Unlocking the Power of CTEs in SQL

intro

Learn how to use CTEs to simplify your SQL codes.

Tools used in the tutorial
Tool Description Link
Dbvisualizer DBVISUALIZER
TOP RATED DATABASE MANAGEMENT TOOL AND SQL CLIENT

Common Table Expressions (CTEs) are a powerful feature of SQL that allows you to create temporary named result sets within a single query. CTEs can simplify complex queries, improve query performance, and make your code more readable and maintainable. In this tutorial, we will explore the basics of CTEs and demonstrate how they can be used to unlock the power of SQL.

Prerequisites

Before diving into the tutorial, you should be familiar with the following:

  • A basic understanding of SQL queries, including SELECT, FROM, WHERE, GROUP BY, and ORDER BY statements.
  • 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:

  1. customers: Contains customer information, including customer_id, firstname, lastname, and email.
  2. orders: Contains order information, including order_id, customer_id, order_date, and total_amount.
  3. order_items: Contains individual items in each order, including order_item_id, order_id, product_id, quantity, and price.
  4. products: Contains product information, including product_id, product_name, category, and price.
  5. reviews: Contains product information, including review_id,product_id,customer_id,review_date,review_text, and rating.

What are CTEs?

A Common Table Expression (CTE) is a named temporary result set that can be referenced within a SELECT, INSERT, UPDATE, or DELETE statement. CTEs are defined using a WITH clause that specifies the name of the CTE and the query that defines the result set.

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1 WITH cte_name AS ( 2 SELECT column1, column2, ... 3 FROM table_name 4 WHERE condition 5 ) 6 SELECT column1, column2, ... 7 FROM cte_name 8 WHERE condition;

The WITH clause is used to define the CTE and the query that defines the result set. The CTE can then be referenced in the main query that follows the WITH clause. For example, let's say we have a table of customer orders and we want to find the total sales for each customer. We can use a CTE to create a temporary result set that calculates the total sales for each customer, and then reference the CTE in our main query to retrieve the results.

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1 WITH customer_sales AS ( 2 SELECT customer_id, SUM(price * quantity) AS total_sales 3 FROM orders 4 JOIN order_items ON orders.order_id = order_items.order_id 5 GROUP BY customer_id 6 ) 7 SELECT customers.customer_name, customer_sales.total_sales 8 FROM customers 9 JOIN customer_sales ON customers.customer_id = customer_sales.customer_id;

In this example, we first define a CTE named "customer_sales" that calculates the total sales for each customer using the orders and order_items tables. We then reference the CTE in our main query to retrieve the customer name and total sales for each customer.

Retrieving the total sales for each customer
Retrieving the total sales for each customer

Benefits of using CTEs

Let’s explore some of the benefits of using CTEs in SQL. They include:

1. Simplification of complex queries

One of the main benefits of CTEs is that they can simplify complex queries by breaking them down into smaller, more manageable parts. For example, let's say we have a table of customer orders and we want to find the total sales for each customer broken down by year and month. We could write a single query that includes all of the necessary joins and groupings, but that query would be very long and difficult to read. Instead, we can use CTEs to break the query down into smaller parts.

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1 WITH customer_sales AS ( 2 SELECT customer_id, YEAR(order_date) AS year, MONTH(order_date) AS month, SUM(price * quantity) AS total_sales 3 FROM orders 4 JOIN order_items ON orders.order_id = order_items.order_id 5 GROUP BY customer_id, YEAR(order_date), MONTH(order_date) 6 ), 7 customer_sales_by_month AS ( 8 SELECT customer_id, year, month, total_sales, SUM(total_sales) OVER (PARTITION BY customer_id, year ORDER BY month) AS sales_to_date 9 FROM customer_sales 10 ) 11 SELECT customers.customer_name, customer_sales_by_month.year, customer_sales_by_month.month, customer_sales_by_month.total_sales, 12 customer_sales_by_month.sales_to_date 13 FROM customers 14 JOIN customer_sales_by_month ON customers.customer_id = customer_sales_by_month.customer_id;

In this example, we first define a CTE named "customer_sales" that calculates the total sales for each customer broken down by year and month. We then define a second CTE named "customer_sales_by_month" which calculates the running total of sales for each customer up to the current month. Finally, we reference the CTEs in our main query to retrieve the results.

By breaking the query down into smaller parts, we can more easily understand and modify the code as needed. This can be especially helpful for larger queries with many joins and groupings.

Retrieving total monthly sales for each customer
Retrieving total monthly sales for each customer

2. Improving query performance

Another benefit of CTEs is that they can improve query performance by reducing the need for subqueries or self-joins. In some cases, a query may require multiple levels of subqueries or self-joins to achieve the desired result. This can be time-consuming and can negatively impact query performance.

By using CTEs, we can perform the necessary calculations once and then reference the CTE in our main query. This can eliminate the need for multiple levels of subqueries or self-joins, leading to faster and more efficient queries.

3. Making code more readable and maintainable

CTEs can also make your code more readable and maintainable by giving temporary result sets meaningful names. By using descriptive names for your CTEs, you can make it easier for others (and yourself!) to understand what the code is doing and why.

For example, let's say we have a table of product reviews and we want to find the average rating for each product category. We could write a single query that includes all of the necessary joins and groupings, but that query would be difficult to understand. Instead, we can use CTEs to break the query down into smaller parts and give each CTE a meaningful name.

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1 WITH product_ratings AS ( 2 SELECT product_id, AVG(rating) AS avg_rating 3 FROM reviews 4 GROUP BY product_id 5 ), 6 product_categories AS ( 7 SELECT product_id, category 8 FROM products 9 ) 10 SELECT product_categories.category, AVG(product_ratings.avg_rating) AS avg_rating 11 FROM product_ratings 12 JOIN product_categories ON product_ratings.product_id = product_categories.product_id 13 GROUP BY product_categories.category;

In this example, we first define a CTE named "product_ratings" that calculates the average rating for each product. We then define a second CTE named "product_categories" that retrieves the category for each product. Finally, we reference the CTEs in our main query to retrieve the average rating for each product category.

By giving each CTE a meaningful name, we can more easily understand what each part of the query is doing and how it contributes to the overall result.

Retrieving the average rating for each product
Retrieving the average rating for each product

4. Allowing to reference the same result set multiple times

Another benefit of CTEs is that they allow you to reference the same result set multiple times within a single query. This can be useful for complex queries that require multiple calculations or subqueries.

For example, let's say we have a table of customer orders and we want to find the average order value for each customer broken down by product category. We could write a single query that includes all of the necessary joins and groupings, but that query would be very long and difficult to read. Instead, we can use CTEs to break the query down into smaller parts.

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1 WITH customer_order_totals AS ( 2 SELECT customer_id, SUM(price * quantity) AS order_total 3 FROM orders 4 JOIN order_items ON orders.order_id = order_items.order_id 5 GROUP BY customer_id 6 ), 7 product_order_totals AS ( 8 SELECT customer_id, product_id, SUM(price * quantity) AS order_total 9 FROM orders 10 JOIN order_items ON orders.order_id = order_items.order_id 11 GROUP BY customer_id, product_id 12 ) 13 SELECT customers.customer_name, products.category, AVG(product_order_totals.order_total / customer_order_totals.order_total) AS avg_order_value 14 FROM customers 15 JOIN orders ON customers.customer_id = orders.customer_id 16 JOIN order_items ON orders.order_id = order_items.order_id 17 JOIN products ON order_items.product_id = products.product_id 18 JOIN customer_order_totals ON customers.customer_id = customer_order_totals.customer_id 19 JOIN product_order_totals ON customers.customer_id = product_order_totals.customer_id AND products.product_id = product_order_totals.product_id 20 GROUP BY customers.customer_name, products.category;

In this example, we first define a CTE named "customer_order_totals" that calculates the total order value for each customer. We then define a second CTE named "product_order_totals" that calculates the total order value for each customer and product combination. Finally, we reference the CTEs in our main query to calculate the average order value for each customer and product category.

Retrieving the average order value for each customer by product category
Retrieving the average order value for each customer by product category

By using CTEs to break the query down into smaller parts, we can more easily understand what the code is doing and how it contributes to the overall result. We can also reference the same result set multiple times without the need for additional subqueries or self-joins.

Conclusion

Common Table Expressions (CTEs) are a powerful feature of SQL that can simplify complex queries, improve query performance, and make your code more readable and maintainable. By using CTEs, you can break your queries down into smaller parts, give temporary result sets meaningful names , and reference the same result set multiple times within a single query.

Once you unlock the power of CTEs, you can take your SQL skills to the next level and become a more effective database developer. So go ahead and use CTEs to unleash the full potential of your SQL queries! 💻

FAQs

What is a CTE in SQL?

A Common Table Expression (CTE) is a named temporary result set that can be referenced within a SELECT, INSERT, UPDATE, or DELETE statement. CTEs are defined using a WITH clause that specifies the name of the CTE and the query that defines the result set.

How do I use CTEs in SQL?

To use CTEs in SQL, you need to define the CTE using the WITH clause, followed by the query that defines the result set. Once the CTE is defined, you can reference it in the main query that follows the WITH clause.

What are the benefits of using CTEs in SQL?

Using CTEs in SQL offers several benefits, including:

  • Simplifying complex queries by breaking them down into smaller, more manageable parts.
  • Improving query performance by reducing the need for subqueries or self-joins.
  • Make your code more readable and maintainable by giving temporary result sets meaningful names.
  • Allowing you to reference the same result set multiple times within a single query.

Can I use CTEs with any type of SQL database?

Yes, CTEs are supported by most modern SQL databases, including popular ones like PostgreSQL, MySQL, SQL Server, and Oracle.

Are there any limitations or considerations when using CTEs?

While CTEs are a powerful tool, there are a few things to keep in mind:

  • CTEs are temporary and only exist within the scope of the query where they are defined.
  • CTEs cannot be referenced outside the query where they are defined.
  • Recursive queries, which involve a CTE referring to itself, require special syntax and consideration.
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About the author
Ochuko Onojakpor
Ochuko Onojakpor

Ochuko is a full-stack Python/React software developer and freelance Technical Writer. He spends his free time contributing to open source and tutoring students on programming in collaboration with Google DSC.

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