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HotHash: Hotness-Aware Consistent Hashing for Cloud Databases

Summary: HotHash combines hotness-proportional range hashing with per-segment randomized virtual rings to preserve locality while balancing skewed workloads. It retains consistent-hashing robustness to node changes and improves average and tail latency by 1.4–150×. (summarized by gpt-5.6-luna on Jul 26 2026)

Paper ID
7446
Venue
SIGMOD
Year
2026
Pagerank
5.093636e-05
Overall Rank
10,255 | 29.65%
DOI
10.1145/3802073

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Authors

BibTeX Citation

@inproceedings{zhao_sigmod26,
        title = {{HotHash: Hotness-Aware Consistent Hashing for Cloud Databases}},
        author = {Zhao, Junyong and Yuan, Jia and Chen, Zui and Madden, Samuel and Cao, Lei},
        series = {{SIGMOD} '26},
        booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
        publisher = {Association for Computing Machinery},
        doi = {10.1145/3802073},
        url = {https://dl.acm.org/doi/10.1145/3802073},
        year = {2026}
}

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