Proceedings of the 9th international World Wide Web conference on Computer networks : the international journal of computer and telecommunications netowrking
Fast and practical indexing and querying of very large graphs
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MapReduce: simplified data processing on large clusters
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PEGASUS: A Peta-Scale Graph Mining System Implementation and Observations
ICDM '09 Proceedings of the 2009 Ninth IEEE International Conference on Data Mining
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Large scale graphs containing O(billion) of vertices are becoming increasingly common in various applications. With graphs of such proportion, efficient querying infrastructure becomes crucial. In this paper, we propose WOOster a hosted querying infrastructure designed specifically for the large graphs. We make two key contributions: a) Design of the WOOster framework. b)Scalable map-reduce algorithms for two popular graph queries: subgraph match and reachability. Our experiments show that the proposed map-reduce algorithms scale well with large synthetic datasets.