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SQL exercises on movie Database: Generate a report which contain the columns movie title, name of the female actor, year of the movie, role, movie genres, the director, date of release, and rating of that movie


24. From the following tables, write a query in SQL to generate a report, which contain the fields movie title, name of the female actor, year of the movie, role, movie genres, the director, date of release, and rating of that movie.

Sample table: movie

 mov_id |                     mov_title                      | mov_year | mov_time |    mov_lang     | mov_dt_rel | mov_rel_country
--------+----------------------------------------------------+----------+----------+-----------------+------------+-----------------
    901 | Vertigo                                            |     1958 |      128 | English         | 1958-08-24 | UK
    902 | The Innocents                                      |     1961 |      100 | English         | 1962-02-19 | SW
    903 | Lawrence of Arabia                                 |     1962 |      216 | English         | 1962-12-11 | UK
    904 | The Deer Hunter                                    |     1978 |      183 | English         | 1979-03-08 | UK
    905 | Amadeus                                            |     1984 |      160 | English         | 1985-01-07 | UK
    906 | Blade Runner                                       |     1982 |      117 | English         | 1982-09-09 | UK
    907 | Eyes Wide Shut                                     |     1999 |      159 | English         |            | UK
    908 | The Usual Suspects                                 |     1995 |      106 | English         | 1995-08-25 | UK
    909 | Chinatown                                          |     1974 |      130 | English         | 1974-08-09 | UK
......
    925 | Braveheart                                         |     1995 |      178 | English         | 1995-09-08 | UK

View the table

Sample table: genres

 gen_id |      gen_title
--------+----------------------
   1001 | Action
   1002 | Adventure
   1003 | Animation
   1004 | Biography
   1005 | Comedy
   1006 | Crime
   1007 | Drama
   1008 | Horror
   1009 | Music
.....
   1013 | War

View the table

Sample table: movie_genres

 mov_id | gen_id
--------+--------
    922 |   1001
    917 |   1002
    903 |   1002
    912 |   1003
    911 |   1005
    908 |   1006
    913 |   1006
    926 |   1007
    928 |   1007
.....
    904 |   1013

View the table

Sample table: rating

 mov_id | rev_id | rev_stars | num_o_ratings
--------+--------+-----------+---------------
    901 |   9001 |      8.40 |        263575
    902 |   9002 |      7.90 |         20207
    903 |   9003 |      8.30 |        202778
    906 |   9005 |      8.20 |        484746
    924 |   9006 |      7.30 |
    908 |   9007 |      8.60 |        779489
    909 |   9008 |           |        227235
    910 |   9009 |      3.00 |        195961
.....
    923 |   9020 |      6.70 |         13091

View the table

Sample table: actor

 act_id |      act_fname       |      act_lname       | act_gender
--------+----------------------+----------------------+------------
    101 | James                | Stewart              | M
    102 | Deborah              | Kerr                 | F
    103 | Peter                | OToole               | M
    104 | Robert               | De Niro              | M
    105 | F. Murray            | Abraham              | M
    106 | Harrison             | Ford                 | M
    107 | Nicole               | Kidman               | F
    108 | Stephen              | Baldwin              | M
    109 | Jack                 | Nicholson            | M
    110 | Mark                 | Wahlberg             | M
.....
    124 | Ali                  | Astin                | F

View the table

Sample table: director

 dir_id |      dir_fname       |      dir_lname
--------+----------------------+----------------------
    201 | Alfred               | Hitchcock
    202 | Jack                 | Clayton
    203 | David                | Lean
    204 | Michael              | Cimino
    205 | Milos                | Forman
    206 | Ridley               | Scott
    207 | Stanley              | Kubrick
    208 | Bryan                | Singer
    209 | Roman                | Polanski
    210 | Paul                 | Thomas Anderson
.....

View the table

Sample table: movie_direction

 dir_id | mov_id
--------+--------
    201 |    901
    202 |    902
    203 |    903
    204 |    904
    205 |    905
    206 |    906
    207 |    907
    208 |    908
    209 |    909
....
    221 |    923

View the table

Sample table: movie_cast

 act_id | mov_id |              role
--------+--------+--------------------------------
    101 |    901 | John Scottie Ferguson
    102 |    902 | Miss Giddens
    103 |    903 | T.E. Lawrence
    104 |    904 | Michael
    105 |    905 | Antonio Salieri
    106 |    906 | Rick Deckard
    107 |    907 | Alice Harford
    108 |    908 | McManus
    110 |    910 | Eddie Adams
.....
    119 |    919 | Alfred Borden

View the table

Sample Solution:

-- Selecting various columns from multiple tables: movie, movie_cast, actor, movie_genres, genres, movie_direction, director, and rating
SELECT mov_title, act_fname, act_lname, 
mov_year, role, gen_title, dir_fname, dir_lname, 
mov_dt_rel, rev_stars
-- Performing natural joins between the movie, movie_cast, actor, movie_genres, genres, movie_direction, director, and rating tables
FROM movie 
NATURAL JOIN movie_cast
NATURAL JOIN actor
NATURAL JOIN movie_genres
NATURAL JOIN genres
NATURAL JOIN movie_direction
NATURAL JOIN director
NATURAL JOIN rating
-- Filtering the result to include only records where act_gender is 'F'
WHERE act_gender='F';

Sample Output:

                     mov_title                      |      act_fname       |      act_lname       | mov_year |              role              |      gen_title       |      dir_fname       |      dir_lname       | mov_dt_rel | rev_stars
----------------------------------------------------+----------------------+----------------------+----------+--------------------------------+----------------------+----------------------+----------------------+------------+-----------
 The Innocents                                      | Deborah              | Kerr                 |     1961 | Miss Giddens                   | Horror               | Jack                 | Clayton              | 1962-02-19 |      7.90
 Princess Mononoke                                  | Claire               | Danes                |     1997 | San                            | Animation            | Hayao                | Miyazaki             | 2001-10-19 |      8.40
 Aliens                                             | Sigourney            | Weaver               |     1986 | Ripley                         | Action               | James                | Cameron              | 1986-08-29 |      8.40
(3 rows)

Code Explanation :

The said query in SQL that retrieves the title, year, release date, and rating of movies, as well as the first and last name of the actresses who played a role in the movie, the genres of the movie, and the first and last name of the director of the movie.
1. The NATURAL JOIN clause joins the movie_cast table to the movie table based on matching column names in the two tables.
2. The actor table joined to the result of the previous join step 1. 3. The movie_genres table joined to the result of the previous join step 2.
4. The genres table joined to the result of the previous join step 3.
5. The movie_direction table joined to the result of the previous join step 4.
6. The director table joined to the result of the previous join step 5.
7. The rating table joined to the result of the previous join step 6.
The WHERE clause filter the result, where only actors with a gender of 'F' will be included in the result set.

Alternative Solutions:

Using Subquery with EXISTS:


SELECT mov_title, act_fname, act_lname, 
       mov_year, role, gen_title, dir_fname, dir_lname, 
       mov_dt_rel, rev_stars
FROM movie 
JOIN movie_cast ON movie.mov_id = movie_cast.mov_id
JOIN actor ON movie_cast.act_id = actor.act_id
JOIN movie_genres ON movie.mov_id = movie_genres.mov_id
JOIN genres ON movie_genres.gen_id = genres.gen_id
JOIN movie_direction ON movie.mov_id = movie_direction.mov_id
JOIN director ON movie_direction.dir_id = director.dir_id
JOIN rating ON movie.mov_id = rating.mov_id
WHERE EXISTS (
    SELECT 1
    FROM actor
    WHERE actor.act_id = movie_cast.act_id
    AND actor.act_gender = 'F'
);

Explanation:

This SQL query uses a subquery with EXISTS to check if there exists an actor with gender 'F' who is part of the cast. If such an actor exists, the main query includes the corresponding movie details.

Using INNER JOINs with Subquery:


SELECT mov_title, act_fname, act_lname, 
       mov_year, role, gen_title, dir_fname, dir_lname, 
       mov_dt_rel, rev_stars
FROM movie 
JOIN movie_cast ON movie.mov_id = movie_cast.mov_id
JOIN actor ON movie_cast.act_id = actor.act_id
JOIN movie_genres ON movie.mov_id = movie_genres.mov_id
JOIN genres ON movie_genres.gen_id = genres.gen_id
JOIN movie_direction ON movie.mov_id = movie_direction.mov_id
JOIN director ON movie_direction.dir_id = director.dir_id
JOIN rating ON movie.mov_id = rating.mov_id
WHERE actor.act_gender = 'F';

Explanation:

This SQL query combines INNER JOINs with a WHERE clause to directly filter for actors with gender 'F'.

Relational Algebra Expression:

Relational Algebra Expression: Generate a report which contain the columns movie title, name of the female actor, year of the movie, role, movie genres, the director, date of release, and rating of that movie.


Relational Algebra Tree:

Relational Algebra Tree: Generate a report which contain the columns movie title, name of the female actor, year of the movie, role, movie genres, the director, date of release, and rating of that movie.


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PREV : From the following tables, write a SQL query to find the years when most of the ‘Mystery Movies’ produced. Count the number of generic title and compute their average rating. Group the result set on movie release year, generic title. Return movie year, generic title, number of generic title and average rating.
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