HAQWA: a Hash-based and Query Workload Aware Distributed RDF Store

Abstract : Like most data models encountered in the Big Data ecosystem, RDF stores are managing large data sets by partitioning triples across a cluster of machines. Nevertheless, the graphical nature of RDF data as well as its associated SPARQL query execution model makes the efficient data distribution more involved than in other data models, e.g., relational. In this paper, we propose a novel system that is characterized by a trade-off between complexity of data partitioning and efficiency of query answering in cases where a query workload is known. The prototype is implemented over the Apache Spark framework, ensuring high availability, fault tolerance and scalability. This short paper presents the main features of the system and highlights the omnipresence of parallel computation across data fragmentation and allocation, encoding and query processing tasks.
Type de document :
Poster
The 14th International Semantic Web Conference, ISWC 2015, Oct 2015, Bethlehem, Pennsylvania, United States. CEUR-WS.org, 1486, CEUR Workshop Proceedings
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https://hal.archives-ouvertes.fr/hal-01214900
Contributeur : Lip6 Publications <>
Soumis le : mardi 13 octobre 2015 - 11:57:18
Dernière modification le : jeudi 22 novembre 2018 - 14:35:46

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  • HAL Id : hal-01214900, version 1

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Olivier Curé, Hubert Naacke, Mohamed-Amine Baazizi, Bernd Amann. HAQWA: a Hash-based and Query Workload Aware Distributed RDF Store. The 14th International Semantic Web Conference, ISWC 2015, Oct 2015, Bethlehem, Pennsylvania, United States. CEUR-WS.org, 1486, CEUR Workshop Proceedings. 〈hal-01214900〉

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