How to concatenate text from multiple rows into a single text string in SQL Server? [Answered]

Query explanation:

Consider a database table holding names, with three rows:

Peter
Paul
Mary

Is there an easy way to turn this into a single string of Peter, Paul, Mary?

Answer #1:

If you are on SQL Server 2017 or Azure, then go to this answer.

I had a similar issue when I was trying to join two tables with one-to-many relationships. In SQL 2005 I found that XML PATH method can handle the concatenation of the rows very easily.

If there is a table called STUDENTS

SubjectID       StudentName
----------      -------------
1               Mary
1               John
1               Sam
2               Alaina
2               Edward

Result I expected was:

SubjectID       StudentName
----------      -------------
1               Mary, John, Sam
2               Alaina, Edward

I used the following T-SQL:

SELECT Main.SubjectID,
       LEFT(Main.Students,Len(Main.Students)-1) As "Students"
FROM
    (
        SELECT DISTINCT ST2.SubjectID, 
            (
                SELECT ST1.StudentName + ',' AS [text()]
                FROM dbo.Students ST1
                WHERE ST1.SubjectID = ST2.SubjectID
                ORDER BY ST1.SubjectID
                FOR XML PATH ('')
            ) [Students]
        FROM dbo.Students ST2
    ) [Main]

You can do the same thing in a more compact way if you can concat the commas at the beginning and use substring to skip the first one so you don’t need to do a sub-query:

SELECT DISTINCT ST2.SubjectID, 
    SUBSTRING(
        (
            SELECT ','+ST1.StudentName  AS [text()]
            FROM dbo.Students ST1
            WHERE ST1.SubjectID = ST2.SubjectID
            ORDER BY ST1.SubjectID
            FOR XML PATH ('')
        ), 2, 1000) [Students]
FROM dbo.Students ST2

Answer #2:

SQL Server 2017+ and SQL Azure: STRING_AGG

Starting with the next version of SQL Server, we can finally concatenate across rows without having to resort to any variable or XML witchery.

STRING_AGG (Transact-SQL)

Without grouping

SELECT STRING_AGG(Name, ', ') AS Departments
FROM HumanResources.Department;

With grouping:

SELECT GroupName, STRING_AGG(Name, ', ') AS Departments
FROM HumanResources.Department
GROUP BY GroupName;

With grouping and sub-sorting

SELECT GroupName, STRING_AGG(Name, ', ') WITHIN GROUP (ORDER BY Name ASC) AS Departments
FROM HumanResources.Department
GROUP BY GroupName;

Answer #3:

This answer may return unexpected results For consistent results, use one of the FOR XML PATH methods detailed in other answers.

Use COALESCE:

DECLARE @Names VARCHAR(8000) 
SELECT @Names = COALESCE(@Names + ', ', '') + Name 
FROM People

Just some explanation (since this answer seems to get relatively regular views):

• Coalesce is really just a helpful cheat that accomplishes two things:

1) No need to initialize @Names with an empty string value.

2) No need to strip off an extra separator at the end.

• The solution above will give incorrect results if a row has a NULL Name value (if there is a NULL, the NULL will make @Names NULL after that row, and the next row will start over as an empty string again. Easily fixed with one of two solutions:

DECLARE @Names VARCHAR(8000) 
SELECT @Names = COALESCE(@Names + ', ', '') + Name
FROM People
WHERE Name IS NOT NULL

or:

DECLARE @Names VARCHAR(8000) 
SELECT @Names = COALESCE(@Names + ', ', '') + 
    ISNULL(Name, 'N/A')
FROM People

Depending on what behavior you want (the first option just filters NULLs out, the second option keeps them in the list with a marker message [replace ‘N/A’ with whatever is appropriate for you]).

Answer #4:

One method not yet shown via the XML data() command in SQL Server is:

Assume a table called NameList with one column called FName,

SELECT FName + ', ' AS 'data()'
FROM NameList
FOR XML PATH('')

returns:

"Peter, Paul, Mary, "

Only the extra comma must be dealt with.

As adopted from @NReilingh’s comment, you can use the following method to remove the trailing comma. Assuming the same table and column names:

STUFF(REPLACE((SELECT '#!' + LTRIM(RTRIM(FName)) AS 'data()' FROM NameList
FOR XML PATH('')),' #!',', '), 1, 2, '') as Brands

Answer #5:

In SQL Server 2005

SELECT Stuff(
  (SELECT N', ' + Name FROM Names FOR XML PATH(''),TYPE)
  .value('text()[1]','nvarchar(max)'),1,2,N'')

---

In SQL Server 2016

you can use the FOR JSON syntax

i.e.

SELECT per.ID,
Emails = JSON_VALUE(
   REPLACE(
     (SELECT _ = em.Email FROM Email em WHERE em.Person = per.ID FOR JSON PATH)
    ,'"},{"_":"',', '),'$[0]._'
) 
FROM Person per

And the result will become

Id  Emails
1   abc@gmail.com
2   NULL
3   def@gmail.com, xyz@gmail.com

This will work even your data contains invalid XML characters

the '"},{"_":"' is safe because if you data contain '"},{"_":"', it will be escaped to "},{\"_\":\"

You can replace ', ' with any string separator.

Answer #6:

Use COALESCE – Learn more from here

For an example:

102

103

104

Then write the below code in SQL Server,

Declare @Numbers AS Nvarchar(MAX) -- It must not be MAX if you have few numbers
SELECT  @Numbers = COALESCE(@Numbers + ',', '') + Number
FROM   TableName where Number IS NOT NULL

SELECT @Numbers

The output would be:

102,103,104

Answer #7:

PostgreSQL arrays are awesome. Example:

Create some test data:

postgres=# \c test
You are now connected to database "test" as user "hgimenez".
test=# create table names (name text);
CREATE TABLE
test=# insert into names (name) values ('Peter'), ('Paul'), ('Mary');
INSERT 0 3
test=# select * from names;
 name
-------
 Peter
 Paul
 Mary
(3 rows)

Aggregate them in an array:

test=# select array_agg(name) from names;
 array_agg
-------------------
 {Peter,Paul,Mary}
(1 row)

Convert the array to a comma-delimited string:

test=# select array_to_string(array_agg(name), ', ') from names;
 array_to_string
-------------------
 Peter, Paul, Mary
(1 row)

DONE

Since PostgreSQL 9.0 it is even easier, quoting from deleted answer by “horse with no name”:

select string_agg(name, ',') 
from names;

Hope you learned something from this post. The primary source of this article is StackOverflow.

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