Scalable Queries and Model Transformations with the Mogwaï Tool

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...

Full description

Saved in:
Bibliographic Details
Published inTheory and Practice of Model Transformation Vol. 10888; pp. 175 - 183
Main Authors Daniel, Gwendal, Sunyé, Gerson, Cabot, Jordi
Format Book Chapter
LanguageEnglish
Published Switzerland Springer International Publishing AG 2018
Springer International Publishing
SeriesLecture Notes in Computer Science
Subjects
ATL
MDE
Model query
Model transformation
OCL
Scalability
Online AccessGet full text

Cover

More Information
Summary: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.
ISBN:9783319933160
3319933167
ISSN:0302-9743
1611-3349
DOI:10.1007/978-3-319-93317-7_9