🛠️ SQL Cheat Sheet: Your Go-To Quick Reference Guide
📌 Introduction
QL Cheat Sheet: SQL (Structured Query Language) is the backbone of database management. Whether you are new to SQL or an experienced database professional, having a handy reference can make working with databases easier and more efficient. This cheat sheet provides a detailed yet easy-to-understand overview of essential SQL commands, helping you retrieve, manipulate, and manage data effectively.
🔎 Retrieving Data with SQL (SELECT Statements)
📜 SELECT – Fetch Specific Data
The SELECT statement is used to fetch data from a table. You can specify which columns you want to retrieve.
SELECT column1, column2 FROM table_name;✅ This will return only the specified columns from the given table.
🌟 SELECT * – Retrieve Everything
If you want to see all the data from a table, use SELECT *.
SELECT * FROM table_name;✅ Be cautious with this! Fetching all columns can slow down queries if the table is large.
🎭 DISTINCT – Remove Duplicate Entries
To return only unique values, use DISTINCT.
SELECT DISTINCT column_name FROM table_name;✅ This ensures that duplicate values in the selected column are not included.
🔍 WHERE – Filter Data Based on Conditions
To refine your query results, use the WHERE clause.
SELECT column_name FROM table_name WHERE condition;✅ Example: WHERE age > 30 will return only rows where the age is greater than 30.
📊 Sorting and Limiting Results
📌 ORDER BY – Sort Your Data
To sort your results, use ORDER BY with ASC (ascending) or DESC (descending).
SELECT column_name FROM table_name ORDER BY column_name ASC|DESC;✅ Example: ORDER BY price DESC will show the most expensive items first.
📌 LIMIT – Control How Many Rows Are Displayed
If you only need a certain number of records, use LIMIT.
SELECT column_name FROM table_name LIMIT number;✅ Example: LIMIT 5 will show only the top 5 results.
🔗 Joining Tables: Merging Data from Multiple Sources
🔄 INNER JOIN – Get Matching Records from Two Tables
The INNER JOIN retrieves only the rows that have matching values in both tables.
SELECT columns FROM table1 INNER JOIN table2 ON table1.column = table2.column;✅ Use this when you only need records that exist in both tables.
🔄 LEFT JOIN – Keep All Left Table Records
A LEFT JOIN returns all rows from the first (left) table and only matching rows from the second (right) table.
SELECT columns FROM table1 LEFT JOIN table2 ON table1.column = table2.column;✅ Use this if you want all records from the left table, even if there’s no match in the right table.
🔄 RIGHT JOIN – Keep All Right Table Records
A RIGHT JOIN is the opposite—it keeps all rows from the right table and only matching rows from the left table.
SELECT columns FROM table1 RIGHT JOIN table2 ON table1.column = table2.column;✅ This ensures no records from the right table are omitted.
✍️ Modifying Data (DML – Data Manipulation Language)
📌 INSERT – Add New Data
To add a new row into a table, use INSERT.
INSERT INTO table_name (column1, column2) VALUES (value1, value2);✅ Example: INSERT INTO students (name, age) VALUES ('John Doe', 25);
📌 UPDATE – Change Existing Data
To modify data in a table, use UPDATE.
UPDATE table_name SET column1 = value1 WHERE condition;✅ Example: UPDATE employees SET salary = 60000 WHERE id = 3;
📌 DELETE – Remove Records
To remove specific records, use DELETE.
DELETE FROM table_name WHERE condition;✅ Example: DELETE FROM customers WHERE last_purchase < '2020-01-01';
📈 Summarizing Data with Aggregate Functions
🔢 COUNT – Count the Number of Records
To count how many rows exist in a table:
SELECT COUNT(column_name) FROM table_name;✅ Example: SELECT COUNT(*) FROM orders; returns the total number of orders.
➕ SUM – Get the Total Value
To get the sum of a numeric column:
SELECT SUM(column_name) FROM table_name;✅ Example: SELECT SUM(sales) FROM revenue; gives the total sales amount.
📉 AVG – Calculate the Average
To find the average of a numeric column:
SELECT AVG(column_name) FROM table_name;✅ Example: SELECT AVG(price) FROM products; gives the average product price.
🔼 MAX & 🔽 MIN – Find Highest and Lowest Values
SELECT MAX(column_name) FROM table_name;
SELECT MIN(column_name) FROM table_name;✅ Example: SELECT MAX(salary) FROM employees; returns the highest salary.
🛠️ Advanced SQL Techniques
📌 GROUP BY – Group Data for Aggregation
To group data and perform calculations on each group:
SELECT column_name, COUNT(*) FROM table_name GROUP BY column_name;✅ Example: SELECT department, COUNT(*) FROM employees GROUP BY department;
📌 HAVING – Filter Aggregate Results
To filter results after aggregation:
SELECT column_name, COUNT(*) FROM table_name GROUP BY column_name HAVING COUNT(*) > 1;✅ Example: HAVING COUNT(*) > 10 ensures only groups with more than 10 entries appear.
📌 Subqueries – Queries Inside Queries
To use one query inside another:
SELECT column_name FROM table_name WHERE column_name = (SELECT column_name FROM another_table);✅ Example: Find employees earning more than the company average salary.
📌 CASE – Apply Conditional Logic in Queries
To add conditional logic within a query:
SELECT column_name,
CASE
WHEN condition1 THEN result1
WHEN condition2 THEN result2
ELSE result3
END
FROM table_name;✅ Example: Categorize ages as ‘Young’, ‘Middle-Aged’, or ‘Senior’.
🚀 SQL Performance Best Practices
- ✔️ Use Indexing – Speeds up searches significantly.
- ✔️ Avoid
SELECT *– Fetch only the necessary columns to improve performance. - ✔️ Normalize Data – Organize data efficiently to reduce redundancy.
- ✔️ Use Joins Instead of Subqueries – Joins often run faster than nested queries.
- ✔️ Filter Early – Apply conditions as soon as possible in your query.
🏁 Final Thoughts
Mastering SQL is a game-changer in handling databases effectively. With this cheat sheet, you have a solid reference for writing powerful queries. Keep practicing, experiment with different queries, and soon, you’ll be an SQL expert!
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💬 Have questions? Drop them in the comments below!