What is CASE Expression?
CASE is like an "IF-THEN-ELSE" statement that you can use directly inside your SQL queries. It allows you to add conditional logic to transform or categorize your data.
Think of it like this:
IF condition1 is true THEN do this
ELSE IF condition2 is true THEN do that
ELSE do something elseThe CASE expression in MySQL is a powerful tool that allows you to implement conditional logic (similar to IF-ELSE) directly in your SQL queries.
This is not the same as the CASE statement, which is used inside stored programs (like stored procedures or triggers). Here, we focus on the CASE expression, which is used within SELECT, WHERE, ORDER BY, and other clauses.
Why Use CASE?
Understanding CASE Expressions: The Power of Conditional Logic in Databases
CASE expressions are one of the most powerful tools in SQL because they bring conditional logic directly into your database queries. Think of them as the database equivalent of "if-then-else" decision making that allows you to transform, categorize, and manipulate data on the fly. The followings are core benefits of using CASE
1. Transform Raw Data into Readable Labels
2. Categorize Data into Groups
3. Apply Conditional Sorting
4. Create Conditional Calculations
Forms of CASE Expression
The CASE expression has two forms: simple CASE and searched CASE.
Quick Comparison:
Simple CASE | Searched CASE |
Compares ONE value against multiple options | Evaluates multiple different conditions |
Uses = (equality) only | Can use >, <, BETWEEN, IS NULL, etc. |
Cannot handle NULL comparisons | Can handle NULL values |
Better for fixed categories | Better for ranges and complex logi |
1. Simple CASE Expression
2. Searched CASE Expression
3. Simple CASE vs Searched CASE
4. Where Can You Use CASE?
5. MySQL CASE expression examples
Practical Examples
Example 1: Customer Segmentation
Example 2: Conditional Sorting
Example 3: Cross-Tab Report with Aggregation
Advanced Examples
Example 1: Multi-Condition Logic
Example 2: Nested CASE Expressions
Best Practices
1. Always Include ELSE Clause
2. Order Conditions Properly
3. Use Appropriate CASE Type
4. Consider Performance
Common Mistakes to Avoid
1. Using Simple CASE with NULL
2. Forgetting Data Type Consistency
3. Not Considering All Possible Values
Practice Exercises
Exercise 1: Basic Transformation
Create a query that transforms product ratings (1-5) into descriptive text:
- 5: "Excellent"
- 4: "Good"
- 3: "Average"
- 2: "Poor"
- 1: "Terrible"
Exercise 2: Conditional Aggregation
Count how many employees are in each salary range:
- High: > $80,000
- Medium: $50,000 - $80,000
- Low: < $50,000
Exercise 3: Complex Conditions
Create a shipping cost calculator:
- If weight > 10kg AND distance > 100km: $25
- If weight > 10kg OR distance > 100km: $15
- Otherwise: $10
CASE with Aggregate Functions - Advanced Extension
What is CASE with Aggregate Functions?
CASE expressions become extremely powerful when combined with aggregate functions like COUNT(), SUM(), AVG(), MAX(), and MIN(). This technique allows you to:
- Count different categories in a single query
- Calculate conditional sums (e.g., total sales by region)
- Create pivot-like reports without complex joins
- Generate cross-tabulation summaries
The Core Concept: Conditional Counting
Detailed Examples
Different Aggregate Functions with CASE
Creating Pivot Tables with CASE
Performance Tips
Common Patterns and Templates
Common Mistakes and Solutions
Practice Exercises
Summary: CASE with Aggregates
Key Benefits:
- ✅ Reduce Query Count: Get multiple metrics in one query
- ✅ Create Pivot Reports: Transform rows into columns
- ✅ Conditional Calculations: Apply different logic based on conditions
- ✅ Flexible Grouping: Analyze data across multiple dimensions
Remember:
- Use
SUM(CASE WHEN ... THEN 1 ELSE 0 END)for conditional counting - Use
COUNT(CASE WHEN ... THEN 1 END)as alternative (no ELSE needed) - Use
AVG(CASE WHEN ... THEN value END)for conditional averages - Always consider performance with proper indexing
- Test your logic with small datasets first
Pro Tip: CASE with aggregates is perfect for dashboard queries and business intelligence reports where you need to summarize data across multiple dimensions in a single result set!
Quiz: Test Your CASE Expression Knowledge
Question 1: Conditional Counting
Question 2: Creating a Pivot Table
Question 3: Conditional Aggregation
Question 4: Advanced Pivot
Question 5: Fill in the Blank
Your Score
How many did you get right?