{"title":"从JSON数据库中提取信息就像使用JSONiq在SQL中提取一样简单","authors":"R. Vinothsaravanan, C. Palanisamy","doi":"10.1109/ICACCE46606.2019.9080010","DOIUrl":null,"url":null,"abstract":"JSON is a prevalent broadly useful information encoding group, utilized in numerous databases and web administrations. It is simple for a programmer to read and write as worked in a relational database. Like XML, JSON is also a semi-structured database in nature. Extracting information from semi-structured database required special query evaluation and processing engine. Using XQuery static information from XML database can access and retrieve easily through FLWOR construct. To extract structural and semi-structural information from JSON will be done through JSONiq query language and processor. The aim of this paper is finding the similarity between the relational query and JSONiq query and proving that simple queries like join, project, select, group, filter, and aggregate as done in SQL can also be done in JSONiq with JSON database.","PeriodicalId":317123,"journal":{"name":"2019 International Conference on Advances in Computing and Communication Engineering (ICACCE)","volume":"9 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"Extracting information from JSON database as simple as extracting in SQL using JSONiq\",\"authors\":\"R. Vinothsaravanan, C. Palanisamy\",\"doi\":\"10.1109/ICACCE46606.2019.9080010\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"JSON is a prevalent broadly useful information encoding group, utilized in numerous databases and web administrations. It is simple for a programmer to read and write as worked in a relational database. Like XML, JSON is also a semi-structured database in nature. Extracting information from semi-structured database required special query evaluation and processing engine. Using XQuery static information from XML database can access and retrieve easily through FLWOR construct. To extract structural and semi-structural information from JSON will be done through JSONiq query language and processor. The aim of this paper is finding the similarity between the relational query and JSONiq query and proving that simple queries like join, project, select, group, filter, and aggregate as done in SQL can also be done in JSONiq with JSON database.\",\"PeriodicalId\":317123,\"journal\":{\"name\":\"2019 International Conference on Advances in Computing and Communication Engineering (ICACCE)\",\"volume\":\"9 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-04-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2019 International Conference on Advances in Computing and Communication Engineering (ICACCE)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICACCE46606.2019.9080010\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 International Conference on Advances in Computing and Communication Engineering (ICACCE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICACCE46606.2019.9080010","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Extracting information from JSON database as simple as extracting in SQL using JSONiq
JSON is a prevalent broadly useful information encoding group, utilized in numerous databases and web administrations. It is simple for a programmer to read and write as worked in a relational database. Like XML, JSON is also a semi-structured database in nature. Extracting information from semi-structured database required special query evaluation and processing engine. Using XQuery static information from XML database can access and retrieve easily through FLWOR construct. To extract structural and semi-structural information from JSON will be done through JSONiq query language and processor. The aim of this paper is finding the similarity between the relational query and JSONiq query and proving that simple queries like join, project, select, group, filter, and aggregate as done in SQL can also be done in JSONiq with JSON database.