DBMS: Week 07 - Advanced SQL Queries in MySQL

International Islamic University H-10, Islamabad, Pakistan
Database Managements Systems
Week 07
Advanced SQL Queries
Engr. Rashid Farid Chishti
http://youtube.com/rfchishti
http://sites.google.com/site/chisht
i

 Understand and apply aggregate functions in SQL
 Use GROUP BY to organize data into groups
 Apply HAVING to filter grouped data
Learning Objectives

 Definition: Functions that perform calculations on a set of values and return a
single value
 Common Aggregate Functions:
 COUNT() : Number of rows
 MAX() : Highest value
 MIN() : Lowest value
 SUM() : Total of numeric values
 AVG() : Average of numeric values
Aggregate Functions Overview

 First make a table
DROP database if exists week_07_db;
create database week_07_db;
use week_07_db;
CREATE TABLE Employee (
id INT AUTO_INCREMENT PRIMARY KEY,
name VARCHAR(100) NOT NULL,
department VARCHAR(50),
salary DECIMAL(10,2)
);

 Add some data;
INSERT INTO employee (name, department, salary)
VALUES
('Ahmed', 'IT', 60000.00),
('Fatima', 'HR', 50000.00),
('Omar', 'IT', 70000.00),
('Zainab', 'Finance', 55000.00),
('Ali', 'Marketing', 62000.00),
('Ayesha', 'HR', 48000.00),
('Hassan', 'IT', 72000.00),
('Khadija', 'Finance', 53000.00),
('Bilal', 'Marketing', 61000.00),
('Yusuf', 'IT', 65000.00);

 SUM() Example:
 AVG() Example:
 Use Case:
 Calculate total and average salaries for employee data
Using SUM() and AVG()
SELECT SUM(salary) FROM Employee;
SELECT AVG(salary) FROM Employee;

 COUNT() Example:
Using COUNT()
SELECT COUNT(*) FROM Employee
WHERE Department='IT';
SELECT COUNT(*) AS 'Marketing' FROM Employee
WHERE Department='Marketing';
SELECT COUNT(*) AS 'Total Emp' FROM Employee;

 MAX() Example:
 MIN() Example:
Using MAX() and MIN() Functions
SELECT MAX(salary) FROM Employee;
SELECT MAX(salary) FROM Employee
SELECT MIN(salary) FROM Employee;
SELECT MIN(salary) FROM Employee

ASC: Ascending Order
DESC: Descending
Order
ORDER BY: Column Name(s)
HAVING: Condition(s)
GROUP BY : Column Name(s)
WHERE: Condition(s)
JOIN: table ON
table.column
FROM: Name of Table(s)
DISTINCT: Name of Table
SELECT: retrieve data from one or more tables in a
database.
Data Query Language (DQL) Command
LIMIT: Number

 Purpose: Groups rows that have the same values into summary rows
 Syntax: SELECT column, COUNT(*) FROM table_name GROUP BY
column;
 Example:
Using GROUP BY Command for Organizing Data
SELECT department, COUNT(*) FROM Employee
GROUP BY department;
GROUP BY department ORDER BY department ASC;
SELECT department, COUNT(*)
FROM Employee
GROUP BY department
ORDER BY COUNT(*) DESC, department ASC;

 Purpose: Filters grouped records
 Syntax:
SELECT column, COUNT(*) FROM table_name
GROUP BY column HAVING COUNT(*) > 10;
 Example:
 Difference from WHERE:
 WHERE filters rows before grouping. HAVING filters after grouping
Filtering Groups with HAVING
GROUP BY department HAVING COUNT(*) > 2;
GROUP BY department HAVING COUNT(*) > 1
ORDER BY department ASC;

 Example:
SELECT category, AVG(price) FROM Products GROUP BY category;
 Use Case:
 Calculate average salary in each department.
Combining GROUP BY and Aggregate Functions
SELECT department, AVG(salary) FROM
Employee
GROUP BY department
ORDER BY AVG(salary) DESC;

 Definition: Query within another query
 Example:
 Use Case: Retrieve employees earning more than the average salary
 Use Case: Retrieve employees earning less than or equal to the average salary
Nested Queries (Subqueries)
SELECT * FROM Employee WHERE salary >
(SELECT AVG(salary) FROM Employee);
SELECT * FROM Employee WHERE salary <=
(SELECT AVG(salary) FROM Employee);

 SELECT Subquery Example:
SELECT name, (SELECT AVG(salary) FROM Employees) AS avg_salary
FROM Employees;
 FROM Subquery Example:
SELECT * FROM (SELECT * FROM Orders WHERE status = 'Pending')
AS PendingOrders;
Subqueries in SELECT and FROM

 Calculate the total number of students in each major
 Retrieve departments where more than 10 employees work
 Find the highest salary in each department
 List all orders with prices above the average order price
Practical Exercises

 Incorrect Grouping: Grouping on columns not in SELECT
 HAVING Misuse: Using HAVING without GROUP BY
 Nested Query Errors: Incorrect subquery syntax
Common Errors in Advanced SQL Queries

 Break down complex queries step by step
 Use aliases for subqueries to improve readability
 Test subqueries individually before integrating them
Best Practices for Advanced Queries

 Aggregate functions allow data summarization
 GROUP BY organizes data, and HAVING filters grouped results
 Subqueries enable more dynamic and complex data retrieval
Best Practices for Advanced Queries

DBMS: Week 07 - Advanced SQL Queries in MySQL

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