ADVANCED QUERY OPTIMIZATION IN SQL DATABASES FOR REAL-TIME BIG DATA ANALYTICS
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| Názov: | ADVANCED QUERY OPTIMIZATION IN SQL DATABASES FOR REAL-TIME BIG DATA ANALYTICS |
|---|---|
| Autori: | Rahman, Md Mostafizur, Islam, Siful, Kamruzzaman, Md, Joy, Zihad Hasan |
| Zdroj: | Academic Journal on Business Administration, Innovation & Sustainability; Vol. 4 No. 3 (2024): Academic Journal on Business Administration, Innovation & Sustainability; 1-14 ; 2997-9552 |
| Informácie o vydavateľovi: | All Academic Research |
| Rok vydania: | 2024 |
| Predmety: | SQL Query Optimization, Multi-level Indexing, Query Rewriting, Dynamic Query Execution Plans, Big Data Analytics |
| Popis: | This study investigates the effectiveness of advanced query optimization techniques in SQL databases, focusing on multi-level indexing, query rewriting, and dynamic query execution plans. The research employs a qualitative approach, gathering data from a variety of SQL databases characterized by large datasets typical of big data environments. Through structured interviews, focus groups, and observational methods, insights from database administrators highlight the practical benefits and challenges associated with implementing these techniques. The findings reveal significant improvements in query performance, with multi-level indexing reducing data retrieval times by approximately 40%, query rewriting decreasing execution times by 35%, and dynamic query execution plans enhancing resource utilization efficiency by 25%. These techniques were also praised for their ease of use, adaptability to different data types and query complexities, and overall reliability. This study contributes to the existing body of knowledge by providing a comprehensive analysis of the practical applications and performance enhancements offered by advanced query optimization methods in SQL databases, underscoring their value in managing large-scale, dynamic data environments. |
| Druh dokumentu: | article in journal/newspaper |
| Popis súboru: | application/pdf |
| Jazyk: | English |
| Relation: | https://allacademicresearch.com/index.php/AJBAIS/article/view/77/72; https://allacademicresearch.com/index.php/AJBAIS/article/view/77 |
| Dostupnosť: | https://allacademicresearch.com/index.php/AJBAIS/article/view/77 |
| Rights: | Copyright (c) 2024 Academic Journal on Business Administration, Innovation & Sustainability |
| Prístupové číslo: | edsbas.CDEBAFD5 |
| Databáza: | BASE |
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| Items | – Name: Title Label: Title Group: Ti Data: ADVANCED QUERY OPTIMIZATION IN SQL DATABASES FOR REAL-TIME BIG DATA ANALYTICS – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Rahman%2C+Md+Mostafizur%22">Rahman, Md Mostafizur</searchLink><br /><searchLink fieldCode="AR" term="%22Islam%2C+Siful%22">Islam, Siful</searchLink><br /><searchLink fieldCode="AR" term="%22Kamruzzaman%2C+Md%22">Kamruzzaman, Md</searchLink><br /><searchLink fieldCode="AR" term="%22Joy%2C+Zihad+Hasan%22">Joy, Zihad Hasan</searchLink> – Name: TitleSource Label: Source Group: Src Data: Academic Journal on Business Administration, Innovation & Sustainability; Vol. 4 No. 3 (2024): Academic Journal on Business Administration, Innovation & Sustainability; 1-14 ; 2997-9552 – Name: Publisher Label: Publisher Information Group: PubInfo Data: All Academic Research – Name: DatePubCY Label: Publication Year Group: Date Data: 2024 – Name: Subject Label: Subject Terms Group: Su Data: <searchLink fieldCode="DE" term="%22SQL+Query+Optimization%22">SQL Query Optimization</searchLink><br /><searchLink fieldCode="DE" term="%22Multi-level+Indexing%22">Multi-level Indexing</searchLink><br /><searchLink fieldCode="DE" term="%22Query+Rewriting%22">Query Rewriting</searchLink><br /><searchLink fieldCode="DE" term="%22Dynamic+Query+Execution+Plans%22">Dynamic Query Execution Plans</searchLink><br /><searchLink fieldCode="DE" term="%22Big+Data+Analytics%22">Big Data Analytics</searchLink> – Name: Abstract Label: Description Group: Ab Data: This study investigates the effectiveness of advanced query optimization techniques in SQL databases, focusing on multi-level indexing, query rewriting, and dynamic query execution plans. The research employs a qualitative approach, gathering data from a variety of SQL databases characterized by large datasets typical of big data environments. Through structured interviews, focus groups, and observational methods, insights from database administrators highlight the practical benefits and challenges associated with implementing these techniques. The findings reveal significant improvements in query performance, with multi-level indexing reducing data retrieval times by approximately 40%, query rewriting decreasing execution times by 35%, and dynamic query execution plans enhancing resource utilization efficiency by 25%. These techniques were also praised for their ease of use, adaptability to different data types and query complexities, and overall reliability. This study contributes to the existing body of knowledge by providing a comprehensive analysis of the practical applications and performance enhancements offered by advanced query optimization methods in SQL databases, underscoring their value in managing large-scale, dynamic data environments. – Name: TypeDocument Label: Document Type Group: TypDoc Data: article in journal/newspaper – Name: Format Label: File Description Group: SrcInfo Data: application/pdf – Name: Language Label: Language Group: Lang Data: English – Name: NoteTitleSource Label: Relation Group: SrcInfo Data: https://allacademicresearch.com/index.php/AJBAIS/article/view/77/72; https://allacademicresearch.com/index.php/AJBAIS/article/view/77 – Name: URL Label: Availability Group: URL Data: https://allacademicresearch.com/index.php/AJBAIS/article/view/77 – Name: Copyright Label: Rights Group: Cpyrght Data: Copyright (c) 2024 Academic Journal on Business Administration, Innovation & Sustainability – Name: AN Label: Accession Number Group: ID Data: edsbas.CDEBAFD5 |
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| RecordInfo | BibRecord: BibEntity: Languages: – Text: English Subjects: – SubjectFull: SQL Query Optimization Type: general – SubjectFull: Multi-level Indexing Type: general – SubjectFull: Query Rewriting Type: general – SubjectFull: Dynamic Query Execution Plans Type: general – SubjectFull: Big Data Analytics Type: general Titles: – TitleFull: ADVANCED QUERY OPTIMIZATION IN SQL DATABASES FOR REAL-TIME BIG DATA ANALYTICS Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Rahman, Md Mostafizur – PersonEntity: Name: NameFull: Islam, Siful – PersonEntity: Name: NameFull: Kamruzzaman, Md – PersonEntity: Name: NameFull: Joy, Zihad Hasan IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 01 Type: published Y: 2024 Identifiers: – Type: issn-locals Value: edsbas – Type: issn-locals Value: edsbas.oa Titles: – TitleFull: Academic Journal on Business Administration, Innovation & Sustainability; Vol. 4 No. 3 (2024): Academic Journal on Business Administration, Innovation & Sustainability Type: main |
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