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

The Big Idea

What if you could turn a messy multi-step data task into a clean, easy-to-follow recipe inside your database?

The Scenario

Imagine you have a big messy spreadsheet with many steps to calculate a final result. You copy data from one sheet to another, do some calculations, then copy again to another sheet for more work. It's confusing and easy to lose track.

The Problem

Doing all these steps manually is slow and mistakes happen often. You might forget to update one sheet or mix up numbers. It's hard to see the whole process clearly, and fixing errors takes a lot of time.

The Solution

Using multiple CTEs (Common Table Expressions) in one query lets you break down complex tasks into clear, named steps inside your database. Each step builds on the previous one, making your work organized and easy to follow.

Before vs After

✗ Before

SELECT * FROM sales WHERE date > '2023-01-01';
-- Then manually filter and join results in separate queries

✓ After

WITH recent_sales AS (
  SELECT * FROM sales WHERE date > '2023-01-01'
), total_by_customer AS (
  SELECT customer_id, SUM(amount) AS total FROM recent_sales GROUP BY customer_id
)
SELECT * FROM total_by_customer WHERE total > 1000;

What It Enables

It enables you to write clear, step-by-step queries that are easier to read, maintain, and debug, even for complex data tasks.

Real Life Example

A store manager can quickly find customers who spent over $1000 in recent months by breaking the query into parts: first selecting recent sales, then summing totals per customer, and finally filtering big spenders.

Key Takeaways

Multiple CTEs let you organize complex queries into simple steps.

This reduces errors and makes your queries easier to understand.

You can reuse results from one step in the next, all in one query.

Practice

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

easy

A. To speed up the database server hardware

B. To create multiple databases at once

C. To permanently store data in the database

D. To break a complex query into smaller, readable parts

Solution

1. Step 1: Understand what CTEs do

   CTEs let you write parts of a query separately with names, making complex queries easier to read.

2. Step 2: Identify the purpose of multiple CTEs

   Using multiple CTEs helps organize and simplify complex logic by splitting it into smaller named queries.

3. Final Answer:

   To break a complex query into smaller, readable parts -> Option D

4. Quick Check:

   Multiple CTEs = Query readability [OK]

Hint: Think of CTEs as named steps in a recipe [OK]

Common Mistakes:

• Confusing CTEs with permanent tables
• Thinking CTEs improve hardware speed
• Assuming CTEs create databases

2. Which of the following is the correct syntax to define two CTEs named cte1 and cte2 in one PostgreSQL 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 (SELECT * FROM table1); WITH cte2 (SELECT * FROM table2); SELECT * FROM cte1, cte2;

C. WITH cte1 = SELECT * FROM table1, cte2 = SELECT * FROM table2 SELECT * FROM cte1 JOIN cte2;

D. WITH cte1 AS SELECT * FROM table1, cte2 AS SELECT * FROM table2 SELECT * FROM cte1 JOIN cte2;

Solution

1. Step 1: Recall correct CTE syntax

   CTEs start with WITH, each named, followed by AS and a query in parentheses, separated by commas.

2. Step 2: Check each option's syntax

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

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:

   Correct CTE syntax = WITH cte1 AS (SELECT * FROM table1), cte2 AS (SELECT * FROM table2) SELECT * FROM cte1 JOIN cte2 ON cte1.id = cte2.id; [OK]

Hint: Remember: WITH cte_name AS (query), separate multiple CTEs by commas [OK]

Common Mistakes:

• Omitting parentheses around CTE queries
• Using semicolons between CTEs
• Using '=' instead of AS

3. Given the following query, what will be the output?

WITH cte1 AS (SELECT 1 AS num), cte2 AS (SELECT num * 2 AS double_num FROM cte1) SELECT * FROM cte2;

medium

A. [{num: 2}]

B. [{num: 1, double_num: 2}]

C. [{double_num: 2}]

D. Syntax error

Solution

1. Step 1: Analyze cte1

   cte1 returns one row with column num = 1.

2. Step 2: Analyze cte2 using cte1

   cte2 selects num * 2 as double_num, so double_num = 1 * 2 = 2.

3. Step 3: Final SELECT from cte2

   Only double_num column is selected, so output is [{double_num: 2}].

4. Final Answer:

   [{double_num: 2}] -> Option C

5. Quick Check:

   cte2 output columns = double_num [OK]

Hint: Check which columns each CTE outputs carefully [OK]

Common Mistakes:

• Assuming cte2 includes all columns from cte1
• Expecting num column in final output
• Thinking query has syntax errors

4. Identify the error in this query using multiple CTEs:

WITH cte1 AS (SELECT id, name FROM users), cte2 AS (SELECT id, age FROM users) SELECT cte1.id, cte1.name, cte2.age FROM cte1 JOIN cte2 ON cte1.id = cte2.user_id;

medium

A. CTEs must be defined with semicolons

B. Column cte2.user_id does not exist

C. Missing comma between CTEs

D. Cannot join two CTEs in one query

Solution

1. Step 1: Check CTE definitions

   Both cte1 and cte2 select id and other columns from users table correctly.

2. Step 2: Check JOIN condition

   Query joins on cte1.id = cte2.user_id, but cte2 has no user_id column, only id.

3. Step 3: Identify error

   Using cte2.user_id causes a column not found error.

4. Final Answer:

   Column cte2.user_id does not exist -> Option B

5. Quick Check:

   Check column names in JOIN = Column cte2.user_id does not exist [OK]

Hint: Verify column names in JOIN conditions carefully [OK]

Common Mistakes:

• Assuming user_id exists in cte2
• Thinking semicolons separate CTEs
• Believing CTEs cannot be joined

5. You want to calculate the average order amount per customer and then find customers whose average order is above 100. Which query 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, SUM(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;

C. 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;

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 uses AVG(amount) with GROUP BY customer_id in avg_orders CTE.

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 high_avg to select customers meeting the condition.

3. Step 3: Final SELECT returns customers with high average orders

   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; selects all from high_avg, giving correct result.

4. 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

5. Quick Check:

   Correct aggregation and filtering = 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; [OK]

Hint: Use one CTE for aggregation, another for filtering [OK]

Common Mistakes:

• Using SUM instead of AVG for average calculation
• Missing GROUP BY clause
• Not filtering in a separate CTE