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Now let s make one more change to the WHERE clause. Suppose you want the IN_STOCK value to be less than 20 and greater than 5 or the IN_STOCK value to be less than 20 and the RETAIL_PRICE value to be less than 15. One way to do this is to place parentheses around the last two predicates:
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SELECT * FROM INVENTORY WHERE IN_STOCK < 20 AND (IN_STOCK > 5 OR RETAIL_PRICE < 15.00);
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The results you receive this time are slightly different because the Blue row no longer evaluates to true:
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COMPACT_DISC_ID --------------99301 99303 99306 CD_TITLE ---------------------Famous Blue Raincoat Court and Spark That Christmas Feeling COPYRIGHT --------1991 1974 1993 RETAIL_PRICE -----------16.99 14.99 10.99 IN_STOCK -------6 18 3
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By combining predicates together, you can create a variety of search conditions that allow you to return exactly the data you need. The key to writing effective search conditions is a thorough understanding of predicates and the operators used to form those predicates. 9 takes you through many of the operators you can use and the types of predicates you can create. With that information, you can create effective, concise search conditions.
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Use the GROUP BY Clause to Group Query Results
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The next clause in the SELECT statement is the GROUP BY clause. The GROUP BY clause has a function very different from the WHERE clause. As the name implies, the GROUP BY clause is used to group together types of information in order to summarize related data. The GROUP BY clause can be included in a SELECT statement whether or not the WHERE clause is used. As you saw in the Use a SELECT Statement to Retrieve Data section, the syntax for the GROUP BY clause, as it appears in the SELECT statement syntax, looks like the following: [ GROUP BY <grouping specification> ] However, the <grouping specification> placeholder can be broken down into smaller elements: <column name> [ { , <column name> } . . . ] | { ROLLUP | CUBE } ( <column name> [ { , <column name> } . . . ] ) In actuality, the <grouping specification> syntax, like some of the other syntax in this book, is even more complex than what I m presenting here; however, for the purposes of this chapter, this syntax will provide you with all the details you need to use the GROUP BY clause effectively. Now let s look at the syntax itself. The first line should be self-explanatory. You specify one or more column names that contain values that should be grouped together. This normally applies to columns that represent some sort of categories whose values
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SQL: A Beginner s Guide
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are repeated within the table. For example, your database might include a table that lists the employees in your organization. Suppose that the table includes a job title for each employee. You might find that you want to group together information in the table by job title, with one row in the result set for each job title value, perhaps to determine such things as the average salary of each job or number of employees holding each job title. If you need to specify more than one column name, be sure to separate them with a comma following each name (except the last). As you can see from the syntax, you can specify the second line rather than the first. In this case, you can use either the ROLLUP or CUBE keyword, along with the list of column names, enclosed in parentheses. Again, be sure to separate column names with commas. With regard to ROLLUP and CUBE, the best way to understand these operators is through the use of examples. In fact, the best way to understand the entire GROUP BY clause is through examples. However, before we get into those, let s take a look at the table on which the examples will be based. Figure 7-4 shows the COMPACT_DISC_STOCK table, which contains a list of CDs, whether they re vocal or instrumental, the price, and how many of each title are currently in stock. Now we can get on with the examples. In the first one we ll look at, I use the GROUP BY clause to group rows based on the CATEGORY column of the COMPACT_DISC_STOCK table, as shown in the following SELECT statement:
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SELECT CATEGORY, SUM(ON_HAND) AS TOTAL_ON_HAND FROM COMPACT_DISC_STOCK GROUP BY CATEGORY;
First, let s take a look at the GROUP BY clause, which specifies that the rows should be grouped together based on the CATEGORY column. If you look at Figure 7-4, you ll see that the column contains only two values: Vocal and Instrumental. As a result, the SELECT statement will return only two rows, one for Instrumental and one for Vocal:
CATEGORY -----------Instrumental Vocal TOTAL_ON_HAND ------------78 217
Now let s look at the SELECT clause in the preceding SELECT statement example. Notice that the select list includes the SUM function, which adds data in the ON_HAND column. The resulting column is then named TOTAL_ON_HAND. The only other column included in the select list is the CATEGORY column. The select list can include only those columns that are specified in the GROUP BY clause or that can somehow be summarized. What this statement does, then, is add together the total ON_HAND values for each value in the CATEGORY column. In this case, there are 217 total CDs in stock that are categorized as Vocal, and 78 in stock that are categorized as Instrumental. If there were another category, then a row would appear for that one as well.
7:
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