Workflow system for MapReduce in cloud environment

The magnitude of data generated and shared by businesses, public administrations, industrial sectors and scientific research, has increased immeasurably. Apache Hadoop is an open source software framework, which enables a scalable and distributed processing of high volumes of data. MapReduce togethe...

Full description

Saved in:

Bibliographic Details
Main Author:	Wadi, Muntadher Saadoon
Format:	Thesis
Language:	English
Published:	2017
Subjects:	Cloud computing Operating systems (Computers)
Online Access:	http://psasir.upm.edu.my/id/eprint/71042/1/FSKTM%202017%206%20-%20IR.pdf
Tags:	Add Tag No Tags, Be the first to tag this record!

id	my-upm-ir.71042
record_format	uketd_dc
spelling	my-upm-ir.710422019-08-13T08:11:25Z Workflow system for MapReduce in cloud environment 2017-07 Wadi, Muntadher Saadoon The magnitude of data generated and shared by businesses, public administrations, industrial sectors and scientific research, has increased immeasurably. Apache Hadoop is an open source software framework, which enables a scalable and distributed processing of high volumes of data. MapReduce together with its Hadoop implementation has been widely adopted in many practical applications. A common practice nowadays is to implement MapReduce applications in a high-performance infrastructure, such as cloud computing. A cloud platform can deploy and manage Hadoop clusters. However, there are tasks required advanced knowledge in computer science and cloud computing when using MapReduce technology that prevent the usage of current technologies and software solutions. For example, MapReduce deployment and maintenance, data integration with Hadoop distributed file system or MapReduce job submission. A MapReduce workflow system is one of the solution that could assist MapReduce and Hadoop developers. Besides, it provides a user-friendly execution platform that encapsulating complexity of data analysis steps. In this research, a new workflows system is developed to facilitate the use of collaborating, coordinating and executing operations of MapReduce programs with a graphical user interface based on Hadoop cloud cluster. The experimental results indicate that the developed workflow system can achieve good speed in performance. It is believed that the workflow system is an ideal stereotype for MapReduce and it will play an important role in the era of big data applications in cloud computing. Cloud computing Operating systems (Computers) 2017-07 Thesis http://psasir.upm.edu.my/id/eprint/71042/ http://psasir.upm.edu.my/id/eprint/71042/1/FSKTM%202017%206%20-%20IR.pdf text en public masters Universiti Putra Malaysia Cloud computing Operating systems (Computers)
institution	Universiti Putra Malaysia
collection	PSAS Institutional Repository
language	English
topic	Cloud computing Operating systems (Computers)
spellingShingle	Cloud computing Operating systems (Computers) Wadi, Muntadher Saadoon Workflow system for MapReduce in cloud environment
description	The magnitude of data generated and shared by businesses, public administrations, industrial sectors and scientific research, has increased immeasurably. Apache Hadoop is an open source software framework, which enables a scalable and distributed processing of high volumes of data. MapReduce together with its Hadoop implementation has been widely adopted in many practical applications. A common practice nowadays is to implement MapReduce applications in a high-performance infrastructure, such as cloud computing. A cloud platform can deploy and manage Hadoop clusters. However, there are tasks required advanced knowledge in computer science and cloud computing when using MapReduce technology that prevent the usage of current technologies and software solutions. For example, MapReduce deployment and maintenance, data integration with Hadoop distributed file system or MapReduce job submission. A MapReduce workflow system is one of the solution that could assist MapReduce and Hadoop developers. Besides, it provides a user-friendly execution platform that encapsulating complexity of data analysis steps. In this research, a new workflows system is developed to facilitate the use of collaborating, coordinating and executing operations of MapReduce programs with a graphical user interface based on Hadoop cloud cluster. The experimental results indicate that the developed workflow system can achieve good speed in performance. It is believed that the workflow system is an ideal stereotype for MapReduce and it will play an important role in the era of big data applications in cloud computing.
format	Thesis
qualification_level	Master's degree
author	Wadi, Muntadher Saadoon
author_facet	Wadi, Muntadher Saadoon
author_sort	Wadi, Muntadher Saadoon
title	Workflow system for MapReduce in cloud environment
title_short	Workflow system for MapReduce in cloud environment
title_full	Workflow system for MapReduce in cloud environment
title_fullStr	Workflow system for MapReduce in cloud environment
title_full_unstemmed	Workflow system for MapReduce in cloud environment
title_sort	workflow system for mapreduce in cloud environment
granting_institution	Universiti Putra Malaysia
publishDate	2017
url	http://psasir.upm.edu.my/id/eprint/71042/1/FSKTM%202017%206%20-%20IR.pdf
_version_	1747812959677054976

Workflow system for MapReduce in cloud environment

Similar Items