DiskJoin: Large-scale Vector Similarity Join with SSD
Summary: DiskJoin: first disk-based similarity join for billion-scale vectors on one machine, leveraging NVMe SSDs to avoid costly cluster communication. It minimizes read amplification via SSD-aware access, uses dynamic cache+eviction policies, and probabilistic pruning to achieve 50×–1000× speedups. (summarized by gpt-5-mini on Feb 11 2026)
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Authors
- 1. Yanqi Chen (University of Massachusetts Amherst)
- 2. Xiao Yan (Wuhan University)
- 3. Alexandra Meliou (Archimedes/Athena Research Center; University of Massachusetts Amherst)
- 4. Eric Lo (Chinese University of Hong Kong)
BibTeX Citation
@inproceedings{chen_sigmod26,
title = {{DiskJoin: Large-scale Vector Similarity Join with SSD}},
author = {Chen, Yanqi and Yan, Xiao and Meliou, Alexandra and Lo, Eric},
series = {{SIGMOD} '26},
booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
publisher = {Association for Computing Machinery},
doi = {10.1145/3769780},
url = {https://dl.acm.org/doi/10.1145/3769780},
year = {2026}
}
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