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Model driven development of hybrid databases using lightweight metamodel extensions

机译:使用轻量级元模型扩展进行模型驱动的混合数据库开发

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摘要

The transition from traditional to Big Data technologies has put new challenges in front of existing database modelling techniques. The 'Design then implement' approach to relational database modelling, could not be fully applied to 'Discover and analyze' databases with rapid data growth. In the context of Big Data, models have preserved a descriptive role: they are used to analyze and understand the architecture of hybrid data structures. From the Model-Driven Engineering point of view, several questions emerge: Could Big Data and hybrid database models represent a formal specification for a solution, which can be transformed to an executable specification for a specific target platform? Does the refining mechanism have its place in the process of hybrid data structure development? An approach to modelling hybrid databases, based on empirically validated concepts of Model-Driven Engineering, is presented in this paper. The approach was applied during the implementation of Precision Agriculture Based Information Service (PAIS) application - a web-based service for the collection and archiving of diverse data on crops, and their presentation to farmers.
机译:从传统技术向大数据技术的过渡给现有数据库建模技术带来了新的挑战。关系数据库建模的“先设计后实施”方法不能完全应用于数据快速增长的“发现和分析”数据库。在大数据的背景下,模型保留了描述性角色:它们用于分析和理解混合数据结构的体系结构。从模型驱动工程的角度来看,出现了几个问题:大数据和混合数据库模型是否可以代表解决方案的正式规范,可以将其转换为特定目标平台的可执行规范?提炼机制在混合数据结构开发过程中是否有其地位?本文提出了一种基于模型驱动工程的经验验证概念的混合数据库建模方法。在实施基于精确农业的信息服务(PAIS)应用程序期间应用了该方法,该服务是基于Web的服务,用于收集和存档各种农作物数据,并将其呈现给农民。

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