Job Schedulers in Mapreduce
Citation
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
Abstract
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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Keywords
MapReduce Schedulers, Data Locality,
Hadoop,scheduing algorithm, MapReduce.