Simulating group_concat MySQL function in Microsoft SQL Server 2005?

sql, sql-server, sql-server-2005, string-aggregation

Solution

No REAL easy way to do this. Lots of ideas out there, though.

Best one I've found:

SELECT table_name, LEFT(column_names , LEN(column_names )-1) AS column_names
FROM information_schema.columns AS extern
CROSS APPLY
(
    SELECT column_name + ','
    FROM information_schema.columns AS intern
    WHERE extern.table_name = intern.table_name
    FOR XML PATH('')
) pre_trimmed (column_names)
GROUP BY table_name, column_names;

Or a version that works correctly if the data might contain characters such as `<`

WITH extern
     AS (SELECT DISTINCT table_name
         FROM   INFORMATION_SCHEMA.COLUMNS)
SELECT table_name,
       LEFT(y.column_names, LEN(y.column_names) - 1) AS column_names
FROM   extern
       CROSS APPLY (SELECT column_name + ','
                    FROM   INFORMATION_SCHEMA.COLUMNS AS intern
                    WHERE  extern.table_name = intern.table_name
                    FOR XML PATH(''), TYPE) x (column_names)
       CROSS APPLY (SELECT x.column_names.value('.', 'NVARCHAR(MAX)')) y(column_names)

Problem

I'm trying to migrate a MySQL-based app over to Microsoft SQL Server 2005 (not by choice, but that's life). In the original app, we used almost entirely ANSI-SQL compliant statements, with one significant exception -- we used MySQL's `group_concat` function fairly frequently. `group_concat`, by the way, does this: given a table of, say, employee names and projects... ``` SELECT empName, projID FROM project_members; ``` returns: ``` ANDY | A100 ANDY | B391 ANDY | X010 TOM | A100 TOM | A510 ``` ... and here's what you get with group_concat: ``` SELECT empName, group_concat(projID SEPARATOR ' / ') FROM project_members GROUP BY empName; ``` returns: ``` ANDY | A100 / B391 / X010 TOM | A100 / A510 ``` So what I'd like to know is: Is it possible to write, say, a user-defined function in SQL Server which emulates the functionality of `group_concat`? I have almost no experience using UDFs, stored procedures, or anything like that, just straight-up SQL, so please err on the side of too much explanation :)

Original source

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