Open AccessYOUTUBE DATA ANALYSIS USING HADOOP FRAMEWORK
Author(s) -
Thogaricheti Ashwini,
Sahana Lm,
E Mahalakshmi,
Shweta S Padti
Publication year - 2021
Publication title -
international journal of engineering applied science and technology
Language(s) - English
Resource type - Journals
ISSN - 2455-2143
DOI - 10.33564/ijeast.2021.v05i11.051
Subject(s) - computer science , upload , big data , application programming interface , process (computing) , interface (matter) , task (project management) , key (lock) , sql , database , data mining , world wide web , operating system , management , bubble , maximum bubble pressure method , economics
— Analysis of consistent and structured data hasseen huge success in past decades. Where the analysis ofunstructured data in the form of multimedia formatremains a challenging task. YouTube is one of the mostused and popular social media tool. The main aim of thispaper is to analyze the data that is generated fromYouTube that can be mined and utilized. API (ApplicationProgramming Interface) and going to be stored in HadoopDistributed File System (HDFS). Dataset can be analyzedusing MapReduce. Which is used to identify the videocategories in which most number of videos are uploaded.The objective of this paper is to demonstrate Hadoopframework, to process and handle big data there are manycomponents. In the existing method, big data can beanalyzed and processed in multiple stages by usingMapReduce. Due to huge space consumption of each job,Implementing iterative map reduce jobs is expensive. AHive method is used to analyze the big data to overcomethe drawbacks of existing methods, which is the state-ofthe-art method. The hive works by extracting the YouTubeinformation by generating API (Application ProgrammingInterface) key and uses the SQL queries.