CliqueSquare: Flat Plans for Massively Parallel RDF Queries

François Goasdoué 1, 2 Zoi Kaoudi 2, 3 Ioana Manolescu 4, 2 Jorge-Arnulfo Quiané-Ruiz 5 Stamatis Zampetakis 2, 4, *
* Auteur correspondant
1 SHAMAN - Symbolic and Human-centric view of dAta MANagement
IRISA-D7 - GESTION DES DONNÉES ET DE LA CONNAISSANCE
2 OAK - Database optimizations and architectures for complex large data
LRI - Laboratoire de Recherche en Informatique, UP11 - Université Paris-Sud - Paris 11, Inria Saclay - Ile de France, CNRS - Centre National de la Recherche Scientifique : UMR8623
Abstract : As increasing volumes of RDF data are being produced and analyzed, many massively distributed architectures have been proposed for storing and querying this data. These architectures are characterized first, by their RDF partitioning and storage method, and second, by their approach for distributed query optimization, i.e., determining which operations to execute on each node in order to compute the query answers. We present CliqueSquare, a novel optimization approach for evaluating conjunctive RDF queries in a massively parallel environment. We focus on reducing query response time, and thus seek to build flat plans, where the number of joins encountered on a root-to-leaf path in the plan is minimized. We present a family of optimization algorithms, relying on n-ary (star) equality joins to build flat plans, and compare their ability to find the flattest possibles. We have deployed our algorithms in a MapReduce-based RDF platform and demonstrate experimentally the interest of the flat plans built by our best algorithms.
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Communication dans un congrès
International Conference on Data Engineering, Apr 2015, Seoul, South Korea
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François Goasdoué, Zoi Kaoudi, Ioana Manolescu, Jorge-Arnulfo Quiané-Ruiz, Stamatis Zampetakis. CliqueSquare: Flat Plans for Massively Parallel RDF Queries. International Conference on Data Engineering, Apr 2015, Seoul, South Korea. <hal-01108705>

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