Graphalytics Global Competition

A Competition Platform to Compare Different Graph Processing Platforms

Bachelor thesis (2017)

Authors

C.S. Cao Electrical Engineering, Mathematics and Computer Science
M.S. Doesburg Electrical Engineering, Mathematics and Computer Science
S. Wang Electrical Engineering, Mathematics and Computer Science

Contributors

W.L. Ngai (mentor)
T.M. Hegeman (mentor)
A. Iosup (coach)
H. Wang (graduation committee member)
Faculty
Electrical Engineering, Mathematics and Computer Science, Electrical Engineering, Mathematics and Computer Science
Copyright: © 2017 Clinton Cao, Michiel Doesburg, Sunwei Wang
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Published Date

25-08-2017

Language

English

Reuse Rights

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Faculty

Electrical Engineering, Mathematics and Computer Science

Abstract

Graphs are becoming more popular day by day. This has lead to the development of different graph-processing platforms, such as Hadoop, Apache Giraph and GraphLab. With this wide variety of graph processing platforms, which one should we choose for a specific use case? Which platform has the best performance? To solve this issue, we can benchmark the different platforms. Our client developed a benchmark suite for graph processing platforms: the LDBC Graphalytics. Users can run the benchmark on the platforms and benchmark result files are generated. This result file contains thousands of lines of information. This makes comparing the benchmark result files not practical. A way to compare the benchmark results easily is to make the platforms compete in competitions. The platforms are then ranked based on their performance. For this, a website is needed to hosts the competitions. In this project, we have developed a global competition website that serves as a solution.