Analysis of MapReduce Model on Big Data Processing within Cloud Computing
Abstract: Nowadays cloud
computing is becoming
a trend on big
data processing. Google
created MapReduce model to
simplify the complex
computation of big
data processing by configuring
and splitting the
data into key/values pair
to be processed
in parallel, usually
within a network of
computers, then merge
the results. However, MapReduce model has its limitations.
Researchers have been trying to improve the model resulting in some newer
models, such as Mantri,
Camdoop, Sudo, and
Nectar model. Each model
exploits the different
characteristics of MapReduce model to
create improvements in
different way and
cases. Challenges and improvements
still remain within
these enhanced models, which
open new possibilities
on area of research.
Author: Marcellinus Ferdinand
Suciadi
Journal Code: jptinformatikagg150004
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