Quotation M. Giménez-García, José, Fernandez Garcia, Javier David, A. Martínez-Prieto, Miguel. Forthcoming. HDT-MR: A Scalable Solution for RDF Compression with HDT and MapReduce. In Extended Semantic Web Conference (ESWC), Hrsg.




HDT a is binary RDF serialization aiming at minimizing the space overheads of traditional RDF formats, while providing retrieval features in compressed space. Several HDT-based applications, such as the recent Linked Data Fragments proposal, leverage these features for diverse publication, interchange and consumption purposes. However, scalability issues emerge in HDT construction because the whole RDF dataset must be processed in a memory-consuming task. This is hindering the evolution of novel applications and techniques at Web scale. This paper introduces HDT-MR, a MapReduce-based technique to process huge RDF and build the HDT serialization. HDT-MR performs in linear time with the dataset size and has proven able to serialize datasets up to several billion triples, preserving HDT compression and retrieval features.


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Publication's profile

Affiliation WU
Type of publication Contribution to conference proceedings
Language English
Title HDT-MR: A Scalable Solution for RDF Compression with HDT and MapReduce
Title of whole publication Extended Semantic Web Conference (ESWC)
Year 2015
URL http://dataweb.infor.uva.es/wp-content/uploads/2015/03/HDT-MR.pdf


Fernandez Garcia, Javier David (Former researcher)
A. Martínez-Prieto, Miguel
M. Giménez-García, José
Institute for Data, Process and Knowledge Management (AE Polleres) (Details)
Research areas (ÖSTAT Classification 'Statistik Austria')
1108 Informatics (Details)
1109 Information and data processing (Details)
1122 Artificial intelligence (Details)
5367 Management information systems (Details)
5937 Information systems (Details)
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