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Outer Joins *
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The SQL join operation combines information from two tables by forming pairs of related rows from the two tables. The row pairs that make up the joined table are those where the matching columns in each of the two tables have the same value. If one of the rows of a table is unmatched in this process, the join can produce unexpected results, as illustrated by these queries: List the salespeople and the offices where they work. SELECT NAME, REP_OFFICE FROM SALESREPS NAME -------------Bill Adams Mary Jones Sue Smith Sam Clark Bob Smith Dan Roberts Tom Snyder Larry Fitch Paul Cruz Nancy Angelli REP_OFFICE ---------13 11 21 11 12 12 NULL 21 12 22
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List the salespeople and the cities where they work. SELECT NAME, CITY FROM SALESREPS, OFFICES WHERE REP_OFFICE = OFFICE NAME ------------Mary Jones Sam Clark Bob Smith Paul Cruz Dan Roberts Bill Adams Sue Smith Larry Fitch Nancy Angelli CITY -------New York New York Chicago Chicago Chicago Atlanta Los Angeles Los Angeles Denver
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Based on the English-language descriptions of these two queries, you would probably expect them to produce the same number of rows. But the first query includes a row for each of the ten salespeople, while the second query produces only nine. Why Because Tom Snyder is currently unassigned and has a NULL value in the REP_OFFICE column (which is the matching column for the join). This NULL value doesn't match any of the office numbers in the OFFICES table, so Tom's row in the SALESREPS table is unmatched. As a result, it "vanishes" in the join. The standard SQL join thus has the potential to lose information if the tables being joined contain unmatched rows.
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Based on the English-language version of the request, you would probably expect the second query to produce results like these: List the salespeople and the cities where they work. SELECT NAME, CITY FROM SALESREPS, OFFICES WHERE REP_OFFICE *= OFFICE NAME ------------Tom Snyder Mary Jones Sam Clark Bob Smith Paul Cruz Dan Roberts Bill Adams Sue Smith Larry Fitch Nancy Angelli CITY -------NULL New York New York Chicago Chicago Chicago Atlanta Los Angeles Los Angeles Denver
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These query results are generated by using a different type of join operation, called an outer join (indicated by the "*=" notation in the WHERE clause). The outer join is an extension of the standard join described earlier in this chapter, which is sometimes called an inner join. The SQL1 standard specifies only the inner join; it does not include the outer join. The earlier IBM SQL products also support only the inner join. However, the outer join is a well-understood and useful part of the relational database model, and it has been implemented in many non-IBM SQL products, including the flagship database products from Microsoft, Sybase, Oracle, and Informix. The outer join is also the most natural way to express a certain type of query request, as shown in the remainder of this section. To understand the outer join well, it's useful to move away from the sample database and consider the two simple tables in Figure 7-12. The GIRLS table lists five girls and the cities where they live; the BOYS table lists five boys and the cities where they live. To find the girl/boy pairs who live in the same city, you could use this query, which forms the inner join of the two tables:
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Figure 7-12: Anatomy of an outer join
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List the girls and boys who live in the same city. SELECT * FROM GIRLS, BOYS WHERE GIRLS.CITY = BOYS.CITY GIRLS.NAME ---------Mary Mary Susan Betty GIRLS.CITY ---------Boston Boston Chicago Chicago BOYS.NAME --------John Henry Sam Sam BOYS.CITY --------Boston Boston Chicago Chicago
The inner join produces four rows of query results. Notice that two of the girls (Anne and Nancy) and two of the boys (James and George) are not represented in the query results. These rows cannot be paired with any row from the other table, and so they are missing from the inner join results. Two of the unmatched rows (Anne and James) have valid values in their CITY columns, but they don't match any cities in the opposite table. The other two unmatched rows (Nancy and George) have NULL values in their CITY columns, and by the rules of SQL NULL handling, the NULL value doesn't match any other value (even another NULL value). Suppose you wanted to list the girl/boy pairs who share the same cities and include the unmatched girls and boys in the list. The outer join of the GIRLS and BOYS tables produces exactly this result. The following list shows the procedure for constructing the outer join, and the outer join is shown graphically in Figure 7-12. 1. Begin with the inner join of the two tables, using matching columns in the normal way. 2. For each row of the first table that is not matched by any row in the second table, add one row to the query results, using the values of the columns in the first table, and assuming a NULL value for all columns of the second table. 3. For each row of the second table that is not matched by any row in the first table, add one row to the query results, using the values of the columns in the second table, and assuming a NULL value for all columns of the first table. 4. The resulting table is the outer join of the two tables. Here is the SQL statement that produces the outer join: List girls and boys in the same city, including any unmatched girls or boys. SELECT * FROM GIRLS, BOYS WHERE GIRLS.CITY *=* BOYS.CITY GIRLS.NAME ---------Mary Mary Susan Betty Anne GIRLS.CITY ---------Boston Boston Chicago Chicago Denver BOYS.NAME --------John Henry Sam Sam NULL BOYS.CITY --------Boston Boston Chicago Chicago NULL
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