An Implementation of Big Data Processing to Separate the Payload Based on Classification Tree Model

Abstract

The process of distinguishing different types of data in the SQL server is the challenging task for further processing of big data. The big data is available in the Webpages, social media networks and cloud based web servers. In this implementation, the data can be retrieved from the cloud based web services. The data is temporarily posted in the REST API, and the data stored permanently in the SQL Server. The stored data is processed using the Classification Tree Model. Based on this method, the separation of types of payload is possible. With the help of this implementation, the types of the documents are automatically categorized using the trained data. Previously the training set has to be prepared for distinguishing different payloads and documents.