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10.5 Data Manipulation via Inline Views
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Inline views are subqueries assuming the role of a table expression in SQL commands. In other words, you specify a subquery (between parentheses) in places where you would normally specify a table or view name. We already discussed inline views in the previous chapter, but we considered inline views only in the FROM component of queries. You can also use inline views for data manipulation purposes. Data manipulation via inline views is especially interesting in combination with updatable join views. Listing 10-19 shows an example of an UPDATE command against an inline updatable join view. Listing 10-19. UPDATE via an Inline Updatable Join View SQL> update ( 2 3 4 5 set msal select e.msal from employees e join departments d using (deptno) where location = 'DALLAS') = msal + 1;
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5 rows updated. SQL> rollback; Rollback complete. SQL> Listing 10-19 shows that you can execute UPDATE commands via an inline join view, giving all employees in Dallas a symbolic salary raise. Note that the UPDATE command does not contain a WHERE
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clause at all; the inline view filters the rows to be updated. This filtering would be rather complicated to achieve in a regular UPDATE command against the EMPLOYEES table. For that, you probably would need a correlated subquery in the WHERE clause. At first sight, it may seem strange to perform data manipulation via inline views (or subqueries), but the number of possibilities is almost unlimited. The syntax is elegant and readable, and the response time is at least the same (if not better) compared with the corresponding commands against the underlying base tables. Obviously, all restrictions regarding data manipulation via updatable join views (as discussed earlier in this section) still apply.
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10.6 Views and Performance
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Normally, the Oracle DBMS processes queries against views in the following way: 1. 2. 3. 4. 5. The DBMS notices that views are involved in the query entered. The DBMS retrieves the view definition from the data dictionary. The DBMS merges the view definition with the query entered. The optimizer chooses an appropriate execution plan for the result of the previous step: a command against base tables. The DBMS executes the plan from the previous step.
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In exceptional cases, the Oracle DBMS may decide to execute the view query from the data dictionary, populate a temporary table with the results, and then use the temporary table as a base table for the query entered. This happens only if the Oracle DBMS is not able to merge the view definition with the query entered, or if the Oracle optimizer determines that using a temporary table is a good idea. In the regular approach, as outlined in the preceding five steps, steps 2 and 3 are the only additional overhead. One of the main advantages of this approach is that you can benefit optimally from indexes on the underlying base tables. For example, suppose you enter the following query against the AVG_EVALUATIONS view: SQL> select * 2 from avg_evaluations 3 where avg_eval >= 4 This query is transformed internally into the statement shown in Listing 10-20. Notice that the WHERE clause is translated into a HAVING clause, and the asterisk (*) in the SELECT clause is expanded to the appropriate list of column expressions. Listing 10-20. Rewritten Query Against the REGISTRATIONS Table SQL> 2 3 4 5 select , from group having r.course avg(r.evaluation) as avg_eval registrations r by r.course avg(r.evaluation) >= 4;
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COURSE AVG_EVAL ------ -------JAV 4.125 OAU 4.5 XML 4.5 SQL> Especially when dealing with larger tables, the performance overhead of using views is normally negligible. If you start defining views on views on views, the performance overhead may become more significant. And, in case you don t trust the performance overhead, you can always use diagnostic tools such as SQL *Plus or SQL Developer AUTOTRACE (see 7, Section 7.6) to check execution plans and statistics.
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