Why LEFT JOIN with NULL result rows in SQL? - Purpose & Use Cases

The Big Idea

What if you could see every customer's info even if they never made a purchase, without messy manual checks?

The Scenario

Imagine you have two lists: one of customers and one of their orders. You want to see all customers, even those who haven't placed any orders yet.

The Problem

Manually matching customers to orders means checking each customer against every order. This is slow, confusing, and easy to miss customers without orders.

The Solution

LEFT JOIN lets you combine these lists so all customers appear, and those without orders show NULL for order details automatically.

Before vs After

✗ Before

for each customer:
  find matching orders
  if none, print customer only

✓ After

SELECT customers.*, orders.* FROM customers LEFT JOIN orders ON customers.id = orders.customer_id;

What It Enables

You can easily see all items from one list with matching details from another, including those with no matches, without extra work.

Real Life Example

A store manager wants a report showing every customer and their last purchase date, even if some customers never bought anything.

Key Takeaways

LEFT JOIN includes all rows from the first table.

Rows without matches show NULL in joined columns.

This helps find missing or unmatched data easily.

Practice

1. What does a LEFT JOIN do in SQL?

easy

A. Returns all rows from the left table and matched rows from the right table, NULL if no match.

B. Returns only rows that have matching values in both tables.

C. Returns all rows from the right table and matched rows from the left table.

D. Deletes rows from the left table that have no match in the right table.

Solution

1. Step 1: Understand LEFT JOIN behavior

   A LEFT JOIN keeps all rows from the left table regardless of matches in the right table.

2. Step 2: Identify NULLs for unmatched rows

   If there is no matching row in the right table, the result shows NULL for right table columns.

3. Final Answer:

   Returns all rows from the left table and matched rows from the right table, NULL if no match. -> Option A

4. Quick Check:

   LEFT JOIN = all left rows + NULL for no match [OK]

Hint: LEFT JOIN keeps all left rows, unmatched right rows show NULL [OK]

Common Mistakes:

• Confusing LEFT JOIN with INNER JOIN
• Thinking unmatched rows are dropped
• Assuming NULLs appear in left table columns

2. Which of the following is the correct syntax for a LEFT JOIN in SQL?

easy

A. SELECT * FROM table1 LEFT OUTER JOIN table2 WHERE table1.id = table2.id;

B. SELECT * FROM table1 JOIN LEFT table2 ON table1.id = table2.id;

C. SELECT * FROM table1 LEFT JOIN table2 USING (id);

D. SELECT * FROM table1 LEFT JOIN table2 ON table1.id = table2.id;

Solution

1. Step 1: Review standard LEFT JOIN syntax

   The correct syntax is: SELECT columns FROM left_table LEFT JOIN right_table ON condition.

2. Step 2: Check each option

   SELECT * FROM table1 LEFT JOIN table2 ON table1.id = table2.id; matches the correct syntax exactly. SELECT * FROM table1 JOIN LEFT table2 ON table1.id = table2.id; has JOIN LEFT which is invalid. SELECT * FROM table1 LEFT OUTER JOIN table2 WHERE table1.id = table2.id; is invalid because JOIN requires an ON clause (syntax error). SELECT * FROM table1 LEFT JOIN table2 USING (id); is correct syntax with parentheses.

3. Final Answer:

   SELECT * FROM table1 LEFT JOIN table2 ON table1.id = table2.id; -> Option D

4. Quick Check:

   LEFT JOIN syntax = LEFT JOIN ... ON ... [OK]

Hint: Use LEFT JOIN ... ON ... for correct syntax [OK]

Common Mistakes:

• Swapping JOIN and LEFT keywords
• Using WHERE instead of ON for join condition
• Omitting parentheses in USING clause

3. Given tables Employees and Departments with data:

Employees:
id | name | dept_id
1 | Alice | 10
2 | Bob | 20
3 | Carol | NULL

Departments:
dept_id | dept_name
10 | Sales
20 | HR
30 | IT

What is the result of this query?

SELECT e.name, d.dept_name FROM Employees e LEFT JOIN Departments d ON e.dept_id = d.dept_id;

medium

A. [{"name": "Alice", "dept_name": "Sales"}, {"name": "Bob", "dept_name": "HR"}]

B. [{"name": "Alice", "dept_name": "Sales"}, {"name": "Bob", "dept_name": "HR"}, {"name": "Carol", "dept_name": null}]

C. [{"name": "Alice", "dept_name": "Sales"}, {"name": "Bob", "dept_name": "HR"}, {"name": "Carol", "dept_name": "IT"}]

D. [{"name": "Alice", "dept_name": null}, {"name": "Bob", "dept_name": null}, {"name": "Carol", "dept_name": null}]

Solution

1. Step 1: Match Employees with Departments by dept_id

   Alice's dept_id 10 matches Sales, Bob's 20 matches HR, Carol's NULL has no match.

2. Step 2: Apply LEFT JOIN behavior

   All employees appear. For Carol, no matching department, so dept_name is NULL.

3. Final Answer:

   [{"name": "Alice", "dept_name": "Sales"}, {"name": "Bob", "dept_name": "HR"}, {"name": "Carol", "dept_name": null}] -> Option B

4. Quick Check:

   LEFT JOIN keeps all left rows, unmatched right columns NULL [OK]

Hint: LEFT JOIN shows NULL for unmatched right table rows [OK]

Common Mistakes:

• Omitting rows with NULL join keys
• Assuming unmatched rows get default values
• Confusing INNER JOIN output with LEFT JOIN

4. Consider this SQL query:

SELECT a.id, b.value FROM A a LEFT JOIN B b ON a.id = b.a_id WHERE b.value > 10;

Why might this query return fewer rows than table A has?

medium

A. Because the query syntax is invalid and causes an error.

B. Because LEFT JOIN only returns rows with matching b.value > 10.

C. Because the WHERE clause filters out rows where b.value is NULL, removing unmatched rows.

D. Because the ON condition is incorrect and causes no matches.

Solution

1. Step 1: Understand LEFT JOIN with WHERE filter

   LEFT JOIN keeps all rows from A, but WHERE filters after join.

2. Step 2: Effect of WHERE on NULLs from unmatched rows

   Rows with no match have b.value as NULL, and WHERE b.value > 10 excludes NULLs, removing those rows.

3. Final Answer:

   Because the WHERE clause filters out rows where b.value is NULL, removing unmatched rows. -> Option C

4. Quick Check:

   WHERE filters NULLs after LEFT JOIN, reducing rows [OK]

Hint: WHERE on right table column after LEFT JOIN filters out NULLs [OK]

Common Mistakes:

• Thinking LEFT JOIN always keeps all left rows regardless of WHERE
• Confusing ON and WHERE filtering effects
• Assuming query syntax error causes fewer rows

5. You have two tables:

Orders:
order_id | customer_id
1 | 101
2 | 102
3 | 103

Customers:
customer_id | name
101 | John
102 | Jane

You want to list all orders with customer names, but show 'Unknown' if no customer found.

Which SQL query correctly achieves this?

hard

A. SELECT o.order_id, COALESCE(c.name, 'Unknown') AS customer_name FROM Orders o LEFT JOIN Customers c ON o.customer_id = c.customer_id;

B. SELECT o.order_id, IFNULL(c.name, 'Unknown') AS customer_name FROM Orders o INNER JOIN Customers c ON o.customer_id = c.customer_id;

C. SELECT o.order_id, c.name FROM Orders o RIGHT JOIN Customers c ON o.customer_id = c.customer_id;

D. SELECT o.order_id, CASE WHEN c.name IS NULL THEN 'Unknown' ELSE c.name END FROM Orders o JOIN Customers c ON o.customer_id = c.customer_id;

Solution

1. Step 1: Use LEFT JOIN to keep all orders

   LEFT JOIN keeps all orders even if no matching customer exists.

2. Step 2: Replace NULL customer names with 'Unknown'

   Use COALESCE to show 'Unknown' when c.name is NULL.

3. Final Answer:

   SELECT o.order_id, COALESCE(c.name, 'Unknown') AS customer_name FROM Orders o LEFT JOIN Customers c ON o.customer_id = c.customer_id; -> Option A

4. Quick Check:

   LEFT JOIN + COALESCE handles missing customers [OK]

Hint: Use LEFT JOIN with COALESCE to replace NULLs [OK]

Common Mistakes:

• Using INNER JOIN excludes orders without customers
• Using RIGHT JOIN reverses table roles incorrectly
• Forgetting to handle NULL customer names