There may be other ways to achieve the same result. Remember that SQL commands are not case sensitive (but data values are).
All of these exercises use the dvdrental database.
Exercises often use multiple commands or aspects of SQL, but they are titled/grouped by their focus.
Get a list of the tables in the database.
Get a list of actors with the first name Julia.
Get a list of actors with the first name Chris, Cameron, or Cuba.
Select the row from customer for customer named Jamie Rice.
Select amount and payment_date from payment where the amount paid was less than $1.
What are the different rental durations that the store allows?
What are the IDs of the last 3 customers to return a rental?
How many films are rated NC-17? How many are rated PG or PG-13?
Challenge: How many different customers have entries in the rental table? Hint
Does the average replacement cost of a film differ by rating?
Challenge: Are there any customers with the same last name?
What is the average rental rate of films? Can you round the result to 2 decimal places?
Challenge: What is the average time that people have rentals before returning? Hint: the output you’ll get may include a number of hours > 24. You can use the function justify_interval on the result to get output that looks more like you might expect.
Challenge 2: Select the 10 actors who have the longest names (first and last name combined).
Which film (id) has the most actors? Which actor (id) is in the most films?