A brief review of scheduling algorithms of Map Reduce model using Hadoop
|International Journal of Engineering Trends and Technology (IJETT)||
|© 2017 by IJETT Journal|
|Year of Publication : 2017|
|Authors : Adhishtha Tyagi, Sonia Sharma
|DOI : 10.14445/22315381/IJETT-V45P209|
Adhishtha Tyagi, Sonia Sharma " A brief review of scheduling algorithms of Map Reduce model using Hadoop", International Journal of Engineering Trends and Technology (IJETT), V45(1),37-42 March 2017. ISSN:2231-5381. www.ijettjournal.org. published by seventh sense research group
Scheduling has been an active area of research in computing systems since their inception. Hadoop framework has become very much popular and most widely used in distributed data processing. Hadoop has become a central platform to store big data through its Hadoop Distributed File System (HDFS) as well as to run analytics on this stored big data using its MapReduce component. The main objective is to study MapReduce framework, MapReduce model, scheduling in hadoop, various scheduling algorithms and various optimization techniques in job scheduling. Scheduling algorithms of MapReduce model using hadoop vary with design and behaviour, and are used for handling many issues like data locality, awareness with resource, energy and time.
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Big Data, MapReduce and Hadoop framework, MapReduce model