基于Hadoop的大数据处理方法研究

当前，我们所处的时代是数据爆炸式增长的时期，随着云计算的概念的普及和互联网技术的飞速发展，数字化的生活方式不断地影响着传统行业的自动化和信息化以及人们的生活习惯， 大数据已经逐渐将我们包围。尽管数据的不断增长为人们带来了非常大的价值，与此同时，也带来了巨大的挑战，很多大型企业所关注的焦点放在了如何大数据处理这个问题上，因此本文选择了大数据处理这一主题进行研究。首先，通过对Hadoop结构的分析，研究Hadoop如何实现大数据的处理，这样可以对Hadoop有更深刻的认识；其次，根据对Hadoop的认识，进行对比分析，分析Hadoop处理大数据与传统方式处理大数据的不同之处，得出其优势所在； 同时对Hadoop的应用场景进行分析，从而对Hadoop在实际应用中的作用有一个清晰的认识；最后基于对 Hadoop处理大数据的分析，对其处理方法的优化进行分析，并对其提出解决弊端与增强优势的建议， 提高 Hadoop在大数据应用上的实用性，同时对大数据行业的发展也有所帮助。

关键词：Hadoop；大数据；云计算

The Research on Processing Method of Big Data Based on Hadoop

Abstract: We are now in an era of which the data processing is undergoing an explosive growth. With the concept of cloud computing known by more and more people and the development of the Internet, The digital lifestyle constantly affects the traditional industry's automation and information, as well as people's life habits. We have been surrounded by big data. Although the growth of data has brought great value to human, it also brings great challenges at the same time. A large number of companies focus on the problem of how to deal with large data now. on account of this reason, big data processing is chose to be study in this paper. First, we studied how to achieve the processing of big data by using Hadoop. After the completion of this study, we can have a deeper understanding of Hadoop. Second, according to the understanding of Hadoop, comparative analysis is made to analyze the difference of dealing with big data between using Hadoop and traditional way . Then it is a summary of Hadoop’s advantages. At the same time, we analyzed the application scenarios of Hadoop, so that we can have a clear understanding of the role of Hadoop in practical applications. Finally, based on the analysis of processing large data by using Hadoop, the optimization of the processing is analyzed. And the suggestions to improve the efficiency were put forward, they can improve the practicability of Hadoop in the large data application and also assist the development of the big data trade.

Keyword: Hadoop; Big data; Cloud computing

*若需了解更多与协助请咨询↓→[电脑QQ][手机QQ]【数据协助】