{"title":"用于决策支持应用程序的可伸缩并行查询服务器","authors":"Jen-Yao Chung","doi":"10.1109/ICDE.1995.380393","DOIUrl":null,"url":null,"abstract":"Decision-support applications require the ability to query against large amounts of detailed historical data. We are exploiting parallel technology to improve query response time through query decomposition, CPU and I/O parallelism, and client/server approach. IBM System/390 Parallel Query Server is built on advanced and low-cost CMOS microprocessors for decision-support applications. We discuss our design, implementation and performance of a scalable parallel query server.<<ETX>>","PeriodicalId":184415,"journal":{"name":"Proceedings of the Eleventh International Conference on Data Engineering","volume":"489 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1995-03-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Scalable parallel query server for decision support applications\",\"authors\":\"Jen-Yao Chung\",\"doi\":\"10.1109/ICDE.1995.380393\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Decision-support applications require the ability to query against large amounts of detailed historical data. We are exploiting parallel technology to improve query response time through query decomposition, CPU and I/O parallelism, and client/server approach. IBM System/390 Parallel Query Server is built on advanced and low-cost CMOS microprocessors for decision-support applications. We discuss our design, implementation and performance of a scalable parallel query server.<<ETX>>\",\"PeriodicalId\":184415,\"journal\":{\"name\":\"Proceedings of the Eleventh International Conference on Data Engineering\",\"volume\":\"489 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1995-03-06\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the Eleventh International Conference on Data Engineering\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICDE.1995.380393\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the Eleventh International Conference on Data Engineering","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICDE.1995.380393","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Scalable parallel query server for decision support applications
Decision-support applications require the ability to query against large amounts of detailed historical data. We are exploiting parallel technology to improve query response time through query decomposition, CPU and I/O parallelism, and client/server approach. IBM System/390 Parallel Query Server is built on advanced and low-cost CMOS microprocessors for decision-support applications. We discuss our design, implementation and performance of a scalable parallel query server.<>
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