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columns to construct the join, before the NULL-extended rows are added to the outer join results. Because the PARENTS table is being used twice in the FROM clause, in two different roles, it s necessary to give it two different table aliases so that the correct names can be specified in the select list. As this example shows, even a four-join query like this one can become quite complex with the SQL2 syntax. However, despite the complexity, the SQL2 query does specify precisely the query that the DBMS is to carry out. There is no ambiguity about the order in which the tables are joined, or about which joins are inner or outer joins. Overall, the added capability is well worth the added complexity introduced by the extended SQL2 FROM clause. Although none of the query examples included in this section had WHERE or ORDER BY clauses, they can be freely used with the extended FROM clause in SQL2. The relationship among the clauses is simple and remains as described earlier in this chapter. The processing specified in the FROM clauses occurs first, including any joins or unions. The join criteria specified in a USING or ON clause are applied as a part of the particular join specification where they appear. When processing of the FROM class is complete, the resulting table is used to apply the selection criteria in the WHERE clause. Thus, the ON clause specifies search criteria that apply to specific joins; the WHERE clause specifies search criteria that apply to the entire table resulting from these joins.

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This chapter described how SQL handles queries that combine data from two or more tables: I In a multitable query (a join), the tables containing the data are named in the FROM clause. I Each row of query results is a combination of data from a single row in each of the tables, and it is the only row that draws its data from that particular combination. I The most common multitable queries use the parent/child relationships created by primary keys and foreign keys. I In general, joins can be built by comparing any pair(s) of columns from the two joined tables, using either a test for equality or any other comparison test. I A join can be thought of as the product of two tables from which some of the rows have been removed. I A table can be joined to itself; self-joins require the use of a table alias. I Outer joins extend the standard (inner) join by retaining unmatched rows of one or both of the joined tables in the query results, and using NULL values for data from the other table. I The SQL2 standard provides comprehensive support for inner and outer joins, and for combining the results of joins with other multitable operations such as unions, intersections, and differences.

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SELECT MOVIE_TITLE FROM MOVIE WHERE MOVIE_ID IN (SELECT MOVIE_ID FROM MOVIE_COPY WHERE MEDIA_FORMAT = 'V' AND DATE_SOLD IS NULL) AND MOVIE_ID NOT IN (SELECT MOVIE_ID

any requests for information don t require the level of detail provided by the SQL queries described in the last two chapters. For example, each of the following requests asks for a single value or a small number of values that summarize the contents of the database:

I What is the total quota for all salespeople I What are the smallest and largest assigned quotas I How many salespeople have exceeded their quota I What is the size of the average order I What is the size of the average order for each sales office I How many salespeople are assigned to each sales office SQL supports these requests for summary data through column functions and the GROUP BY and HAVING clauses of the SELECT statement, which are described in this chapter.

SQL lets you summarize data from the database through a set of column functions. A SQL column function takes an entire column of data as its argument and produces a single data item that summarizes the column. For example, the AVG() column function takes a column of data and computes its average. Here is a query that uses the AVG() column function to compute the average value of two columns from the SALESREPS table: What are the average quota and average sales of our salespeople

SELECT AVG(QUOTA), AVG(SALES) FROM SALESREPS AVG(QUOTA) AVG(SALES) ------------ -----------$300,000.00 $289,353.20

FROM MOVIE_COPY WHERE MEDIA_FORMAT = 'D' AND DATE_SOLD IS NULL);

Figure 8-1 graphically shows how the query results are produced. The first column function in the query takes values in the QUOTA column and computes their average; the second one averages the values in the SALES column. The query produces a single row of query results summarizing the data in the SALESREPS table. SQL offers six different column functions, as shown in Figure 8-2. The column functions offer different kinds of summary data: I SUM() computes the total of a column. I AVG() computes the average value in a column.

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