Currently most of the cloud applications method great deal of knowledge to supply the required results. Information volumes to be processed by cloud applications are growing a lot of quicker than computing power. These growth difficulties on new approaches for process and analyzing the knowledge. The paper explores the employment of Hadoop map reduce framework to execute scientific workflows within the cloud. Cloud computing provides monumental clusters for economical giant division and information analysis. In such file systems, a file is divided into variety of file chunks allotted in distinct nodes so Map Reduce tasks will perform in parallel over the nodes to form resource utilization effective and to enhance the interval of the task.