{"title":"支持无模式NoSQL数据存储中的模式演化","authors":"L. Meurice, Anthony Cleve","doi":"10.1109/SANER.2017.7884653","DOIUrl":null,"url":null,"abstract":"NoSQL data stores are becoming popular due to their schema-less nature. They offer a high level of flexibility, since they do not require to declare a global schema. Thus, the data model is maintained within the application source code. However, due to this flexibility, developers have to struggle with a growing data structure entropy and to manage legacy data. Moreover, support to schema evolution is lacking, which may lead to runtime errors or irretrievable data loss, if not properly handled. This paper presents an approach to support the evolution of a schema-less NoSQL data store by analyzing the application source code and its history. We motivate this approach on a subject system and explain how useful it is to understand the present database structure and facilitate future developments.","PeriodicalId":6541,"journal":{"name":"2017 IEEE 24th International Conference on Software Analysis, Evolution and Reengineering (SANER)","volume":"41 1","pages":"457-461"},"PeriodicalIF":0.0000,"publicationDate":"2017-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"12","resultStr":"{\"title\":\"Supporting schema evolution in schema-less NoSQL data stores\",\"authors\":\"L. Meurice, Anthony Cleve\",\"doi\":\"10.1109/SANER.2017.7884653\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"NoSQL data stores are becoming popular due to their schema-less nature. They offer a high level of flexibility, since they do not require to declare a global schema. Thus, the data model is maintained within the application source code. However, due to this flexibility, developers have to struggle with a growing data structure entropy and to manage legacy data. Moreover, support to schema evolution is lacking, which may lead to runtime errors or irretrievable data loss, if not properly handled. This paper presents an approach to support the evolution of a schema-less NoSQL data store by analyzing the application source code and its history. We motivate this approach on a subject system and explain how useful it is to understand the present database structure and facilitate future developments.\",\"PeriodicalId\":6541,\"journal\":{\"name\":\"2017 IEEE 24th International Conference on Software Analysis, Evolution and Reengineering (SANER)\",\"volume\":\"41 1\",\"pages\":\"457-461\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2017-02-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"12\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2017 IEEE 24th International Conference on Software Analysis, Evolution and Reengineering (SANER)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/SANER.2017.7884653\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 IEEE 24th International Conference on Software Analysis, Evolution and Reengineering (SANER)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SANER.2017.7884653","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Supporting schema evolution in schema-less NoSQL data stores
NoSQL data stores are becoming popular due to their schema-less nature. They offer a high level of flexibility, since they do not require to declare a global schema. Thus, the data model is maintained within the application source code. However, due to this flexibility, developers have to struggle with a growing data structure entropy and to manage legacy data. Moreover, support to schema evolution is lacking, which may lead to runtime errors or irretrievable data loss, if not properly handled. This paper presents an approach to support the evolution of a schema-less NoSQL data store by analyzing the application source code and its history. We motivate this approach on a subject system and explain how useful it is to understand the present database structure and facilitate future developments.