Automatic Generation of UML Model-based Image Processing Source Code in Hadoop Platform

被引:0
|
作者
Ko, Mi-Eun [1 ]
Park, Young B. [2 ]
机构
[1] Dankook Univ, Dept Comp Engn, Grad Sch, Artificial Intelligence & Informat Architecture, Yongin, South Korea
[2] Dankook Univ, Dept Software Sci, Yongin, South Korea
基金
新加坡国家研究基金会;
关键词
Hadoop Map-Reduce; HIPI; Model-Driven Engineering; Automatic Source Code Generation;
D O I
暂无
中图分类号
TP301 [理论、方法];
学科分类号
081202 ;
摘要
Hadoop Map-Reduce has been attracting attention for large-scale image data parallel processing environment for searching and analyzing large-sized images. Hadoop Map-Reduce is a platform for processing large amounts of data, allowing Map-Reduce operations to be processed in parallel to speed up complex tasks. It takes a lot of development time to integrate Hadoop Map-Reduce with various image analysis technologies, and it is difficult to confirm the results before compiling and building the source code. In order to solve this problem, this paper proposes a method to create a model using a modeling tool for platform independent development and automatically generate source code based on the model.
引用
收藏
页码:62 / 65
页数:4
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