Many a time we come across a scenario where we want to fetch data from all over database
tables based on delimited some string. It is very difficult and time to consume to write different queries based on every table/column to quickly search for data all over the SQL Database. But I would prefer passing the delimited string to the stored procedure and fetching data with table and column names.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 | DECLARE @SearchStr nvarchar(max) SET @SearchStr = '45206' CREATE TABLE #Results (ColumnName nvarchar(max), ColumnValue nvarchar(max)) SET NOCOUNT ON DECLARE @TableName nvarchar(max), @ColumnName nvarchar(max), @SearchStr2 nvarchar(max) SET @TableName = '' SET @SearchStr2 = QUOTENAME('%' + @SearchStr + '%','''') WHILE @TableName IS NOT NULL BEGIN SET @ColumnName = '' SET @TableName = ( SELECT MIN(QUOTENAME(TABLE_SCHEMA) + '.' + QUOTENAME(TABLE_NAME)) FROM INFORMATION_SCHEMA.TABLES WHERE TABLE_TYPE = 'BASE TABLE' AND QUOTENAME(TABLE_SCHEMA) + '.' + QUOTENAME(TABLE_NAME) > @TableName AND OBJECTPROPERTY( OBJECT_ID( QUOTENAME(TABLE_SCHEMA) + '.' + QUOTENAME(TABLE_NAME) ), 'IsMSShipped' ) = 0 ) WHILE (@TableName IS NOT NULL) AND (@ColumnName IS NOT NULL) BEGIN SET @ColumnName = ( SELECT MIN(QUOTENAME(COLUMN_NAME)) FROM INFORMATION_SCHEMA.COLUMNS WHERE TABLE_SCHEMA = PARSENAME(@TableName, 2) AND TABLE_NAME = PARSENAME(@TableName, 1) AND DATA_TYPE IN ('char', 'varchar', 'nchar', 'nvarchar', 'int', 'decimal') AND QUOTENAME(COLUMN_NAME) > @ColumnName ) IF @ColumnName IS NOT NULL BEGIN INSERT INTO #Results EXEC ( 'SELECT ''' + @TableName + '.' + @ColumnName + ''', LEFT(' + @ColumnName + ', 3630) FROM ' + @TableName + ' (NOLOCK) ' + ' WHERE ' + @ColumnName + ' LIKE ' + @SearchStr2 ) END END END SELECT ColumnName, ColumnValue FROM #Results DROP TABLE #Results |
I think you can fulfill your need. You may follow this post.
Quickly Search For Data All Over Database
The article was published on May 17, 2018 @ 10:21 AM
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