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CONSTRUCT Queries Performance on a Spark-Based Big RDF Triplestore

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The Semantic Web (ESWC 2022)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 13261))

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Abstract

Despite their potential, CONSTRUCT queries have gained little attraction so far among data practitioners, vendors and researchers. In this paper, we first exhibit performance bottlenecks of existing triplestores for supporting CONSTRUCT queries over large knowledge graphs. Then, we describe a novel Spark-based architecture for big triplestores, called TESS, that we have designed and implemented to overcome the above limitations by using parallel computing. TESS ensures ACID properties that are required for a sound and complete implementation of CONSTRUCT-based forward-chaining rules reasoning.

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Notes

  1. 1.

    Extraction, Transformation, Load.

  2. 2.

    https://spinrdf.org/spin.html.

  3. 3.

    https://www.w3.org/TR/shacl-af/#rules.

  4. 4.

    https://project-hobbit.eu/challenges/mighty-storage-challenge2018/.

  5. 5.

    https://community.openlinksw.com/t/sparql-query-limiting-results-to-100000-triples/2131.

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Acknowledgements

This work has been supported by the the French National Research Agency with projects LabEx PERSYVAL Lab (11-LABX-0025-01), DUNE SIDES 3.0 (ANR-16-DUNE -0002-02), P3IA MIAI@Grenoble Alpes (ANR-19-P3IA-0003) and CE23 CQFD (ANR-18-CE23-0003).

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Authors and Affiliations

  1. Université Grenoble Alpes, Saint-Martin-d’Hères, France

    Adam Sanchez-Ayte, Fabrice Jouanot & Marie-Christine Rousset

Authors
  1. Adam Sanchez-Ayte
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  2. Fabrice Jouanot
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  3. Marie-Christine Rousset
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Corresponding author

Correspondence to Adam Sanchez-Ayte .

Editor information

Editors and Affiliations

  1. University of Amsterdam, Amsterdam, Noord-Holland, The Netherlands

    Paul Groth

  2. Universidad Simón Bolívar, Leibniz Information Centre for Science and Technology, Hannover, Niedersachsen, Germany

    Maria-Esther Vidal

  3. Institut Polytechnique de Paris "DIG", Télécom ParisTech, Palaiseau, France

    Fabian Suchanek

  4. University of Southern California, Marina del Rey, CA, USA

    Pedro Szekley

  5. IBM Research - Thomas J. Watson Research, Yorktown Heights, NY, USA

    Pavan Kapanipathi

  6. LaSIGE, Fac de Ciencias,Edif C6, Pis0 3, Universidade de Lisboa, Lisbon, Portugal

    Catia Pesquita

  7. University of Nantes, Nantes, France

    Hala Skaf-Molli

  8. Aalto University, Espoo, Finland

    Minna Tamper

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Sanchez-Ayte, A., Jouanot, F., Rousset, MC. (2022). CONSTRUCT Queries Performance on a Spark-Based Big RDF Triplestore. In: Groth, P., et al. The Semantic Web. ESWC 2022. Lecture Notes in Computer Science, vol 13261. Springer, Cham. https://doi.org/10.1007/978-3-031-06981-9_26

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  • DOI: https://doi.org/10.1007/978-3-031-06981-9_26

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