创建JSON Column CREATE TABLE TestJson ( Id int IDENTITY CONSTRAINT PK_TestJson_Id PRIMARY KEY, JsonData nvarchar(max) CONSTRAINT [Content should be formatted as JSON] CHECK(ISJSON(JsonData)>0) ); Json Column 其实就是 nvarchar 来的, 只是在上面加了一层 constraint 而已. ISJSON 是一个判断 t...
'''),1,1,''')) + '' }'' as json from ' + @TableName + ' with(nolock) where ('+@ColumnIn+' in (Select MyValues from dbo.funSplitArray('''+@ColumnValues+''','',''))) '+@Condition--+' ORDER BY '+@SortColumn+' '+@SortType exec sp_sqlexec @query --SELECT @query...
用于判断,@ColumnValues nvarchar(max):值'aaa,bbb,ccc',@Condition NVARCHAR(max):条件(and 1=1)@Json varchar(max) OUTPUT:生成的JSON数据@Limit int =NULL :取前多少条,为null 取所有@ConvertColumns NVARCHAR(max)=null:要转换的列(目前已经排除为nvarchar(max)的列)===*/create PROC...
从snowflake/SQL中的JSON数据子数组创建表是指在Snowflake数据库中,通过使用SQL语句从JSON数据的子数组中创建一个新的表。 具体步骤如下: 首先,使用CREATE TABLE语句创建一个新的表,并定义表的列和数据类型。例如: 首先,使用CREATE TABLE语句创建一个新的表,并定义表的列和数据类型。例如: 接下来,使用INSERT INT...
Json_Modify:更新Json字符串中的属性值,并返回更新的Json字符串。 JSON_MODIFY(column_name, ‘$.json_field’, ‘change_info’); SELECT JSON_MODIFY(json_detail, '$.value1', 11) as json_detailfrom demo_plus.dbo.wm_json_demowhere JSON_VALUE(json_detail, '$.key')= 7;...
First we will see how we should declare a variable and assign a JSON string to it. 首先,我们将看到如何声明变量并为其分配JSON字符串。 DECLARE @vJson AS NVARCHAR(4000) = N'{"EmployeeInfo": { "FirstName": "John", "LastName": "Doe", ...
JSON_MODIFY (Transact-SQL)changes a value in a JSON string. Example In the following example, the query uses both relational and JSON data (stored in a column namedjsonCol) from a table calledPeople: SQL SELECTName, Surname, JSON_VALUE(jsonCol,'$.info.address.PostCode')ASPostCode, JSON_...
CREATE TABLE YourTable ( ID INT, JSONColumn NVARCHAR(MAX) ) 插入包含复杂JSON字符串的行。使用INSERT语句并将JSON字符串分配给JSON列。例如: 代码语言:txt 复制 INSERT INTO YourTable (ID, JSONColumn) VALUES (1, '{"name": "John", "age": 30, "address": {"street": "123 Street", "city":...
(raw:store.bicycle,'price double, color string') bicycleFROMstore_data'{ "price":19.95, "color":"red" }'-- the column returned is an array of string arrays>SELECTfrom_json(raw:store.basket[*],'array<array<string>>') basketsFROMstore_data'[ ["1","2","{\"b\":\"y\",\"...
Create a simple table as a starting point — no JSON column yet. The columns represent the employee number (EMPNO), employee name (ENAME), job title (JOB), manager (MGR), date of hire (HIREDATE), salary (SAL), sales commission (COMM), and department number (DEPTNO). ...