SURVEY ON IMPROVE JOB PERFORMANCE USING MAPREDUCE IN HADOOP

Abstract

— In recent years the different scheduling technique became a more attractive point mark to many researchers,
but even though many achievement that have been made, then also still many trouble in this field. The main goal of this
paper is to provide a better understanding of scheduling technique in MapReduce and analyze very important research
directions in this field. There are lots of key techniques in MapReduce to improve the job performance in open source
platform to choose as Hadoop. To address it, analyze and optimize the resource allocation in different aspect. The
performance of Hadoop can be increased by proper resource management to the task in default scheduling te chnique. In
Hadoop a program called map reduce is used for gathering data according to query. As use Hadoop is used for large
amount of data therefore scheduling in Hadoop must be effective for better performance. So objective is to study and
identify various scheduling technique, which are used to maximize job performance in Hadoop.