{"title":"连接共享一切系统,以实现高效的并行查询处理","authors":"K. Hua, Chiang Lee, J. Peir","doi":"10.1109/PDIS.1991.183113","DOIUrl":null,"url":null,"abstract":"The most debated architectures for parallel database processing are Shared Nothing (SN) and Shared Everything (SE) structures. Although SN is considered to be most scalable, it is very sensitive to the data skew problem. On the other hand, SE allows the collaborating processors to share the work load more efficiently. It, however, suffers from the limitation of the memory and disk I/O band-width. The authors present a hybrid architecture in which SE clusters are interconnected through a communication network to form a SN structure at the inter-cluster level. In this approach, processing elements are clustered into SE systems to minimize the skew effect. Each cluster, however, is kept small within the limitation of the memory and I/O technology to avoid the data access bottleneck. A generalized performance model was developed to perform sensitivity analysis for the hybrid structure, and to compare it against SE and SN organizations.<<ETX>>","PeriodicalId":210800,"journal":{"name":"[1991] Proceedings of the First International Conference on Parallel and Distributed Information Systems","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"1991-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"16","resultStr":"{\"title\":\"Interconnecting shared-everything systems for efficient parallel query processing\",\"authors\":\"K. Hua, Chiang Lee, J. Peir\",\"doi\":\"10.1109/PDIS.1991.183113\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The most debated architectures for parallel database processing are Shared Nothing (SN) and Shared Everything (SE) structures. Although SN is considered to be most scalable, it is very sensitive to the data skew problem. On the other hand, SE allows the collaborating processors to share the work load more efficiently. It, however, suffers from the limitation of the memory and disk I/O band-width. The authors present a hybrid architecture in which SE clusters are interconnected through a communication network to form a SN structure at the inter-cluster level. In this approach, processing elements are clustered into SE systems to minimize the skew effect. Each cluster, however, is kept small within the limitation of the memory and I/O technology to avoid the data access bottleneck. A generalized performance model was developed to perform sensitivity analysis for the hybrid structure, and to compare it against SE and SN organizations.<<ETX>>\",\"PeriodicalId\":210800,\"journal\":{\"name\":\"[1991] Proceedings of the First International Conference on Parallel and Distributed Information Systems\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1991-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"16\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"[1991] Proceedings of the First International Conference on Parallel and Distributed Information Systems\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/PDIS.1991.183113\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"[1991] Proceedings of the First International Conference on Parallel and Distributed Information Systems","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/PDIS.1991.183113","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Interconnecting shared-everything systems for efficient parallel query processing
The most debated architectures for parallel database processing are Shared Nothing (SN) and Shared Everything (SE) structures. Although SN is considered to be most scalable, it is very sensitive to the data skew problem. On the other hand, SE allows the collaborating processors to share the work load more efficiently. It, however, suffers from the limitation of the memory and disk I/O band-width. The authors present a hybrid architecture in which SE clusters are interconnected through a communication network to form a SN structure at the inter-cluster level. In this approach, processing elements are clustered into SE systems to minimize the skew effect. Each cluster, however, is kept small within the limitation of the memory and I/O technology to avoid the data access bottleneck. A generalized performance model was developed to perform sensitivity analysis for the hybrid structure, and to compare it against SE and SN organizations.<>