# SQL Quick Reference

*SELECT, JOIN, subqueries, indexes, transactions*

> Source: SQL Standard / SQLite Documentation (sqlite.org) · MIT

## SELECT

```
SELECT * FROM users;
SELECT name, email FROM users;
SELECT DISTINCT city FROM users;
SELECT name AS full_name FROM users;
```

## WHERE

### Comparison Operators

| Command | Description |
|---------|-------------|
| `= <> (!=)` | Equal / not equal |
| `< > <= >=` | Comparison operators |
| `AND OR NOT` | Logical operators |
| `IS NULL / IS NOT NULL` | Null checks |

### Pattern Matching

```
SELECT * FROM users WHERE name LIKE 'A%';
-- % = any chars, _ = single char
SELECT * FROM users WHERE age IN (20, 25, 30);
SELECT * FROM users WHERE age BETWEEN 18 AND 30;
```

## JOIN

### Join Types

| Command | Description |
|---------|-------------|
| `INNER JOIN` | Rows matching in both tables |
| `LEFT JOIN` | All left rows + matching right |
| `RIGHT JOIN` | All right rows + matching left |
| `FULL OUTER JOIN` | All rows from both tables |
| `CROSS JOIN` | Cartesian product of both tables |

### Join Syntax

```
SELECT u.name, o.total
FROM users u
INNER JOIN orders o ON u.id = o.user_id;

SELECT u.name, o.total
FROM users u
LEFT JOIN orders o ON u.id = o.user_id;
```

## INSERT / UPDATE / DELETE

### Insert

```
INSERT INTO users (name, email)
VALUES ('Alice', 'alice@example.com');

INSERT INTO users (name, email) VALUES
('Bob', 'bob@ex.com'),
('Carol', 'carol@ex.com');
```

### Update

```
UPDATE users SET email = 'new@ex.com'
WHERE id = 1;
```

### Delete

```
DELETE FROM users WHERE id = 1;
DELETE FROM users; -- delete all rows
```

## CREATE TABLE

### Syntax

```
CREATE TABLE users (
  id    INTEGER PRIMARY KEY AUTOINCREMENT,
  name  TEXT NOT NULL,
  email TEXT UNIQUE,
  age   INTEGER DEFAULT 0,
  score REAL
);
```

### Common Data Types

| Command | Description |
|---------|-------------|
| `INTEGER` | Whole numbers |
| `REAL` | Floating-point numbers |
| `TEXT` | String / text data |
| `BLOB` | Binary data |
| `BOOLEAN` | TRUE / FALSE (stored as 0/1) |
| `DATE / DATETIME` | Date and timestamp values |

### Constraints

| Command | Description |
|---------|-------------|
| `PRIMARY KEY` | Unique row identifier |
| `NOT NULL` | Value required |
| `UNIQUE` | No duplicate values |
| `DEFAULT val` | Default value if omitted |
| `CHECK (expr)` | Custom validation rule |
| `FOREIGN KEY` | Reference to another table |

## Aggregate Functions

| Command | Description |
|---------|-------------|
| `COUNT(*)` | Number of rows |
| `COUNT(col)` | Non-null values in column |
| `SUM(col)` | Sum of numeric column |
| `AVG(col)` | Average of numeric column |
| `MIN(col)` | Minimum value |
| `MAX(col)` | Maximum value |

### Example

```
SELECT COUNT(*) AS total,
       AVG(age) AS avg_age,
       MAX(score) AS top_score
FROM users;
```

## GROUP BY / HAVING

```
SELECT city, COUNT(*) AS num_users
FROM users
GROUP BY city;

SELECT city, AVG(age) AS avg_age
FROM users
GROUP BY city
HAVING AVG(age) > 25;
```

*WHERE filters rows before grouping; HAVING filters groups after aggregation*

## ORDER BY / LIMIT

```
SELECT * FROM users ORDER BY name ASC;
SELECT * FROM users ORDER BY age DESC;
SELECT * FROM users
ORDER BY city, name
LIMIT 10 OFFSET 20;  -- skip 20, take 10
```

## Subqueries

### In WHERE Clause

```
SELECT name FROM users
WHERE id IN (
  SELECT user_id FROM orders
  WHERE total > 100
);
```

### As Derived Table

```
SELECT city, avg_age FROM (
  SELECT city, AVG(age) AS avg_age
  FROM users GROUP BY city
) WHERE avg_age > 30;
```

## Indexes

```
CREATE INDEX idx_name ON users(name);
CREATE UNIQUE INDEX idx_email
  ON users(email);
DROP INDEX idx_name;
```

### When to Index

| Command | Description |
|---------|-------------|
| `Columns in WHERE` | Speed up filtering |
| `Columns in JOIN ON` | Speed up join lookups |
| `Columns in ORDER BY` | Speed up sorting |
| `High-cardinality cols` | Many unique values benefit most |