Why Multiple CTEs in one query in SQL? - Purpose & Use Cases

The Big Idea

What if you could turn a messy, multi-step data task into a clean, easy-to-follow query in seconds?

The Scenario

Imagine you have a big spreadsheet with sales data, customer info, and product details all mixed up. You want to find the top customers by sales, but first, you need to clean and organize the data step-by-step. Doing this by hand means copying and filtering data multiple times across sheets.

The Problem

Manually filtering and organizing data is slow and easy to mess up. You might forget a step or mix up numbers. It's hard to keep track of changes, and if the data updates, you have to redo everything from scratch.

The Solution

Using multiple CTEs (Common Table Expressions) in one query lets you break down complex tasks into clear, manageable steps inside the database. Each CTE acts like a mini-table you can build on, making your query easier to read and maintain.

Before vs After

✗ Before

SELECT * FROM sales WHERE date > '2023-01-01';
-- Then manually join with customers and products in separate steps

✓ After

WITH recent_sales AS (
  SELECT * FROM sales WHERE date > '2023-01-01'
), top_customers AS (
  SELECT customer_id, SUM(amount) AS total FROM recent_sales GROUP BY customer_id
)
SELECT * FROM top_customers;

What It Enables

It enables you to write clear, step-by-step queries that handle complex data tasks all at once, saving time and reducing errors.

Real Life Example

A business analyst can quickly find the top-selling products last quarter by first filtering sales data, then summarizing totals, and finally joining with product info--all in one neat query.

Key Takeaways

Manual data handling is slow and error-prone.

Multiple CTEs let you organize complex queries into simple steps.

This approach makes queries easier to read, maintain, and update.

Practice

1. What is the main purpose of using multiple CTEs (Common Table Expressions) in a single SQL query?

easy

A. To automatically create indexes on the tables used

B. To break down complex queries into simpler, named parts for better readability

C. To permanently store intermediate results in the database

D. To speed up the database engine by running queries in parallel

Solution

1. Step 1: Understand the role of CTEs

   CTEs are temporary named result sets used inside a query to organize complex logic.

2. Step 2: Identify the benefit of multiple CTEs

   Using multiple CTEs lets you split a big query into smaller, readable parts without permanent storage or indexing.

3. Final Answer:

   To break down complex queries into simpler, named parts for better readability -> Option B

4. Quick Check:

   Multiple CTEs improve query clarity = D [OK]

Hint: Multiple CTEs split queries into named parts for clarity [OK]

Common Mistakes:

• Thinking CTEs create permanent tables
• Assuming CTEs improve query speed automatically
• Confusing CTEs with indexes

2. Which of the following is the correct syntax to define two CTEs named cte1 and cte2 in one SQL query?

easy

A. WITH cte1 AS (SELECT * FROM table1), cte2 AS (SELECT * FROM table2) SELECT * FROM cte1 JOIN cte2 ON cte1.id = cte2.id;

B. WITH cte1 AS (SELECT * FROM table1) cte2 AS (SELECT * FROM table2) SELECT * FROM cte1 JOIN cte2 ON cte1.id = cte2.id;

C. WITH cte1 (SELECT * FROM table1); WITH cte2 (SELECT * FROM table2); SELECT * FROM cte1 JOIN cte2 ON cte1.id = cte2.id;

D. WITH cte1 = (SELECT * FROM table1), cte2 = (SELECT * FROM table2) SELECT * FROM cte1 JOIN cte2 ON cte1.id = cte2.id;

Solution

1. Step 1: Recall correct CTE syntax

   Multiple CTEs are separated by commas after WITH, each defined as name AS (query).

2. Step 2: Check each option

   WITH cte1 AS (SELECT * FROM table1), cte2 AS (SELECT * FROM table2) SELECT * FROM cte1 JOIN cte2 ON cte1.id = cte2.id; correctly uses commas and AS keyword; others miss commas or use wrong syntax.

3. Final Answer:

   WITH cte1 AS (SELECT * FROM table1), cte2 AS (SELECT * FROM table2) SELECT * FROM cte1 JOIN cte2 ON cte1.id = cte2.id; -> Option A

4. Quick Check:

   Multiple CTEs separated by commas = B [OK]

Hint: Separate multiple CTEs with commas after WITH [OK]

Common Mistakes:

• Omitting commas between CTEs
• Using semicolons between CTEs
• Using equals sign instead of AS

3. Given the following SQL query with multiple CTEs, what will be the output?

WITH cte1 AS (SELECT 1 AS num UNION ALL SELECT 2), cte2 AS (SELECT num FROM cte1 WHERE num = 2) SELECT * FROM cte2;

medium

A. 1 and 2

B. 1

C. 2

D. No rows returned

Solution

1. Step 1: Analyze cte1 content

   cte1 returns two rows with num values 1 and 2.

2. Step 2: Analyze cte2 filtering

   cte2 selects only rows from cte1 where num = 2, so only one row with num=2.

3. Final Answer:

   2 -> Option C

4. Quick Check:

   cte2 filters num=2 = A [OK]

Hint: Trace each CTE step-by-step to find final output [OK]

Common Mistakes:

• Assuming cte2 returns all rows from cte1
• Confusing UNION ALL with UNION
• Ignoring the WHERE filter in cte2

4. Identify the error in the following SQL query using multiple CTEs:

WITH cte1 AS (SELECT id, name FROM users) SELECT * FROM cte1; WITH cte2 AS (SELECT id FROM orders) SELECT * FROM cte2;

medium

A. CTEs cannot select from tables

B. CTEs must be named with different names

C. Missing JOIN condition between cte1 and cte2

D. Multiple WITH clauses are not allowed in one query

Solution

1. Step 1: Review CTE syntax rules

   Only one WITH clause is allowed per query; multiple CTEs must be separated by commas inside one WITH.

2. Step 2: Identify the error in the query

   The query uses two separate WITH clauses, which is invalid syntax.

3. Final Answer:

   Multiple WITH clauses are not allowed in one query -> Option D

4. Quick Check:

   Only one WITH clause per query = A [OK]

Hint: Use one WITH clause with commas for multiple CTEs [OK]

Common Mistakes:

• Writing multiple WITH clauses in one query
• Forgetting commas between CTEs
• Assuming CTEs create permanent tables

5. You want to calculate the average order amount per customer and then find customers whose average order is above 100. Which of the following queries correctly uses multiple CTEs to achieve this?

hard

A. WITH avg_orders AS (SELECT customer_id, AVG(amount) AS avg_amount FROM orders GROUP BY customer_id), high_avg AS (SELECT customer_id FROM avg_orders WHERE avg_amount > 100) SELECT * FROM high_avg;

B. WITH avg_orders AS (SELECT customer_id, AVG(amount) AS avg_amount FROM orders), high_avg AS (SELECT customer_id FROM avg_orders WHERE avg_amount > 100) SELECT * FROM high_avg;

C. WITH avg_orders AS (SELECT customer_id, amount FROM orders GROUP BY customer_id), high_avg AS (SELECT customer_id FROM avg_orders WHERE amount > 100) SELECT * FROM high_avg;

D. WITH avg_orders AS (SELECT customer_id, AVG(amount) AS avg_amount FROM orders GROUP BY customer_id) SELECT * FROM avg_orders WHERE avg_amount > 100;

Solution

1. Step 1: Calculate average order per customer

   WITH avg_orders AS (SELECT customer_id, AVG(amount) AS avg_amount FROM orders GROUP BY customer_id), high_avg AS (SELECT customer_id FROM avg_orders WHERE avg_amount > 100) SELECT * FROM high_avg; correctly groups orders by customer_id and calculates AVG(amount).

2. Step 2: Filter customers with avg_amount > 100

   WITH avg_orders AS (SELECT customer_id, AVG(amount) AS avg_amount FROM orders GROUP BY customer_id), high_avg AS (SELECT customer_id FROM avg_orders WHERE avg_amount > 100) SELECT * FROM high_avg; uses a second CTE to filter customers with average above 100, then selects from it.

3. Final Answer:

   WITH avg_orders AS (SELECT customer_id, AVG(amount) AS avg_amount FROM orders GROUP BY customer_id), high_avg AS (SELECT customer_id FROM avg_orders WHERE avg_amount > 100) SELECT * FROM high_avg; -> Option A

4. Quick Check:

   Multiple CTEs for calculation and filtering = C [OK]

Hint: Use one CTE to calculate, second to filter results [OK]

Common Mistakes:

• Missing GROUP BY when calculating averages
• Not filtering on aggregated column
• Incorrect CTE definitions without commas