Converting Vertical Tables to Horizontal Tables in SQL Using XML PATH

SQL Vertical Table to Horizontal Query

SQL is a powerful and versatile language used for managing relational databases. One common use case in SQL is to query data from multiple tables that have a relationship with each other. In this post, we will explore how to convert a vertical table (a table where each row represents a single record) into a horizontal table (a table where each column represents a field or attribute).

Understanding the Problem

The problem presented in the Stack Overflow question is as follows:

We have two tables: dat_desk_employee and dat_desk. The dat_desk_employee table contains employee IDs and corresponding desk numbers, represented as foreign keys (fk_desk and fk_employee, respectively).
The goal is to write an SQL query that will return a horizontal representation of the data from dat_desk_employee, where each row represents an employee and their assigned desks.

Current Query

The provided query in the question attempts to solve this problem but has an error:

select fk_employee,
    stuff((SELECT distinct ', ' + cast(fk_desk as varchar(10))
    from dat_desk_employee e
    where e.fk_employee = e.fk_employee
    FOR XML PATH('')),1,1,'')
from dat_desk_employee e
group by fk_employee
order by fk_employee asc

This query uses the stuff function to concatenate all distinct values of fk_desk into a single string separated by commas. However, the inner select statement has the same alias (e.fk_employee) for both the outer and inner queries.

Corrected Query

The corrected query should use a different alias in the inner query:

select fk_employee,
    stuff((SELECT distinct ', ' + cast(fk_desk as varchar(10))
    from dat_desk_employee e2  -- changed 'e' to 'e2'
    where e2.fk_employee = e.fk_employee
    FOR XML PATH('')),1,1,'')
from dat_desk_employee e
group by fk_employee
order by fk_employee asc

In the corrected query, e2 is used as an alias for the inner table, avoiding the conflict with the outer query’s alias (e).

Explanation

To understand how this query works, let’s break down its components:

SELECT distinct ', ' + cast(fk_desk as varchar(10)): This selects all distinct values of fk_desk and concatenates them into a string separated by commas. The cast function is used to convert the fk_desk values from an integer data type to a varchar data type, which allows us to concatenate strings.
FOR XML PATH(''): This specifies that we want to use the XML PATH function to aggregate the distinct values into a single string. The empty string ' indicates that we want to include each value in the aggregated string.
stuff(...): This is the aggregation function used to concatenate all values from the inner query into a single string.

Creating Sample Data

To test the corrected query, let’s create some sample data:

create table dat_desk_employee (fk_desk int, fk_employee int);
insert into dat_desk_employee values
(1000, 2),(1000, 10),(1000, 23),(1000, 34),(1000, 55),
(1001, 3),(1001, 10),(1001, 23),(1001, 35),(1001, 60);

This creates the dat_desk_employee table with the specified values.

Running the Query

Now we can run the corrected query:

select fk_employee,
    stuff((SELECT distinct ', ' + cast(fk_desk as varchar(10))
    from dat_desk_employee e2  
    where e2.fk_employee = e.fk_employee
    FOR XML PATH('')),1,1,'') fk_desks
from dat_desk_employee e
group by fk_employee
order by fk_employee asc

Running this query will produce the following result:

fk_employee | fk_desks   
----------: | :----------
          2 |  1000      
          3 |  1001      
         10 |  1000, 1001
         23 |  1000, 1001
         34 |  1000      
         35 |  1001      
         55 |  1000      
         60 |  1001

This result shows the horizontal representation of the data from dat_desk_employee, where each row represents an employee and their assigned desks.

Conclusion

In this post, we explored how to convert a vertical table into a horizontal table using SQL. We discussed the issues with the original query and provided a corrected version that uses the XML PATH function to aggregate distinct values into a single string. We also created sample data and ran the corrected query to demonstrate its effectiveness.

Additional Tips and Variations

In some cases, you may want to exclude certain rows from the aggregation process. To do this, you can modify the WHERE clause in the inner query to include additional conditions.
If your table has a large number of distinct values, using the XML PATH function can be slow. In such cases, consider using a window function like ROW_NUMBER() or RANK() instead.
To further improve performance, consider indexing the columns used in the aggregation process.