Big Data Analysis and Its Scheduling Policy – Hadoop
Journal Title: IOSR Journals (IOSR Journal of Computer Engineering) - Year 2015, Vol 17, Issue 1
Abstract
Abstract: This paper is deals with Parallel Distributed system. Hadoop has become a central platform tostore big data through its Hadoop Distributed File System (HDFS) as well as to run analytics on this stored bigdata using its MapReduce component. Map Reduce programming model have shown great value inprocessing huge amount of data. Map Reduce is a common framework for data-intensive distributedcomputing of batch jobs. Hadoop Distributed File System (HDFS) is a Java-based file system that providesscalable and reliable data storage that is designed to span large clusters of commodity servers. In all Hadoopimplementations, the default FIFO scheduler is available where jobs are scheduled in FIFO order with supportfor other priority based schedulers also. During this paper, we are going to study a Hadoop framework, HDFSdesign and Map reduce Programming model. And also various schedulers possible with Hadoop and providedsome behavior of the current scheduling schemes in Hadoop on a locally deployed cluster is described.
Authors and Affiliations
Divya S , Kanya Rajesh R , Rini Mary NithilaI , Vinothini M
Keywords
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