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We next focus on the use of aliases. There are two types of aliases that are used most frequently: column alias and table alias.

In short, column aliases exist to help organizing output. In the previous example, whenever we see total sales, it is listed as SUM(sales). While this is comprehensible, we can envision cases where the column heading can be complicated (especially if it involves several arithmetic operations). Using a column alias would greatly make the output much more readable.

The second type of alias is the table alias. This is accomplished by putting an alias directly after the table name in the FROM clause. This is convenient when you want to obtain information from two separate tables (the technical term is 'perform joins'). The advantage of using a table alias when doing joins is readily apparent when we talk about joins.

Before we get into joins, though, let's look at the syntax for both the column and table aliases:

SELECT "table_alias"."column_name1" "column_alias"
FROM "table_name" "table_alias"

Briefly, both types of aliases are placed directly after the item they alias for, separate by a white space. We again use our table, Store_Information,

Table Store_Information

We use the same example as that in the SQL GROUP BY section, except that we have put in both the column alias and the table alias:

SELECT A1.store_name Store, SUM(A1.Sales) "Total Sales"
FROM Store_Information A1
GROUP BY A1.store_name

Result:

Notice that difference in the result: the column titles are now different. That is the result of using the column alias. Notice that instead of the somewhat cryptic "Sum(Sales)", we now have "Total Sales", which is much more understandable, as the column header.

Now we want to look at joins. To do 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

Table Geography

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:

The first two lines tell SQL to select two fields, the first one is the field "region_name" from table Geography (aliased as REGION), and the second one is the sum of the field "Sales" from table Store_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 correct WHERE 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.

 SQL OUTER JOIN

Previously, we had looked at left join, or inner join, where we select rows common to the participating tables to a join. What about the cases where we are interested in selecting elements in a table regardless of whether they are present in the second table? We will now need to use the SQL OUTER JOIN command.

The syntax for performing an outer join in SQL is database-dependent. For example, in Oracle, we will place an "(+)" in the WHERE clause on the other side of the table for which we want to include all the rows.

Let's assume that we have the following two tables,

Table Store_Information

Table Geography

and we want to find out the sales amount for all of the stores. If we do a regular join, we will not be able to get what we want because we will have missed "New York," since it does not appear in the Store_Information table. Therefore, we need to perform an outer join on the two tables above:

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

Note that in this case, we are using the Oracle syntax for outer join.

Result:

Note: NULL is returned when there is no match on the second table. In this case, "New York" does not appear in the table Store_Information, thus its corresponding "SALES" column is NULL.