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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, the authors address the problem of processing multiple graph queries over a large set of graphs. They devise several methods that support efficient processing of multiple graph queries based on MapReduce. Particularly, they focus on processing multiple queries for graph data in parallel with a single input scan. They show that their methods improve the performance of multiple graph query processing with various experiments.
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