Cocoa Confections
Cocoa Confections is a small bakery that sells brownies, cookies, pies, and other delicious treats to customers online. It keeps records of all of its online sales in an SQL database that is automatically populated as customers place orders on its site.
In its database, Cocoa Confections has a customers table to keep track of customer contact information, and an orders table to keep track of various orders that those customers have placed. The schema of these tables is as follows:
CREATE TABLE customers (
customer_id INT NOT NULL AUTO_INCREMENT PRIMARY KEY,
first_name VARCHAR(255) NOT NULL,
last_name VARCHAR(255) NOT NULL,
email VARCHAR(255) NOT NULL,
address VARCHAR(255) DEFAULT NULL,
city VARCHAR(255) DEFAULT NULL,
state VARCHAR(2) DEFAULT NULL,
zip_code VARCHAR(5) DEFAULT NULL,
);
CREATE TABLE orders (
order_id INT NOT NULL AUTO_INCREMENT PRIMARY KEY,
customer_id INT NOT NULL,
order_placed_date DATE NOT NULL,
FOREIGN KEY (customer_id) REFERENCES customers (customer_id)
);It's the end of 2016, and the owner of Cocoa Confections wants to write an SQL query that finds the COUNT of orders placed in 2016 by customer e-mail address. She wants to ORDER the results by the COUNT of orders placed in 2016, descending, so that she can personally send thank-you e-mails to Cocoa Confection's top customers by order volume.
Can you write a query that will help the owner of Cocoa Confections find the COUNT of all orders placed in 2016, by customer e-mail address, sorted descending?
Hint: Combine tables
The owner of Cocoa Confections wants to find the COUNT of orders placed by e-mail address. But the email field is located within the customers table, not the orders table. What type of statement do we need to use to combine the two tables together?
Hint: Use an
INNER JOINTo combine our two tables together, we'll use a JOIN. Since the orders table has a customer_id field, we can match that against the customer_id in the customers table to link up the two separate data sources. We'll use an INNER JOIN so that data is only included if the customer_id listed matches both of our input tables. Try the following to get you started — it'll compile a list of all orders in our database with all requisite customer information appended:
SELECT
*
FROM
orders
INNER JOIN
customers ON orders.customer_id = customers.customer_id;Hint: Use
COUNT(*)Now that we have a complete list of orders with e-mail addresses included, we can use the COUNT(*) and GROUP BY functions to get a list of orders by e-mail address. This will return a COUNT of all orders in our database by e-mail address. We'll also restrict our SELECT clause so that it only pulls the e-mail address and the COUNT of orders from our database, excluding all other fields.
SELECT
email, COUNT(*)
FROM
orders
INNER JOIN
customers on orders.customer_id = customers.customer_id
GROUP BY
email;
/*
Results:
+------------------------------+----------+
| email | COUNT(*) |
+------------------------------+----------+
| adawson@yahoo.com | 6 |
| aferguson@gmail.com | 16 |
| amy.cummings@yahoo.com | 13 |
...100 rows in set (0.01 sec)
*/Hint: Use
WHERE and ORDER BYWe're not done yet! We still need to restrict the dates of our pull to 2016 only. How do we filter for particular results in SQL? Using a WHERE clause! We'll also need to use an ORDER BY clause to ensure that our results are sorted descending by number of orders. These two clauses, combined, should look something like this:
WHERE
order_placed_date BETWEEN CAST('2016-01-01' AS DATE) AND CAST('2016-12-31' AS DATE)
ORDER BY
2016_num_orders DESC;
Note that we need to use the CAST function to ensure that our numerical inputs are properly interpreted as dates by MySQL.
Does your answer combine tables?
Your solution will need to combine the customers table with the orders table. Does it do so?
Do you use an
INNER JOIN?To combine the customers and orders tables together, an INNER JOIN query will be most effective. Does the solution you've created use an INNER JOIN statement?
Does your answer count total orders?
Don't forget that in order to find the total number of orders placed by e-mail address, you'll need to use SQL's COUNT(*) or SUM functions, which also necessitate a GROUP BY clause in your query. Does your solution contain those features?
Have you included results from only 2016 and ordered descending?
Don't forget that we're only pulling orders from the year 2016, so we'll need to restrict our pull to that year only. We'll also need to arrange our results in descending order by total COUNT. Have you got those features in your query?
The solution
Great! Sounds like you're on the right track, so let's move on to the solution.
Here's our full solution to the problem:
SELECT
customers.email, COUNT(*) AS 2016_num_orders
FROM
orders
INNER JOIN
customers on orders.customer_id = customers.customer_id
WHERE
orders.order_placed_date BETWEEN CAST('2016-01-01' AS DATE) AND CAST('2016-12-31' AS DATE)
GROUP BY
customers.email
ORDER BY
2016_num_orders DESC;
/*
Results:
+------------------------------+-----------------+
| email | 2016_num_orders |
+------------------------------+-----------------+
| doreen.glover@yahoo.com | 14 |
| rpayne@hotmail.com | 10 |
| fobrien@gmail.com | 10 |
...99 rows in set (0.01 sec)
*/Check out what's happening above:
First, we use a SELECT statement to pull specific fields from our database. We'll pull the email field, which is located on the customers table, and the aggregated COUNT(*) of records, using the AS clause to refer to this column as 2016_num_orders.
We'll use a FROM orders clause to note that we're pulling this data from our orders table. But since the email field isn't located on the orders table, we'll also need to perform an INNER JOIN linking the orders.customer_id field to the customers.customer_id field.
We'll use a WHERE clause to restrict our data range to 2016 only using two criteria: >= '2016-01-01' and <= '2016-12-31'.
Since we're using a COUNT(*) function to sum records, we'll need to use a GROUP BY clause to tell SQL that we want to group our results by email address.
Finally, we'll tell SQL that we want our results arranged by number of orders, from greatest to least, using ORDER BY.
Our query is complete!