Enhanced Late-Straggler Algorithm With On-Demand Etl For Big Data Retrieval

The growth of digital information is phenomenal. Digital documents dominate nearly every aspect of doing business to the point that it is hard to imagine doing without them. With an unprecedented potential lurking in its depths, the ongoing digital information revolution also presents risks and c...

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Main Author: Zakaria Katrawi, Anwar Hussein
Format: Thesis
Language:English
Published: 2022
Subjects:
Online Access:http://eprints.usm.my/60026/
http://eprints.usm.my/60026/1/24%20Pages%20from%20ANWAR%20HUSSEIN%20ZAKARIA%20KATRAWI.pdf
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author Zakaria Katrawi, Anwar Hussein
author_facet Zakaria Katrawi, Anwar Hussein
author_sort Zakaria Katrawi, Anwar Hussein
building USM Institutional Repository
collection Online Access
description The growth of digital information is phenomenal. Digital documents dominate nearly every aspect of doing business to the point that it is hard to imagine doing without them. With an unprecedented potential lurking in its depths, the ongoing digital information revolution also presents risks and challenges, mainly when dealing with the extraction and analysis of digital data. The conventional method ETL of Big Data processing consists of Extraction, Transformation, and Loading integrated into a warehouse. Using this method without any optimization often leads to a delay in data retrieval, known as the straggler problem, which is a situation that arises when tasks are delayed due to low processing on some nodes. The straggler problem is considered by many as a major problem, especially when the data resources are important and if these resources are inefficiently used. Hence, detecting and, therefore, eliminating the straggler problem early is crucial to enhancing the ETL performance.
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institution Universiti Sains Malaysia
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language English
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publishDate 2022
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spelling usm-600262024-02-28T06:49:58Z http://eprints.usm.my/60026/ Enhanced Late-Straggler Algorithm With On-Demand Etl For Big Data Retrieval Zakaria Katrawi, Anwar Hussein T1-995 Technology(General) The growth of digital information is phenomenal. Digital documents dominate nearly every aspect of doing business to the point that it is hard to imagine doing without them. With an unprecedented potential lurking in its depths, the ongoing digital information revolution also presents risks and challenges, mainly when dealing with the extraction and analysis of digital data. The conventional method ETL of Big Data processing consists of Extraction, Transformation, and Loading integrated into a warehouse. Using this method without any optimization often leads to a delay in data retrieval, known as the straggler problem, which is a situation that arises when tasks are delayed due to low processing on some nodes. The straggler problem is considered by many as a major problem, especially when the data resources are important and if these resources are inefficiently used. Hence, detecting and, therefore, eliminating the straggler problem early is crucial to enhancing the ETL performance. 2022-11 Thesis NonPeerReviewed application/pdf en http://eprints.usm.my/60026/1/24%20Pages%20from%20ANWAR%20HUSSEIN%20ZAKARIA%20KATRAWI.pdf Zakaria Katrawi, Anwar Hussein (2022) Enhanced Late-Straggler Algorithm With On-Demand Etl For Big Data Retrieval. PhD thesis, Perpustakaan Hamzah Sendut.
spellingShingle T1-995 Technology(General)
Zakaria Katrawi, Anwar Hussein
Enhanced Late-Straggler Algorithm With On-Demand Etl For Big Data Retrieval
title Enhanced Late-Straggler Algorithm With On-Demand Etl For Big Data Retrieval
title_full Enhanced Late-Straggler Algorithm With On-Demand Etl For Big Data Retrieval
title_fullStr Enhanced Late-Straggler Algorithm With On-Demand Etl For Big Data Retrieval
title_full_unstemmed Enhanced Late-Straggler Algorithm With On-Demand Etl For Big Data Retrieval
title_short Enhanced Late-Straggler Algorithm With On-Demand Etl For Big Data Retrieval
title_sort enhanced late-straggler algorithm with on-demand etl for big data retrieval
topic T1-995 Technology(General)
url http://eprints.usm.my/60026/
http://eprints.usm.my/60026/1/24%20Pages%20from%20ANWAR%20HUSSEIN%20ZAKARIA%20KATRAWI.pdf