Prediction of Sustenance and Retail Advertising using Bigdata

Abstract

This paper proposes the forecast of future deals by utilizing past informational collections with the assistance of Big information. In the field of retail showcasing colossal datasets are being made with the data about the different items. These datasets containing enormous information about different items can't be manage Relational databases. This is the motivation behind why we are picking Hadoop Tools, for example, Sqoop, Hdfs, Pig, Hive. Sqoop enables us to stack the information in to Hdfs. Hive enables us to break down the informational collections and gauge dependent on the datasets that are as of now accessible. Pig is abnormal state scripting language which can be utilized to break down information. Different Linear Regression calculation is executed in the R studio.