Query rewriting using multitier materialized views for Cyber manufacturing reporting
Within cyber manufacturing context, Internet of Data (IoD) technology has enabled manufacturing sector to store and transfer mass data rapidly for processing. Data growth which is driven by advancement in the way data are produced and interconnected has caused volume of data a crucial issue to addre...
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| Main Authors: | , , |
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| 格式: | Article |
| 语言: | English |
| 出版: |
Penerbit UTeM
2018
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| 在线阅读: | http://eprints.utem.edu.my/id/eprint/21970/2/JAMT%20published.pdf http://eprints.utem.edu.my/id/eprint/21970/ http://journal.utem.edu.my/index.php/jamt/article/view/4008 |
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| 总结: | Within cyber manufacturing context, Internet of Data (IoD) technology has enabled manufacturing sector to store and transfer mass data rapidly for processing. Data growth which is driven by advancement in the way data are produced and interconnected has caused volume of data a crucial issue to address. As such, in monitoring delicate wafer processing in semiconductor manufacturing, reporting delay problem caused by databases of high data volumes is intolerable. This is because, various reports (that require access to large databases) need to be frequently generated in the shortest time possible. Reporting delay is usually handled through SQL query rewriting.In this paper, the results of experimenting SQL query rewriting by utilizing multitier materialized views structure is presented.In particular, we define sub-materialized views (SMVs) concept, and implement it using real data sets from SilTerra (a semiconductor industry). The outcome of the experiment supports the hypothesis that SQL query rewriting using SMV outperforms the classic rewriting. The results reveal that the performance of SMV is far better (than without SMV) for complex queries against large data sets. The benefits of SMV are not limited to cyber manufacturing domain as the use of SMV can contribute other industries with similar problem. |
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