The document describes tasks completed for week 7 of a database course. It includes: 1. Implementing database relations from last week using a selected DBMS. 2. Generating random test data and inserting it into the designed database using a Python script. This added 19 cinema records, 530 movie records, over 541,000 show records, and 208 theater records. 3. Writing 5 SQL queries to retrieve meaningful information from the database, such as total income by movie and theater attendance percentages.

1. Week 7
57-01012-62009-8 Thanaphat Kalaya

2. Task 1
Implement last week relations to database using selected DBMS

3. Solution
Relations
Cinemas
Theaters
show
Movies
c_id
t_id seat_cap c_id
t_id m_id time_slot price num_adult num_child
m_id

4. Solution
Relations
Cinemas
Theaters
show
Movies
c_id
t_id seat_cap c_id
t_id m_id time_slot price num_adult num_child
m_id

5. Solution
Relations
Cinemas
Theaters
show
Movies
c_id
t_id seat_cap c_id
t_id m_id time_slot price num_adult num_child
m_id

6. Note : foreign keys

7. Solution
Relations
Cinemas
Theaters
show
Movies
c_id
t_id seat_cap c_id
t_id m_id time_slot price num_adult num_child
m_id

8. Solution
code : cinemas
CREATE TABLE `cinemas` (
`c_id` INT(10) UNSIGNED NOT NULL AUTO_INCREMENT,
`c_name` CHAR(50) NOT NULL DEFAULT '0',
PRIMARY KEY (`c_id`)
);

9. Solution
code : theaters
CREATE TABLE `theaters` (
`t_id` INT(10) UNSIGNED NOT NULL AUTO_INCREMENT,
`t_num` INT(10) NOT NULL,
`seat_cap` INT(10) UNSIGNED NOT NULL,
`c_id` INT(10) UNSIGNED NOT NULL,
PRIMARY KEY (`t_id`),
INDEX `c_id` (`c_id`),
CONSTRAINT `c_id` FOREIGN KEY (`c_id`) REFERENCES `cinemas` (`c_id`)
);

10. Solution
code : theaters
CREATE TABLE `movies` (
`m_id` INT(10) UNSIGNED NOT NULL AUTO_INCREMENT,
`m_name` CHAR(50) NULL DEFAULT '0',
`m_release` DATE NOT NULL,
PRIMARY KEY (`m_id`)
);

11. Solution
code : theaters
CREATE TABLE `shows` (
`t_id` INT(10) UNSIGNED NOT NULL,
`m_id` INT(10) UNSIGNED NOT NULL,
`time_slot` DATETIME NOT NULL,
`price` INT(11) UNSIGNED NOT NULL,
`num_adult` INT(11) UNSIGNED NOT NULL,
`num_child` INT(11) UNSIGNED NOT NULL,
INDEX `t_id` (`t_id`),
INDEX `m_id` (`m_id`),
CONSTRAINT `m_id` FOREIGN KEY (`m_id`) REFERENCES `movies` (`m_id`),
CONSTRAINT `t_id` FOREIGN KEY (`t_id`) REFERENCES `theaters` (`t_id`)
);

12. Task 2
Insert random data into your designed database using selected
DBMS

13. Solution
random_to_theaterDB.py

14. Solution
random_to_theaterDB.py

15. run the code

16. …

17. … (1 hrs. later)

18. …

19. … (6 hrs. later)

20. …

21. okey I think I should stop by now.
(8 hrs. later)

22. Result

23. Result

24. Result

25. Result

26. Result

27. Result
The program generated
- 19 rows of data for table “cinemas”
- 530 rows of data for table “movies”
- 541,457 rows of data for table “shows”
- 208 rows of data for table “theaters”

28. Task 3
Write 5 meaningful/practical SQL queries

29. #1 Query
select
cinemas.c_name,
movies.m_name,
theaters.t_num,
shows.time_slot,
shows.price
from shows
inner join movies on shows.m_id = movies.m_id
inner join theaters on theaters.t_id = shows.t_id
inner join cinemas on cinemas.c_id = theaters.c_id
order by c_name,m_name,time_slot,t_num,price;

30. #1 Query Result (2.360 sec.)

31. #2 Query
select
cinemas.c_name,
movies.m_name,
theaters.t_num,
shows.time_slot,
round((shows.num_adult / (shows.num_adult + shows.num_child)) * 100) as percent_adult,
round((shows.num_child / (shows.num_adult + shows.num_child)) * 100) as percent_child,
shows.price*(shows.num_adult + shows.num_child) as income
from shows
inner join movies on shows.m_id = movies.m_id
inner join theaters on theaters.t_id = shows.t_id
inner join cinemas on cinemas.c_id = theaters.c_id
order by c_name,m_name,time_slot,t_num,price;

32. #2 Query Result (2.766 sec.)

33. #3 Query
select
cinemas.c_name,
movies.m_name,
theaters.t_num,
shows.time_slot,
shows.price,
round((shows.num_adult / (shows.num_adult + shows.num_child)) * 100) as percent_adult,
round((shows.num_child / (shows.num_adult + shows.num_child)) * 100) as percent_child,
shows.price*(shows.num_adult + shows.num_child) as income
from shows
inner join movies on shows.m_id = movies.m_id
inner join theaters on theaters.t_id = shows.t_id
inner join cinemas on cinemas.c_id = theaters.c_id
order by c_name,m_name,time_slot,t_num,price;

34. #3 Query Result (2.782 sec.)

35. #4 Query
select
cinemas.c_name,
movies.m_name,
theaters.t_num,
shows.time_slot,
shows.price,
shows.num_adult,
shows.num_child,
shows.num_adult + shows.num_child as num_customers,
theaters.seat_cap,
round((shows.num_adult / (shows.num_adult + shows.num_child)) * 100) as percent_adult,
round((shows.num_child / (shows.num_adult + shows.num_child)) * 100) as percent_child,
shows.price*(shows.num_adult + shows.num_child) as income
from shows
inner join movies on shows.m_id = movies.m_id
inner join theaters on theaters.t_id = shows.t_id
inner join cinemas on cinemas.c_id = theaters.c_id
order by c_name,m_name,time_slot,t_num,price;

36. #4 Query Result (3.063 sec.)

37. #5 Query
select distinct
movies.m_name,
sum(shows.price*(shows.num_adult + shows.num_child)) as total_income
from shows
inner join movies on shows.m_id = movies.m_id
group by movies.m_id
order by total_income desc;

38. #5 Query Result (0.406 sec.)

39. End of week 7