How Map Reduce On A Distributed Environment Readily And...

Abstract: This is a project to demonstrate how Map Reduce in a distributed environment readily and easily allows us to take several measurements that describe the empirical data and to answer several questions like, for example, stars that are like our sun, and how many Earth-like planets have been observed. This project has been done as part of the coursework for the course Distributed Computing. After applying the Map Reduce and Hadoop techniques to the planetary database, and to the star database, we realize that bringing a large dataset into a tidy and insightful categorization is made easy using Map Reduce. It also shows the power, and elegance of map-reduce in the realm of astronomy and the physical sciences. Introduction: Astronomy, is a fascinating area of the science where most of the information is unknown. We have been seeing stars since time immemorial. And most of us must have thought about, if living beings like on earth, present out of our universe. We know that there are stars, planets, galaxies like the ones where earth is part of. The immediate question that raises is whether there is any planet like earth, any star like sun. In recent times, there has been tremendous advancements in the study of space and the data that is received in some form, from the satellites is huge. There are new discoveries, new findings about the planets and stars that were unknown to the world. The satellites send data day by day and the research is going on in finding someShow MoreRelatedSoftware Defined Networks : Cloud Administrations1746 Words   |  7 Pagesplane and management plane. It focuses on the separation of control plane from the data plane. By separating the control logic out from the switch we are able to use a centralized controller that can view and control the network and routing. SDN gives us a more programmable and customize freedom to the network. 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