Achieving new SQL query performance levels through parallel execution in SQL Server
This article provides an in-depth look at implementing parallel SQL query processing using the Microsoft SQL Server database management system. It examines how parallelism can significantly accelerate query execution by leveraging multi-core processors and clustered environments. The article explore...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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EDP Sciences
2023-01-01
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| Series: | E3S Web of Conferences |
| Online Access: | https://www.e3s-conferences.org/articles/e3sconf/pdf/2023/97/e3sconf_bft2023_04005.pdf |
| _version_ | 1827373272452300800 |
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| author | Nuriev Marat Zaripova Rimma Potapov Andrey Kuznetsov Maxim |
| author_facet | Nuriev Marat Zaripova Rimma Potapov Andrey Kuznetsov Maxim |
| author_sort | Nuriev Marat |
| collection | DOAJ |
| description | This article provides an in-depth look at implementing parallel SQL query processing using the Microsoft SQL Server database management system. It examines how parallelism can significantly accelerate query execution by leveraging multi-core processors and clustered environments. The article explores SQL Server's sophisticated parallel processing capabilities including automatic query parallelization, intra-query parallelism techniques like parallel joins and parallel data aggregation, as well as inter-query parallelism for concurrent query execution. It covers key considerations around effective parallelization such as managing concurrency and locks, handling data skew, resource governance, and monitoring. Challenges like debugging parallel plans and potential bottlenecks from excessive parallelism are also discussed along with mitigation strategies. Real-world examples demonstrate how judicious application of parallel processing helps optimize complex analytics workloads involving massive datasets. The insights presented provide guidance to database developers and administrators looking to enable parallel SQL query execution in SQL Server environments for substantial performance gains and scalability. |
| first_indexed | 2024-03-08T11:13:30Z |
| format | Article |
| id | doaj.art-8051a90247d545a0896cd4f43a255882 |
| institution | Directory Open Access Journal |
| issn | 2267-1242 |
| language | English |
| last_indexed | 2024-03-08T11:13:30Z |
| publishDate | 2023-01-01 |
| publisher | EDP Sciences |
| record_format | Article |
| series | E3S Web of Conferences |
| spelling | doaj.art-8051a90247d545a0896cd4f43a2558822024-01-26T10:39:29ZengEDP SciencesE3S Web of Conferences2267-12422023-01-014600400510.1051/e3sconf/202346004005e3sconf_bft2023_04005Achieving new SQL query performance levels through parallel execution in SQL ServerNuriev Marat0Zaripova Rimma1Potapov Andrey2Kuznetsov Maxim3Kazan National Research Technical University named after A. N. Tupolev – KAIKazan State Power Engineering UniversityKazan State Power Engineering UniversityKazan State Agrarian UniversityThis article provides an in-depth look at implementing parallel SQL query processing using the Microsoft SQL Server database management system. It examines how parallelism can significantly accelerate query execution by leveraging multi-core processors and clustered environments. The article explores SQL Server's sophisticated parallel processing capabilities including automatic query parallelization, intra-query parallelism techniques like parallel joins and parallel data aggregation, as well as inter-query parallelism for concurrent query execution. It covers key considerations around effective parallelization such as managing concurrency and locks, handling data skew, resource governance, and monitoring. Challenges like debugging parallel plans and potential bottlenecks from excessive parallelism are also discussed along with mitigation strategies. Real-world examples demonstrate how judicious application of parallel processing helps optimize complex analytics workloads involving massive datasets. The insights presented provide guidance to database developers and administrators looking to enable parallel SQL query execution in SQL Server environments for substantial performance gains and scalability.https://www.e3s-conferences.org/articles/e3sconf/pdf/2023/97/e3sconf_bft2023_04005.pdf |
| spellingShingle | Nuriev Marat Zaripova Rimma Potapov Andrey Kuznetsov Maxim Achieving new SQL query performance levels through parallel execution in SQL Server E3S Web of Conferences |
| title | Achieving new SQL query performance levels through parallel execution in SQL Server |
| title_full | Achieving new SQL query performance levels through parallel execution in SQL Server |
| title_fullStr | Achieving new SQL query performance levels through parallel execution in SQL Server |
| title_full_unstemmed | Achieving new SQL query performance levels through parallel execution in SQL Server |
| title_short | Achieving new SQL query performance levels through parallel execution in SQL Server |
| title_sort | achieving new sql query performance levels through parallel execution in sql server |
| url | https://www.e3s-conferences.org/articles/e3sconf/pdf/2023/97/e3sconf_bft2023_04005.pdf |
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