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Parallel Processing of Multiple Graph Queries Using MapReduce

Authors:
Song-Hyon Kim
Kyong-Ha Lee
Hyebong Choi
Yoon-Joon Lee

Keywords: parallel processing; MapReduce; graph query; big data;

Abstract:
Recently the volume of the graph data set is often too large to be processed with a single machine in a timely manner. A multi-user environment deteriorates this situation with many graph queries given by multiple users. In this paper, we address the problem of processing multiple graph queries over a large set of graphs. We devise several methods that support efficient processing of multiple graph queries based on MapReduce. Particularly, we focus on processing multiple queries for graph data in parallel with a single input scan. We show that our methods improve the performance of multiple graph query processing with various experiments.

Pages: 33 to 38

Copyright: Copyright (c) IARIA, 2013

Publication date: January 27, 2013

Published in: conference

ISSN: 2308-4332

ISBN: 978-1-61208-247-9

Location: Seville, Spain

Dates: from January 27, 2013 to February 1, 2013