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CliqueSquare in Action: Flat Plans for Massively Parallel RDF Queries

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Abstract

RDF is an increasingly popular data model for many practical applications, leading to large volumes of RDF data; efficient RDF data management methods are crucial to allow applications to scale. We propose to demonstrate CliqueSquare, an RDF data management system built on top of a MapReduce-like infrastructure. The main technical novelty of CliqueSquare resides in its logical query optimization algorithm, guaranteed to find a logical plan as flat as possible for a given query, meaning: a plan having the smallest possible number of join operators on top of each other. CliqueSquare's ability to build flat plans allows it to take advantage of a parallel processing framework in order to shorten response times. We demonstrate loading and querying the data, with a particular focus on query optimization, and on the performance benefits of CliqueSquare's flat plans.
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Dates and versions

hal-01108710 , version 1 (23-01-2015)

Identifiers

  • HAL Id : hal-01108710 , version 1

Cite

Benjamin Djahandideh, François Goasdoué, Zoi Kaoudi, Ioana Manolescu, Jorge-Arnulfo Quiané-Ruiz, et al.. CliqueSquare in Action: Flat Plans for Massively Parallel RDF Queries. International Conference on Data Engineering, Apr 2015, Seoul, South Korea. ⟨hal-01108710⟩
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