Analysis on Enhancing Storm to Efficiently Process Big Data in Real Time

被引：0
|
作者：
Nivash, J. P. [1 ]
Raj, Ebin Deni [1 ]
Babu, L. D. Dhinesh [1 ]
Nirmala, M. [1 ]
Kumar, Manoj, V [1 ]
机构：
[1] VIT Univ, Sch Informat Technol & Engn, Vellore, Tamil Nadu, India
来源：
2014 INTERNATIONAL CONFERENCE ON COMPUTING, COMMUNICATION AND NETWORKING TECHNOLOGIES (ICCCNT | 2014年
关键词：
Bigdata; Real time data processing; Hadoop; Apache Storm;
D O I：
暂无
中图分类号：
TM [电工技术]; TN [电子技术、通信技术];
学科分类号：
0808 ; 0809 ;
摘要：
The rapid growth of huge data has become a challenge to the data analysts in recent time. As the data is growing exponentially many techniques are on the rise, for processing the real time data. Many data processing models like Hadoop, Apache YARN, Mapreduce, Storm, and Akka are leading the Big Data domain. This paper analyses and compares all the data processing models stated above. Researchers are trying to increase the efficiency of the algorithms used in the data processing. In this paper, we propose two algorithms namely JATS and SD, which will enhance the efficiency of the storm data processing architecture.
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页数：5
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