Joining Rows of One Table to Columns of Another in SQL

As a technical blogger, I’ve encountered numerous questions from developers who struggle with joining tables in different directions. In this article, we’ll delve into the world of cross joins and use cases, exploring how to join rows of one table to columns of another.

Understanding Cross Joins

A cross join, also known as an outer join or cartesian product, is a type of SQL join that combines rows from two tables based on their intersection. The result set contains all possible combinations of rows from both tables. This is in contrast to the standard inner join, which only includes rows where there’s a match between the two tables.

In the example provided, we want to combine the transactions table with the standards table. However, instead of joining on a common column like ID or Department, we’re aiming for a cross join.

The Problem with Cross Joins

While cross joins can be useful in certain situations, they often lead to data duplication and make it difficult to analyze the data. In our case, we want to use the columns from the standards table as separate rows in the resulting table.

Using a Case Expression for Column Joins

To achieve this, we can utilize a combination of SQL joins and CASE expressions. The idea is to join the two tables using an inner join, but instead of combining rows directly, we’ll use a CASE expression to map each row from the transactions table to the corresponding column values in the standards table.

Setting Up the Example

Let’s create our example tables and data:

CREATE TABLE transactions (
  ID INTEGER PRIMARY KEY,
  Department VARCHAR(255) NOT NULL
);

CREATE TABLE standards (
  IT REAL NOT NULL,
  CustomerService REAL NOT NULL,
  Cleaning REAL NOT NULL
);

INSERT INTO transactions (ID, Department)
VALUES
  (1, 'IT'),
  (2, 'Customer Service'),
  (3, 'Cleaning');

INSERT INTO standards (IT, CustomerService, Cleaning)
VALUES
  (9.12, 17.8, 24.86),
  (10.56, 20.12, 27.39);

The Joining Query

We’ll now craft the SQL query that combines our tables in the desired manner:

SELECT t.*,
       CASE 
         WHEN t.Department = 'IT' THEN s.IT
         WHEN t.Department = 'Customer Service' THEN s.`Customer Service`
         WHEN t.Department = 'Cleaning' THEN s.Cleaning
       END AS Standard
FROM transactions t JOIN standards s;

How It Works

Here’s a step-by-step explanation of the joining query:

1. We start by selecting all columns (*) from both tables, transactions (t) and standards (s).
2. The CASE expression is used to map each row from the transactions table to the corresponding column values in the standards table based on the department.
3. We use a simple WHEN-THEN structure to specify these mappings:
   • If the department is ‘IT’, we select the IT value from the standards table.
   • If the department is ‘Customer Service’, we select the CustomerService value.
   • If the department is ‘Cleaning’, we select the Cleaning value.
4. The resulting columns will contain all possible combinations of values, with each row corresponding to a unique combination of departments and standard values.

Output

Running this query will produce the desired output:

Conclusion

Joining rows of one table to columns of another can be achieved through a cross join and the use of CASE expressions. By utilizing this technique, you can transform data from different formats into a more useful structure.

While cross joins might not always lead to the desired outcome, there are instances where they’re necessary or beneficial. In such cases, using CASE expressions can help mitigate some of the issues associated with these types of joins.

By mastering SQL’s various join techniques and combining them with smart use of CASE expressions, you’ll be better equipped to handle data transformation tasks in your own projects.

Last modified on 2024-09-08