Big Data Technique for the Weather Prediction using Hadoop MapReduce

• Main Authors: Khalid Adam, Ismail Hammad, Mohamed, Izzeldin I., Ahmed, Nidal A., Younis, Younis M., Elfadil, Nazar
• Format: Article
• Language: English
• Published: IJMTER 2020
• Subjects: QA76 Computer software
• Online Access: http://umpir.ump.edu.my/id/eprint/30697/1/Paper_Big%20Data%20Technique%20for%20the%20Weather%20Prediction%20using%20Hadoop%20MapReduce.pdf; http://umpir.ump.edu.my/id/eprint/30697/; https://www.ijmter.com/papers/volume-7/issue-5

Currently analyzing large amounts of data has become a big challenge. This data could be medical, scientific, financial, climatological, or marketing. Several techniques are used to analysis meaningful information by use Big Data technologies. Weather one of area use big data technologies to support numerous important domain such as water resources, agriculture, air traffic, and tourism. Weather prediction is field of meteorology that is done by collecting data from the different stations related to the current state of the weather like Temperate, Humidity and Visibility. Thus, the most challenging problem for scientists to analysis this big amount of data. in this paper we focus on analyzing the weather data set using Hadoop/MapReduce and we used the historical data set from NOAA. The temperature, humidity and visibility attributes has been extracted from the dataset by the MapReduce Algorithm into structure data. Graphical analysis has been used to represent the result from the MapReduce Algorithm.