34. Stocked up movies

easy

Instruction
  • Write a query to return the titles of movies with more than >7 dvd copies in the inventory.
  • The film titles are unique, i.e., no 2 films share the same titles.

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

Sample results


         title
------------------------
 ACADEMY DINOSAUR
 APACHE DIVINE

Solution postgres

SELECT title
FROM film
WHERE film_id IN (
	SELECT 
	    film_id
	FROM inventory
	GROUP BY film_id
	HAVING COUNT(*) >=8
);
    

Explanation

This query is selecting the title of all films from the "film" table where the film_id is present in a subquery.

The subquery is selecting all film_ids from the "inventory" table where there are at least 8 records for that film_id.

In other words, the main query is returning the titles of films that have at least 8 copies available in the inventory.

Last Submission postgres

Expected results



More IN, BETWEEN, LIKE, CASE WHEN questions

ID Title Level FTPR
178 Members who worked at both Microsoft and Google linkedin medium
34%
177 Purchases by platform report amazon medium
10%
176 Employees' annual bonus amazon easy
12%
160 Sellers with no sales by day ebay hard
11%
156 Cancellation rate by unbanned users lyft hard
15%
155 Driver with the highest cancellation rate lyft easy
24%
151 Salary report dropbox easy
18%
138 Happy restaurants doordash easy
14%
136 Extremely late orders doordash easy
11%
131 Churned accounts affirm hard
10%
102 Histogram by visit session duration google hard
17%
35 Film length report easy
27%
33 Returning customers medium
8%
32 Unpopular movies hard
17%
31 Movies that have not been returned easy
26%
30 Inactive customers in May easy
22%
29 Second highest spend customer medium
14%
28 Film with the second largest cast medium
26%
27 Film with the largest cast easy
27%
26 Second shortest film easy
30%
25 Shortest film easy
46%
24 Films with more than 10 actors medium
19%
22 Average cost per rental transaction easy
42%
15 Fast movie watchers vs slow watchers hard
6%
14 Good days and bad days hard
4%
13 Actors' first name medium
14%
12 Actors' last name ending in 'EN' or 'RY' easy
27%
11 Actors' last name easy
21%