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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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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:
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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.
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Column Functions
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
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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I MIN() finds the smallest value in a column. I MAX() finds the largest value in a column. I COUNT() counts the number of values in a column. I COUNT(*) counts rows of query results. The argument to a column function can be a simple column name, as in the previous example, or it can be a SQL expression, as shown here: What is the average quota performance of our salespeople
RETRIEVING DATA SELECT AVG(100 * (SALES/QUOTA)) FROM SALESREPS AVG(100*(SALES/QUOTA)) ----------------------102.60
To process this query, SQL constructs a temporary column containing the value of the expression (100 * (SALES/QUOTA)) for each row of the SALESREPS table and then computes the averages of the temporary column.
Figure 8-1.
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