An Efficient Approach to Triple Search and Join of HDT Processing Using GPU

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Resource Description Framework (RDF) is originally designed as a metadata data model. It has an advantage of efficient exchange between different metadata by supporting a set of common rules. To process RDF data efficiently, SPARQL (SPARQL Protocol and RDF Query Language) was introduced. In this era of emerging Web of Data, the amount and size of published RDF data have dramatically increased. Most studies so far have focused on the compression of RDF data and fast SPARQL query processing using single core CPUs. Thus, they do not utilize well current multicore environment. We in this study propose SPARQL query processing using a GPU multicore system. We focus on a search and join method using Header, Dictionary, Triples (HDT) data format and present its experimental results.
Publisher
IARIA
Issue Date
2015-05-24
Language
English
Citation

The Seventh International Conference on Advances in Databases, Knowledge, and Data Applications, pp.70 - 74

ISSN
2308-4332
URI
http://hdl.handle.net/10203/199668
Appears in Collection
CS-Conference Papers(학술회의논문)

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