在hadoop上应用MVC数据模型实现商业智能的交付

W. Romsaiyud
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引用次数: 7

摘要

模型-视图-控制器(MVC)模式是一种非常有用和流行的设计模式,它将域的建模、表示和基于用户输入的操作分离到三个独立的类中。模型作为构建软件的领域,视图作为模型的可视化表示。它通常是框架呈现给浏览器和控制器的结果标记,控制器负责处理输入、对模型进行操作,并决定应该执行什么操作,例如呈现视图或重定向到支持业务模型的另一个页面。采用Hadoop MapReduce范式收集多个数据集,用于批量处理生成大量数据。本文采用MVC模式对Hadoop MapReduce进行了增强,使其能够跨平台处理大规模、不同的数据集。总的来说,该系统主要包括五种方法:1)2.收集本地系统数据文件系统中包含的注册商系统、网络邮件、网络博客、新闻、英文维基百科等不同平台的数据源;从输入格式生成数据到映射槽,3)从业务逻辑计算作业,4)4 .创建基于数据实体框架的数据模型;显示支持业务接口的用户界面。
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Applying MVC data model on hadoop for delivering the business intelligence
Model-View-Controller (MVC) pattern is very useful and popular design pattern that separates the modeling of the domain, the presentation, and the actions based on user input into three separate classes. The model acts as the domain that software is built around, the view as the visual representation of a model. It is usually the resulting markup that the framework renders to the browser and the controller responsible for processing input, acting upon the model, and deciding on what action should be performed, such as rendering a view or redirecting to another page for supporting a business models. Hadoop MapReduce paradigm applied for collected the several datasets for generating the large volume of data in batch processing. In this paper enhanced the Hadoop MapReduce for processing large scale and different data set across platform with MVC pattern. In general, the system consists of five mainly methods: 1.) Collected data sources from different platforms such as the registrar system, web mail, web blogs, news and the English Wikipedia that are included in the data file system at local system, 2.) Generate the data into a map slot from input format, 3.) calculate the jobs from the business logic, 4.) Create a data model based on data entity framework, and 5.) Display an user interface for supporting the business interfaces.
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