Find columns with special characters

Standard

Problem

im specialImagine a database where you want to know how many times a certain column contains a special character. The reason I had to do this was because I needed to know the impact of an export interface which wasn’t working properly with special characters.

But as lazy as I am as it comes to do repetitive tasks, I had to find a way I could easily get all columns with special characters in a data set without a lot of hassle.

The solution

Fortunately for me I can use the internal INFORMATION views of a database in SQL Server to get all the columns with their table, schema and type of data. Because this database only used varchar columns for saving text data I only had to search for this data type. You can easily extend the selecting by adding the neccesary types like TEXT, NVARCHAR etc.

To create the script I had to accomplish the following things:

  1. Retrieve all the colums that could contain text
  2. Set up a pattern to check the columns with
  3. Loop through the columns
  4. In every loop save the results
  5. Make up a data set of the data retrieved

I eventually got to this script:

-- Replace the mydatabase with the name of your database 
USE [mydatabase] 

-- Delete possible present temporary tables 
IF Object_id('tempdb..#columns') IS NOT NULL 
  DROP TABLE #columns 

IF Object_id('tempdb..#results') IS NOT NULL 
  DROP TABLE #results 

IF Object_id('tempdb..#rows') IS NOT NULL 
  DROP TABLE #rows 

-- Create a table for holding all the columns 
CREATE TABLE #columns 
  ( 
     id            INT NOT NULL PRIMARY KEY IDENTITY(1, 1), 
     database_name VARCHAR(100), 
     schema_name   VARCHAR(50), 
     table_name    VARCHAR(200), 
     column_name   VARCHAR(200), 
     position      INT 
  ) 

-- Create a table for holding the results 
CREATE TABLE #results 
  ( 
     database_name VARCHAR(100), 
     schema_name   VARCHAR(50), 
     table_name    VARCHAR(200), 
     column_name   VARCHAR(200), 
     count         INT 
  ) 

-- Declare the variables needed 
DECLARE @max INT, 
        @cnt INT 
DECLARE @sql     NVARCHAR(max), 
        @pattern VARCHAR(200) 

-- Get all the columns 
INSERT INTO #columns 
SELECT table_catalog, 
       table_schema, 
       table_name, 
       column_name, 
       ordinal_position 
FROM   information_schema.columns 
WHERE  data_type = 'varchar' 
ORDER  BY table_catalog, 
          table_name, 
          ordinal_position 

-- Get the minimum id and max that are needed for the loop 
SELECT @cnt = Min(id) 
FROM   #columns 

SELECT @max = Max(id) 
FROM   #columns 

--Setup the pattern 
SELECT @pattern = 'ëïöüäéíóáèìòàËÏÖÄÉÍÓÁÈÌÒÀ' 

-- Make sure the @sql variable is empty 
SELECT @sql = '' 

-- Start loop 
WHILE( @cnt < ��@max ) 
  BEGIN 
      -- Setup the sql statement 
      SELECT @sql = 'INSERT INTO #results SELECT ''' + database_name + ''', ''' 
                    + schema_name + ''', ''' + table_name + ''', ''' 
                    + column_name + ''', COUNT(1) AS count FROM [' + database_name + '].[' 
                    + schema_name + '].[' + table_name + '] WHERE [' 
                    + column_name 
                    + '] COLLATE Latin1_General_BIN2 LIKE ''%[' 
                    + @pattern + ']%'' ESCAPE ''E'' ' 
      FROM   #columns 
      WHERE  id = @cnt 

      -- Execute the sql statement 
      EXEC Sp_executesql 
        @sql 

      -- Increae the counter 
      SELECT @cnt += 1 
  END 

-- Select the data 
SELECT results.database_name, 
       results.schema_name, 
       results.table_name, 
       results.column_name, 
       results.count AS 'count_results' 
FROM   #results results 
WHERE  results.count >= 1

This might take a while when you need to search through a lot of columns and records.  When the script you will get a result like below:

results specialcharacters

results specialcharacters

 

 

 

 

 

 

 

The pattern can contain any character that you want. I only searched for some of the most common special characters but any character will do.

I hope you find this post helpfull and I appreciate any comment.