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An Extended Form of MATLAB To-map Reduce Frameworks in HADOOP Based Cloud Computing Environments

机译:基于HADOOP的云计算环境中的MATLAB To-map Reduce框架的扩展形式

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Aim of study to extend the implementation of Matlab to Mapreduce translation based on the M2M translation technique. Cloud computing is a service which provides services by handling massive amount of data. To handle it effectively it needs some technology like Hadoop. Hadoop is an open source project written in Java. It is optimised to handle massive amount of data (structured, unstructured, semi-structured) through parallelism. Thus to achieve this parallelism Hadoop Distributed File System (HDFS) uses Mapreduce as a programming index. Here proposing a translator which converts Matlab commands to Mapreduce commands especially concentrated in executing some basic commands in Mapreduce environment to access large datasets. Matlab is a very effective tool for numerical computing since executing this command in a platform independent, distributed environment makes it more efficient.
机译:研究目的是基于M2M翻译技术将Matlab的实现扩展到Mapreduce翻译。云计算是一项通过处理大量数据来提供服务的服务。为了有效地处理它,它需要诸如Hadoop之类的技术。 Hadoop是一个用Java编写的开源项目。它经过优化,可以通过并行处理大量数据(结构化,非结构化,半结构化)。因此,为了实现这种并行性,Hadoop分布式文件系统(HDFS)使用Mapreduce作为编程索引。这里提出一个转换器,将Matlab命令转换为Mapreduce命令,尤其是集中在Mapreduce环境中执行一些基本命令以访问大型数据集的转换器。 Matlab是用于数值计算的非常有效的工具,因为在独立于平台的分布式环境中执行此命令使其效率更高。

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