文章基本信息

标题：Climate Change Detection using Hadoop with MapReduce
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作者：Priyanka More ; Sunita Nandgave ; Megha Kadam 等
期刊名称：International Journal of Innovative Research in Computer and Communication Engineering
印刷版ISSN：2320-9798
电子版ISSN：2320-9801
出版年度：2019
卷号：7
期号：3
页码：1925-1932
DOI：10.15680/IJIRCCE.2019. 0703064
出版社：S&S Publications
摘要：Big Data is a term refers to a collection of large amount of data which requires new technologies to make potential to get value from it by analysis and capturing method. In every aspect of human life, weather has a lot of importance. It has direct impact on each part of human society or human beings. Accurate analytics of weather collecting, storing and processing a large amount of weather data is necessary. So a scalable data storage platform and efficient or effective change detection algorithms are required to monitor the changes in the environment. An existing or traditional data storage techniques and algorithms are not applicable to process the large amount of weather data. In the proposed system, a scalable data processing framework that is Map-Reduce is used with a climate change detection algorithms which is Spatial Cumulative Sum algorithm and Bootstrap Analysis algorithm. This paper presents, the large volume of weather data is stored on Hadoop Distributed File System (HDFS) and Map-Reduce algorithm is applied to calculate the minimum and maximum of climate parameters. Spatial Autocorrelation based climate change detection algorithm is proposed to monitor the changes in the climate of a particular city of india.
关键词：Big Data; HADOOP; Map;Reduce; Temperature