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Weighted Reservoir Sampling from Distributed Streams

Summary: First message-optimal algorithm for weighted sampling without replacement (weighted SWOR) from distributed streams, achieving optimal message, space, and time complexity and a nearly-tight message lower bound (up to log(1/ε)). Uses this primitive to give the first distributed algorithms for residual heavy hitters in skewed-weight streams and to tighten/improve message complexity bounds for distributed L1 (count) tracking, yielding matching lower bounds. (summarized by gpt-5-mini on Feb 09 2026)

Paper ID
1758
Venue
PODS
Year
2019
Pagerank
5.9749691e-05
Overall Rank
4,718 | 67.18%
DOI
10.1145/3294052.3319696

Incoming Non-self Citations Over Time

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Incoming Citations (Sorted by Pagerank)

Showing 5 of 5 citing papers.

Rank Citing Paper Year Venue Pagerank
4,172 The Adversarial Robustness of Sampling 2020 PODS 6.3879072e-05
8,610 Efficient Dynamic Weighted Set Sampling and Its Extension 2024 VLDB 4.4853485e-05
8,993 LightRW: FPGA Accelerated Graph Dynamic Random Walks 2023 SIGMOD 4.4130611e-05
10,353 Perfect Sampling in Turnstile Streams Beyond Small Moments 2025 PODS 4.1945683e-05
11,320 Truly Perfect Samplers for Data Streams and Sliding Windows 2022 PODS 4.1945683e-05
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Outgoing Citations (Sorted by Pagerank)

Showing 8 of 8 cited papers.

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

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