Mogwaï: a Framework to Handle Complex Queries on Large Models

Abstract : While Model Driven Engineering is gaining more industrial interest, scalability issues when managing large models have become a major problem in current modeling frameworks. Scalable model persistence has been achieved by using NoSQL backends for model storage, but existing modeling framework APIs have not evolved accordingly, limiting NoSQL query performance benefits. In this paper we present the Mogwaï a scalable and efficient model query framework based on a direct translation of OCL queries to Gremlin, a query language supported by several NoSQL databases. Generated Gremlin expressions are computed inside the database itself, bypassing limitations of existing framework APIs and improving overall performance, as confirmed by our experimental results showing an improvement of execution time up to a factor of 20 and a reduction of the memory overhead up to a factor of 75 for large models.
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Communication dans un congrès
RCIS 2016 - 10th International Conference on Research Challenges in Information Science, Jun 2016, Grenoble, France. Research Challenges in Information Science (RCIS), 2016 IEEE Tenth International Conference on, pp.1-12, 〈10.1109/RCIS.2016.7549343〉
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Soumis le : lundi 11 juillet 2016 - 11:30:05
Dernière modification le : jeudi 7 mars 2019 - 16:10:11

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Gwendal Daniel, Gerson Sunyé, Jordi Cabot. Mogwaï: a Framework to Handle Complex Queries on Large Models. RCIS 2016 - 10th International Conference on Research Challenges in Information Science, Jun 2016, Grenoble, France. Research Challenges in Information Science (RCIS), 2016 IEEE Tenth International Conference on, pp.1-12, 〈10.1109/RCIS.2016.7549343〉. 〈hal-01344019〉

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