So far in this course, every query we’ve written has done one simple thing: 👉 It fetched rows exactly as they exist in the database. For example: SELECT FROM users;
MSMuhammad SufiyanSoftware Engineer · Aug 8
Backend Engineering HubT-
So far in this course, every query we’ve written has done one simple thing:
👉 It fetched rows exactly as they exist in the database.
For example:
SELECT * FROM users;
This simply returns all rows.
But in real-world applications, we usually don’t just want raw rows.
We want insights like:
How many users are there?
What is the average salary?
How many orders did each user place?
What is the total revenue?
To answer questions like these, we use:
Aggregation
Grouping
Let’s break them down step by step.
🧮 1️⃣ Aggregation – Reducing Many Values Into One
Aggregation means:
Taking many values and reducing them into a single summarized value.
Think of it like calculating the total marks of a class.
🔹 Example Table: orders
id
amount
1
100
2
200
3
300
If we want the total sales:
SELECT SUM(amount) FROM orders;
Result:
600
We had 3 rows.
Now we have 1 single summarized value.
That is aggregation.
🔹 Common Aggregate Functions
Function
What It Does
COUNT()
Counts rows
SUM()
Adds values
AVG()
Calculates average
MAX()
Finds highest value
MIN()
Finds lowest value
🔸 Example: Count total users
SELECT COUNT(*) FROM users;
🔸 Example: Find average salary
SELECT AVG(salary) FROM employees;
🧠 Key Idea
Aggregation:
Many values ➜ One single value
🧩 2️⃣ GROUP BY – Dividing Rows Into Categories
Now comes the powerful concept: GROUP BY
GROUP BY means:
Divide rows into groups based on a column.
🎓 Real-Life Example
Imagine a students table:
name
city
Ali
Karachi
Ahmed
Lahore
Sana
Karachi
Bilal
Lahore
Fatima
Karachi
Now we ask:
How many students are from each city?
We need to group by city first.
SELECT city, COUNT(*)
FROM students
GROUP BY city;
Result:
city
count
Karachi
3
Lahore
2
Here’s what happened internally:
1. PostgreSQL looked at all rows. 2. It divided them into groups based on city. 3. Then it applied COUNT to each group.
🧠 Important Mental Model
Think of GROUP BY like sorting students into classrooms by city.
Then aggregation calculates something for each classroom.
📌 General Pattern
SELECT column_name, AGG_FUNCTION(column)
FROM table_name
GROUP BY column_name;
🚨 Common Beginner Mistake
This query will cause an error:
SELECT city, name
FROM students
GROUP BY city;
Why?
Because when you use GROUP BY:
Every selected column must either:
Be included in GROUP BY
OR be inside an aggregate function
Correct version:
SELECT city, COUNT(*)
FROM students
GROUP BY city;
🧮 Aggregation + Grouping Together
Now let’s combine both concepts.
Example Table: orders
id
user_id
amount
1
1
100
2
1
200
3
2
150
Question:
How much did each user spend in total?
SELECT user_id, SUM(amount)
FROM orders
GROUP BY user_id;
Result:
user_id
sum
1
300
2
150
This is how real business reporting works.
🔎 Difference Between GROUP BY and Aggregation
Concept
Purpose
Aggregation
Reduce many values into one
GROUP BY
Divide rows into categories
Together, they allow powerful data summaries.
🏢 Real-World Use Cases
Total revenue per month
Number of users per country
Average rating per product
Total orders per customer
Highest salary per department
🎯 Final Summary
Aggregation:
Reduces many values into one.
GROUP BY:
Divides rows into groups before applying aggregation.
Together:
They turn raw data into meaningful insights.
🧠 Practice Exercises
1. Count employees per department. 2. Find average salary per city. 3. Find highest order amount per user. 4. Count orders per month.
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