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SQL Cheatsheet

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Comprehensive SQL cheatsheet with SELECT, JOINs, INSERT/UPDATE/DELETE, aggregation, window functions, subqueries, and best practices. Use when needing quick reference for SQL queries, database operations, or common query patterns.

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SQL Cheatsheet

Quick reference for SQL queries and database operations.

📖 Basic SELECT

Retrieve Data

-- Select all columns
SELECT * FROM table_name;

-- Select specific columns
SELECT column1, column2 FROM table_name;

-- Select with alias
SELECT column1 AS alias1, column2 AS alias2 FROM table_name;

-- Distinct values
SELECT DISTINCT column FROM table_name;

-- Limit results
SELECT * FROM table_name LIMIT 10;

-- MySQL/PostgreSQL LIMIT with offset
SELECT * FROM table_name LIMIT 10 OFFSET 20;

-- SQL Server TOP
SELECT TOP 10 * FROM table_name;

WHERE Clause

-- Equality
SELECT * FROM table WHERE column = 'value';

-- Comparison
SELECT * FROM table WHERE column > 100;
SELECT * FROM table WHERE column <= 50;

-- Multiple conditions
SELECT * FROM table WHERE column1 = 'a' AND column2 > 10;
SELECT * FROM table WHERE column1 = 'a' OR column2 > 10;

-- IN clause
SELECT * FROM table WHERE column IN ('a', 'b', 'c');

-- BETWEEN
SELECT * FROM table WHERE column BETWEEN 1 AND 100;

-- LIKE (pattern matching)
SELECT * FROM table WHERE column LIKE 'prefix%';  -- Starts with
SELECT * FROM table WHERE column LIKE '%suffix';  -- Ends with
SELECT * FROM table WHERE column LIKE '%contains%';  -- Contains
SELECT * FROM table WHERE column LIKE '_attern';  -- Single char wildcard

-- IS NULL / IS NOT NULL
SELECT * FROM table WHERE column IS NULL;
SELECT * FROM table WHERE column IS NOT NULL;

-- NOT
SELECT * FROM table WHERE column NOT IN ('a', 'b');

ORDER BY

-- Ascending (default)
SELECT * FROM table ORDER BY column ASC;

-- Descending
SELECT * FROM table ORDER BY column DESC;

-- Multiple columns
SELECT * FROM table ORDER BY column1 ASC, column2 DESC;

🔗 JOINs

INNER JOIN (intersection)

SELECT a.*, b.*
FROM table_a a
INNER JOIN table_b b ON a.id = b.a_id;

LEFT JOIN (all from left)

SELECT a.*, b.*
FROM table_a a
LEFT JOIN table_b b ON a.id = b.a_id;

RIGHT JOIN (all from right)

SELECT a.*, b.*
FROM table_a a
RIGHT JOIN table_b b ON a.id = b.a_id;

FULL OUTER JOIN (all from both)

-- PostgreSQL, SQL Server
SELECT a.*, b.*
FROM table_a a
FULL OUTER JOIN table_b b ON a.id = b.a_id;

CROSS JOIN (cartesian product)

SELECT a.*, b.*
FROM table_a a
CROSS JOIN table_b b;

SELF JOIN

SELECT a.name, b.name AS manager_name
FROM employees a
LEFT JOIN employees b ON a.manager_id = b.id;

Multiple JOINs

SELECT o.*, c.name, p.product_name
FROM orders o
INNER JOIN customers c ON o.customer_id = c.id
INNER JOIN products p ON o.product_id = p.id;

➕ Aggregation

COUNT, SUM, AVG, MIN, MAX

-- Count rows
SELECT COUNT(*) FROM table;

-- Count non-null values
SELECT COUNT(column) FROM table;

-- Sum
SELECT SUM(column) FROM table;

-- Average
SELECT AVG(column) FROM table;

-- Minimum
SELECT MIN(column) FROM table;

-- Maximum
SELECT MAX(column) FROM table;

GROUP BY

-- Group by one column
SELECT category, COUNT(*)
FROM products
GROUP BY category;

-- Group by multiple columns
SELECT category, status, COUNT(*), SUM(price)
FROM products
GROUP BY category, status;

-- With WHERE (filter before grouping)
SELECT category, COUNT(*)
FROM products
WHERE price > 100
GROUP BY category;

HAVING (filter after grouping)

SELECT category, COUNT(*) as product_count
FROM products
GROUP BY category
HAVING COUNT(*) > 10;

-- HAVING with WHERE
SELECT category, COUNT(*)
FROM products
WHERE price > 100
GROUP BY category
HAVING COUNT(*) > 5;

GROUP BY + ORDER BY

SELECT category, SUM(price) as total
FROM products
GROUP BY category
ORDER BY total DESC;

➡️ Window Functions

Basic Window

-- Row number
SELECT
  name,
  department,
  salary,
  ROW_NUMBER() OVER (ORDER BY salary DESC) as rank
FROM employees;

-- Partition by department
SELECT
  name,
  department,
  salary,
  ROW_NUMBER() OVER (PARTITION BY department ORDER BY salary DESC) as dept_rank
FROM employees;

Ranking Functions

-- ROW_NUMBER: unique number, no ties
ROW_NUMBER() OVER (ORDER BY salary DESC)

-- RANK: gaps in ranking for ties
RANK() OVER (ORDER BY salary DESC)

-- DENSE_RANK: no gaps for ties
DENSE_RANK() OVER (ORDER BY salary DESC)

-- NTILE: divide into buckets
NTILE(4) OVER (ORDER BY salary DESC) as quartile

Aggregate Window Functions

SELECT
  name,
  department,
  salary,
  AVG(salary) OVER (PARTITION BY department) as dept_avg,
  SUM(salary) OVER (PARTITION BY department) as dept_total
FROM employees;

Running Total / Cumulative Sum

SELECT
  date,
  amount,
  SUM(amount) OVER (ORDER BY date) as running_total
FROM transactions;

📝 Subqueries & CTEs

Subquery in WHERE

SELECT *
FROM products
WHERE price > (SELECT AVG(price) FROM products);

Subquery in FROM

SELECT avg_price
FROM (
  SELECT category, AVG(price) as avg_price
  FROM products
  GROUP BY category
) AS category_avg
WHERE avg_price > 100;

Subquery in SELECT

SELECT
  name,
  (SELECT COUNT(*) FROM orders WHERE orders.customer_id = customers.id) as order_count
FROM customers;

EXISTS / NOT EXISTS

SELECT *
FROM customers c
WHERE EXISTS (
  SELECT 1 FROM orders o
  WHERE o.customer_id = c.id
);

Common Table Expressions (CTE)

WITH category_stats AS (
  SELECT
    category,
    COUNT(*) as count,
    AVG(price) as avg_price
  FROM products
  GROUP BY category
)
SELECT * FROM category_stats
WHERE count > 10;

Recursive CTE

WITH RECURSIVE employee_hierarchy AS (
  -- Anchor member
  SELECT id, name, manager_id, 1 as level
  FROM employees
  WHERE manager_id IS NULL

  UNION ALL

  -- Recursive member
  SELECT e.id, e.name, e.manager_id, eh.level + 1
  FROM employees e
  JOIN employee_hierarchy eh ON e.manager_id = eh.id
)
SELECT * FROM employee_hierarchy;

✏️ Modify Data

INSERT

-- Insert single row
INSERT INTO table (column1, column2)
VALUES ('value1', 'value2');

-- Insert multiple rows
INSERT INTO table (column1, column2)
VALUES
  ('value1', 'value2'),
  ('value3', 'value4');

-- Insert from another table
INSERT INTO table2 (column1, column2)
SELECT column1, column2 FROM table1 WHERE condition;

UPDATE

-- Update all rows (careful!)
UPDATE table
SET column1 = 'new_value';

-- Update specific rows
UPDATE table
SET column1 = 'new_value'
WHERE condition;

-- Update multiple columns
UPDATE table
SET column1 = 'value1', column2 = 'value2'
WHERE condition;

-- Update with join (PostgreSQL)
UPDATE products p
SET price = price * 1.1
FROM categories c
WHERE p.category_id = c.id AND c.name = 'Electronics';

DELETE

-- Delete all rows (careful!)
DELETE FROM table;

-- Delete specific rows
DELETE FROM table WHERE condition;

-- Delete with subquery
DELETE FROM products
WHERE category_id NOT IN (SELECT id FROM categories);

TRUNCATE (faster than DELETE for all rows)

TRUNCATE TABLE table_name;

🏗️ Schema Operations

CREATE TABLE

CREATE TABLE users (
  id SERIAL PRIMARY KEY,
  username VARCHAR(50) UNIQUE NOT NULL,
  email VARCHAR(100) UNIQUE NOT NULL,
  created_at TIMESTAMP DEFAULT CURRENT_TIMESTAMP,
  is_active BOOLEAN DEFAULT TRUE
);

-- With foreign key
CREATE TABLE orders (
  id INT PRIMARY KEY AUTO_INCREMENT,
  user_id INT NOT NULL,
  total DECIMAL(10,2) NOT NULL,
  FOREIGN KEY (user_id) REFERENCES users(id)
);

ALTER TABLE

-- Add column
ALTER TABLE table ADD COLUMN new_column VARCHAR(100);

-- Modify column
ALTER TABLE table ALTER COLUMN column TYPE VARCHAR(200);

-- Rename column
ALTER TABLE table RENAME COLUMN old_name TO new_name;

-- Drop column
ALTER TABLE table DROP COLUMN column;

-- Add constraint
ALTER TABLE table ADD CONSTRAINT constraint_name UNIQUE (column);

DROP TABLE

DROP TABLE table_name;

-- Drop if exists
DROP TABLE IF EXISTS table_name;

CREATE INDEX

-- Basic index
CREATE INDEX idx_table_column ON table(column);

-- Composite index
CREATE INDEX idx_table_col1_col2 ON table(column1, column2);

-- Unique index
CREATE UNIQUE INDEX idx_table_column ON table(column);

-- Drop index
DROP INDEX idx_table_column;

💡 Useful Patterns

Pagination

-- PostgreSQL, MySQL
SELECT * FROM table
ORDER BY id
LIMIT 10 OFFSET 40;  -- Page 5 (10 per page)

-- SQL Server
SELECT * FROM table
ORDER BY id
OFFSET 40 ROWS FETCH NEXT 10 ROWS ONLY;

Top N Per Group

WITH ranked AS (
  SELECT
    name,
    department,
    salary,
    ROW_NUMBER() OVER (PARTITION BY department ORDER BY salary DESC) as rn
  FROM employees
)
SELECT * FROM ranked WHERE rn <= 3;

Find Duplicates

SELECT column, COUNT(*)
FROM table
GROUP BY column
HAVING COUNT(*) > 1;

Date Functions

-- Current date/time
SELECT CURRENT_DATE;
SELECT CURRENT_TIMESTAMP;
SELECT NOW();  -- PostgreSQL

-- Extract parts
SELECT EXTRACT(YEAR FROM date_column) FROM table;
SELECT EXTRACT(MONTH FROM date_column) FROM table;

-- Date arithmetic
SELECT date_column + INTERVAL '7 days' FROM table;
SELECT DATE_ADD(date_column, INTERVAL 7 DAY) FROM table;  -- MySQL

CASE Statements

SELECT
  name,
  price,
  CASE
    WHEN price < 50 THEN 'Budget'
    WHEN price < 100 THEN 'Mid-range'
    ELSE 'Premium'
  END as price_category
FROM products;

COALESCE (handle NULL)

SELECT COALESCE(column, 'default_value') FROM table;

⚡ Performance Tips

  1. Use EXPLAIN to understand query execution plans
  2. Index columns used in WHERE, JOIN, and ORDER BY
  3. **Avoid SELECT *** - select only needed columns
  4. Use LIMIT to preview results
  5. Prefer UNION ALL over UNION if duplicates don't matter
  6. Avoid functions on indexed columns in WHERE clause
  7. Use EXISTS instead of IN for large datasets
  8. Batch large operations to avoid locking

Test queries with EXPLAIN:

EXPLAIN SELECT * FROM table WHERE condition;
EXPLAIN ANALYZE SELECT * FROM table WHERE condition;  -- PostgreSQL