基于Hadoop的大数据实时处理架构

Yong Cao
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引用次数: 0

摘要

互联网时代产生的数据呈指数级增长。有时如此庞大的数据无法及时处理,人们无法从中挖掘出有用的信息。为了实现对海量数据的高效处理,本文开发了基于Hadoop平台的大数据实时处理架构,使用HBase作为数据库,结合c#编程语言和MapReduce编程模式设计了一个大数据处理系统,使用户可以通过移动设备查看和上传数据。云计算中心的数据处理结果。对MapReduce和大数据处理体系结构各功能模块进行了性能测试。测试结果表明,MapReduce在处理大数据方面具有一定的优势,各功能模块的数据处理时间随着数据量的增加而增加。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Big data real-time processing architecture based on Hadoop
The data generated in the Internet age is increasing exponentially. Sometimes such a huge amount of data cannot be processed in time, and people cannot dig out useful information from it. In order to realize the efficient processing of massive data, this paper develops a big data real-time processing architecture based on the Hadoop platform, uses HBase as the database, and combines the C# programming language and the MapReduce programming mode to design a big data processing system, so that users can view and upload data through mobile devices. The data processing results of the cloud computing center. The performance test of MapReduce and various functional modules of the big data processing architecture is carried out. The test results show that MapReduce has certain advantages in processing big data, and the data processing time of each functional module increases with the increase of data volume.
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