As the availability of large scale RDF data sets has grown, there has been a corresponding growth in researchers' and practitioners' interest in analyzing and investigating these data sets. However, given their size and messiness, there is significant overhead in setting up the infrastructure to store and query them. In this paper, we present TripleCloud, a system that aims to lower the entry cost to exploring Web-scale RDF data sets. The system takes advantage of existing cloud based key-value stores (e.g. BigTable, HBase) to both enable scalability as well as hide the complexities of infrastructure deployment and maintenance. It layers over these key-value stores a robust query engine able to return approximate answers. We test the scalability of the approach scaling to over 3 billion triples for complex queries. In addition to an implementation over HBase, TripleCloud runs over the Google App Engine, allowing us to perform a cost evaluation of the approach. © 2011 IEEE.
|Title of host publication||IEEE/WIC/ACM International Conferences on Web Intelligence and Intelligent Agent Technolog|
|Publication status||Published - 2011|
|Event||International Conferences on Web Intelligence and Intelligent Agent Technology - |
Duration: 1 Jan 2011 → 1 Jan 2011
|Conference||International Conferences on Web Intelligence and Intelligent Agent Technology|
|Period||1/01/11 → 1/01/11|