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With these comparison operators, we can create many different queries. Often we will compare a value of an attribute (say MemberType) to a literal value (say Junior ). Table 2-2 shows some examples of Boolean expressions that we can use as conditions in the WHERE clause of an SQL statement for selecting rows from the Member table.
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Table 2-2. Examples of Boolean Expressions on the Member Table
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Expression
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MemberType = 'Junior' Handicap <= 12 JoinDate < '01/01/2000' Gender = 'F'
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Retrieved Rows
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All junior members All members with a handicap of 12 or less Everyone who has been a member since before the beginning of 2000 All the women
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Some implementations of SQL are case sensitive when comparing text, and others are not. Being case sensitive means that, in comparisons, the different cases of the letters will make a difference; in other words, Junior is different from junior , which is different from JUNIOR . I usually check out any new database system I use to see what it does. If you do not care about the case of the attribute you are considering (that is, you are happy to retrieve rows where MemberType is Junior or jUnIoR or whatever), you can use the SQL function UPPER as in Listing 2-15. This will turn the value of each text attribute into uppercase before you do the comparison so that you know what is happening.
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Listing 2-15. Selecting Rows Where the Case of a Text Value Is Not Important SELECT * FROM Member m WHERE UPPER(m.MemberType) = 'JUNIOR'
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Logical Operators
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We can also combine Boolean expressions to create more interesting conditions. For example, we can specify that two expressions must both be true before we retrieve a particular row. Let s assume we want to find all the junior girls. This requires two conditions to be true: they must be female, and they must be juniors. We can easily express each of these conditions independently. After that, we can use the logical operator AND, as in Listing 2-16, to say that both conditions must be true.
CHAPTER 2 SIMPLE QUERIES ON ONE TABLE
Listing 2-16. Finding All the Junior Girls SELECT * FROM Member m WHERE m.MemberType = 'Junior' AND m.Gender = 'F'
Here we will look at three logical operators: AND, OR, and NOT. We have already seen how AND works. If we use OR between two expressions, then we require only one of the expressions to be true (but if they are both true, that is OK as well). NOT is used before an expression. For example, for our Member table, we might ask for rows obeying the condition NOT (MemberType = 'Social'). This means check each row, and if the value of MemberType is Social , then we don t want that row. Table 2-3 gives some examples for the Member table. In the diagrams, each circle represents a set of rows (that is, those for social members or those for members with handicaps under 12). The shaded area represents the result of the operation.
Table 2-3. Examples of Logical Operators
Expression
MemberType = 'Senior' AND Handicap < 12
Description of Retrieved Data
Seniors with a handicap under 12
Diagram of Retrieved Data
Senior <12
MemberType = 'Senior' OR Handicap < 12
All the senior members as well as anyone else with a good handicap (those less than 12)
Senior
NOT MemberType = 'Social'
All the members except the social ones (for the current data, that would be just the seniors and juniors)
Social
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The little truth tables in Figure 2-4 can be helpful in understanding and remembering how the Boolean operators work. You read them like this: In Figures 2-4a and 2-4b, we have two expressions, one along the top and one down the left. Each expression can have one of two values: True (T) or False (F). If we combine them with the Boolean expression AND, then Figure 2-4a shows that the overall statement is True only if both the contributing statements are True (the square in the top left). If we combine them with an OR statement, then the overall statement is False only if both contributing statements are False (bottom right of Figure 2-4b). The table in Figure 2-4c says that if our original statement is True and we put NOT in front, then the result is False (left column), and vice versa.
Figure 2-4. Truth tables for logical operators (T = True, F = False)
Sometimes it can be a bit tricky turning natural-language descriptions into Boolean expressions. If you were asked for a list that included all the woman and all the juniors (don t ask why!), you might translate this literally and write the condition MemberType = 'Junior' AND Gender = 'F'. However, the AND means both conditions must be true, so this would give us junior women. What our natural-language statement really means is I want the row for any member if they are either a woman OR they are a junior (or both). Be careful.
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