Job Schedulers in Mapreduce
|International Journal of Engineering Trends and Technology (IJETT)||
|© 2017 by IJETT Journal|
|Year of Publication : 2017|
|Authors : Miss Jadhav Usha Dattatraya, Prof V.R Chirchi
|DOI : 10.14445/22315381/IJETT-V47P213|
Miss Jadhav Usha Dattatraya, Prof V.R Chirchi "Job Schedulers in Mapreduce", International Journal of Engineering Trends and Technology (IJETT), V47(2),83-87 May 2017. ISSN:2231-5381. www.ijettjournal.org. published by seventh sense research group
The aim of this paper is to provide a better understanding of job schedulers in MapReduce and identify important research directions in this area. it present advantages and disadvantages of different jobs scheduling algorithm in MapReduce also job schedulers in MapReduce and then their features and the application of each category of the schedulers are expressed and the Mapreduce is a programming model and an associated implementation for processing and generating large datasets that is amenable to a broad variety of real-world tasks users specify the computation in terms of a map and a reduce function, and the underlying runtime system automatically parallelizes the computation across large-scale clusters of machines, handles machine failures, and schedules inter-machine communication to make efficient use of the network and disks.
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MapReduce Schedulers, Data Locality, Hadoop,scheduing algorithm, MapReduce.