Open AccessAn Implementation of Big Data Processing to Separate the Payload Based on Classification Tree Model
Author(s) -
G. Renukadevi*,
K. Selvakumar,
T. Senthil Murugan,
S. Venkatakrishnan
Publication year - 2020
Publication title -
international journal of innovative technology and exploring engineering
Language(s) - English
Resource type - Journals
ISSN - 2278-3075
DOI - 10.35940/ijitee.c8794.019320
Subject(s) - computer science , payload (computing) , task (project management) , big data , cloud computing , tree (set theory) , database , process (computing) , web page , server , set (abstract data type) , sql , world wide web , data mining , operating system , computer network , programming language , mathematical analysis , mathematics , management , network packet , economics
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.