Approach
The following approach can be used to de-duplicate a delimited list of values.
- Use the
REPLACE() function to convert different delimiters into the same delimiter.
- Use the
REPLACE() function to inject XML closing and opening tags to create an XML fragment
- Use the
CAST(expr AS XML) function to convert the above fragment into the XML data type
- Use
OUTER APPLY to apply the table-valued function nodes() to split the XML fragment into its constituent XML tags. This returns each XML tag on a separate row.
- Extract just the value from the XML tag using the
value() function, and returns the value using the specified data type.
- Append a comma after the above-mentioned value.
- Note that these values are returned on separate rows. The usage of the
DISTINCT keyword now removes duplicate rows (i.e. values).
- Use the
FOR XML PATH('') clause to concatenate the values across multiple rows into a single row.
Query
Putting the above approach in query form:
SELECT DISTINCT PivotedTable.PivotedColumn.value('.','nvarchar(max)') + ','
FROM (
-- This query returns the following in theDataXml column:
-- <tag>test1</tag><tag>test2</tag><tag>test1</tag><tag>test2</tag><tag>test3</tag><tag>test4</tag><tag>test4</tag><tag>test4</tag>
-- i.e. it has turned the original delimited data into an XML fragment
SELECT
DataTable.DataColumn AS DataRaw
, CAST(
'<tag>'
-- First replace commas with pipes to have only a single delimiter
-- Then replace the pipe delimiters with a closing and opening tag
+ replace(replace(DataTable.DataColumn, ',','|'), '|','</tag><tag>')
-- Add a final set of closing tags
+ '</tag>'
AS XML) AS DataXml
FROM ( SELECT 'test1,test2,test1|test2,test3|test4,test4|test4' AS DataColumn) AS DataTable
) AS x
OUTER APPLY DataXml.nodes('tag') AS PivotedTable(PivotedColumn)
-- Running the query without the following line will return the data in separate rows
-- Running the query with the following line returns the rows concatenated, i.e. it returns:
-- test1,test2,test3,test4,
FOR XML PATH('')
Input & Result
Given the input:
test1,test2,test1|test2,test3|test4,test4|test4
The above query will return the result:
test1,test2,test3,test4,
Notice the trailing comma at the end. I'll leave it as an exercise to you to remove that.
EDIT: Count of Duplicates
OP requested in a comment "how do i get t5he count of duplicates as well? in a seperate column".
The simplest way would be to use the above query but remove the last line FOR XML PATH(''). Then, counting all values and distinct values returned by the SELECT expression in the above query (i.e. PivotedTable.PivotedColumn.value('.','nvarchar(max)')). The difference between the count of all values and the count of distinct values is the count of duplicate values.
SELECT
COUNT(PivotedTable.PivotedColumn.value('.','nvarchar(max)')) AS CountOfAllValues
, COUNT(DISTINCT PivotedTable.PivotedColumn.value('.','nvarchar(max)')) AS CountOfUniqueValues
-- The difference of the previous two counts is the number of duplicate values
, COUNT(PivotedTable.PivotedColumn.value('.','nvarchar(max)'))
- COUNT(DISTINCT PivotedTable.PivotedColumn.value('.','nvarchar(max)')) AS CountOfDuplicateValues
FROM (
-- This query returns the following in theDataXml column:
-- <tag>test1</tag><tag>test2</tag><tag>test1</tag><tag>test2</tag><tag>test3</tag><tag>test4</tag><tag>test4</tag><tag>test4</tag>
-- i.e. it has turned the original delimited data into an XML fragment
SELECT
DataTable.DataColumn AS DataRaw
, CAST(
'<tag>'
-- First replace commas with pipes to have only a single delimiter
-- Then replace the pipe delimiters with a closing and opening tag
+ replace(replace(DataTable.DataColumn, ',','|'), '|','</tag><tag>')
-- Add a final set of closing tags
+ '</tag>'
AS XML) AS DataXml
FROM ( SELECT 'test1,test2,test1|test2,test3|test4,test4|test4' AS DataColumn) AS DataTable
) AS x
OUTER APPLY DataXml.nodes('tag') AS PivotedTable(PivotedColumn)
For the same input shown above, the output of this query is:
CountOfAllValues CountOfUniqueValues CountOfDuplicateValues
---------------- ------------------- ----------------------
8 4 4