{"title":"执行数据映射器","authors":"Paulo Carreira, H. Galhardas","doi":"10.1145/1012453.1012455","DOIUrl":null,"url":null,"abstract":"Data mappers are essential operators for implementing data transformations supporting schema mapping and integration scenarios such as legacy data migration, ETL processes for data warehousing, data cleaning activities, and business integration initiatives. Despite their widespread use, no formalization of this important operation has been proposed so far. In this paper we propose the data mapper operator as an extension to the relational algebra. We supply a set of algebraic rewriting rules for optimizing queries that combine standard relational operators with data mappers. Finally, we propose algorithms for their efficient physical execution.","PeriodicalId":306187,"journal":{"name":"Information Quality in Information Systems","volume":"26 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2004-06-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"17","resultStr":"{\"title\":\"Execution of data mappers\",\"authors\":\"Paulo Carreira, H. Galhardas\",\"doi\":\"10.1145/1012453.1012455\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Data mappers are essential operators for implementing data transformations supporting schema mapping and integration scenarios such as legacy data migration, ETL processes for data warehousing, data cleaning activities, and business integration initiatives. Despite their widespread use, no formalization of this important operation has been proposed so far. In this paper we propose the data mapper operator as an extension to the relational algebra. We supply a set of algebraic rewriting rules for optimizing queries that combine standard relational operators with data mappers. Finally, we propose algorithms for their efficient physical execution.\",\"PeriodicalId\":306187,\"journal\":{\"name\":\"Information Quality in Information Systems\",\"volume\":\"26 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2004-06-18\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"17\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Information Quality in Information Systems\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/1012453.1012455\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Information Quality in Information Systems","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/1012453.1012455","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Data mappers are essential operators for implementing data transformations supporting schema mapping and integration scenarios such as legacy data migration, ETL processes for data warehousing, data cleaning activities, and business integration initiatives. Despite their widespread use, no formalization of this important operation has been proposed so far. In this paper we propose the data mapper operator as an extension to the relational algebra. We supply a set of algebraic rewriting rules for optimizing queries that combine standard relational operators with data mappers. Finally, we propose algorithms for their efficient physical execution.