinery},
doi = {10.1145/3786685},
url = {https://dl.acm.org/doi/10.1145/3786685},
year = {2026}
}
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