An optimal approach for social data analysis in Big Data

被引：0
|
作者：
Kamala, V. R. [1 ]
MaryGladence, L. [1 ]
机构：
[1] Sathyabama Univ, Dept Informat Technonol, Madras, Tamil Nadu, India
来源：
2015 INTERNATIONAL CONFERENCE ON COMPUTATION OF POWER, ENERGY, INFORMATION AND COMMUNICATION (ICCPEIC) | 2015年
关键词：
Big Data; Hadoop; Hive; Spark; HACE; ALGORITHMS;
D O I：
暂无
中图分类号：
TP3 [计算技术、计算机技术];
学科分类号：
0812 ;
摘要：
The term Big Data refers to huge, complex and heterogeneous data. Based on the HACE characteristics of Big Data, which isHeterogeneous, Autonomous, Complex and Evolving associations, there are many algorithms proposed. Hadoop is an open source framework used extensively for distributed storage and processing. Hadoop framework provides parallel distributive data processing standards which increases the overall computational power and processing time. But choosing the right component for our requirement is an important task. It helps in optimizing the overall performance of the data analysis irrespective of data volume. Here we describe the Hadoop technology stack and their optimal usage for analyzing various data sources, especially the social data.
引用
收藏
页码：205 / 208
页数：4
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