---
note type:
  - sql
  - database
  - theory
date: 2026-06-03
done:
link: https://app.pluralsight.com/ilx/video-courses/sql-joins-constraints-normalization-subqueries/course-overview
---
# Common Aggregate Functions

|title|cost|duration|
|---|---|---|
|Gone with the wind|390000|220|
|Frankenstein|3000000|50|
|Creature from the black lagoon|500000|79|
|NULL|100|10|

## 1. COUNT()

## Count all rows

`SELECT COUNT(*) FROM Movies;`

**Output:**

```
4
```

- Counts all rows, including rows where columns are `NULL`.

### Count non-NULL values in a column

`SELECT COUNT(title) FROM Movies;`

 **Output:**

```
3
```

- `NULL` title is **not counted**.

## 2. MIN()

`SELECT MIN(cost) FROM Movies;`

**Output:**

```
100
```

- Returns the smallest value in the column.

## 3. MAX()

`SELECT MAX(cost) FROM Movies;`

**Output:**

```
3000000
```

- Returns the largest value.

## 4. SUM()

`SELECT SUM(cost) FROM Movies;`

**Output:**

```
3890100
```

Calculation:

```
390000 + 3000000 + 500000 + 100 = 3890100
```

- Adds all values in the column.
- Ignores `NULL` values (none in `cost` here).

## 5. AVG()

`SELECT AVG(cost) FROM Movies;`

**Output:**

```
972525
```

Calculation:

```
3890100 / 4 = 972525
```

- Computes the average of all values.

---

## Using Multiple Aggregates

```
SELECT

    COUNT(*) AS total_movies,

    MIN(cost) AS cheapest,

    MAX(cost) AS most_expensive,

    SUM(cost) AS total_cost,

    AVG(cost) AS average_cost

FROM Movies;
```

**Output:**

```
total_movies | cheapest | most_expensive | total_cost | average_cost
4            | 100      | 3000000        | 3890100    | 972525
```

# Filtering Aggregates

| title                          | cost    | duration | genre  |
| ------------------------------ | ------- | -------- | ------ |
| Gone with the wind             | 390000  | 220      | Drama  |
| Frankenstein                   | 3000000 | 50       | Horror |
| Creature from the black lagoon | 500000  | 79       | Horror |
| Casablanca                     | 1000000 | 102      | Drama  |
| Toy Story                      | 2000000 | 81       | Family |
| NULL                           | 100     | 10       | Horror |

## GROUP BY

`GROUP BY` groups rows so aggregates are calculated per group rather than across the whole table.

```
SELECT genre, SUM(cost) AS total_cost
FROM Movies
GROUP BY genre;
```

Output:

```
genre   | total_cost
Drama   | 1390000
Horror  | 3500100
Family  | 2000000
```


```
SELECT genre, AVG(duration) AS avg_duration
FROM Movies
GROUP BY genre;
```

Output:

```
genre   | avg_duration
Drama   | 161
Horror  | 46.33
Family  | 81
```

---

## WHERE (filtering rows before aggregation)

`WHERE` filters rows **before** grouping and aggregation.

```
SELECT genre, COUNT(*) AS num_movies
FROM Movies
WHERE duration > 60
GROUP BY genre;
```

Output:

```
genre   | num_movies
Drama   | 2
Horror  | 1
Family  | 1
```

Explanation:

- The row with duration = 10 is excluded before grouping.

## HAVING (filtering groups after aggregation)

`HAVING` filters results **after aggregation**.

```
SELECT genre, SUM(cost) AS total_cost
FROM Movies
GROUP BY genre
HAVING SUM(cost) >= 2000000;
```

Output:

```
genre   | total_cost
Horror  | 3500100
Family  | 2000000   -- note: included only if >= was used
```

If strictly `> 2000000`, only:

```
Horror  | 3500100
```


```
SELECT genre, COUNT(*) AS num_movies
FROM Movies
GROUP BY genre
HAVING COUNT(*) > 2;
```

Output:

```
genre   | num_movies
Horror  | 3
```

## Combined Example

```
SELECT genre, AVG(cost) AS avg_cost
FROM Movies
WHERE duration > 60
GROUP BY genre
HAVING AVG(cost) > 1000000;
```

Steps:

1. WHERE filters rows (duration > 60)
2. GROUP BY groups remaining data
3. HAVING filters grouped results

Output:

```
genre   | avg_cost
Family  | 2000000
```