PHP and MySQL Web Development 4th Ed-tqw-_darksiderg

250 Chapter 10 Working with Your MySQL Database
These items are in separate tables because they relate to separate real-world objects.
This is one of the principles of good database design that we described in Chapter 8,
“Designing Your Web Database.”
To put this information together in SQL, you must perform an operation called a
join.This simply means joining two or more tables together to follow the relationships
between the data. For example, if you want to see the orders that customer Julie Smith
has placed, you will need to look at the customers table to find Julie’s customerid and
then at the orders table for orders with that customerid.
Although joins are conceptually simple, they are one of the more subtle and complex
parts of SQL. Several different types of joins are implemented in MySQL, and each is
used for a different purpose.
Simple Two-Table Joins
Let’s begin by looking at some SQL for the query about Julie Smith we just discussed:
select orders.orderid, orders.amount, orders.date
from customers, orders
where customers.name = ‘Julie Smith’
and customers.customerid = orders.customerid;
The output of this query is
+---------+--------+------------+
| orderid | amount | date |
+---------+--------+------------+
| 1 | 69.98 | 2007-04-02 |
| 4 | 24.99 | 2007-05-01 |
+---------+--------+------------+
There are a few things to notice here. First, because information from two tables is needed
to answer this query, you must list both tables.
By listing two tables, you also specify a type of join, possibly without knowing it.The
comma between the names of the tables is equivalent to typing INNER JOIN or CROSS
JOIN.This is a type of join sometimes also referred to as a full join, or the Cartesian product
of the tables. It means,“Take the tables listed, and make one big table.The big table
should have a row for each possible combination of rows from each of the tables listed,
whether that makes sense or not.” In other words, you get a table, which has every row
from the customers table matched up with every row from the orders table, regardless
of whether a particular customer placed a particular order.
That brute-force approach doesn’t make a lot of sense in most cases. Often what you
want is to see the rows that really do match—that is, the orders placed by a particular
customer matched up with that customer.
You achieve this result by placing a join condition in the WHERE clause.This special type
of conditional statement explains which attributes show the relationship between the
two tables. In this case, the join condition is
customers.customerid = orders.customerid