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6. The next table, COMPACT_DISC_TYPES, includes two foreign keys, along with its primary
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key. The foreign keys reference the COMPACT_DISCS table and the MUSIC_TYPES table, both of which you ve already created. Enter and execute the following SQL statement:
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CREATE TABLE COMPACT_DISC_TYPES ( COMPACT_DISC_ID INT, MUSIC_TYPE_ID INT, CONSTRAINT PK_COMPACT_DISC_TYPES PRIMARY KEY ( COMPACT_DISC_ID, MUSIC_TYPE_ID), CONSTRAINT FK_COMPACT_DISC_ID_01 FOREIGN KEY (COMPACT_DISC_ID) REFERENCES COMPACT_DISCS, CONSTRAINT FK_MUSIC_TYPE_ID FOREIGN KEY (MUSIC_TYPE_ID) REFERENCES MUSIC_TYPES ); 7. Now you can create the ARTISTS table. Enter and execute the following SQL statement: CREATE TABLE ARTISTS ( ARTIST_ID INT, ARTIST_NAME VARCHAR(60) NOT NULL, PLACE_OF_BIRTH VARCHAR(60) DEFAULT 'Unknown' NOT NULL, CONSTRAINT PK_ARTISTS PRIMARY KEY (ARTIST_ID) ) ; 8. The last table you ll create (at least for now) is the ARTIST_CDS table. Enter and execute
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the following SQL statement:
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CREATE TABLE ARTIST_CDS ( ARTIST_ID INT, COMPACT_DISC_ID INT, CONSTRAINT PK_ARTIST_CDS PRIMARY KEY ( ARTIST_ID, COMPACT_DISC_ID ), CONSTRAINT FK_ARTIST_ID FOREIGN KEY (ARTIST_ID) REFERENCES ARTISTS, CONSTRAINT FK_COMPACT_DISC_ID_02 FOREIGN KEY (COMPACT_DISC_ID) REFERENCES COMPACT_DISCS ) ;
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Your database now has six tables, each one configured with the necessary defaults and constraints. In this Try This exercise, we followed a specific order for creating the tables in order to more easily implement the foreign keys. However, you could have created the tables in any order, without their foreign keys unless the referenced table was already created and then added in the foreign keys later, but this would have added extra steps. In fact, had you wanted to, you could have altered the tables that had existed prior to this exercise (rather than dropping them and then recreating them), as long as you created primary keys (or UNIQUE constraints) on the referenced tables before creating foreign keys on the referencing tables. Regardless of the approach you take, the end result should be that your database now has the necessary tables to begin moving on to other components of SQL.
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Enforcing Data Integrity
Define CHECK Constraints
Earlier in the chapter, in the Understand Integrity Constraints section, I discussed the various constraint categories and the types of constraints they support. (Refer back to Figure 4-1 for an overview of these categories.) One type of constraint , the CHECK constraint, can be defined as table constraints, column constraints, domain constraints, or within assertions. A CHECK constraint allows you to specify what values can be included in a column. You can define a range of values (for example, between 10 and 100), a list of values (for example, blues, jazz, pop, country), or a number of other conditions that restrict exactly what values are permitted in a column. CHECK constraints are the most flexible of all the constraints and are often the most complicated. Despite this, the basic syntax used for a CHECK constraint is relatively simple. To create a column CHECK constraint, use the following syntax in a column definition: <column name> { <data type> | <domain> } CHECK ( <search condition> ) To create a table CHECK constraint, use the following syntax in a table definition: [ CONSTRAINT <constraint name> ] CHECK ( <search condition> ) I ll be discussing domain constraints and assertions later in this section. As you can see by the syntax, a CHECK constraint is relatively straightforward. However, the values used for the <search condition> clause can be very extensive and, consequently, quite complex. The main concept is that the <search condition> is tested (one could say checked ) for any SQL statement that attempts to modify the data in a column covered by the CHECK constraint, and if it evaluates to TRUE, the SQL statement is allowed to complete; if it evaluates to FALSE, the SQL statement fails and an error message is displayed. The best way for you to learn about the clause is by looking at examples. However, most <search condition> components are based on the use of predicates in order to create the search condition. A predicate is an expression that operates on values. For example, a predicate can be used to compare values (for instance, COLUMN_1 > 10). The greater- than symbol (>) is a comparison predicate, sometimes referred to as a comparison operator. In this case, the predicate verifies that any value inserted into COLUMN_1 is greater than 10. Many <search condition> components also rely on the use of subqueries. A subquery is an expression that is used as a component within another expression. Subqueries are used when an expression must access or calculate multiple layers of data, such as having to search a second table to provide data for the first table. Both predicates and subqueries are complicated enough subjects to be beyond the scope of a discussion about CHECK constraints, and indeed each subject is treated separately in its own chapter. (See 9 for information about predicates and 12 for information about subqueries.) Despite the fact that both topics are discussed later in the book, I want to provide you with at least a few examples of CHECK constraints to give you a feel for how they re implemented in an SQL environment. The first example we ll look at is a CHECK constraint that defines the minimum and maximum values that can be inserted into a column. The following table definition in this
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