BIG DATA TECHNIQUES HADOOP AND MAP REDUCE FOR WEATHER FORECASTING
Nowadays analyzing large amounts of data has become a big challenge. Data could be scientific, medical, meteorological, climatically, financial or marketing. Data mining techniques is used to extract meaningful information from large data set. Weather forecasting can be used to support many important sectors that are affected by climate like agriculture, water resources, air traffic, and tourism. Weather forecasting is an area of meteorology that is done by collecting data from the different stations related to the current state of the weather like temperate, rainfall, wind, and fog. Weather forecasting is the most challenging problem for scientists. Hadoop and MapReduce are the most models used to analysis a huge data set. This paper explains a system that uses the historical weather data of a region and apply the MapReduce and Hadoop techniques to analysis these historical data.