Title :
Applying MapReduce Programming Model for Handling Scientific Problems
Author :
Yun Hee Kang ; Park, Young B.
Author_Institution :
Dept. of Inf. & Commun., Baekseok Univ., Cheonan, South Korea
Abstract :
According to data volumes in scientific applications have grown exponentially, new scientific methods to analyze and organize the data are required. MapReduce programming is driving Internet services and those services operation in a cloud environment. Hence it is required to efficiently provide resources for handling diverse MapReduce applications. In this paper we show the Hadoop application with map and reduce functions for the data transformation.
Keywords :
data analysis; parallel programming; Hadoop application; Internet services; MapReduce programming model; cloud environment; data analysis; data organization; data transformation; data volumes; scientific applications; scientific methods; Computational modeling; Data analysis; Data models; Distributed databases; Educational institutions; Filtering algorithms; Programming;
Conference_Titel :
Information Science and Applications (ICISA), 2014 International Conference on
Conference_Location :
Seoul
Print_ISBN :
978-1-4799-4443-9
DOI :
10.1109/ICISA.2014.6847367
