M. Giménez-García, José, Fernandez Garcia, Javier David, A. Martínez-Prieto, Miguel. 2014. MapReduce-based Solutions for Scalable SPARQL Querying. Open Journal of Semantic Web (OJSW) 1 (1): 1-18.

RIS

@ARTICLE{M. Giménez-García2014,
title = {MapReduce-based Solutions for Scalable SPARQL Querying},
author = {José M. Giménez-García and Javier David Fernandez Garcia and Miguel A. Martínez-Prieto},
year = {2014},
url = {http://dataweb.infor.uva.es/wp-content/uploads/2014/03/ojsw14.pdf},
volume = {1},
number = {1},
language = {EN},
pages = {1-18},
series = {MapReduce-based Solutions for Scalable SPARQL Querying},
journal = {Open Journal of Semantic Web (OJSW)},
abstract = {The use of RDF to expose semantic data on the Web has seen a dramatic increase over the last few years. Nowadays, RDF datasets are so big and interconnected that, in fact, classical mono-node solutions present significant scalability problems when trying to manage big semantic data. MapReduce, a standard framework for distributed processing of great quantities of data, is earning a place among the distributed solutions facing RDF scalability issues. In this article, we survey the most important works addressing RDF management and querying through diverse MapReduce approaches, with a focus on their main strategies, optimizations and results.},
}