Anzeige
Erschienen in:
2018 | OriginalPaper | Buchkapitel
Scalable Queries and Model Transformations with the Mogwaï Tool
verfasst von : Gwendal Daniel, Gerson Sunyé, Jordi Cabot
Erschienen in: Theory and Practice of Model Transformation
Aktivieren Sie unsere intelligente Suche, um passende Fachinhalte oder Patente zu finden.
Wählen Sie Textabschnitte aus um mit Künstlicher Intelligenz passenden Patente zu finden. powered by
Markieren Sie Textabschnitte, um KI-gestützt weitere passende Inhalte zu finden. powered by
Abstract
Scalability of modeling frameworks has become a major issue hampering MDE adoption in the industry. Specifically, scalable model persistence, as well as efficient query and transformation engines, are two of the key challenges that need to be addressed to enable the support for very large models in current applications. In this paper we demonstrate Mogwaï, a tool designed to efficiently compute queries and transformations (expressed in OCL and ATL) over models stored in NoSQL databases. Mogwaï relies on a translational approach that maps constructs of the supported input languages to Gremlin, a generic NoSQL query language, and a model to datastore mapping allowing to compute the generated query on top of several datastores. The produced queries are computed on the database side, benefiting of all its optimizations, improving the execution time and reducing the memory footprint compared to standard solutions. The Mogwaï tool is released as a set of open source Eclipse plugins and is fully available online.