The Complexity of Counting Cycles in the Adjacency List Streaming Model
Summary: Characterizes sublinear-space complexity of cycle counting in the adjacency-list streaming model: provides a two-pass triangle estimator using Õ(m / T^{2/3}) space. Proves no sublinear multipass algorithms for l-cycles (l≥5); 4-cycles are intermediate—sublinear in multipass but impossible in single-pass. (summarized by gpt-5-mini on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. John Kallaugher (University of Texas)
- 2. Andrew McGregor (University of Massachusetts Amherst)
- 3. Eric Price (University of Texas)
- 4. Sofya Vorotnikova (University of Massachusetts Amherst)
BibTeX Citation
@inproceedings{kallaugher_pods19,
address = {New York, NY, USA},
series = {{PODS} '19},
title = {{The Complexity of Counting Cycles in the Adjacency List Streaming Model}},
url = {https://dl.acm.org/doi/10.1145/3294052.3319706},
doi = {10.1145/3294052.3319706},
booktitle = {Proceedings of the {ACM} {SIGMOD} Symposium on {Principles} of {Database} {Systems}},
publisher = {Association for Computing Machinery},
author = {Kallaugher, John and McGregor, Andrew and Price, Eric and Vorotnikova, Sofya},
year = {2019}
}
Incoming Citations (Sorted by Pagerank)
Showing 4 of 4 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 5,506 | Accurate and Fast Approximate Graph Pattern Mining at Scale | 2025 | VLDB | 6.1925892e-05 |
| 6,873 | Triangle and Four Cycle Counting in the Data Stream Model | 2020 | PODS | 5.7495468e-05 |
| 9,048 | An Improved Fully Dynamic Algorithm for Counting 4-Cycles in General Graphs Using Fast Matrix Multiplication | 2025 | PODS | 5.3251649e-05 |
| 11,520 | Approximately Counting Subgraphs in Data Streams | 2022 | PODS | 5.093636e-05 |
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Outgoing Citations (Sorted by Pagerank)
Showing 3 of 3 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 |
| 5,110 | Better Algorithms for Counting Triangles in Data Streams | 2016 | PODS | 6.3609746e-05 |
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|---|---|---|---|---|
| 1 | 8,744 | On Asymptotic Cost of Triangle Listing in Random Graphs | 2017 | PODS |
| 2 | 9,048 | An Improved Fully Dynamic Algorithm for Counting 4-Cycles in General Graphs Using Fast Matrix Multiplication | 2025 | PODS |
| 3 | 4,500 | Approximately Counting Triangles in Large Graph Streams Including Edge Duplicates with a Fixed Memory Usage | 2018 | VLDB |
| 4 | 458 | Counting Triangles in Data Streams | 2006 | PODS |
| 5 | 8,928 | How the Degeneracy Helps for Triangle Counting in Graph Streams | 2020 | PODS |
| 6 | 2,635 | Sliding Window-based Approximate Triangle Counting over Streaming Graphs with Duplicate Edges | 2021 | SIGMOD |
| 7 | 11,520 | Approximately Counting Subgraphs in Data Streams | 2022 | PODS |
| 8 | 1,103 | Counting and Sampling Triangles from a Graph Stream | 2013 | VLDB |
| 9 | 5,110 | Better Algorithms for Counting Triangles in Data Streams | 2016 | PODS |
| 10 | 6,873 | Triangle and Four Cycle Counting in the Data Stream Model | 2020 | PODS |