Movies

Log into code.cs50.io, click on your terminal window, and execute cd by itself. You should find that your terminal window’s prompt resembles the below:

$

Next execute

wget https://cdn.cs50.net/2022/fall/psets/7/movies.zip

in order to download a ZIP called movies.zip into your codespace.

Then execute

unzip movies.zip

to create a folder called movies. You no longer need the ZIP file, so you can execute

rm movies.zip

and respond with “y” followed by Enter at the prompt to remove the ZIP file you downloaded.

Now type

cd movies

followed by Enter to move yourself into (i.e., open) that directory. Your prompt should now resemble the below.

movies/ $

Execute ls by itself, and you should see 13 .sql files, as well as movies.db.

If you run into any trouble, follow these same steps again and see if you can determine where you went wrong!

Whenever you engage with a new database, it’s best to first understand its schema. In a terminal window, run sqlite3 movies.db so that you can begin executing queries on the database.

First, when sqlite3 prompts you to provide a query, type .schema and press enter. This will output the CREATE TABLE statements that were used to generate each of the tables in the database. By examining those statements, you can identify the columns present in each table.

Notice that the movies table has an id column that uniquely identifies each movie, as well as columns for the title of a movie and the year in which the movie was released. The people table also has an id column, and also has columns for each person’s name and birth year.

Movie ratings, meanwhile, are stored in the ratings table. The first column in the table is movie_id: a foreign key that references the id of the movies table. The rest of the row contains data about the rating for each movie and the number of votes the movie has received on IMDb.

Finally, the stars and directors tables match people to the movies in which they acted or directed. (Only principal stars and directors are included.) Each table has just two columns: movie_id and person_id, which reference a specific movie and person, respectively.

The challenge ahead of you is to write SQL queries to answer a variety of different questions by selecting data from one or more of these tables.

See sqlstyle.guide for pointers on good style in SQL, especially as your queries get more complex!

Recall that you can select one (or more) columns from a database using SELECT, per the example below,

SELECT column0, column1 FROM table;

where column0 is the title of one column, and column1 is the title of another.

And recall that you can filter the rows returned in a query with the WHERE keyword, followed by a condition. You can use =, >, <, and other operators too.

SELECT column FROM table
WHERE condition;

See this SQL keywords reference for some SQL syntax that may be helpful!

Recall that a WHERE clause can evaluate conditions not just with numbers, but with strings.

Try breaking this query into two steps. First, find the movies with a release date on or after 2018. Then, put those movies’ titles in alphabetical order.

To find the movies with a release date on or after 2018, recall that a condition in SQL supports the use of many common comparison operators, including >= for “greater than or equal to.” Check to see if your query returns the correct number of movies, per How to Test.

Finally, sort the query’s results alphabetically by title. Recall that ORDER BY can sort data by a column in your results, per the example below.

...
ORDER BY column;

Notice this question asks you not for individual movies with a rating of 10.0, but for the number of movies with such a rating. In other words, you should collect (“aggregate”) the results of your query into a single number (the number of rows). Recall that SQL supports an “aggregation function” called COUNT, which you can use on a column per the example below.

SELECT COUNT(column)
FROM table;

For this query, you’ll likely want to make use of SQL’s LIKE keyword. Recall that LIKE can make use of so-called “wildcard characters”, such as %, that will match any character (or sequence thereof).

SELECT column0, column1
FROM table
WHERE column1 LIKE pattern;

Here’s another example of a query in which you’ll need to aggregate data. Consider SQL’s AVG aggregation function, to compute an average.

Consider, too, that this query makes use of data stored in two separate tables: ratings and movies. Recall that—so long as one table has a foreign key that matches a column in another table—you can combine two tables using SQL’s JOIN keyword. To use the JOIN keyword, you should specify the table you’d like to join and the column by which to do so.

SELECT column0
FROM table0
JOIN table1 ON table0.column1 = table1.column2

Recall that ORDER BY need not always sort in ascending order. You can specify that your results be sorted in descending order by appending DESC.

...
ORDER BY column DESC;

When you see a more complex query such as this one, it’s best to break it down into smaller pieces. Ultimately, your query should arrive at a list of names, per the below.

-- Select names
SELECT name
FROM people
WHERE ...

But how’s best to arrive at the names of those who starred in Toy Story? Consider that the people table alone doesn’t have this information (but the stars table might!). Indeed, the stars table combines two columns, person_id and movie_id: any person with a person_id that is associated with Toy Story’s movie_id starred in Toy Story.

-- Select names
SELECT name
FROM people
WHERE ...

-- Select person IDs
SELECT person_id
FROM stars
WHERE movie_id = ...

A natural next step, then, is to find Toy Story’s movie ID.

-- Select names
SELECT name
FROM people
WHERE ...

-- Select person IDs
SELECT person_id
FROM stars
WHERE movie_id = ...

-- Find Toy Story's ID
SELECT id
FROM movies
WHERE title = 'Toy Story';

Of course, you’ve presently written three separate queries. But notice that some queries (the first two) would be complete by including results of the query directly below them. The process of making a query that depends on the results of a “subquery” is called “nesting” queries. It’s quite the hint, but here’s one way to nest the above queries!

-- Select names
SELECT name
FROM people
WHERE id IN 
(
    -- Select person IDs
    SELECT person_id
    FROM stars
    WHERE movie_id = (
        
        -- Select Toy Story's ID
        SELECT id
        FROM movies
        WHERE title = 'Toy Story'
    )
);

Notice that this query, like the previous, requires you to use data from multiple tables. Recall that you can “nest” queries in SQL, which allows you to break a larger query into smaller ones. Perhaps you could write queries to…

1. Find the IDs of movies released in 2004
2. Find the IDs of people who starred in those movies
3. Find the names of people with those people IDs

Then, try nesting those queries to arrive at a single query that returns all people who starred in a movie released in 2004. Consider how you might then order the results of your query.

Notice that this query, like the previous, requires you to use data from multiple tables. Recall that you can “nest” queries in SQL, which allows you to break a larger query into smaller ones. Perhaps you could write queries to…

1. Find the IDs of movies with at least a 9.0 rating
2. Find the IDs of people who directed those movies
3. Find the names of people with those people IDs

Then, try nesting those queries to arrive at a single query that returns the names of all people who have directed a movie that received a rating of at least 9.0.

Notice that this query, like the previous, requires you to use data from multiple tables. Recall that you can “nest” queries in SQL, which allows you to break a larger query into smaller ones. Perhaps you could write queries to…

1. Find the ID of Chadwick Boseman
2. Find the IDs of movies associated with Chadwick Boseman’s ID
3. Find the movie titles with those movie IDs

Then, try nesting those queries to arrive at a single query that returns the titles of Chadwick Boseman’s movies.

From there, you’ll need to determine the ratings of those titles and sort those titles by rating, in descending order. Consider how you could combine a relevant table (likely ratings!) and order the results by a relevant column.

Finally, read up on SQL’s LIMIT keyword, which will return the top \(n\) rows in a query.

Notice that this query, like the previous, requires you to use data from multiple tables. Recall that you can “nest” queries in SQL, which allows you to break a larger query into smaller ones. Perhaps you could write queries to…

1. Find the ID of Johnny Depp
2. Find the ID of Helena Bonham Carter
3. Find the IDs of movies associated with Johnny Depp’s ID
4. Find the IDs of movies associated with Helena Bonham Carter’s ID
5. Find movie titles from the movie IDs associated with both Johnny Depp and Helena Bonham Carter

Then, try nesting those queries to arrive at a single query that returns the movies in which both Johnny Depp and Helena Bonham Carter starred.

Recall that you can build compound conditions in SQL using AND or OR.

Notice that this query, like the previous, requires you to use data from multiple tables. Recall that you can “nest” queries in SQL, which allows you to break a larger query into smaller ones. Perhaps you could write queries to…

1. Find the ID of Kevin Bacon (the one born in 1958!)
2. Find the IDs of movies associated with Kevin Bacon’s ID
3. Find the IDs of people associated with those movie IDs
4. Find the names of people with those people IDs

Then, try nesting those queries to arrive at a single query that returns the names of all people who starred in a movie in which Kevin Bacon also starred. Keep in mind that you’ll want to exclude Kevin Bacon himself from the results!