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Sketch-based Querying of Distributed Sliding-Window Data Streams

Summary: Introduces ECM-sketch, a probabilistically accurate, time/count-based sliding-window synopsis supporting point and inner-product queries over high-dimensional streams. Local sketches compose into low-error summaries for distributed aggregation and continuous monitoring, enabling frequency, heavy-hitter, and quantile queries. (summarized by gpt-5.6-luna on Jul 24 2026)

Paper ID
10725
Venue
VLDB
Year
2012
Pagerank
5.5610113e-05
Overall Rank
7,713 | 47.09%
DOI
10.14778/2336664.2336667

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@article{papapetrou_vldb12,
        title = {{Sketch-based Querying of Distributed Sliding-Window Data Streams}},
        author = {Papapetrou, Odysseas and Garofalakis, Minos and Deligiannakis, Antonios},
        journal = {PVLDB},
        series = {{VLDB} '12},
        volume = {5},
        number = {10},
        pages = {992--1003},
        doi = {10.14778/2336664.2336667},
        url = {https://doi.org/10.14778/2336664.2336667},
        year = {2012}
}

Incoming Citations (Sorted by Pagerank)

Showing 3 of 3 citing papers.

Rank Citing Paper Year Venue Pagerank
7,479 Distributed Online Tracking 2015 SIGMOD 5.6081446e-05
8,878 Scotch: Generating FPGA-Accelerators for Sketching at Line Rate 2021 VLDB 5.3532614e-05
10,865 Approximation-First Timeseries Query At Scale 2025 VLDB 5.093636e-05
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Outgoing Citations (Sorted by Pagerank)

Showing 6 of 6 cited papers.

Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.

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