***********
- ************************************************************************************
- *****************************************
**********
- **************
>= $100. - ****************
>= $20, <$100. - *************
<$20.
****
- ****************************************************
*********
Table 1: film
col_name | col_type
----------------------+--------------------------
film_id | integer
title | text
description | text
release_year | integer
language_id | smallint
original_language_id | smallint
rental_duration | smallint
rental_rate | numeric
length | smallint
replacement_cost | numeric
rating | text
Table 2: inventory
Each row is unique, inventoy_id is the primary key of this table.
col_name | col_type --------------+-------------------------- inventory_id | integer film_id | smallint store_id | smallint
Table 3: payment
Movie rental payment transactions table
col_name | col_type --------------+-------------------------- payment_id | integer customer_id | smallint staff_id | smallint rental_id | integer amount | numeric payment_ts | timestamp with time zone
Table 4: rental
col_name | col_type --------------+-------------------------- rental_id | integer rental_ts | timestamp with time zone inventory_id | integer customer_id | smallint return_ts | timestamp with time zone staff_id | smallint
Sample results
film_group | count ------------+------- medium | 123 high | 456 low | 789
Solution postgres
SELECT film_group, COUNT(*)
FROM (
SELECT
F.film_id,
CASE WHEN SUM(P.amount) >= 100 THEN 'high'
WHEN SUM(P.amount) >= 20 THEN 'medium'
ELSE 'low' END film_group
FROM film F
LEFT JOIN inventory I
ON I.film_id = F.film_id
LEFT JOIN rental R
ON R.inventory_id = I.inventory_id
LEFT JOIN payment P
ON P.rental_id = R.rental_id
GROUP BY F.film_id
) X
GROUP BY film_group
;
Explanation
This query is counting the number of films falling into three different categories based on their rental income. The categories are 'low', 'medium', and 'high'. The query first joins tables film, inventory, rental, and payment to obtain the rental income for each film. It then groups the films by their ID and assigns them to one of the three categories based on their rental income. Finally, the query counts the number of films in each category and returns the result.
Expected results