COUNT(*) vs COUNT(column) difference in SQL - Visual Side-by-Side Comparison

Concept Flow - COUNT(*) vs COUNT(column) difference

Start Query

↓

COUNT(*) counts all rows

↓

COUNT(column) counts non-NULL values in that column

↓

Return count result

↓

End Query

The query starts, then COUNT(*) counts every row regardless of NULLs, while COUNT(column) counts only rows where the column is not NULL, then returns the count.

Execution Sample

SQL

SELECT COUNT(*) AS total_rows, COUNT(age) AS age_count FROM people;

Counts total rows and counts only rows where 'age' is not NULL in the 'people' table.

Execution Table

Step	Row ID	age Value	COUNT(*) Running Total	COUNT(age) Running Total
1	1	25	1	1
2	2	NULL	2	1
3	3	30	3	2
4	4	NULL	4	2
5	5	22	5	3
Exit	-	-	-	All rows processed

💡 All 5 rows processed; COUNT(*) counts all rows, COUNT(age) counts only non-NULL ages

Variable Tracker

Variable	Start	After 1	After 2	After 3	After 4	After 5	Final
COUNT(*)	0	1	2	3	4	5	5
COUNT(age)	0	1	1	2	2	3	3

Key Moments - 2 Insights

Why does COUNT(*) count more rows than COUNT(age)?

COUNT(*) counts every row no matter what, but COUNT(age) only counts rows where 'age' is not NULL, as shown in execution_table rows 2 and 4 where age is NULL and COUNT(age) does not increase.

Does COUNT(column) count rows with NULL values in that column?

No, COUNT(column) skips NULL values. In the execution_table, rows with NULL age do not increase COUNT(age), unlike COUNT(*) which counts all rows.

Visual Quiz - 3 Questions

Look at the execution_table, what is COUNT(age) after processing row 3?

A 1

B 2

C 3

D 0

💡 Hint

Check the 'COUNT(age) Running Total' column at Step 3 in the execution_table.

At which step does COUNT(*) first differ from COUNT(age)?

A Step 3

B Step 1

C Step 2

D Step 5

💡 Hint

Look at the running totals for COUNT(*) and COUNT(age) in execution_table rows 1 and 2.

If all 'age' values were NOT NULL, how would COUNT(*) and COUNT(age) compare?

A Both would be equal

B COUNT(age) would be greater

C COUNT(*) would be greater

D Cannot determine

💡 Hint

Consider how COUNT(age) counts only non-NULL values and COUNT(*) counts all rows.

Concept Snapshot

COUNT(*) counts all rows in a table, including those with NULLs.
COUNT(column) counts only rows where the specified column is NOT NULL.
Use COUNT(*) to get total rows.
Use COUNT(column) to count non-NULL entries in that column.
They differ when the column has NULL values.
Both return a single number as result.

Full Transcript

This visual execution shows how COUNT(*) and COUNT(column) work differently in SQL. COUNT(*) counts every row regardless of NULLs, while COUNT(column) counts only rows where the column has a value (not NULL). The example table has 5 rows with some NULL ages. The execution table traces counting step-by-step, showing COUNT(*) increases every row, but COUNT(age) only increases when age is not NULL. This helps beginners see why counts differ and when to use each function.

Practice

1. What is the main difference between COUNT(*) and COUNT(column_name) in SQL?

easy

A. COUNT(*) counts only rows where all columns are NOT NULL, COUNT(column_name) counts all rows.

B. COUNT(*) and COUNT(column_name) always return the same result.

C. COUNT(*) counts only NULL values, COUNT(column_name) counts non-NULL values.

D. COUNT(*) counts all rows, while COUNT(column_name) counts only rows where the column is NOT NULL.

Solution

1. Step 1: Understand COUNT(*)

   COUNT(*) counts every row in the table, including those with NULL values in any column.

2. Step 2: Understand COUNT(column_name)

   COUNT(column_name) counts only rows where the specified column is NOT NULL, ignoring rows where that column is NULL.

3. Final Answer:

   COUNT(*) counts all rows; COUNT(column_name) counts only non-NULL values in that column. -> Option D

4. Quick Check:

   COUNT(*) counts all rows, COUNT(column) skips NULLs [OK]

Hint: Remember: * counts all rows, column counts non-NULL only [OK]

Common Mistakes:

• Thinking COUNT(column) counts NULL values
• Assuming COUNT(*) ignores NULLs
• Believing both always return same count

2. Which of the following SQL queries correctly counts the number of rows where the column email is NOT NULL?

easy

A. SELECT COUNT(email) FROM users;

B. SELECT COUNT(*) FROM users WHERE email IS NULL;

C. SELECT COUNT(email) FROM users WHERE email IS NULL;

D. SELECT COUNT(*) FROM users;

Solution

1. Step 1: Analyze COUNT(email)

   COUNT(email) counts only rows where email is NOT NULL, so it already filters NULLs.

2. Step 2: Check the WHERE clause necessity

   Adding WHERE email IS NOT NULL is redundant with COUNT(email), so SELECT COUNT(email) FROM users; is correct and simpler.

3. Final Answer:

   SELECT COUNT(email) FROM users; -> Option A

4. Quick Check:

   COUNT(column) counts non-NULL rows without WHERE [OK]

Hint: COUNT(column) counts non-NULL rows without extra WHERE [OK]

Common Mistakes:

• Adding unnecessary WHERE clause with COUNT(column)
• Using COUNT(*) with wrong WHERE condition
• Confusing NULL and NOT NULL filters

3. Given the table orders with 5 rows where the discount column has values: 10, NULL, 5, NULL, 0, what will be the result of SELECT COUNT(*) AS total, COUNT(discount) AS discount_count FROM orders;?

medium

A. total = 5, discount_count = 3

B. total = 5, discount_count = 5

C. total = 3, discount_count = 3

D. total = 3, discount_count = 5

Solution

1. Step 1: Count total rows with COUNT(*)

   COUNT(*) counts all 5 rows regardless of NULLs.

2. Step 2: Count non-NULL discount values with COUNT(discount)

   Only 3 rows have non-NULL discount values (10, 5, 0), so discount_count is 3.

3. Final Answer:

   total = 5, discount_count = 3 -> Option A

4. Quick Check:

   COUNT(*) = all rows, COUNT(column) = non-NULL rows [OK]

Hint: COUNT(*) counts all rows; COUNT(column) skips NULLs [OK]

Common Mistakes:

• Counting NULLs in COUNT(column)
• Confusing total rows with non-NULL counts
• Assuming 0 is NULL

4. You wrote this query: SELECT COUNT(column_name) FROM table_name; but it returns 0. The column has some NULL and some non-NULL values. What is the most likely problem?

medium

A. COUNT(column_name) counts NULL values, so it should not return 0.

B. The column_name is misspelled or does not exist in the table.

C. COUNT(*) should be used instead of COUNT(column_name) to count non-NULL values.

D. The table is empty, so COUNT(column_name) returns 0.

Solution

1. Step 1: Check column existence

   If COUNT(column_name) returns 0 but column has non-NULL values, likely the column name is wrong or missing.

2. Step 2: Understand COUNT behavior

   COUNT(column_name) counts non-NULL values; if column exists and has non-NULLs, result won't be zero.

3. Final Answer:

   Column name is misspelled or does not exist. -> Option B

4. Quick Check:

   Wrong column name causes zero count [OK]

Hint: Check column spelling if COUNT(column) returns zero unexpectedly [OK]

Common Mistakes:

• Assuming COUNT(column) counts NULLs
• Using COUNT(*) when column is misspelled
• Ignoring empty table possibility without checking

5. You have a table employees with 100 rows. The phone_number column has 80 non-NULL values and 20 NULLs. You want to find how many employees have a phone number and how many total employees there are. Which query gives both counts correctly?

hard

A. SELECT COUNT(phone_number) + COUNT(*) AS total FROM employees;

B. SELECT COUNT(*) AS with_phone, COUNT(phone_number) AS total_employees FROM employees;

C. SELECT COUNT(phone_number) AS with_phone, COUNT(*) AS total_employees FROM employees;

D. SELECT COUNT(phone_number) AS total_employees, COUNT(*) AS with_phone FROM employees;

Solution

1. Step 1: Count employees with phone numbers

   COUNT(phone_number) counts only non-NULL phone numbers, so it returns 80.

2. Step 2: Count total employees

   COUNT(*) counts all rows, so it returns 100.

3. Final Answer:

   SELECT COUNT(phone_number) AS with_phone, COUNT(*) AS total_employees FROM employees; -> Option C

4. Quick Check:

   COUNT(phone_number) = 80, COUNT(*) = 100 [OK]

Hint: Use COUNT(column) for non-NULL, COUNT(*) for total rows [OK]

Common Mistakes:

• Swapping counts in SELECT clause
• Adding counts instead of separate columns
• Confusing which count counts NULLs