CASE with aggregate functions in SQL - Time & Space Complexity

Time Complexity: CASE with aggregate functions

O(n)

Understanding Time Complexity

We want to understand how the time to run a SQL query with CASE inside aggregate functions changes as the data grows.

Specifically, how does the query's work increase when there are more rows to process?

Scenario Under Consideration

Analyze the time complexity of the following SQL query.

SELECT
  department_id,
  SUM(CASE WHEN status = 'active' THEN salary ELSE 0 END) AS active_salary,
  COUNT(CASE WHEN status = 'inactive' THEN 1 ELSE NULL END) AS inactive_count
FROM employees
GROUP BY department_id;

This query calculates total salary for active employees and counts inactive employees per department.

Identify Repeating Operations

Look for repeated actions in the query.

• Primary operation: Scanning each row in the employees table once.
• How many times: Once per row, applying the CASE checks and updating sums or counts.

How Execution Grows With Input

As the number of rows grows, the query does more work.

Input Size (n)	Approx. Operations
10	About 10 row checks and updates
100	About 100 row checks and updates
1000	About 1000 row checks and updates

Pattern observation: The work grows directly with the number of rows; doubling rows roughly doubles work.

Final Time Complexity

Time Complexity: O(n)

This means the query's work grows in a straight line with the number of rows it processes.

Common Mistake

[X] Wrong: "Using CASE inside aggregates makes the query slower than scanning all rows once."

[OK] Correct: The CASE just adds a quick check per row; the query still scans each row only once, so it doesn't multiply the work.

Interview Connect

Understanding how aggregate functions with CASE scale helps you explain query performance clearly and confidently.

Self-Check

"What if we added a nested subquery inside the CASE? How would that affect the time complexity?"

Practice

1. What does the following SQL snippet do?
SELECT SUM(CASE WHEN status = 'active' THEN 1 ELSE 0 END) FROM users;

easy

A. Counts how many users have status other than 'active'.

B. Calculates the total number of users regardless of status.

C. Returns the sum of all status values.

D. Counts how many users have status 'active'.

Solution

1. Step 1: Understand the CASE inside SUM

   The CASE returns 1 for each row where status is 'active', else 0.

2. Step 2: SUM adds all 1s and 0s

   SUM counts how many rows have status 'active' by adding 1s.

3. Final Answer:

   Counts how many users have status 'active'. -> Option D

4. Quick Check:

   SUM(CASE WHEN condition THEN 1 ELSE 0 END) counts matches [OK]

Hint: SUM with CASE counting 1s counts matching rows [OK]

Common Mistakes:

• Thinking SUM adds status values instead of counting
• Confusing ELSE 0 with ELSE NULL
• Assuming it counts non-active users

2. Which of the following is the correct syntax to count rows where score is greater than 50 using CASE inside COUNT?

easy

A. SELECT COUNT(CASE WHEN score > 50 THEN 1 END) FROM results;

B. SELECT COUNT(CASE score > 50 THEN 1 ELSE 0 END) FROM results;

C. SELECT COUNT(CASE WHEN score > 50 THEN 1 ELSE 0 END) FROM results;

D. SELECT COUNT(CASE score > 50 THEN 1 END) FROM results;

Solution

1. Step 1: Recall COUNT counts non-null values

   COUNT counts rows where expression is NOT NULL.

2. Step 2: Use CASE to return 1 for matches, NULL otherwise

   CASE WHEN condition THEN 1 END returns 1 or NULL (default ELSE NULL).

3. Final Answer:

   SELECT COUNT(CASE WHEN score > 50 THEN 1 END) FROM results; -> Option A

4. Quick Check:

   COUNT with CASE returning NULL for no match counts only matches [OK]

Hint: COUNT counts non-null, so ELSE NULL is default [OK]

Common Mistakes:

• Using ELSE 0 causes COUNT to count all rows
• Omitting WHEN keyword
• Using invalid CASE syntax

3. Given the table sales with columns region and amount, what is the output of this query?

SELECT region, SUM(CASE WHEN amount > 100 THEN amount ELSE 0 END) AS big_sales FROM sales GROUP BY region;

medium

A. Sum of all sales amounts per region.

B. Sum of sales amounts greater than 100 per region.

C. Count of sales greater than 100 per region.

D. Sum of sales amounts less than or equal to 100 per region.

Solution

1. Step 1: Analyze CASE inside SUM

   CASE returns amount if > 100, else 0, so only big sales count fully.

2. Step 2: SUM adds these amounts per region

   SUM totals amounts > 100 per region, ignoring smaller sales by adding 0.

3. Final Answer:

   Sum of sales amounts greater than 100 per region. -> Option B

4. Quick Check:

   SUM with CASE filters values conditionally [OK]

Hint: SUM with CASE ELSE 0 sums only matching values [OK]

Common Mistakes:

• Thinking it counts rows instead of sums amounts
• Ignoring ELSE 0 and expecting NULL filtering
• Confusing greater than with less than

4. Identify the error in this query:

SELECT department, COUNT(CASE department = 'HR' THEN 1 ELSE NULL END) FROM employees GROUP BY department;

medium

A. Missing WHEN keyword in CASE statement.

B. COUNT cannot be used with CASE.

C. GROUP BY should include COUNT column.

D. ELSE NULL is invalid in CASE.

Solution

1. Step 1: Check CASE syntax

   CASE requires WHEN before condition; here it's missing.

2. Step 2: Confirm correct syntax

   Correct form: CASE WHEN department = 'HR' THEN 1 ELSE NULL END.

3. Final Answer:

   Missing WHEN keyword in CASE statement. -> Option A

4. Quick Check:

   CASE syntax needs WHEN before condition [OK]

Hint: CASE must have WHEN before condition [OK]

Common Mistakes:

• Omitting WHEN keyword
• Misusing COUNT with CASE
• Incorrect GROUP BY usage

5. You want to find the average salary of employees, but only include salaries above 50000. Which query correctly uses CASE with AVG to achieve this?

hard

A. SELECT AVG(CASE WHEN salary > 50000 THEN salary ELSE 0 END) FROM employees;

B. SELECT AVG(CASE salary > 50000 THEN salary END) FROM employees;

C. SELECT AVG(CASE WHEN salary > 50000 THEN salary ELSE NULL END) FROM employees;

D. SELECT AVG(CASE salary > 50000 THEN salary ELSE NULL END) FROM employees;

Solution

1. Step 1: Understand AVG ignores NULLs

   AVG calculates average of non-null values only.

2. Step 2: Use CASE to return salary if > 50000, else NULL

   This excludes salaries ≤ 50000 from average calculation.

3. Final Answer:

   SELECT AVG(CASE WHEN salary > 50000 THEN salary ELSE NULL END) FROM employees; -> Option C

4. Quick Check:

   AVG with CASE ELSE NULL excludes unwanted rows [OK]

Hint: Use ELSE NULL to exclude rows from AVG calculation [OK]

Common Mistakes:

• Using ELSE 0 includes zeros in average, skewing result
• Omitting WHEN keyword
• Using invalid CASE syntax