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and the PERFORMERS table contains 9 rows, the entire query results would contain 99 rows. Let s take a closer look at this. The Famous Blue Raincoat row in the CD_INVENTORY table has been joined with each row in the PERFORMERS table, which totals 9 rows. Each of the remaining 10 rows in the CD_INVENTORY table is matched to each row in the PERFORMERS table in the same way. As a result, there are 99 rows (11 9 = 99). As you can see, these query results are not the most useful. However, you can generate more meaningful results if you use a WHERE clause to create an equi-join (also written as equijoin), which is a type of join that equates the values in one or more columns in the first table to the values in one or more corresponding columns in the second table. As you might guess from the name, the comparison operator in an equi-join is always an equal to (=) operator. For example, you can qualify the previous SELECT statement in the following way:
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SELECT * FROM CD_INVENTORY, PERFORMERS WHERE CD_INVENTORY.PERF_ID = PERFORMERS.PERF_ID;
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Now your query results will include only those rows in which the value in the PERF_ID column of the CD_INVENTORY table matches the value in the PERF_ID column of the PERFORMERS table. Notice that you have to qualify the column names by adding the table names. You must do this whenever columns from different tables have the same name. If you execute this statement, you ll receive the following query results:
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CD_NAME PERF_ID ---------------------- ------Famous Blue Raincoat 102 Blue 101 Court and Spark 101 Past Light 105 Fundamental 104 Blues on the Bayou 103 Longing in Their Hearts 104 Luck of the Draw 104 Deuces Wild 103 Nick of Time 104 Both Sides Now 101 IN_STOCK -------12 24 17 9 22 19 18 25 17 11 13 PERF_ID ------102 101 101 105 104 103 104 104 103 104 101 PERF_NAME TYPE_ID ---------------- ------Jennifer Warnes 12 Joni Mitchell 10 Joni Mitchell 10 William Ackerman 15 Bonnie Raitt 10 B.B. King 11 Bonnie Raitt 10 Bonnie Raitt 10 B.B. King 11 Bonnie Raitt 10 Joni Mitchell 10
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The data returned by this query is now a lot more meaningful. Each CD is matched with the appropriate performer, and only 11 rows are displayed, rather than 99. However, even these query results include repetitive data (the PERF_ID column). In addition, you might find that not only do you want to eliminate duplicate columns, but you also want to display only certain columns and perhaps qualify your search condition even further. Let s modify the SELECT statement we ve been looking at by specifying column names in the SELECT clause to limit the columns returned and adding another predicate to the WHERE clause to limit the rows returned, as shown in the following example:
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SELECT FROM WHERE AND CD_INVENTORY.CD_NAME, PERFORMERS.PERF_NAME, CD_INVENTORY.IN_STOCK CD_INVENTORY, PERFORMERS CD_INVENTORY.PERF_ID = PERFORMERS.PERF_ID CD_INVENTORY.IN_STOCK < 15;
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In this statement, I have specified that three columns should be included in the query results. Notice that I ve qualified the column names by including the table names. Notice also that the WHERE clause includes an additional predicate, connected with the first predicate by the AND keyword. Now any rows that are returned must also have IN_STOCK values less than 15. If you execute this statement, you ll receive the following query results:
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CD_NAME -------------------Famous Blue Raincoat Both Sides Now Past Light Nick of Time PERF_NAME ---------------Jennifer Warnes Joni Mitchell William Ackerman Bonnie Raitt IN_STOCK -------12 13 9 11
As you can see, we ve refined the query results down to just the most essential information. Of course, you can create all sorts of queries, depending on your needs, as long as you follow the basic guidelines for creating a comma-separated join:
The FROM clause must include all table names. The WHERE clause should define a join condition, avoiding a Cartesian product. The column references must be qualified when column names are shared among tables.
Aside from these guidelines, you re free to create whatever sort of SELECT statement is necessary to extract the information you need from the participating tables. And while using the WHERE clause to specify the join condition was the original way to do joins in SQL, later in this chapter you will see that there are now other syntax variations using the JOIN keyword, which most SQL programmers prefer over the original syntax. But no matter what syntax you use, always keep in mind that there needs to be some sort of logical connection between the tables. This connection is often seen in the form of a foreign key, but that doesn t have to be the case. (For more information about foreign keys, see 4.) Tables can be joined whether or not a foreign key exists. And although the equi-join is the most common, you may occasionally find a different join comparison operator useful, such as less than (<) or BETWEEN, in which case the join is referred to as a theta-join.
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