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Determining Exact Quantiles with Randomized Summaries

Summary: Leverages randomized summaries (KLL) to form probabilistic filters that shrink the quantile range, reducing passes vs deterministic methods. Deployed in IoTDB's LSM-tree, it enables cross-query pass sharing and shows ~0.5 fewer passes with ~18% speedup empirically. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
6896
Venue
SIGMOD
Year
2024
Pagerank
5.2755515e-05
Overall Rank
9,386 | 35.61%
DOI
10.1145/3639280

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@inproceedings{chen_sigmod24,
        title = {{Determining Exact Quantiles with Randomized Summaries}},
        author = {Chen, Ziling and Guan, Haoquan and Song, Shaoxu and Huang, Xiangdong and Wang, Chen and Wang, Jianmin},
        series = {{SIGMOD} '24},
        booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
        publisher = {Association for Computing Machinery},
        doi = {10.1145/3639280},
        url = {https://dl.acm.org/doi/10.1145/3639280},
        year = {2024}
}

Incoming Citations (Sorted by Pagerank)

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10,673 Pandora: An Efficient and Rapid Solution for Persistence-Based Tasks in High-Speed Data Streams 2025 SIGMOD 5.093636e-05
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