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joins correctly in SQL requires many of the elements we have introduced so far. Let's assume that we have the following two tables,

Table Store_Information

store_name	Sales	Date
Los Angeles	$1500	Jan-05-1999
San Diego	$250	Jan-07-1999
Los Angeles	$300	Jan-08-1999
Boston	$700	Jan-08-1999

Table Geography

region_name	store_name
East	Boston
East	New York
West	Los Angeles
West	San Diego

and we want to find out sales by region. We see that table Geography includes information on regions and stores, and table Store_Information contains sales information for each store. To get the sales information by region, we have to combine the information from the two tables. Examining the two tables, we find that they are linked via the common field, "store_name". We will first present the SQL statement and explain the use of each segment later:

SELECT A1.region_name REGION, SUM(A2.Sales) SALES
FROM Geography A1, Store_Information A2
WHERE A1.store_name = A2.store_name
GROUP BY A1.region_name

Result:

REGION		SALES
East		$700
West		$2050

The first two lines tell SQL to select two fields, the first one is the field "region_name" from tableGeography (aliased as REGION), and the second one is the sum of the field "Sales" from tableStore_Information (aliased as SALES). Notice how the table aliases are used here: Geography is aliased as A1, and Store_Information is aliased as A2. Without the aliasing, the first line would become

SELECT Geography.region_name REGION, SUM(Store_Information.Sales) SALES

which is much more cumbersome. In essence, table aliases make the entire SQL statement easier to understand, especially when multiple tables are included.

Next, we turn our attention to line 3, the WHERE statement. This is where the condition of the join is specified. In this case, we want to make sure that the content in "store_name" in table Geography matches that in table Store_Information, and the way to do it is to set them equal. This WHERE statement is essential in making sure you get the correct output. Without the correctWHERE statement, a Cartesian Join will result. Cartesian joins will result in the query returning every possible combination of the two (or whatever the number of tables in the FROM statement) tables. In this case, a Cartesian join would result in a total of 4 x 4 = 16 rows being returned.