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example creates three columns and one CHECK constraint (as a table constraint) that restricts the values of one of the columns to a range of numbers between 0 and 30:
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CREATE TABLE CD_TITLES ( COMPACT_DISC_ID INT, CD_TITLE VARCHAR(60) NOT NULL, IN_STOCK INT NOT NULL, CONSTRAINT CK_IN_STOCK CHECK ( IN_STOCK > 0 AND IN_STOCK < 30 ) );
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If you were to try to enter a value into the IN_STOCK column other than 1 through 29, you would receive an error. You can achieve the same results by defining a column constraint:
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CREATE TABLE CD_TITLES ( COMPACT_DISC_ID INT, CD_TITLE VARCHAR(60) NOT NULL, IN_STOCK INT NOT NULL CHECK ( IN_STOCK > 0 AND IN_STOCK < 30 ) );
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Let s take a closer look at the <search condition> clause in these statements, which in this case is ( IN_STOCK > 0 AND IN_STOCK < 30 ). The clause first tells us that any value entered into the IN_STOCK column must be greater than 0 (IN_STOCK > 0). The AND keyword tells us that the conditions defined on either side of AND must be applied. Finally, the clause tells us that the value must be less than 30 (IN_STOCK < 30). Because the AND keyword is used, the value must be greater than 0 and less than 30. Another way that a CHECK constraint can be used is to explicitly list the values that can be entered into the column. This is a handy option if you have a limited number of values and they re not likely to change (or will change infrequently). The following SQL statement creates a table that includes a CHECK constraint that defines in which decade the music belongs:
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CREATE TABLE CD_TITLES ( COMPACT_DISC_ID INT, CD_TITLE VARCHAR(60) NOT NULL, ERA CHAR(5), CONSTRAINT CK_ERA CHECK ( ERA IN ( '1940s', '1950s', '1960s', '1970s', '1980s', '1990s', '2000s' ) ) );
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The value entered into the ERA column must be one of the seven decades represented by the search condition. If you tried to enter a value other than a null value or one of these seven, you would receive an error. Notice that the IN operator is used to designate that the ERA column values must be one of the set of values enclosed by parentheses following the keyword IN. If the number of parentheses starts to confuse you, you can separate your code into lines that follow the embedding of those parentheses. For example, the preceding statement can be written as follows:
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CREATE TABLE CD_TITLES ( COMPACT_DISC_ID INT, CD_TITLE VARCHAR(60)
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NOT NULL,
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4:
Enforcing Data Integrity
ERA CHAR(5), CONSTRAINT CK_ERA CHECK ( ERA IN ( '1940s', '1950s', '1960s', '1970s', '1980s', '1990s', '2000s' ) ) );
Each set of parentheses and its content is indented to a level that corresponds to the level of embedding for that particular clause, just like an outline. Using this method tells you exactly which clauses are enclosed in which set of parentheses, and the statement is executed just the same as if you hadn t separated out the lines. The downside is that it takes up a lot of room (which is why I don t use this method in this book), although it might be a helpful tool for you for those statements that are a little more complicated. Now let s look at one other example of a CHECK constraint. This example is similar to the first one we looked at, only this one is concerned with values between certain numbers:
CREATE TABLE CD_TITLES ( COMPACT_DISC_ID INT, CD_TITLE VARCHAR(60) NOT NULL, IN_STOCK INT NOT NULL, CONSTRAINT CK_IN_STOCK CHECK ( ( IN_STOCK BETWEEN 0 AND 30 ) OR ( IN_STOCK BETWEEN 49 AND 60 ) ) ) ;
In this statement, you use the BETWEEN operator to specify a range which includes the endpoints. Because you are creating two different ranges, you enclose each range specification in parentheses: ( IN_STOCK BETWEEN 0 AND 30 ) and ( IN_STOCK BETWEEN 49 AND 60 ). These two range specifications are then connected by an OR keyword, which indicates that either one or the other condition must be met. As a result, any value entered into the IN_STOCK column must be from 0 through 30 or from 49 through 60. As I said earlier, you will learn more about search conditions in 9. At that time, you ll see just how flexible the CHECK constraint is. And when used with subqueries (see 12), they provide a powerful tool for explicitly defining what values are permitted in a particular column.
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