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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my-usm-ep.600262024-02-28T06:49:58Z Enhanced Late-Straggler Algorithm With On-Demand Etl For Big Data Retrieval 2022-11 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 http://eprints.usm.my/60026/ http://eprints.usm.my/60026/1/24%20Pages%20from%20ANWAR%20HUSSEIN%20ZAKARIA%20KATRAWI.pdf application/pdf en public phd doctoral Perpustakaan Hamzah Sendut Pusat Ipv6 Termaju |
| institution |
Universiti Sains Malaysia |
| collection |
USM Institutional Repository |
| language |
English |
| topic |
T1-995 Technology(General) |
| spellingShingle |
T1-995 Technology(General) Zakaria Katrawi, Anwar Hussein Enhanced Late-Straggler Algorithm With On-Demand Etl For Big Data Retrieval |
| 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. |
| format |
Thesis |
| qualification_name |
Doctor of Philosophy (PhD.) |
| qualification_level |
Doctorate |
| author |
Zakaria Katrawi, Anwar Hussein |
| author_facet |
Zakaria Katrawi, Anwar Hussein |
| author_sort |
Zakaria Katrawi, Anwar Hussein |
| title |
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_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_sort |
enhanced late-straggler algorithm with on-demand etl for big data retrieval |
| granting_institution |
Perpustakaan Hamzah Sendut |
| granting_department |
Pusat Ipv6 Termaju |
| publishDate |
2022 |
| url |
http://eprints.usm.my/60026/1/24%20Pages%20from%20ANWAR%20HUSSEIN%20ZAKARIA%20KATRAWI.pdf |
| _version_ |
1794024078206566400 |