SQL Joins and advanced joins and Subqueries

 

Refernce : Expert Guide to Advanced SQL Joins: What You Need to Know

It's helpful to visualize how these different SQL joins work. Here's a breakdown in a table-like format, along with explanations:

SQL Join Types Overview

Join Type	Description	Key Characteristics	Use Cases
INNER JOIN	Returns rows where there is a match in both tables.	- Shows only matching records. - Excludes unmatched rows from both tables.	- Retrieving related data that exists in both tables. - Finding records with corresponding entries in another table.
LEFT OUTER JOIN (LEFT JOIN)	Returns all rows from the left table, and the matched rows from the right table.	- Includes all records from the left table. - Fills in NULL values for columns from the right table where there's no match.	- Retrieving all records from one table and their related data from another, even if some records don't have matches. - Finding records in one table that don't have corresponding entries in another.
RIGHT OUTER JOIN (RIGHT JOIN)	Returns all rows from the right table, and the matched rows from the left table.	- Includes all records from the right table. - Fills in NULL values for columns from the left table where there's no match.	- Retrieving all records from one table and their related data from another, even if some records don't have matches. - Less commonly used than LEFT JOIN, but useful when the "right" table is the primary focus.
FULL OUTER JOIN	Returns all rows when there is a match in either the left or right table.	- Includes all records from both tables. - Fills in NULL values for columns where there's no match.	- Retrieving all records from both tables, regardless of matches. - Finding records that exist in either table but not both.
SELF JOIN	Joins a table to itself.	- Requires aliasing the table to distinguish between instances. - Used for comparing rows within the same table.	- Finding hierarchical relationships within a table (e.g., employee-manager relationships). - Comparing rows with similar attributes.

Prerequisites

Before diving into the tutorial, you should have the following;

• A basic understanding of SQL queries, including SELECT, FROM, WHERE, GROUP BY, and ORDER BY statements.
• Familiarity with basic join types, such as INNER JOIN, LEFT JOIN, RIGHT JOIN, and FULL OUTER JOIN is also essential.
• An SQL database client like DbVisualizer to run your SQL code and manage your database resources.

Dataset Overview

For this tutorial, we will use a fictional e-commerce database with the following tables:

customers: Contains customer information, including customer_id, firstname, lastname, and email.

orders: Contains order information, including order_id, customer_id, order_date, and total_amount.

order_items: Contains individual items in each order, including order_item_id, order_id, product_id, quantity, and price.

products: Contains product information, including product_id, product_name, category, and price.

You can create the tables above in DbVisualizer by following the steps below:

Connect to your database server as shown in this guide. After establishing a connection, navigate to the “Database” tab, right-click on “Databases” in the connections dropdown, and select “Create databases,” as shown in the image below:

Navigating the database connections dropdown

Finally, enter a name for your database and click on “Execute,” as shown in the image below:

Executing the database creation

Create a table by right-clicking on “Tables” in your database dropdown, then clicking on “Create Table”.

Selecting create table in the dropdown

Finally, enter a name for your table and the column's properties.

Creating the customers table

Repeat the steps above for the other tables we listed earlier.

Advanced Join Techniques

Now that we have our tables ready, let’s jump right into the various advanced join techniques we have.

Self-Join

A self-join is a technique where a table is joined to itself. This can be useful for comparing records within the same table. A good example is to find all customers who share the same last name.

COPY

1SELECT c1.firstname AS"First Name 1", c1.lastname AS"Last Name 1",2c2.firstname AS"First Name 2", c2.lastname AS"Last Name 2"3FROM customers c14JOIN customers c2 ON c1.lastname = c2.lastname5WHERE c1.customer_id <> c2.customer_id;

In this example, we join the customers table to itself on the last_name column. The WHERE clause ensures that we only display distinct customers who share the same last name.

Running the join statement to retrieve customers with the same last name

Multiple Joins

You can join more than two tables in a single query. This is useful when you need to retrieve data from several related tables, for example, to find the total amount spent by each customer on each product category.

COPY

1SELECT c.customer_id, c.firstname, c.lastname, p.category,2SUM(oi.price * oi.quantity) as "Total Amount"3FROM customers c4JOIN orders o ON c.customer_id = o.customer_id5JOIN order_items oi ON o.order_id = oi.order_id6JOIN products p ON oi.product_id = p.product_id7GROUP BY c.customer_id, p.category;

In this example, we join four tables together to get the desired information. The orders table is joined with the customers table on the customer_id column, the order_items table is joined with the orders table on the order_id column, and the products table is joined with the order_items table on the product_id column. The GROUP BY clause is used to aggregate the total amount spent by each customer on each product category.

A JOIN statement to retrieve the total amount spent by each customer on each category

Using Subqueries in Joins

Subqueries can be used within a join to filter, aggregate, or manipulate data before joining. A typical example is to find the customers who have spent the most in each product category.

COPY

1WITH category_spending AS (2SELECT c.customer_id, c.first_name, c.last_name, p.category,3SUM(oi.price * oi.quantity) AS"Total Amount"4FROM customers c5JOIN orders o ON c.customer_id = o.customer_id6JOIN order_items oi ON o.order_id = oi.order_id7JOIN products p ON oi.product_id = p.product_id8GROUP BY c.customer_id, p.category9)1011SELECT cs1.customer_id, cs1.firstname, cs1.lastname, cs1.category, cs1."Total Amount"12FROM category_spending cs113JOIN (14SELECT category, MAX("Total Amount") AS"Max Amount"15FROM category_spending16GROUP BY category17) cs2 ON cs1.category =cs2.category AND cs1."Total Amount" = cs2."Max Amount"18ORDER BY cs1.category;

In this example, we use a subquery within a join to find the customers who have spent the most in each product category. The category_spending subquery calculates the total amount spent by each customer in each product category. Then, we use another subquery in the join condition to find the maximum total amount spent in each category. Finally, we join the category_spending subquery with the results of the maximum total amount subquery to get the desired information.

Join statement to retrieve the customer who spent the most on each category

Conclusion

Congratulations! You've now explored some advanced SQL join techniques, including self-joins, multiple joins, and using subqueries in joins. These techniques will empower you to extract valuable insights from your data and make well-informed decisions.

Remember that mastering SQL joins takes time and practice. Keep experimenting with different scenarios and datasets to become a true SQL expert. 🤓 The more you practice, the more you'll appreciate the power and flexibility of SQL joins. Embrace the world of SQL and unlock the full potential of your data! 🌍🔓

FAQ

What is a self-join in SQL?

A self-join is a technique where a table is joined to itself. It is useful for comparing records within the same table, such as finding customers who share the same last name.

How do I perform a self-join in SQL?

To perform a self-join in SQL, you need to use the same table twice in the query and join them based on a common column. For example, you can join a "customers" table to itself using the last name column.

Can I join more than two tables in a single SQL query?

Yes, you can join multiple tables in a single SQL query. This is useful when you need to retrieve data from several related tables. You can use join conditions to specify how the tables are related to each other.

How do I use subqueries in SQL joins?

Subqueries can be used within SQL joins to filter, aggregate, or manipulate data before joining. For example, you can use a subquery to find customers who have spent the most in each product category before joining them with other tables.

What are the advantages of using advanced SQL joins?

Using advanced SQL joins allows you to extract useful information from your database by combining data from multiple tables. It helps you uncover relationships, perform complex analyses, and make informed decisions based on your data.