Survey on AI Powered New Techniques for Query Processing and Optimization
As one of the most challenging problems in data management, query processing and optimization are always widely concerned by researchers. However, it is very difficult for traditional techniques to meet the diverse requirements of modern database system due to the needs of hand-tuning for specific w...
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| Format: | Article |
| Language: | zho |
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Journal of Computer Engineering and Applications Beijing Co., Ltd., Science Press
2020-07-01
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| Series: | Jisuanji kexue yu tansuo |
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| Online Access: | http://fcst.ceaj.org/CN/abstract/abstract2258.shtml |
| _version_ | 1818891396518510592 |
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| author | SONG Yumeng, GU Yu, LI Fangfang, YU Ge |
| author_facet | SONG Yumeng, GU Yu, LI Fangfang, YU Ge |
| author_sort | SONG Yumeng, GU Yu, LI Fangfang, YU Ge |
| collection | DOAJ |
| description | As one of the most challenging problems in data management, query processing and optimization are always widely concerned by researchers. However, it is very difficult for traditional techniques to meet the diverse requirements of modern database system due to the needs of hand-tuning for specific workloads and datasets. Inspired by advances in applying artificial intelligence (AI) to multi-field researches, recently, the AI powered new techniques for query processing and optimization have been proposed and made significant success. In view of these researches, this paper first presents the main tasks of the AI powered new techniques of query processing and optimization, and analyzes the differences between the new tasks and traditional AI tasks. Second, the recent research progress is reviewed, and the main advantages and application bottlenecks are summarized. Third, this paper discusses the main challenges of the AI powered new techniques of query processing and optimization. Finally, the future research directions are prospected. |
| first_indexed | 2024-12-19T17:40:09Z |
| format | Article |
| id | doaj.art-01fec024dfed471c8579d59384b14e6a |
| institution | Directory Open Access Journal |
| issn | 1673-9418 |
| language | zho |
| last_indexed | 2024-12-19T17:40:09Z |
| publishDate | 2020-07-01 |
| publisher | Journal of Computer Engineering and Applications Beijing Co., Ltd., Science Press |
| record_format | Article |
| series | Jisuanji kexue yu tansuo |
| spelling | doaj.art-01fec024dfed471c8579d59384b14e6a2022-12-21T20:12:14ZzhoJournal of Computer Engineering and Applications Beijing Co., Ltd., Science PressJisuanji kexue yu tansuo1673-94182020-07-011471081110310.3778/j.issn.1673-9418.1911063Survey on AI Powered New Techniques for Query Processing and OptimizationSONG Yumeng, GU Yu, LI Fangfang, YU Ge0School of Computer Science and Engineering, Northeastern University, Shenyang 110169, ChinaAs one of the most challenging problems in data management, query processing and optimization are always widely concerned by researchers. However, it is very difficult for traditional techniques to meet the diverse requirements of modern database system due to the needs of hand-tuning for specific workloads and datasets. Inspired by advances in applying artificial intelligence (AI) to multi-field researches, recently, the AI powered new techniques for query processing and optimization have been proposed and made significant success. In view of these researches, this paper first presents the main tasks of the AI powered new techniques of query processing and optimization, and analyzes the differences between the new tasks and traditional AI tasks. Second, the recent research progress is reviewed, and the main advantages and application bottlenecks are summarized. Third, this paper discusses the main challenges of the AI powered new techniques of query processing and optimization. Finally, the future research directions are prospected.http://fcst.ceaj.org/CN/abstract/abstract2258.shtmlquery optimizationartificial intelligencemachine learningdeep learningdatabase systems |
| spellingShingle | SONG Yumeng, GU Yu, LI Fangfang, YU Ge Survey on AI Powered New Techniques for Query Processing and Optimization Jisuanji kexue yu tansuo query optimization artificial intelligence machine learning deep learning database systems |
| title | Survey on AI Powered New Techniques for Query Processing and Optimization |
| title_full | Survey on AI Powered New Techniques for Query Processing and Optimization |
| title_fullStr | Survey on AI Powered New Techniques for Query Processing and Optimization |
| title_full_unstemmed | Survey on AI Powered New Techniques for Query Processing and Optimization |
| title_short | Survey on AI Powered New Techniques for Query Processing and Optimization |
| title_sort | survey on ai powered new techniques for query processing and optimization |
| topic | query optimization artificial intelligence machine learning deep learning database systems |
| url | http://fcst.ceaj.org/CN/abstract/abstract2258.shtml |
| work_keys_str_mv | AT songyumengguyulifangfangyuge surveyonaipowerednewtechniquesforqueryprocessingandoptimization |