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PART II
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ORDER_NUM AMOUNT COMPANY ---------- ----------- ---------------112987 $27,500.00 Acme Mfg. 113069 $31,350.00 Chen Associates 113045 $45,000.00 Zetacorp 112961 $31,500.00 J.P. Sinclair
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Figure 7-7 shows the parent/child relationships in this query. Logically, it extends the join sequence of the previous example one more step, linking an order to its customer, the customer to their salesperson, and the salesperson to their office.
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The vast majority of multitable queries are based on parent/child relationships, but SQL does not require that the matching columns be related as a foreign key and primary key. Any pair of columns from two tables can serve as matching columns, provided they have
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Part II:
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comparable data types (or data types that can be converted to compatible types). This example shows a query that uses a pair of dates as matching columns: Find all orders received on a day when a new salesperson was hired.
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SELECT ORDER_NUM, AMOUNT, ORDER_DATE, NAME FROM ORDERS, SALESREPS WHERE ORDER_DATE = HIRE_DATE; ORDER_NUM AMOUNT ORDER_DATE ---------- ----------- ----------112968 $3,978.00 12-OCT-07 112979 $15,000.00 12-OCT-07 112975 $2,100.00 12-OCT-07 112968 $3,978.00 12-OCT-07 112979 $15,000.00 12-OCT-07 112975 $2,100.00 12-OCT-07
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OFFICES Table
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OFFICE 22 11 12 13 21 CITY Denver New York Chicago Atlanta Los Angeles REGION MGR Western 108 Eastern 106 Eastern 104 Eastern NULL Western 108
NAME -----------Mary Jones Mary Jones Mary Jones Larry Fitch Larry Fitch Larry Fitch
SALESREPS Table EMPL_NUM NAME
108 103 107
AGE REP_OFFICE
TITLE
Larry Fitch Paul Cruz Nancy Angelli
62 29 49
21 12 22
Sales Mgr Sales Rep Sales Rep
CUSTOMERS Table
CUST_NUM 2111 2102 2103 COMPANY JCP Inc. First Corp. Acme Mfg. CUST_REP 103 101 105 CREDIT_LIMIT $50,000.00 $65,000.00 $50,000.00
Query Results
CUST 2117 2111 2101 AMOUNT $31,500.00 $3,745.00 $1,458.00 17-DEC-89 11-JAN-90 03-JAN-90 ORDER_DATE
ORDERS Table
ORDER_NUM 112961 113012 112989
FIGURE 7-7
A four-table join
7:
Multitable Queries (Joins)
ORDERS Table
ORDER_NUM 113051 112978 113076 113062 112379 113027 112992 112875 113055 ORDER_DATE CUST
SALESREPS Table EMPL_NUM NAME
105 109 102 106 104 101 110 108 103 107 Bill Adams Mary Jones Sue Smith Sam Clark Bob Smith Dan Roberts Tom Snyder Larry Fitch Paul Cruz Nancy Angelli
HIRE_DATE
12-FEB-88 12-OCT-89 10-DEC-86 14-JUN-88 19-MAY-88 20-OCT-86 13-JAN-90 12-OCT-89 01-MAR-87 14-NOV-89
10-FEB-90 12-OCT-89 30-JAN-90
2118 2102 2107
24-FEB-90 12-OCT-89 22-JAN-90
2124 2114 2103
PART II
04-NOV-89 12-OCT-89 15-FEB-90
2118 2111 2108
FIGURE 7-8
A join not involving primary and foreign keys
The results of this query come from pairs of rows in the ORDERS and SALESREPS tables where the ORDER_DATE happens to match the HIRE_DATE for the salesperson, as shown in Figure 7-8. Neither of these columns is a foreign key or a primary key, and the relationship between the pairs of rows is admittedly a strange one the only thing the matched orders and salespeople have in common is that they happen to have the same dates. However, SQL happily joins the tables anyway. Matching columns like the ones in this example generate a many-to-many relationship between the two tables. Many orders can share a single salesperson s hire date, and more than one salesperson may have been hired on the same date. For example, note that three different orders (112968, 112975, and 112979) were received on October 12, 2007, and two different salespeople (Larry Fitch and Mary Jones) were hired that same day. The three orders, each matched to both of the two salespeople, produce six rows of query results. This many-to-many relationship is different from the one-to-many relationship created by primary key/foreign key matching columns. The situation can be summarized as follows: Joins that match primary keys to foreign keys always create one-to-many, parent/ child relationships. Other joins may also generate one-to-many relationships if the matching column in at least one of the tables has unique values for all rows of the table. In general, joins on arbitrary matching columns generate many-to-many relationships. Note that these three different situations have nothing to do with how you write the SELECT statement that expresses the join. All three types of joins are written the same way by including a comparison test for the matching column pairs in the WHERE clause or in the ON clause. Nonetheless, it s useful to think about joins in this way to understand how to turn an English-language request into the correct SELECT statement.
Part II:
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