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Research Conference on Metadata and Semantics Research

MTSR 2018: Metadata and Semantic Research pp 13–25Cite as

Document Based RDF Storage Method for Efficient Parallel Query Processing

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Part of the book series: Communications in Computer and Information Science ((CCIS,volume 846))

Abstract

In this paper, we investigate the problem of efficiently evaluating SPARQL queries, over large amount of linked data utilizing distributed NoSQL system. We propose an efficient approach for partitioning large linked data graphs using distributed frameworks (MapReduce), as well as an effective data model for storing linked data in a document database using a maximum replication factor of 2 (i.e., in the worst case scenario, the data graph will be doubled in storage size). The model proposed and the partitioning approach ensure high-performance query evaluation and horizontal scaling for the type of queries called generalized star queries (i.e., queries allowing both subject-object and object-subject edges from a central node), due to the fact that no joining operations over multiple datasets are required to evaluate the queries. Furthermore, we present an implementation of our approach using MongoDB and an algorithm for translating generalized star queries into MongoDB query language, based on the proposed data model.

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Notes

  1. 1.

    In this paper we do not consider typed literals.

  2. 2.

    Note that not all variables of Q necessarily appear in the output pattern O(Q) of Q.

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Author information

Authors and Affiliations

  1. Database and Information Systems Group (DBIS), Department of Archives, Library Science and Museology, Ionian University, Corfu, Greece

    Eleftherios Kalogeros, Manolis Gergatsoulis & Matthew Damigos

Authors
  1. Eleftherios Kalogeros
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  2. Manolis Gergatsoulis
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  3. Matthew Damigos
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Corresponding author

Correspondence to Manolis Gergatsoulis .

Editor information

Editors and Affiliations

  1. Alexander Technological Educational Institute (ATEI) of Thessaloniki, Thessaloniki, Greece

    Emmanouel Garoufallou

  2. Department of Informatics, Systems and Communication, University of Milano-Bicocca, Milan, Italy

    Fabio Sartori

  3. Alexander Technological Educational Institute (ATEI) of Thessaloniki, Thessaloniki, Greece

    Rania Siatri

  4. Library and Information Services, Cyprus University of Technology, Limassol, Cyprus

    Marios Zervas

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Kalogeros, E., Gergatsoulis, M., Damigos, M. (2019). Document Based RDF Storage Method for Efficient Parallel Query Processing. In: Garoufallou, E., Sartori, F., Siatri, R., Zervas, M. (eds) Metadata and Semantic Research. MTSR 2018. Communications in Computer and Information Science, vol 846. Springer, Cham. https://doi.org/10.1007/978-3-030-14401-2_2

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  • DOI: https://doi.org/10.1007/978-3-030-14401-2_2

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-14400-5

  • Online ISBN: 978-3-030-14401-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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