A Comprehensive View of Scheduling Algorithms for MapReduce Framework in Hadoop

Abstract

We reside in information world which makes great difficulty in quantifying the aggregate volume of information put away electronically, and exist in the unit of Zettabytes or Exabyte, hence termed as Big Data. They can be unstructured, organized or semi organized, processing of these data cannot able to be done with normal data management techniques. Hadoop framework is utilized to process huge datasets in a proficient and economical way. MapReduce system is utilized to gather information according to the solicitation. To handle expansive volume of information legitimate planning is obliged to accomplish more noteworthy execution. Scheduling jobs in parallel across the nodes is an important concern in MapReduce clusters. Also to improve the performance with the large volume of data proper scheduling method should be adopted. The objective of the work is to study about the different scheduling techniques used in Hadoop environment and to achieve effective fairness without starvation.