{"title":"广义偏指数","authors":"P. Seshadri, A. Swami","doi":"10.1109/ICDE.1995.380355","DOIUrl":null,"url":null,"abstract":"This paper demonstrates the use of generalized partial indexes for efficient query processing. We propose that partial indexes be built on those portions of the database that are statistically likely to be the most useful for query processing. We identify three classes of statistical information, and two levels at which it may be available. We describe indexing strategies that use this information to significantly improve average query performance. Results from simulation experiments demonstrate that the proposed generalized partial indexing strategies perform well compared to the traditional approach to indexing.<<ETX>>","PeriodicalId":184415,"journal":{"name":"Proceedings of the Eleventh International Conference on Data Engineering","volume":"236 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1995-03-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"67","resultStr":"{\"title\":\"Generalized partial indexes\",\"authors\":\"P. Seshadri, A. Swami\",\"doi\":\"10.1109/ICDE.1995.380355\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper demonstrates the use of generalized partial indexes for efficient query processing. We propose that partial indexes be built on those portions of the database that are statistically likely to be the most useful for query processing. We identify three classes of statistical information, and two levels at which it may be available. We describe indexing strategies that use this information to significantly improve average query performance. Results from simulation experiments demonstrate that the proposed generalized partial indexing strategies perform well compared to the traditional approach to indexing.<<ETX>>\",\"PeriodicalId\":184415,\"journal\":{\"name\":\"Proceedings of the Eleventh International Conference on Data Engineering\",\"volume\":\"236 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1995-03-06\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"67\",\"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.1995.380355\",\"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.1995.380355","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
This paper demonstrates the use of generalized partial indexes for efficient query processing. We propose that partial indexes be built on those portions of the database that are statistically likely to be the most useful for query processing. We identify three classes of statistical information, and two levels at which it may be available. We describe indexing strategies that use this information to significantly improve average query performance. Results from simulation experiments demonstrate that the proposed generalized partial indexing strategies perform well compared to the traditional approach to indexing.<>