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Over the last two decades, frameworks for distributed-memory parallel computation, such as MapReduce, Hadoop, Spark and Dryad, have gained significant popularity with the growing prevalence of large network datasets. The Massively Parallel…

Data Structures and Algorithms · Computer Science 2022-07-19 Amartya Shankha Biswas , Talya Eden , Quanquan C. Liu , Slobodan Mitrović , Ronitt Rubinfeld

In this work, we present the first efficient and practical algorithm for estimating the number of triangles in a graph stream using predictions. Our algorithm combines waiting room sampling and reservoir sampling with a predictor for the…

Data Structures and Algorithms · Computer Science 2024-09-24 Cristian Boldrin , Fabio Vandin

Triangle counting in hypergraph streams, including both hyper-vertex and hyper-edge triangles, is a fundamental problem in hypergraph analytics, with broad applications. However, existing methods face two key limitations: (i) an incomplete…

Data Structures and Algorithms · Computer Science 2025-09-03 Lingkai Meng , Long Yuan , Xuemin Lin , Wenjie Zhang , Ying Zhang

The problem of (approximately) counting the number of triangles in a graph is one of the basic problems in graph theory. In this paper we study the problem in the streaming model. We study the amount of memory required by a randomized…

Data Structures and Algorithms · Computer Science 2013-04-05 Vladimir Braverman , Rafail Ostrovsky , Dan Vilenchik

We give a sharp bound on the number of triangles in a graph with fixed number of edges. We also characterize graphs that achieve the maximum number of triangles. Using the upper bound on number of triangles, we prove that if $G$ is a…

Group Theory · Mathematics 2022-05-13 Tony N. Mavely , Viji Z. Thomas

A new algorithm for exactly sampling from the set of proper colorings of a graph is presented. This is the first such algorithm that has an expected running time that is guaranteed to be linear in the size of a graph with maximum degree \(…

Probability · Mathematics 2026-01-01 Kritika Bhandari , Mark Huber

MapReduce has become the de facto standard model for designing distributed algorithms to process big data on a cluster. There has been considerable research on designing efficient MapReduce algorithms for clustering, graph optimization, and…

Data Structures and Algorithms · Computer Science 2018-06-19 Nicholas J. A. Harvey , Christopher Liaw , Paul Liu

This paper studies sufficient conditions to obtain efficient distributed algorithms coloring graphs optimally (i.e.\ with the minimum number of colors) in the LOCAL model of computation. Most of the work on distributed vertex coloring so…

Combinatorics · Mathematics 2019-01-25 Étienne Bamas , Louis Esperet

We develop an algorithmic framework for graph colouring that reduces the problem to verifying a local probabilistic property of the independent sets. With this we give, for any fixed $k\ge 3$ and $\varepsilon>0$, a randomised…

Data Structures and Algorithms · Computer Science 2020-04-16 Ewan Davies , Ross J. Kang , François Pirot , Jean-Sébastien Sereni

Big graphs (networks) arising in numerous application areas pose significant challenges for graph analysts as these graphs grow to billions of nodes and edges and are prohibitively large to fit in the main memory. Finding the number of…

Distributed, Parallel, and Cluster Computing · Computer Science 2017-06-19 Shaikh Arifuzzaman , Maleq Khan , Madhav Marathe

We tackle the problem of counting the number of $k$-cliques in large-scale graphs, for any constant $k \ge 3$. Clique counting is essential in a variety of applications, among which social network analysis. Due to its computationally…

Distributed, Parallel, and Cluster Computing · Computer Science 2018-04-13 Irene Finocchi , Marco Finocchi , Emanuele G. Fusco

We present a randomized distributed algorithm that computes a $\Delta$-coloring in any non-complete graph with maximum degree $\Delta \geq 4$ in $O(\log \Delta) + 2^{O(\sqrt{\log\log n})}$ rounds, as well as a randomized algorithm that…

Data Structures and Algorithms · Computer Science 2020-08-04 Mohsen Ghaffari , Juho Hirvonen , Fabian Kuhn , Yannic Maus

The task of listing all triangles in an undirected graph is a fundamental graph primitive with numerous applications. It is trivially solvable in time cubic in the number of vertices. It has seen a significant body of work contributing to…

Data Structures and Algorithms · Computer Science 2018-12-24 Matthias Bentert , Till Fluschnik , André Nichterlein , Rolf Niedermeier

Counting triangles in a graph and incident to each vertex is a fundamental and frequently considered task of graph analysis. We consider how to efficiently do this for huge graphs using massively parallel distributed-memory machines.…

Distributed, Parallel, and Cluster Computing · Computer Science 2023-07-24 Peter Sanders , Tim Niklas Uhl

In this paper, we prove a local limit theorem for the distribution of the number of triangles in the Erdos-Renyi random graph $G(n,p)$, where $p \in (0,1)$ is a fixed constant. Our proof is based on bounding the characteristic function…

Combinatorics · Mathematics 2014-12-09 Justin Gilmer , Swastik Kopparty

Pattern counting in graphs is a fundamental primitive for many network analysis tasks, and a number of methods have been developed for scaling subgraph counting to large graphs. Many real-world networks carry a natural notion of strength of…

Social and Information Networks · Computer Science 2019-10-03 Raunak Kumar , Paul Liu , Moses Charikar , Austin R. Benson

We count the asymptotic number of triangles in uniform random graphs where the degree distribution follows a power law with degree exponent $\tau\in(2,3)$. We also analyze the local clustering coefficient $c(k)$, the probability that two…

Probability · Mathematics 2018-12-12 Pu Gao , Remco van der Hofstad , Angus Southwell , Clara Stegehuis

In this short note, we give a novel algorithm for $O(1)$ round triangle counting in bounded arboricity graphs. Counting triangles in $O(1)$ rounds (exactly) is listed as one of the interesting remaining open problems in the recent survey of…

Data Structures and Algorithms · Computer Science 2024-05-02 Quanquan C. Liu , C. Seshadhri

We prove several new tight distributed lower bounds for classic symmetry breaking graph problems. As a basic tool, we first provide a new insightful proof that any deterministic distributed algorithm that computes a $\Delta$-coloring on…

Distributed, Parallel, and Cluster Computing · Computer Science 2022-06-03 Alkida Balliu , Sebastian Brandt , Fabian Kuhn , Dennis Olivetti

We resolve a number of long-standing open problems in online graph coloring. More specifically, we develop tight lower bounds on the performance of online algorithms for fundamental graph classes. An important contribution is that our…

Data Structures and Algorithms · Computer Science 2017-07-04 Susanne Albers , Sebastian Schraink