A Survey on Map Reduce Algorithm for Big data analysis using Hadoop, Pig and Hive utility tools - Kadre, Ankita; Yadav, SR (International Journal of Computer Sciences and Engineering, 2025)
Data is growing at a rate which cannot be handled by the traditional methods of computing. To store and process such data new data analysis and storage techniques have emerged over the last few years. Hadoop is one such parallel processing open source framework which provides distributed storage and processing of big data. This paper introduces Big Data, a new platform which enables accessing, manipulating, analyzing, and visualizing data residing on a Hadoop cluster. In this paper a survey is done on big data analysis using Hadoop and other utility tools like Pig and Hive. The majority of large-scale data intensive applications executed by data centers are based on Map-Reduce or its open-source implementation, Hadoop. Such applications are executed on large clusters requiring large amounts of energy, making the energy costs a large fraction of the data center’s overall costs. Therefore to minimizing the energy consumption when executing Map-Reduce jobs is a critical concern for data centers. In this survey Flight data has been analyzed in terms of the mentioned parameters such as time complexity and energy consumption information’s are retrieved using Hadoop.