是否有SQL语句可以返回表中列的类型?


当前回答

对于Apache Derby,如下面的答案所示:

select columndatatype from sys.syscolumns
  where referenceid = (
    select tableid from sys.systables
    where tablename = 'YOUR_TABEL_NAME'
    and columnname= 'YOUR_COLUMN_NAME')

其他回答

对于IBM DB2:

SELECT TYPENAME FROM SYSCAT.COLUMNS WHERE TABSCHEMA='your_schema_name' AND TABNAME='your_table_name' AND COLNAME='your_column_name'
SHOW COLUMNS FROM //table_name// ;

它将为您提供关于表中所有列的信息。

对于SQL Server,这个系统存储过程将返回所有表信息,包括列数据类型:

exec sp_help YOURTABLENAME

要在上面的答案的基础上进行构建,获得列数据类型的格式与声明列的格式相同通常是很有用的。

例如,varchar(50), varchar(max), decimal(p, s)。

这允许你这样做:

SELECT 
  [Name]         = c.[name]
, [Type]         = 
    CASE 
      WHEN tp.[name] IN ('varchar', 'char', 'varbinary') THEN tp.[name] + '(' + IIF(c.max_length = -1, 'max', CAST(c.max_length AS VARCHAR(25))) + ')' 
      WHEN tp.[name] IN ('nvarchar','nchar') THEN tp.[name] + '(' + IIF(c.max_length = -1, 'max', CAST(c.max_length / 2 AS VARCHAR(25)))+ ')'      
      WHEN tp.[name] IN ('decimal', 'numeric') THEN tp.[name] + '(' + CAST(c.[precision] AS VARCHAR(25)) + ', ' + CAST(c.[scale] AS VARCHAR(25)) + ')'
      WHEN tp.[name] IN ('datetime2') THEN tp.[name] + '(' + CAST(c.[scale] AS VARCHAR(25)) + ')'
      ELSE tp.[name]
    END
, [RawType]      = tp.[name]
, [MaxLength]    = c.max_length
, [Precision]    = c.[precision]
, [Scale]        = c.scale
, [IsNullable]   = c.is_nullable
FROM sys.tables t 
JOIN sys.schemas s ON t.schema_id = s.schema_id
JOIN sys.columns c ON t.object_id = c.object_id
JOIN sys.types tp ON c.user_type_id = tp.user_type_id
WHERE s.[name] = 'dbo' AND t.[name] = 'MyTable'

由于有些人要求数据类型的精度,我想分享我为此目的而创建的脚本。

SELECT TABLE_NAME As 'TableName'
       COLUMN_NAME As 'ColumnName'
       CONCAT(DATA_TYPE, '(', COALESCE(CHARACTER_MAXIMUM_LENGTH, NUMERIC_PRECISION, DATETIME_PRECISION, ''), IIF(NUMERIC_SCALE <> 0, CONCAT(', ', NUMERIC_SCALE), ''), ')', IIF(IS_NULLABLE = 'YES', ', null', ', not null')) As 'ColumnType'
FROM INFORMATION_SCHEMA.COLUMNS
WHERE -- ...
ORDER BY 'TableName', 'ColumnName'

这并不完美,但在大多数情况下都有效。

使用sql server