A Novel Approach for Analysing the Weather by using Big Data Tool

In the last few decades, the generation of data has increased and it is expected to increase in future. So that it is necessary to process a large amount of data set in weather and analyse the same using the traditional methods. In the existing system, it aims to forecast the chances of rainfall by using predictive analysis in Hadoop. It helps to predict the rainfall in minimum and maximum by taking the data as input. It uses the apache PIG. It have some disadvantages, so in proposed system we use a Naïve Bayse algorithm to predict earth quake, floods , etc., It focuses on meteorological data to predict the seasons to separate the weather data based on Longitudinal and Latitudinal which can be used to analyse the reliability factor of cyclone, earthquake, rainfall, temperature and humidity. It provides specific service to an assessment of pollution impacts from different organization and thermal power plants. It is easy and fast to predict class of test data set. It also performs well in multi class prediction.