Querying Key-Value Stores Under Simple Semantic Constraints : Rewriting and Parallelization

Olivier Rodriguez 1 Corentin Colomier 1 Cecilie Rivière 1 Reza Akbarinia 2 Federico Ulliana 1, 3
1 UM - Université de Montpellier
2 ZENITH - Scientific Data Management
LIRMM - Laboratoire d'Informatique de Robotique et de Microélectronique de Montpellier, CRISAM - Inria Sophia Antipolis - Méditerranée
3 GRAPHIK - Graphs for Inferences on Knowledge
LIRMM - Laboratoire d'Informatique de Robotique et de Microélectronique de Montpellier, CRISAM - Inria Sophia Antipolis - Méditerranée
Abstract : We propose to demonstrate a system for accessing Key-Value stores in the presence of semantic constraints, as considered in the setting of ontology-mediated query answering. The constraints we study are expressed in a native rule language for JSON records and their purpose is to establish a high level view over a collection of legacy and possibly heterogenous Key-Value stores. To ensure correct and complete data access, constraints are taken into account via query rewriting techniques tailored for MongoDB queries. The nature of queries and constraints also enable the deployment of parallelization techniques for optimizing query rewriting and therefore the whole data access task. During the demonstration, attendees will first be able to query JSON datasets in the presence of rules thereby illustrating how semantic constraints bring novel and pertinent answers to queries. Then, it will be possible to make a detailed analysis of query rewriting and compare the parallel version of the reformulation algorithm with the baseline centralized one.
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Submitted on : Friday, October 20, 2017 - 11:44:33 AM
Last modification on : Tuesday, April 16, 2019 - 6:26:02 PM
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Olivier Rodriguez, Corentin Colomier, Cecilie Rivière, Reza Akbarinia, Federico Ulliana. Querying Key-Value Stores Under Simple Semantic Constraints : Rewriting and Parallelization. BDA: Gestion de Données — Principes, Technologies et Applications, Nov 2017, Nancy, France. ⟨lirmm-01620207⟩

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