MapReduce-based Solutions for Scalable SPARQL Querying

  1. José M. Giménez-Garcia
  2. Javier D. Fernández
  3. Miguel A. Martínez-Prieto
Revista:
Open Journal of Semantic Web (OJSW)

ISSN: 2199-336X

ISBN: 201705194824

Año de publicación: 2014

Volumen: 1

Número: 1

Páginas: 1-18

Tipo: Artículo

GOOGLE SCHOLAR lock_openAcceso abierto editor

Otras publicaciones en: Open Journal of Semantic Web (OJSW)

Resumen

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 rconnected 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.