{"title":"自调整数据库系统:自动数据库模式设计和调整的系统性文献综述","authors":"M. Mozaffari, Anton Dignös, J. Gamper, U. Störl","doi":"10.1145/3665323","DOIUrl":null,"url":null,"abstract":"\n Self-tuning is a feature of autonomic databases that includes the problem of automatic schema design. It aims at providing an optimized schema that increases the overall database performance. While in relational databases automatic schema design focuses on the automated design of the physical schema, in NoSQL databases all levels of representation are considered: conceptual, logical, and physical. This is mainly because the latter are mostly schema-less and lack a standard schema design procedure as is the case for SQL databases. In this work, we carry out a systematic literature survey on automatic schema design in both SQL\n and\n NoSQL databases. We identify the levels of representation and the methods that are used for the schema design problem, and we present a novel taxonomy to classify and compare different schema design solutions. Our comprehensive analysis demonstrates that, despite substantial progress that has been made, schema design is still a developing field and considerable challenges need to be addressed, notably for NoSQL databases. We highlight the most important findings from the results of our analysis and identify areas for future research work.\n","PeriodicalId":50926,"journal":{"name":"ACM Computing Surveys","volume":null,"pages":null},"PeriodicalIF":23.8000,"publicationDate":"2024-05-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Self-tuning Database Systems: A Systematic Literature Review of Automatic Database Schema Design and Tuning\",\"authors\":\"M. Mozaffari, Anton Dignös, J. Gamper, U. Störl\",\"doi\":\"10.1145/3665323\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"\\n Self-tuning is a feature of autonomic databases that includes the problem of automatic schema design. It aims at providing an optimized schema that increases the overall database performance. While in relational databases automatic schema design focuses on the automated design of the physical schema, in NoSQL databases all levels of representation are considered: conceptual, logical, and physical. This is mainly because the latter are mostly schema-less and lack a standard schema design procedure as is the case for SQL databases. In this work, we carry out a systematic literature survey on automatic schema design in both SQL\\n and\\n NoSQL databases. We identify the levels of representation and the methods that are used for the schema design problem, and we present a novel taxonomy to classify and compare different schema design solutions. Our comprehensive analysis demonstrates that, despite substantial progress that has been made, schema design is still a developing field and considerable challenges need to be addressed, notably for NoSQL databases. We highlight the most important findings from the results of our analysis and identify areas for future research work.\\n\",\"PeriodicalId\":50926,\"journal\":{\"name\":\"ACM Computing Surveys\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":23.8000,\"publicationDate\":\"2024-05-17\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"ACM Computing Surveys\",\"FirstCategoryId\":\"94\",\"ListUrlMain\":\"https://doi.org/10.1145/3665323\",\"RegionNum\":1,\"RegionCategory\":\"计算机科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"COMPUTER SCIENCE, THEORY & METHODS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"ACM Computing Surveys","FirstCategoryId":"94","ListUrlMain":"https://doi.org/10.1145/3665323","RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"COMPUTER SCIENCE, THEORY & METHODS","Score":null,"Total":0}
Self-tuning Database Systems: A Systematic Literature Review of Automatic Database Schema Design and Tuning
Self-tuning is a feature of autonomic databases that includes the problem of automatic schema design. It aims at providing an optimized schema that increases the overall database performance. While in relational databases automatic schema design focuses on the automated design of the physical schema, in NoSQL databases all levels of representation are considered: conceptual, logical, and physical. This is mainly because the latter are mostly schema-less and lack a standard schema design procedure as is the case for SQL databases. In this work, we carry out a systematic literature survey on automatic schema design in both SQL
and
NoSQL databases. We identify the levels of representation and the methods that are used for the schema design problem, and we present a novel taxonomy to classify and compare different schema design solutions. Our comprehensive analysis demonstrates that, despite substantial progress that has been made, schema design is still a developing field and considerable challenges need to be addressed, notably for NoSQL databases. We highlight the most important findings from the results of our analysis and identify areas for future research work.
期刊介绍:
ACM Computing Surveys is an academic journal that focuses on publishing surveys and tutorials on various areas of computing research and practice. The journal aims to provide comprehensive and easily understandable articles that guide readers through the literature and help them understand topics outside their specialties. In terms of impact, CSUR has a high reputation with a 2022 Impact Factor of 16.6. It is ranked 3rd out of 111 journals in the field of Computer Science Theory & Methods.
ACM Computing Surveys is indexed and abstracted in various services, including AI2 Semantic Scholar, Baidu, Clarivate/ISI: JCR, CNKI, DeepDyve, DTU, EBSCO: EDS/HOST, and IET Inspec, among others.