Why NULLs in JOIN conditions in SQL? - Purpose & Use Cases

The Big Idea

What if missing data silently breaks your JOINs and hides important connections?

The Scenario

Imagine you have two lists of friends and their favorite colors, but some friends haven't told you their favorite color yet (it's missing). You want to find friends who appear in both lists with the same favorite color.

The Problem

Trying to match these lists manually is tricky because missing favorite colors (NULLs) don't behave like normal values. If you just compare them directly, you might miss friends who should match or get confused results.

The Solution

Understanding how NULLs work in JOIN conditions helps you write queries that correctly handle missing information, so you get accurate matches even when some data is unknown.

Before vs After

✗ Before

SELECT * FROM list1 JOIN list2 ON list1.color = list2.color;

✓ After

SELECT * FROM list1 JOIN list2 ON (list1.color = list2.color OR (list1.color IS NULL AND list2.color IS NULL));

What It Enables

This concept lets you accurately combine data from different sources even when some values are missing, making your results trustworthy and complete.

Real Life Example

In a customer database, some customers might not have provided their phone number. When joining with a support ticket list by phone number, handling NULLs properly ensures you don't miss matching customers who share missing phone numbers.

Key Takeaways

NULLs represent unknown or missing data, which needs special handling in JOINs.

Direct comparisons with NULLs fail because NULL is not equal to anything, even NULL.

Using conditions that explicitly check for NULLs in JOINs ensures correct matching.

Practice

1. What happens when you use an INNER JOIN on columns that contain NULL values in SQL?

easy

A. Rows with NULL in join columns are always included.

B. Rows with NULL in join columns are excluded from the result.

C. The query returns an error due to NULL values.

D. Rows with NULL are treated as equal and joined together.

Solution

1. Step 1: Understand how INNER JOIN works with = condition

   When joining tables, SQL compares join columns using =. If a column has NULL, it means unknown, so comparison fails.

2. Step 2: Effect of NULL in join columns

   Since NULL = NULL is not true, rows with NULL in join columns do not match and are excluded.

3. Final Answer:

   Rows with NULL in join columns are excluded from the result. -> Option B

4. Quick Check:

   NULL means unknown, so no match [OK]

Hint: Remember: NULL never equals NULL in joins [OK]

Common Mistakes:

• Assuming NULL equals NULL in join conditions
• Expecting NULL rows to appear in INNER JOIN results
• Thinking NULL causes query errors in JOIN

2. Which of the following SQL JOIN syntaxes correctly includes rows with NULL values in the join column from the left table?

easy

A. SELECT * FROM A INNER JOIN B ON A.id = B.id;

B. SELECT * FROM A RIGHT JOIN B ON A.id = B.id;

C. SELECT * FROM A LEFT JOIN B ON A.id = B.id;

D. SELECT * FROM A FULL JOIN B ON A.id = B.id WHERE A.id IS NOT NULL;

Solution

1. Step 1: Identify JOIN types that keep left table rows

   LEFT JOIN keeps all rows from the left table, including those with NULL in join columns.

2. Step 2: Check other options

   INNER JOIN excludes unmatched rows; RIGHT JOIN keeps right table rows; FULL JOIN keeps all but filtering with WHERE A.id IS NOT NULL removes left table NULLs.

3. Final Answer:

   SELECT * FROM A LEFT JOIN B ON A.id = B.id; -> Option C

4. Quick Check:

   LEFT JOIN keeps left rows even if join column is NULL [OK]

Hint: Use LEFT JOIN to keep left table NULL rows [OK]

Common Mistakes:

• Using INNER JOIN expecting NULL rows to appear
• Filtering NULLs after FULL JOIN with WHERE clause
• Confusing RIGHT JOIN with LEFT JOIN behavior

3. Given tables:
Table A: id
1
2
NULL

Table B: id
2
NULL

What is the result of this query?

SELECT A.id, B.id FROM A INNER JOIN B ON A.id = B.id;

medium

A. (1, 2), (2, 2), (NULL, NULL)

B. (NULL, NULL)

C. (1, 2), (2, 2)

D. (2, 2)

Solution

1. Step 1: Understand INNER JOIN with NULLs

   INNER JOIN matches rows where A.id = B.id. NULLs do not match anything, even NULL.

2. Step 2: Check matching rows

   Only A.id = 2 matches B.id = 2. Rows with NULL do not match.

3. Final Answer:

   (2, 2) -> Option D

4. Quick Check:

   NULLs do not match, only 2 joins [OK]

Hint: NULLs never match in INNER JOIN conditions [OK]

Common Mistakes:

• Including NULL = NULL as a match
• Assuming all rows join regardless of NULL
• Confusing INNER JOIN with OUTER JOIN behavior

4. You wrote this query:

SELECT * FROM A LEFT JOIN B ON A.id = B.id WHERE B.id IS NOT NULL;

But it returns no rows, even though you expect rows from A with NULL id. What is the likely problem?

medium

A. The WHERE B.id IS NOT NULL filters out all rows including those with NULL in A.id.

B. LEFT JOIN does not include rows with NULL in join columns.

C. You should use INNER JOIN instead of LEFT JOIN.

D. The join condition A.id = B.id causes a syntax error.

Solution

1. Step 1: Understand LEFT JOIN with WHERE filter

   LEFT JOIN keeps all A rows, but WHERE B.id IS NOT NULL filters only rows where B.id is NOT NULL after join.

2. Step 2: Effect on rows with NULL in A.id

   Rows with NULL in A.id do not match B.id, so B.id is NULL after the join. The WHERE B.id IS NOT NULL condition excludes these rows.

3. Final Answer:

   The WHERE B.id IS NOT NULL filters out all rows including those with NULL in A.id. -> Option A

4. Quick Check:

   WHERE filters after join, can exclude expected rows [OK]

Hint: Remember WHERE filters after JOIN, can exclude NULL rows [OK]

Common Mistakes:

• Thinking LEFT JOIN excludes NULL join columns
• Using INNER JOIN expecting NULL rows
• Assuming join condition causes syntax error

5. You want to join tables A and B on id columns, but include rows where id is NULL in either table. Which query correctly returns all rows from both tables, matching on id including NULLs treated as equal?

hard

A. SELECT * FROM A FULL JOIN B ON A.id = B.id OR (A.id IS NULL AND B.id IS NULL);

B. SELECT * FROM A FULL JOIN B ON A.id = B.id;

C. SELECT * FROM A INNER JOIN B ON A.id = B.id OR (A.id IS NULL AND B.id IS NULL);

D. SELECT * FROM A LEFT JOIN B ON A.id = B.id WHERE A.id IS NOT NULL;

Solution

1. Step 1: Understand FULL JOIN and NULL behavior

   FULL JOIN returns all rows from both tables, but A.id = B.id excludes NULL matches because NULL = NULL is false.

2. Step 2: Add explicit NULL check in join condition

   Using OR (A.id IS NULL AND B.id IS NULL) treats NULLs as equal, including those rows in join results.

3. Step 3: Check other options

   SELECT * FROM A FULL JOIN B ON A.id = B.id;

   excludes NULL matches;

   SELECT * FROM A INNER JOIN B ON A.id = B.id OR (A.id IS NULL AND B.id IS NULL);

   uses INNER JOIN, excluding unmatched rows;

   SELECT * FROM A LEFT JOIN B ON A.id = B.id WHERE A.id IS NOT NULL;

   filters out NULLs.

4. Final Answer:

   SELECT * FROM A FULL JOIN B ON A.id = B.id OR (A.id IS NULL AND B.id IS NULL); -> Option A

5. Quick Check:

   Explicit NULL checks in JOIN condition include NULL matches [OK]

Hint: Add IS NULL checks in JOIN to match NULLs explicitly [OK]

Common Mistakes:

• Assuming NULL = NULL matches automatically
• Using INNER JOIN instead of FULL JOIN for all rows
• Filtering NULLs unintentionally with WHERE clause