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Mogwa?: A framework to handle complex queries on large models

机译:mogwa ?:一个在大型型号上处理复杂查询的框架

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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 Mogwai?, 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.
机译:虽然模型驱动的工程正在获得更多的工业利益,但管理大型模型时的可扩展性问题已成为当前建模框架中的一个主要问题。通过使用NoSQL后备用于模型存储,而是可以实现可扩展的模型持久性,但现有的建模框架API未相应地演变,限制了NoSQL查询性能优势。在本文中,我们介绍了MOGWAI?,基于OCL查询的直接转换到GREMLIN的可扩展和高效的模型查询框架,由几个NOSQL数据库支持的查询语言。生成的Gremlin表达式在数据库本身内计算,绕过现有框架API的限制并提高整体性能,通过我们的实验结果证实,显示了高达20倍的执行时间和减少到一个因素的记忆开销的减少大型型号为75。

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