Multiple CTEs in one query in SQL - Mini Project: Build & Apply

Using Multiple CTEs in One SQL Query

📖 Scenario: You work for a small bookstore. You have a database with sales data and book details. You want to find the total sales for each book and then find which books sold more than 50 copies.

🎯 Goal: Build a SQL query using two Common Table Expressions (CTEs). The first CTE calculates total sales per book. The second CTE filters books with sales greater than 50. Finally, select the book title and total sales from the filtered results.

📋 What You'll Learn

Create a CTE named BookSales that sums sales per book_id from the sales table.

Create a second CTE named TopSellingBooks that selects books from BookSales with total sales greater than 50.

Join TopSellingBooks with the books table to get the book titles.

Select the book title and total sales in the final output.

💡 Why This Matters

🌍 Real World

Using multiple CTEs helps break complex queries into smaller parts, making them easier to read and maintain in real business databases.

💼 Career

Many data analyst and database developer jobs require writing queries with multiple CTEs to organize data processing steps clearly.

1

Create the BookSales CTE

Write a SQL query that starts with a CTE named BookSales. This CTE should select book_id and the sum of quantity as total_sales from the sales table, grouped by book_id.

SQL

WITH BookSales AS (
    -- Your code here
)

Hint

Use WITH BookSales AS (SELECT book_id, SUM(quantity) AS total_sales FROM sales GROUP BY book_id) to create the first CTE.

2

Add the TopSellingBooks CTE

Add a second CTE named TopSellingBooks after BookSales. This CTE should select all columns from BookSales where total_sales is greater than 50.

SQL

WITH BookSales AS (
    SELECT book_id, SUM(quantity) AS total_sales
    FROM sales
    GROUP BY book_id
),
TopSellingBooks AS (
    -- Your code here
)

Hint

Use TopSellingBooks AS (SELECT * FROM BookSales WHERE total_sales > 50) to filter books with sales over 50.

3

Join TopSellingBooks with books table

After the two CTEs, write the main query that joins TopSellingBooks with the books table on book_id. Select books.title and TopSellingBooks.total_sales.

SQL

WITH BookSales AS (
    SELECT book_id, SUM(quantity) AS total_sales
    FROM sales
    GROUP BY book_id
),
TopSellingBooks AS (
    SELECT * FROM BookSales WHERE total_sales > 50
)
SELECT
    -- Your code here

Hint

Use JOIN books ON TopSellingBooks.book_id = books.book_id to get book titles.

4

Complete the query with proper formatting

Ensure the full query uses commas correctly between CTEs and ends with a semicolon. The query should start with WITH BookSales AS, then TopSellingBooks AS, and finally the SELECT statement joining the tables.

SQL

WITH BookSales AS (
    SELECT book_id, SUM(quantity) AS total_sales
    FROM sales
    GROUP BY book_id
),
TopSellingBooks AS (
    SELECT * FROM BookSales WHERE total_sales > 50
)
SELECT
    books.title, TopSellingBooks.total_sales
FROM TopSellingBooks
JOIN books ON TopSellingBooks.book_id = books.book_id
-- Your code here

Hint

End your query with a semicolon ; to complete it.

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