YOUTUBE DATA ANALYSIS USING HADOOP FRAMEWORK

TLDR

Hadoop framework is demonstrated to process and handle big data there are many components and a Hive method is used to analyze the big data to overcome the drawbacks of existing methods, which is the state-ofthe-art method.

Abstract

— Analysis of consistent and structured data has

seen huge success in past decades. Where the analysis of

unstructured data in the form of multimedia format

remains a challenging task. YouTube is one of the most

used and popular social media tool. The main aim of this

paper is to analyze the data that is generated from

YouTube that can be mined and utilized. API (Application

Programming Interface) and going to be stored in Hadoop

Distributed File System (HDFS). Dataset can be analyzed

using MapReduce. Which is used to identify the video

categories in which most number of videos are uploaded.

The objective of this paper is to demonstrate Hadoop

framework, to process and handle big data there are many

components. In the existing method, big data can be

analyzed and processed in multiple stages by using

MapReduce. Due to huge space consumption of each job,

Implementing iterative map reduce jobs is expensive. A

Hive method is used to analyze the big data to overcome

the drawbacks of existing methods, which is the state-ofthe-art method. The hive works by extracting the YouTube

information by generating API (Application Programming

Interface) key and uses the SQL queries.