Introduction
Many a time, SQL programmers are faced with a requirement to generate report-like resultsets right off of a Transact SQL query. In most cases, the requirement arises from the fact that there are no sufficient tools or in-house expertise to develop tools that can extract the data as a resultset and massage the data in the desired display format. Quite often folks are confused about the potential of breaking relational fundamentals say like First Normal Form or the scalar nature of typed values. (Talking about 1NF violations in a language like SQL which lacks sufficient domain support, allows NULLs and supports duplicates is somewhat ironic to begin with, but that is a topic which requires detailed explanations.)

Concatenating column values or expressions from multiple rows are usually best done in a client side application language, since the string manipulation capabilities of Transact SQL and SQL based DBMSs are somewhat limited. However, you can do these using different approaches in Transact SQL, but avoiding such methods for long term solutions is your best bet.

A core issue

Even though SQL in general deviates considerably from the relational model, its reliance on certain core aspects of relational foundations makes SQL functional and powerful. One such core aspect is the set based nature of SQL expressions (well, multi-sets to be exact, but for the given context let us ignore the issue of duplication). The primary idea is that tables are unordered and hence the resultsets of any query that does not have an explicit ORDER BY clause is unordered as well. In other words, the rows in a resultset of a query do not have a prescribed position, unless it is explicitly specified in the query expression.

On the other hand, a concatenated list is an ordered structure. Each element in the list has a specific position. In fact, concatenation itself is an order-utilizing operation in the sense that values can be prefixed or post fixed to an existing list. So approaches that are loosely called “concatenating row values”, “aggregate concatenation” etc. would have to make sure that some kind of an order, either explicit or implicit, should be specified prior to concatenating the row values. If such an ordering criteria is not provided, the concatenated string would be arbitrary in nature.

Considerations

Generally, requests for row value concatenations often comes in two basic flavors, when the number of rows is known and small (typically less than 10) and when the number of rows is unknown and potentially large. It may be better to look at each of them separately.

In some cases, all the programmer wants is just the list of values from a set of rows. There is no grouping or logical partitioning of values like the list of email addresses separated by a semicolon or some such. In such situations, the approaches can be the same except the join conditions may vary. Minor variations of the examples list on this page illustrate such solutions as well.

For the purpose of this article the Products table from Northwind database is used to illustrate column value concatenations with a grouping column. Northwind is a sample database in SQL Server 2000 default installations. You can download a copy from from the Microsoft Downloads Consider the resultset produced by the following query:

    SELECT CategoryId, ProductName 
      FROM Northwind..Products ;
  
    CategoryId  ProductName                              
    ----------- ---------------------------------------- 
    1           Chai
    1           Chang
    ...
    2           Aniseed Syrup
    2           Chef Anton's Cajun Seasoning
    ...
    ...
    8           Spegesild
    
    (77 row(s) affected)

The goal is to return a resultset with two columns one with the Category Identifier and the other with a concatenated list of all the Product Names separated by a delimiting character, say a comma for instance.

    CategoryId  Product List
    ----------- -----------------------------------------------------------------------------
    1           Chai, Chang, Chartreuse verte, Côte de Blaye, ...
    2           Aniseed Syrup, Chef Anton's Cajun Seasoning, ...
    3           Chocolade, Gumbär Gummibärchen, Maxilaku, ...
    4           Camembert Pierrot, Flotemysost, Geitost, Gorgonzola Telino, ...
    5           Filo Mix, Gnocchi di nonna Alice, Gustaf's Knäckebröd, ...
    6           Alice Mutton, Mishi Kobe Niku, Pâté chinois, ...
    7           Longlife Tofu, Manjimup Dried Apples, Rössle Sauerkraut, ...
    8           Boston Crab Meat, Carnarvon Tigers, Escargots de Bourgogne, ...
    
    (8 row(s) affected)
 

Concatenating values when the number of items is small and known upfront

When the number of rows are small and almost known upfront, it is easier to generate the code. One common approach with a small set of finite rows it the pivoting method. Here is an example where only first four alphabetically sorted product names per categoryid is retrieved:

    SELECT CategoryId,
           MAX( CASE seq WHEN 1 THEN ProductName ELSE '' END ) + ', ' +
           MAX( CASE seq WHEN 2 THEN ProductName ELSE '' END ) + ', ' +
           MAX( CASE seq WHEN 3 THEN ProductName ELSE '' END ) + ', ' +
           MAX( CASE seq WHEN 4 THEN ProductName ELSE '' END )
      FROM ( SELECT p1.CategoryId, p1.ProductName,
                    ( SELECT COUNT(*) 
                        FROM Northwind.dbo.Products p2
                       WHERE p2.CategoryId = p1.CategoryId
                         AND p2.ProductName <= p1.ProductName )
               FROM Northwind.dbo.Products p1 ) D ( CategoryId, ProductName, seq )
     GROUP BY CategoryId ;

The idea above is to create a expression inside the correlated subquery that produces a rank (seq) based on the product names and then use it in the outer query. Using common table expressions and the ROW_NUMBER() function, you can re-write this as:

; WITH CTE ( CategoryId, ProductName, seq )
    AS ( SELECT p1.CategoryId, p1.ProductName,
                ROW_NUMBER() OVER ( PARTITION BY CategoryId ORDER BY ProductName )
           FROM Northwind.dbo.Products p1 )
    SELECT CategoryId,
           MAX( CASE seq WHEN 1 THEN ProductName ELSE '' END ) + ', ' +
           MAX( CASE seq WHEN 2 THEN ProductName ELSE '' END ) + ', ' +
           MAX( CASE seq WHEN 3 THEN ProductName ELSE '' END ) + ', ' +
           MAX( CASE seq WHEN 4 THEN ProductName ELSE '' END )
      FROM CTE 
     GROUP BY CategoryId ;

Note that ROW_NUMBER() is a newly introduced feature in SQL 2005. If you are using any previous versions, you will have to use the subquery approach (You can also use a self-join, to write it a bit differently). Using the recently introduced PIVOT operator, you can write the above as following :

    SELECT CategoryId, 
           "1" + ', ' + "2" + ', ' + "3" + ', ' + "4" AS Product_List
      FROM ( SELECT CategoryId, ProductName, 
                    ROW_NUMBER() OVER (PARTITION BY CategoryId ORDER BY ProductName)
               FROM Northwind.dbo.Products ) P ( CategoryId, ProductName, seq )
     PIVOT ( MAX( ProductName ) FOR seq IN ( "1", "2", "3", "4" ) ) AS P_ ;

Not only the syntax appears a bit confusing, it does not appear to offer anything functionally beyond the CASE approach above. However, in rare situations, it could come in handy.

Concatenating values when the number of items is not known

When the number of items that are to be concatenated is not known upfront, the code can become a bit more demanding. The new features in SQL 2005 make some of the approaches a bit easy. For instance, the recursive common table expressions (CTEs) and the FOR XML PATH('') syntax makes the server do the hard work behind the concatenation leaving the programmer to deal with the presentation issues. The examples below make this point obvious.

Recursive CTE methods

The idea behind this method is from a newsgroup posting by Vadim Tropashko similar to the ideas behind generating a materialized path for hierarchies.

    WITH CTE ( CategoryId, product_list, product_name, length ) 
          AS ( SELECT CategoryId, CAST( '' AS VARCHAR(8000) ), CAST( '' AS VARCHAR(8000) ), 0
                 FROM Northwind..Products
                GROUP BY CategoryId
                UNION ALL
               SELECT p.CategoryId, CAST( product_list + 
                      CASE WHEN length = 0 THEN '' ELSE ', ' END + ProductName AS VARCHAR(8000) ), 
                      CAST( ProductName AS VARCHAR(8000)), length + 1
                 FROM CTE c
                INNER JOIN Northwind..Products p
                   ON c.CategoryId = p.CategoryId
                WHERE p.ProductName > c.product_name )
    SELECT CategoryId, product_list 
      FROM ( SELECT CategoryId, product_list, 
                    RANK() OVER ( PARTITION BY CategoryId ORDER BY length DESC )
               FROM CTE ) D ( CategoryId, product_list, rank )
     WHERE rank = 1 ;

The CASE in the recursive part of the CTE is used to eliminate the initial comma and you can use RIGHT or the SUBSTRING functions to substitute it. Also, this may not be the best performing option, however certain additional tuning could be done to make them suitable for medium sized datasets.

Another approach using recursive common table expressions was sent in by Anub Philip, an Engineer from Sathyam Computers that uses separate common table expressions for the anchor and recursive parts.

    WITH Ranked ( CategoryId, rnk, ProductName )  
             AS ( SELECT CategoryId,
                         ROW_NUMBER() OVER( PARTITION BY CategoryId ORDER BY CategoryId ),
                         CAST( ProductName AS VARCHAR(8000) ) 
                    FROM Northwind..Products),
   AnchorRanked ( CategoryId, rnk, ProductName )  
             AS ( SELECT CategoryId, rnk, ProductName 
                    FROM Ranked
                   WHERE rnk = 1 ),
    RecurRanked ( CategoryId, rnk, ProductName ) 
             AS ( SELECT CategoryId, rnk, ProductName 
                    FROM AnchorRanked
                   UNION ALL 
                  SELECT Ranked.CategoryId, Ranked.rnk,
                         RecurRanked.ProductName + ', ' + Ranked.ProductName
                    FROM Ranked
                   INNER JOIN RecurRanked 
                      ON Ranked.CategoryId = RecurRanked.CategoryId 
                     AND Ranked.rnk = RecurRanked.rnk + 1 )
    SELECT CategoryId, MAX( ProductName ) 
      FROM RecurRanked
     GROUP BY CategoryId;

On an initial glance, this query may seem a bit expensive in comparison, however the reader is encouraged check the execution plans and make any additional tweaks as needed.

The blackbox XML methods

An example for string concatenation using FOR XML clause with PATH mode is detailed below. It was initially posted by Eugene Kogan later became common in public newsgroups.

    SELECT p1.CategoryId,
          ( SELECT ProductName + ',' 
              FROM Northwind.dbo.Products p2
             WHERE p2.CategoryId = p1.CategoryId
             ORDER BY ProductName
               FOR XML PATH('') ) AS Products
      FROM Northwind.dbo.Products p1
     GROUP BY CategoryId ;

Again, the similar approach originally found in the beta newsgroups, using CROSS APPLY operator.

    SELECT DISTINCT CategoryId, ProductNames
      FROM Products p1
     CROSS APPLY ( SELECT ProductName + ',' 
                     FROM Products p2
                    WHERE p2.CategoryId = p1.CategoryId 
                    ORDER BY ProductName 
                      FOR XML PATH('') )  D ( ProductNames )

You may notice a comma at the end of the concatenated string, which you can remove using a STUFF, SUBSTRING or LEFT function. While the above methods are deemed reliable by many at the time of writing, there is no guarantee that it will stay that way given the internal workings and evaluation rules of FOR XML PATH() expression in correlated subqueries are not well documented.

Using Common Language Runtime

Though this article is about approaches using Transact SQL, this section is included due to the popularity of CLR aggregates in SQL 2005. Not only it empowers the CLR programmer with new options for database development, in some cases, they work at least as well as native Transact SQL approaches.

If you are familiar with .NET languages, SQL 2005 offers a convenient way to create user defined aggregate functions using C#, VB.NET or similar languages that is supported by the Common Language Runtime (CLR). Here is an example of a string concatenate aggregate function written using C#.

    using System;
    using System.Collections.Generic;
    using System.Data.SqlTypes;
    using System.IO;
    using Microsoft.SqlServer.Server;

    [Serializable]
    [SqlUserDefinedAggregate(Format.UserDefined,  MaxByteSize=8000)]
    public struct strconcat : IBinarySerialize{
        private List values;

        public void Init()    {
            this.values = new List();
        }

        public void Accumulate(SqlString value)    {
            this.values.Add(value.Value);
        }

        public void Merge(strconcat value)    {
            this.values.AddRange(value.values.ToArray());
        }

        public SqlString Terminate()    {
            return new SqlString(string.Join(", ", this.values.ToArray()));
        }

        public void Read(BinaryReader r)    {
            int itemCount = r.ReadInt32();
            this.values = new List(itemCount);
            for (int i = 0; i <= itemCount - 1; i++)    {
                this.values.Add(r.ReadString());
            }
        }

        public void Write(BinaryWriter w)    {
            w.Write(this.values.Count);
            foreach (string s in this.values)      {
                w.Write(s);
            }
        }
    }

Once you build and deploy this assembly on the server, you should be able to execute your concatenation query as:

    SELECT CategoryId, 
           dbo.strconcat(ProductName) 
      FROM Products 
     GROUP BY CategoryId ; 

If you are a total newbie on CLR languages, and would like to learn more about developing database solutions using CLR languages, consider starting at Introduction to Common Language Runtime (CLR) Integration

Scalar UDF with recursion

Recursive functions in t-SQL have a drawback that the maximum nesting level is 32. So this approach is applicable only for smaller datasets, especially when the number of items within a group, that needs to be concatenated, is less than 32.

    CREATE FUNCTION udf_recursive ( @cid INT, @i INT ) 
    RETURNS VARCHAR(8000) AS BEGIN 
        DECLARE @r VARCHAR(8000), @l VARCHAR(8000) 
        SELECT @i = @i - 1,  @r = ProductName + ', ' 
          FROM Products p1 
         WHERE CategoryId = @cid 
           AND @i = ( SELECT COUNT(*) FROM Products p2 
                       WHERE p2.CategoryId = p1.CategoryId 
                         AND p2.ProductName <= p1.ProductName ) ; 
        IF @i > 0 BEGIN 
              EXEC @l = dbo.udf_recursive @cid, @i ;
              SET @r =  @l + @r ;
    END 
    RETURN @r ;
    END 

This function can be invoked as follows:

    SELECT CategoryId, 
           dbo.udf_recursive( CategoryId, COUNT(ProductName) ) 
      FROM Products 
     GROUP BY CategoryId ; 

Table valued UDF with a WHILE loop

This approach is based on the idea by Linda Wierzbecki where a table variable with three columns is used within a table valued UDF. The first column represents the group, second represents the currently processing value within a group and the third represents the concatenated list of values.

    CREATE FUNCTION udf_tbl_Concat() RETURNS @t TABLE(
            CategoryId INT, 
            Product VARCHAR(40), 
            list VARCHAR(8000) ) 
    BEGIN 
     INSERT @t (CategoryId, Product, list) 
     SELECT CategoryId, MIN(ProductName),  MIN(ProductName) 
       FROM Products 
      GROUP BY CategoryId 
    WHILE ( SELECT COUNT(Product) FROM @t ) > 0 BEGIN 
        UPDATE t 
           SET list = list + COALESCE(
                         ( SELECT ', ' + MIN( ProductName ) 
                             FROM Products 
                            WHERE Products.CategoryId = t.CategoryId 
                              AND Products.ProductName > t.Product), ''), 
               Product = ( SELECT MIN(ProductName) 
                             FROM Products 
                            WHERE Products.CategoryId = t.CategoryId 
                              AND Products.ProductName > t.Product ) 
          FROM @t t END 
    RETURN 
    END 

The usage of the above function can be like:

    SELECT CategoryId, list AS Products
      FROM udf_tbl_Concat() ; 

Dynamic SQL

This approach is a variation of the kludge often known using the nickname as dynamic cross tabulation.

This approach is a variation of the kludge often known using the nickname as dynamic cross tabulation. There is enough literature out there which demonstrates the drawbacks and implications of using Dynamic SQL. A popular one, at least from Transact SQL programmer’s perspective, is Erland's Curse and Blessings of Dynamic SQL. The Dynamic SQL approaches can be developed based on creating a Transact SQL query string based on the number of groups and then use a series of CASE expressions or ROW_NUMBER() function to pivot the data for concatenation.

    DECLARE @r VARCHAR(MAX), @n INT, @i INT 
    SELECT @i = 1,
           @r = 'SELECT CategoryId, ' + CHAR(13), 
           @n = (SELECT TOP 1 COUNT( ProductName ) 
                   FROM Products 
                  GROUP BY CategoryId 
                  ORDER BY COUNT( ProductName ) DESC ) ;	
    WHILE @i <= @n BEGIN 
	    SET @r = @r + 
	    CASE WHEN @i = 1  
	         THEN 'MAX( CASE Seq WHEN ' + CAST( @i AS VARCHAR ) + ' 
                                 THEN ProductName 
				                 ELSE SPACE(0) END ) + ' + CHAR(13) 
      	     WHEN @i = @n 
             THEN 'MAX( CASE Seq WHEN ' + CAST( @i AS VARCHAR ) + ' 
                                 THEN '', '' + ProductName 
                                 ELSE SPACE(0) END ) ' + CHAR(13) 
             ELSE 'MAX( CASE Seq WHEN ' + CAST( @i AS VARCHAR ) + ' 
                                 THEN '', '' + ProductName 
                                 ELSE SPACE(0) END ) + ' + CHAR(13)  
	    END ;
 	    SET @i = @i + 1 ;
    END 
    SET @r = @r + ' 
    FROM ( SELECT CategoryId, ProductName, 
                  ROW_NUMBER() OVER ( PARTITION BY CategoryId ORDER BY ProductName )
             FROM Products p ) D ( CategoryId, ProductName, Seq ) 
           GROUP BY CategoryId;' 
    EXEC( @r ) ;

The Cursor approach

The drawbacks of rampant usage of cursors are well-known among the Transact SQL community. Given the fact that they are generally resource intensive, procedural and inefficient, one should strive to avoid cursors or loop based solutions in general Transact SQL programming.

    DECLARE @tbl TABLE (id INT PRIMARY KEY, list VARCHAR(8000)) 
    SET NOCOUNT ON 
    DECLARE @c INT, @p VARCHAR(8000), @cNext INT, @pNext VARCHAR(40) 
    DECLARE c CURSOR FOR 
        SELECT CategoryId, ProductName 
          FROM Products 
         ORDER BY CategoryId, ProductName ;
        OPEN c ;
        FETCH NEXT FROM c INTO @cNext, @pNext ;
        SET @c = @cNext ;
        WHILE @@FETCH_STATUS = 0 BEGIN 
             IF @cNext > @c BEGIN 
                  INSERT @tbl SELECT @c, @p ;
                  SELECT @p = @PNext, @c = @cNext ;
             END ELSE 
                  SET @p = COALESCE(@p + ',', SPACE(0)) + @pNext ;
             FETCH NEXT FROM c INTO @cNext, @pNext 
        END 
        INSERT @tbl SELECT @c, @p ;
        CLOSE c ;
    DEALLOCATE c ;
    SELECT * FROM @tbl ;

Non-reliable approaches

This section details a couple of notorious methods often publicized by some in public forums. The problem with these methods is that they rely on the physical implementation model; changes in indexes, statistics etc or even a change of a simple expression in the SELECT list or ORDER BY clause can change the output. Also these are undocumented, unsupported and unreliable to the point where one can consistently demonstrate failures. Therefore these methods are not at all recommended for production mode systems.

Scalar UDF with t-SQL update extension

The usage of an expression that involves a column, a variable and an expression in the SET clause in an UPDATE statement rarely appear intuitive. However, in general, the optimizer often seems to process these values in the order of materialization, either in the internal work tables or any other storage structures.

    CREATE FUNCTION udf_update_concat (@CategoryId INT) 
        RETURNS VARCHAR(MAX) AS 
    BEGIN 
    DECLARE @t TABLE(p VARCHAR(40));
    DECLARE @r VARCHAR(MAX) ;
        SET @r = SPACE(0) ;
        INSERT @t ( p ) SELECT ProductName FROM Products 
                         WHERE CategoryId = @CategoryId ;
        IF @@ROWCOUNT > 0 
            UPDATE @t 
               SET @r = @r + p + ',' ;
        RETURN(@r) 
    END 

Here is how to use this function:

    SELECT CategoryId, dbo.udf_update_concat(CategoryId) 
      FROM Products 
     GROUP BY CategoryId ; 

Again, it is important to consider that lack of physical independence that is being exploited here before using or recommending this as a usable and meaningful solution.

Scalar UDF with variable concatenation in SELECT

This is an approach purely dependent on the physical implementation and internal access paths. Before using this approach, make sure to refer to the relevant knowledgebase article.

    CREATE FUNCTION dbo.udf_select_concat ( @c INT )
    RETURNS VARCHAR(MAX) AS BEGIN
    DECLARE @p VARCHAR(MAX) ;
           SET @p = '' ;
        SELECT @p = @p + ProductName + ','
          FROM Products
         WHERE CategoryId = @c ;
    RETURN @p
    END

And, as for its usage:

    SELECT CategoryId, dbo.udf_select_concat( CategoryId )
      FROM Products
     GROUP BY CategoryId ;

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