This project is developed to understand underlying trends in flight data by using Big Data Analysis tools such as MapReduce, Hadoop and the 3 V's of Big Data, which are Velocity, Variety, and Volume. Dataset used
A system has been implemented that will take data features such as airline carrier name, source and destination, date of journey, flight duration, ticket prices, etc. Based on this dataset available, the system will perform an elaborate analysis and deduce various results based on the trends of the data over the given time using MapReduce. After analyzing the data, the model will then calculate the average price of ticket for the given source and destination. It will also calculate the maximum and minimum price of tickets over a specific time period by using map reduce programs.
