Towards Making Distributed RDF processing FLINker

Azzam, Amr and Kirrane, Sabrina ORCID: https://orcid.org/0000-0002-6955-7718 and Polleres, Axel ORCID: https://orcid.org/0000-0001-5670-1146 (2018) Towards Making Distributed RDF processing FLINker. In: 4th International Conference on Big Data Innovations and Applications (Innovate-Data2018), 6-8 August 2018, Barcelona,Spain.

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Abstract

In the last decade, the Resource Description Framework (RDF) has become the de-facto standard for publishing semantic data on the Web. This steady adoption has led to a significant increase in the number and volume of available RDF datasets, exceeding the capabilities of traditional RDF stores. This scenario has introduced severe big semantic data challenges when it comes to managing and querying RDF data at Web scale. Despite the existence of various off-the-shelf Big Data platforms, processing RDF in a distributed environment remains a significant challenge. In this position paper, based on an indepth analysis of the state of the art, we propose to manage large RDF datasets in Flink, a well-known scalable distributed Big Data processing framework. Our approach, which we refer to as FLINKer extends the native graph abstraction of Flink, called Gelly, with RDF graph and SPARQL query processing capabilities.

Item Type: Conference or Workshop Item (Paper)
Additional Information: Supported by the EUs Horizon 2020 research and innovation programme: grant 731601 (SPECIAL) and the Austrian Research Promotion Agency's (FFG) program "ICT of the Future": grant 861213 (CitySpin)
Keywords: RDF, SPARQL, Flink, Big Semantic Data
Divisions: Departments > Informationsverarbeitung u Prozessmanag. > Informationswirtschaft > Polleres
Version of the Document: Accepted for Publication
Variance from Published Version: Minor
Depositing User: Javier David Fernandez Garcia
Date Deposited: 06 Sep 2018 08:32
Last Modified: 04 Dec 2019 09:50
URI: https://epub.wu.ac.at/id/eprint/6493

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