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On the algebra of data sketches

Summary: Proposes a mergeable, distributed data sketch for multi-node streams that supports set-theoretic operations on summaries. Key strengths: weighted elements, simultaneous ops across many sketches, and low-overhead accuracy control without expensive numerical computations. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
12352
Venue
VLDB
Year
2021
Pagerank
4.5086031e-05
Overall Rank
8,452 | 41.21%
DOI
10.14778/3461535.3461553

Incoming Non-self Citations Over Time

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Incoming Citations (Sorted by Pagerank)

Showing 2 of 2 citing papers.

Rank Citing Paper Year Venue Pagerank
8,451 Efficient framework for operating on data sketches 2023 VLDB 4.5086031e-05
9,038 OmniSketch: Efficient Multi-Dimensional High-Velocity Stream Analytics with Arbitrary Predicates 2024 VLDB 4.4039656e-05
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Outgoing Citations (Sorted by Pagerank)

Showing 1 of 1 cited papers.

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

Rank Cited Paper Year Venue Pagerank
402 Mergeable Summaries 2012 PODS 0.00024196343
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