On Sampling from Massive Graph Streams
Summary: GPS is an order-based reservoir sampling framework for graphs, weighting edge samples to optimize subgraph estimation. Separates sampling from estimation (post- and in-stream) with a Martingale-based unbiased estimator; yields <1% error on subgraph counts while using <0.01% of edges. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Nesreen K. Ahmed (Intel)
- 2. Nick Duffield (Texas A&M University)
- 3. Theodore L. Willke (Intel)
- 4. Ryan A. Rossi (Palo Alto Research Center)
BibTeX Citation
@article{ahmed_vldb17,
title = {{On Sampling from Massive Graph Streams}},
author = {Ahmed, Nesreen K. and Duffield, Nick and Willke, Theodore L. and Rossi, Ryan A.},
journal = {PVLDB},
series = {{VLDB} '17},
volume = {10},
number = {11},
pages = {1430--1443},
doi = {10.14778/3137628.3137652},
url = {https://doi.org/10.14778/3137628.3137652},
year = {2017}
}Incoming Citations (Sorted by Pagerank)
Showing 5 of 5 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 4,143 | Efficient Biclique Counting in Large Bipartite Graphs | 2023 | SIGMOD | 6.8760066e-05 |
| 5,598 | Hypergraph Motifs: Concepts, Algorithms, and Discoveries | 2020 | VLDB | 6.1546212e-05 |
| 10,575 | AGIS: Fast Approximate Graph Pattern Mining with Structure-Informed Sampling | 2026 | VLDB | 5.093636e-05 |
| 10,877 | Efficient and Adaptive Estimation of Local Triadic Coefficients | 2025 | VLDB | 5.093636e-05 |
| 11,094 | Efficient Computation of Hyper-triangles on Hypergraphs | 2025 | VLDB | 5.093636e-05 |
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Outgoing Citations (Sorted by Pagerank)
Showing 4 of 4 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 458 | Counting Triangles in Data Streams | 2006 | PODS | 0.0001810876 |
| 1,103 | Counting and Sampling Triangles from a Graph Stream | 2013 | VLDB | 0.000121583 |
| 1,396 | Estimating PageRank on Graph Streams | 2008 | PODS | 0.00010921308 |
| 2,013 | Space Efficient Mining of Multigraph Streams | 2005 | PODS | 9.3068345e-05 |
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|---|---|---|---|---|
| 1 | 10,192 | An Efficient Streaming Algorithm for Approximating Graphlet Distributions | 2026 | SIGMOD |
| 2 | 2,013 | Space Efficient Mining of Multigraph Streams | 2005 | PODS |
| 3 | 11,520 | Approximately Counting Subgraphs in Data Streams | 2022 | PODS |
| 4 | 2,635 | Sliding Window-based Approximate Triangle Counting over Streaming Graphs with Duplicate Edges | 2021 | SIGMOD |
| 5 | 10,847 | GREAT: Generalized Reservoir Sampling based Triangle Counting Estimation over Streaming Graphs | 2025 | VLDB |
| 6 | 10,411 | Triangle Counting in Hypergraph Streams: A Complete and Practical Approach | 2026 | SIGMOD |
| 7 | 1,103 | Counting and Sampling Triangles from a Graph Stream | 2013 | VLDB |
| 8 | 458 | Counting Triangles in Data Streams | 2006 | PODS |
| 9 | 4,500 | Approximately Counting Triangles in Large Graph Streams Including Edge Duplicates with a Fixed Memory Usage | 2018 | VLDB |
| 10 | 5,110 | Better Algorithms for Counting Triangles in Data Streams | 2016 | PODS |