Mastering the Essentials of SQL

June 16, 2024 (3w ago)

This guide dives into essential SQL queries and techniques

SQL (Structured Query Language) is a powerful tool for managing and manipulating databases. Whether you're extracting data, updating records, or analyzing information, SQL provides a variety of commands to perform these tasks efficiently. In this blog post, we'll explore some fundamental SQL queries using an example database with tables like employees, salaries, and titles.

Basic SELECT Statements

To retrieve all records from a table, the SELECT * statement is used:

SELECT * FROM employees;
SELECT * FROM salaries;

If you only need specific columns, you can specify them in the SELECT statement:

SELECT emp_no FROM employees;

SELECT birth_date, first_name, emp_no
FROM employees;

Aliasing Columns

Sometimes, you may want to rename columns in your query results for better readability. This is done using the AS keyword:

SELECT emp_no AS "Personalnummer", title
FROM titles;

Removing Duplicates

The DISTINCT keyword ensures that only unique values are returned:

SELECT DISTINCT title
FROM titles;

SELECT DISTINCT first_name AS "Vorname"
FROM employees;

Filtering Data with WHERE Clause

The WHERE clause is used to filter records based on specific conditions:

SELECT first_name, birth_date
FROM employees
WHERE birth_date = '1960-04-15';

SELECT *
FROM employees
WHERE last_name = 'Bale' AND gender = 'F';

SELECT *
FROM employees
WHERE last_name = 'Bale' AND gender = 'F' AND first_name = 'Lena';

Using IN for Multiple Values

The IN keyword provides a concise way to specify multiple values in a WHERE clause:

SELECT *
FROM titles
WHERE title IN ('Engineer', 'Senior Engineer', 'Assistant Engineer')
  AND to_date = '9999-01-01';

SELECT *
FROM titles
WHERE title IN ('Staff', 'Senior Staff')
  AND from_date = '1995-12-03';

Comparison Operators

SQL supports various comparison operators to refine your queries further:

SELECT *
FROM titles
WHERE title IN ('Staff', 'Senior Staff')
  AND from_date < '1995-12-03'; // Can also use >, !=, >=, etc.

SELECT *
FROM titles
WHERE title IN ('Staff', 'Senior Staff')
  AND from_date BETWEEN '1995-12-03' AND '2002-12-31';

SELECT *
FROM titles
WHERE title NOT IN ('Staff', 'Senior Staff')
  AND from_date BETWEEN '1995-12-03' AND '2002-12-31';

Pattern Matching with LIKE

The LIKE operator is used for pattern matching in SQL:

SELECT *
FROM employees 
WHERE first_name LIKE 'G%'; // Matches any first name starting with 'G'

SELECT *
FROM employees 
WHERE hire_date LIKE '1995%'; // Matches any hire date in the year 1995

SELECT *
FROM employees 
WHERE first_name NOT LIKE 'G%'; // Excludes any first name starting with 'G'

Aggregating Data

SQL provides aggregation functions like COUNT, MAX, MIN, and AVG to perform calculations on your data:

SELECT count(*)
FROM employees
WHERE gender = 'F';

SELECT
  emp_no AS "Personalnummer",
  count(*) AS "Gehälter",
  max(salary) AS "Höchste_Gehalt",
  min(salary) AS "Kleinste_Gehalt",
  max(salary) - min(salary) AS "Gehaltsdifferenz",
  avg(salary) AS "Durschnittsgehalt"
FROM salaries
GROUP BY emp_no;

Understanding GROUP BY

The GROUP BY clause is used in conjunction with aggregate functions (such as COUNT, MAX, MIN, AVG, etc.) to group the result set by one or more columns. This allows you to perform aggregations on each group of data separately.

For example, in the query:

SELECT
  emp_no AS "Personalnummer",
  count(*) AS "Gehälter",
  max(salary) AS "Höchste_Gehalt",
  min(salary) AS "Kleinste_Gehalt",
  max(salary) - min(salary) AS "Gehaltsdifferenz",
  avg(salary) AS "Durschnittsgehalt"
FROM salaries
GROUP BY emp_no;

This query groups the salaries table by the emp_no column. For each emp_no, it calculates:

  • The total number of salaries (count(*) AS "Gehälter"),
  • The highest salary (max(salary) AS "Höchste_Gehalt"),
  • The lowest salary (min(salary) AS "Kleinste_Gehalt"),
  • The difference between the highest and lowest salary (max(salary) - min(salary) AS "Gehaltsdifferenz"),
  • The average salary (avg(salary) AS "Durschnittsgehalt").

You can also filter aggregated results using the HAVING clause:

SELECT
  emp_no AS "Personalnummer",
  count(*) AS "Gehälter",
  max(salary) AS "Höchste_Gehalt"
FROM salaries
WHERE emp_no > 10300
GROUP BY emp_no
HAVING max(salary) > 100000;

Joining Tables

SQL joins allow you to combine records from two or more tables based on related columns:

SELECT *
FROM employees e
INNER JOIN salaries s ON e.emp_no = s.emp_no;

SELECT
  first_name,
  last_name,
  salary
FROM employees e
INNER JOIN salaries s ON e.emp_no = s.emp_no
WHERE salary > 100000 AND to_date = '9999-01-01';

SELECT
  first_name,
  last_name,
  salary,
  title
FROM employees e
INNER JOIN salaries s ON e.emp_no = s.emp_no
INNER JOIN titles t ON e.emp_no = t.emp_no
WHERE salary > 100000 AND s.to_date = '9999-01-01'
  AND t.to_date = '9999-01-01';

SELECT
  first_name,
  last_name,
  salary,
  title
FROM employees e
INNER JOIN salaries s ON e.emp_no = s.emp_no
INNER JOIN titles t ON e.emp_no = t.emp_no
INNER JOIN dept_manager dm ON e.emp_no = dm.emp_no
WHERE salary > 100000 AND s.to_date = '9999-01-01'
  AND t.to_date = '9999-01-01'
  AND dm.to_date = '9999-01-01';

Working with Left and Right Joins

Left and right joins include all records from one table and the matched records from the other:

SELECT *
FROM employees e
LEFT JOIN salaries s ON e.emp_no = s.emp_no;

SELECT *
FROM employees e
LEFT JOIN salaries s ON e.emp_no = s.emp_no
WHERE s.emp_no IS NULL;

SELECT *
FROM employees e
RIGHT JOIN salaries s ON e.emp_no = s.emp_no;

Creating and Modifying Tables

Creating and modifying database structures is another crucial aspect of SQL:

-- Create the database
CREATE DATABASE Cars;

-- Use the newly created database
USE Cars;

-- Create the table with specified columns
CREATE TABLE CarDetails (
    CarID INT PRIMARY KEY AUTO_INCREMENT,
    Make VARCHAR(50) NOT NULL,
    Model VARCHAR(50) NOT NULL,
    Year INT NOT NULL,
    Price DECIMAL(10, 2) NOT NULL
);

-- Insert sample data into the table
INSERT INTO CarDetails (Make, Model, Year, Price)
VALUES
    ('Toyota', 'Camry', 2020, 24000.00),
    ('Honda', 'Civic', 2019, 22000.00),
    ('Ford', 'Mustang', 2021, 26000.00),
    ('Chevrolet', 'Malibu', 2018, 21000.00);

To add a new column and update existing rows with random colors:

-- Add a new column
ALTER TABLE CarDetails
ADD COLUMN Color VARCHAR(20);

-- Temporarily disable safe update mode
SET SQL_SAFE_UPDATES = 0;

-- Updating rows with random colors
SET @colors = 'Red,Blue,Green,Black,White,Silver,Gray';

-- Split the colors into a temporary table
CREATE TEMPORARY TABLE TempColors (Color VARCHAR(20));

-- Insert colors into the temporary table
INSERT INTO TempColors (Color)
SELECT SUBSTRING_INDEX(SUBSTRING_INDEX(@colors, ',', numbers.n), ',', -1) 
FROM (
    SELECT 1 n UNION ALL SELECT 2 UNION ALL SELECT 3 UNION ALL SELECT 4 
    UNION ALL SELECT 5 UNION ALL SELECT 6 UNION ALL SELECT 7
) numbers;

-- Update CarDetails with random colors
UPDATE CarDetails 
SET Color = (
    SELECT Color 
    FROM TempColors 
    ORDER BY RAND() 
    LIMIT 1
);

-- Drop the temporary table
DROP TEMPORARY TABLE TempColors;

-- Re-enable safe update mode
SET SQL_SAFE_UPDATES = 1;

To update specific rows and delete records, you can use the UPDATE and DELETE statements:

UPDATE CarDetails
SET Color = 'Silver'
WHERE CarID = 1;

DELETE FROM CarDetails
WHERE CarID = 2;

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