Uber Data Analysis using Map Reduce
P. Devika1, Y. Prasanna2, P. Swetha3, G. Akhilesh Babu4
1P. Devika, Department of Computer Science and Engineering, MLR Institute of Technology, Dundigal, Hyderabad, India.
2Y. Prasanna , Department of Computer Science and Engineering, MLR Institute of Technology, Dundigal, Hyderabad, India.
3P. Swetha , Department of Computer Science and Engineering, MLR Institute of Technology, Dundigal, Hyderabad, India.
4G. Akhilesh Babu, Department of Computer Science and Engineering, MLR Institute of Technology, Dundigal, Hyderabad, India.
Manuscript received on November 15, 2019. | Revised Manuscript received on November 23, 2019. | Manuscript published on November 30, 2019. | PP: 2511-2513 | Volume-8 Issue-4, November 2019. | Retrieval Number: D7111118419/2019©BEIESP | DOI: 10.35940/ijrte.D7111.118419
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Map Reduce has become of the foremost often used framework for processing of giant quantity of knowledge hold on in Hadoop cluster. It is used for multi processing of giant quantity of knowledge speedily. Firstly, it had been designed by google to produce the correspondence and cut back the fault tolerance of knowledge. We are using Uber Data for analyzing the vehicle with most popular trips. As mapreduce is used to process huge amounts of data, we are using mapreducing model to analyze uber data and give insights about the most used vehicle, number of trips it has covered. The main objective of this project is to investigate no of trips so as to produce data for the company to take care of the records and helps to company in creating huge information for long run endeavor.
Keywords: Data for Analyzing the Vehicle With Most Popular Trips..
Scope of the Article: Data Analytics.