How to Write a Common Table Expression (CTE) in Redshift

Common Table Expressions (CTEs) are a powerful tool in Amazon Redshift that help simplify complex queries, improve readability, and even optimize performance. In this article, we'll walk you through how to write a CTE in Redshift with examples and best practices.

What is a Common Table Expression (CTE)?

A Common Table Expression (CTE) is a temporary result set that you can reference within a SELECT, INSERT, UPDATE, or DELETE statement. CTEs are defined using the WITH keyword and are particularly useful for breaking down complex queries into simpler, more readable components. They can also help with recursion and help eliminate redundant code.

Basic Syntax of a CTE

WITH cte_name AS (
    SELECT column1, column2
    FROM your_table
    WHERE some_condition
)
SELECT *
FROM cte_name;
                                

In the syntax above:

• cte_name is the name of your CTE. It acts as a temporary table that can be referenced in the main query.
• The query inside the WITH clause selects the columns you need from a table, applying any necessary filters or transformations.
• The final SELECT statement retrieves data from the CTE.

Example: Using CTEs in Redshift

Let’s consider an example where you need to find the top 5 products by sales from a table called sales. Using a CTE, you can first calculate the total sales per product and then filter the top 5:

WITH total_sales AS (
    SELECT product_id, SUM(sales_amount) AS total_sales
    FROM sales
    GROUP BY product_id
)
SELECT product_id, total_sales
FROM total_sales
ORDER BY total_sales DESC
LIMIT 5;
                                

In this example:

• The CTE total_sales calculates the total sales per product.
• The main query then selects from this CTE, ordering the results by total_sales in descending order and limiting the results to the top 5.

Best Practices for Using CTEs in Redshift

• Keep CTEs simple: Avoid writing overly complex logic inside a CTE. If your CTE grows too complex, consider breaking it down into multiple smaller CTEs or using temporary tables.
• Use CTEs for readability: One of the main advantages of CTEs is improved readability. Use them to clarify complex joins, subqueries, or aggregations.
• Limit the use of recursion: Redshift supports recursive CTEs, but recursion can be performance-intensive. Use it judiciously.
• Leverage CTEs for optimizing performance: In some cases, using CTEs can improve query performance by reducing redundant calculations or breaking down complex queries into manageable steps.

Conclusion

Common Table Expressions (CTEs) are a powerful tool for simplifying complex queries, improving readability, and optimizing performance in Amazon Redshift. By breaking down complex logic into smaller, more manageable components, you can write cleaner and more efficient queries. Whether you're performing aggregations, filtering, or working with recursive queries, CTEs can help streamline your Redshift queries and make them easier to maintain.