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Querying SQL Data
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COMPACT_DISC: VARCHAR(60) Famous Blue Raincoat Blue Court and Spark Past Light Kojiki That Christmas Feeling Patsy Cline: 12 Greatest Hits Carreras Domingo Pavarotti in Concert After the Rain: The Soft Sounds of Erik Satie Out of Africa Leonard Cohen The Best of Fundamental Blues on the Bayou Orlando
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CATEGORY: VARCHAR(15) Vocal Vocal Vocal Instrumental Instrumental Vocal Vocal Vocal Instrumental Instrumental Vocal Vocal Vocal Instrumental
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PRICE: NUMERIC(5,2) 16.99 14.99 14.99 15.99 15.99 14.99 16.99 15.99 16.99 16.99 15.99 15.99 14.99 14.99
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ON_HAND: INT 13 42 22 17 6 8 32 27 21 29 12 34 27 5
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CD information in the COMPACT_DISC_STOCK table
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Are there performance considerations regarding the use of GROUP BY Yes, the use of GROUP BY can cause performance issues because the RDBMS usually must perform a sort in order to properly group the rows, and sorts of large numbers of rows (tens of thousands or more) can consume considerable resources. But also be aware that the ORDER BY clause (presented later in this chapter) and the DISTINCT keyword also usually require sorts and thus have similar performance considerations. That doesn t mean you should be afraid to use them, but rather that you should strive to learn the performance impact of your SQL statements as you gain experience, and thus become more skilled at writing statements that perform best on your particular vendor implementation. For example, in Oracle, a GROUP BY that lists all columns in the SELECT clause is more efficient than using the DISTINCT keyword, and yet the query results of the two approaches are identical.
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SQL: A Beginner s Guide
As I said earlier, you can still use the WHERE clause in a SELECT statement that includes a GROUP BY clause. For example, suppose you want to view totals only for CDs that sell for less than $16.00. To do this, simply modify your SELECT statement as follows:
SELECT FROM WHERE GROUP CATEGORY, SUM(ON_HAND) AS TOTAL_ON_HAND COMPACT_DISC_STOCK PRICE < 16.00 BY CATEGORY;
Your query results from this statement will be slightly different than if the WHERE clause had not been included:
CATEGORY -----------Instrumental Vocal TOTAL_ON_HAND ----------28 172
Notice that with CDs that sell for $16.00 or more excluded, your results now show only 28 instrumental CDs and 172 vocal CDs. In the previous two examples, the GROUP BY clause specified only one column. However, you can specify additional columns as necessary. This allows you to create subgroups that group data within the scope of the main groups. For example, suppose you want to group data not only according to the values in the CATEGORY column, but also according to the values in the PRICE column. To do this, you should include the PRICE column in the select list as well as the GROUP BY clause, as shown in the following SELECT statement:
SELECT CATEGORY, PRICE, SUM(ON_HAND) AS TOTAL_ON_HAND FROM COMPACT_DISC_STOCK GROUP BY CATEGORY, PRICE;
Now your query results will include six rows, rather than two:
CATEGORY -----------Instrumental Vocal Instrumental Vocal Instrumental Vocal PRICE ----14.99 14.99 15.99 15.99 16.99 16.99 TOTAL_ON_HAND ------------5 99 23 73 50 45
Notice that for each CATEGORY value, there are three rows, one for each of the PRICE values. For example, in the Vocal group, there are 99 CDs at 14.99, 73 CDs at 15.99, and 45 CDs at 16.99. The number of rows depends on how many different values there are in the columns specified in the GROUP BY clause. In this example, there are two different values in the CATEGORY column and three different values in the PRICE column, which means that six (two times three) rows will be returned.
7:
Querying SQL Data
NOTE
The order in which your query results are returned can vary from implementation to implementation. For example, some products might return all the Instrumental rows together, followed by all the Vocal rows. However, regardless of how the information appears in your user interface, the end results should be the same. Also, most implementations permit you to add an ORDER BY clause (discussed later in this chapter) to sort the summarized rows.
Now let s take a look at the ROLLUP and CUBE operators. Both operators are similar in function in that they return additional data in your query results when added to the GROUP BY clause. The main difference between the two is that the CUBE operator returns more information than the ROLLUP operator. Let s start with an example of the ROLLUP operator so I can demonstrate the difference. In the following SELECT statement, the GROUP BY clause applies the ROLLUP operator to the CATEGORY and PRICE columns:
SELECT CATEGORY, PRICE, SUM(ON_HAND) AS TOTAL_ON_HAND FROM COMPACT_DISC_STOCK GROUP BY ROLLUP (CATEGORY, PRICE);
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