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Randomized Error Removal for Online Spread Estimation in Data Streaming

Summary: Introduces multi-flow spread sketches using randomized error removal to improve per-flow distinct counting under tight memory. Formal analysis and hardware/software evaluations show superior accuracy, update throughput, and online query throughput over prior art. (summarized by gpt-5.6-luna on Jul 24 2026)

Paper ID
12483
Venue
VLDB
Year
2021
Pagerank
6.2369655e-05
Overall Rank
5,385 | 63.06%
DOI
10.14778/3447689.3447707

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@article{wang_vldb21,
        title = {{Randomized Error Removal for Online Spread Estimation in Data Streaming}},
        author = {Wang, Haibo and Ma, Chaoyi and Odegbile, Olufemi O and Chen, Shigang and Peir, Jih-Kwon},
        journal = {PVLDB},
        series = {{VLDB} '21},
        volume = {14},
        number = {6},
        pages = {1040--1052},
        doi = {10.14778/3447689.3447707},
        url = {https://doi.org/10.14778/3447689.3447707},
        year = {2021}
}

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