Paper Key : IRJ************945
Author: Harshal Shivaji Istalkar,Akshay Ashok Gaikwad,Pushpa Anand Kamble ,Prof. B. R. Patil
Date Published: 11 Nov 2024
Abstract
As organizations increasingly rely on vastamounts of employee data for decision making,traditional data storage and processingmethods struggle to meet the demands ofscalability, fault tolerance, and speed. This researchpresents the design and developmentof a web-based system for employee datamanagement, utilizing Hadoops distributedcomputing framework. The system leveragesHadoop Distributed File System (HDFS) forstorage and MapReduce for parallel data processing,ensuring efficient handling of largedatasets. Additionally, Apache Hive is used toprovide structured querying capabilities, enablingusers to perform complex data analysiswith ease. The study explores the architecture,implementation process, and performanceevaluation of the system, highlightingthe benefits of Hadoop in big data scenarios.Our findings indicate that integrating Hadoopinto web applications offers substantial improvementsin scalability and processing efficiency,making it a viable solution for enterprisesdealing with large-scale employee data.