An Experimental Evaluation of Vertex-Centric K-Core Decomposition using Giraph and GraphChi
Date
2017-07-11
Authors
Hu, Xin
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Abstract
The analysis of characteristics of large-scale graphs has shown tremendous bene ts in
social networks, spam detection, epidemic disease control, analyzing software systems
and so on. However, today, processing graph algorithms on massive datasets is not
an easy task not only because of the large data volume, but also the complexity of the
graph algorithm. Therefore, a number of large-scale processing platforms have been
developed to tackle these problems. GraphChi is a popular system that is capable
of executing massive graph datasets on a single PC. Some researchers claim that
GraphChi has the same or even better performance, compared with distributed graphanalytics
platforms such as the popular Apache Giraph. In this paper, we implement
a well-optimized k-core decomposition algorithm on Giraph. Then we provide a
comparison of the performance of running the k-core decomposition algorithm in
Giraph and GraphChi using various graph datasets.
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Keywords
vertex-centric model, graph theory, Apache Giraph, GraphChi