earticle

영어

In this paper, 10 years of airline data set in USA is collected. And, the analysis of the airline data set is performed using cloud computing service of Microsoft Azure which runs Hadoop cluster in the cloud. Hadoop Hive QL statements have been used for analyzing the data. Data visualization has been achieved by extracting the output of the Hive code. Using big data technologies like Hadoop and Hive in the cloud, it is easy to analyze the massive data set in SQL like language, export the output results and visualize them excel spreadsheets. Interesting sets of trends and patterns exists in this large data sets, the paper presents the insights that resides between flight diversions and flight distance, flight cancellation and flight distance for the time period.