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CREATE VIEW SELECT FROM WHERE CREATE VIEW SELECT FROM WHERE
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EASTREPS AS * SALESREPS REP_OFFICE IN (11, 12, 13) NYREPS AS * EASTREPS REP_OFFICE = 11
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For purposes of illustration, the NYREPS view is defined in terms of the EASTREPS view, although it could just as easily have been defined in terms of the underlying table. Under the SQL2 standard, the following DROP VIEW statement removes both of the views from the database:
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DROP VIEW EASTREPS CASCADE
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The CASCADE option tells the DBMS to delete not only the named view, but also any views that depend on its definition. In contrast, this DROP VIEW statement:
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fails with an error, because the RESTRICT option tells the DBMS to remove the view only if no other views depend on it. This provides an added precaution against unintentional side-effects of a DROP VIEW statement. The SQL2 standard requires that either RESTRICT or CASCADE be specified. But many commercial SQL products support a version of the DROP VIEW statement without an explicitly specified option for backward compatibility with earlier versions of their products released before the publication of the SQL2 standard. The specific behavior of dependent views in this case depends on the particular DBMS brand.
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Conceptually, a view is a virtual table within a database. The row/column data in the view is not physically stored in the database: it is derived from actual data in the underlying source tables. If the view definition is relatively simple (for example, if the view is a simple row/column subset of a single table, or a simple join based on foreign key relationships), it is fairly easy for the DBMS to translate database operations on the view into operations on the underlying tables. In this situation, the DBMS will perform this translation on the fly, operation by operation as it processes database queries or updates. In general, operations that update the database through a view (INSERT,
SQL: The Complete Reference
UPDATE, or DELETE operations) will always be carried out in this way by translating the operation into one or more operations on the source tables. If the view definition is more complicated, the DBMS may need to actually materialize the view to carry out a query against it. That is, the DBMS will actually carry out the query that defines the view and store the query results in a temporary table within the database. Then the DBMS carries out the requested query against this temporary table to obtain the requested results. When the query processing has finished, the DBMS discards the temporary table. Figure 14-6 shows this materialization process. Clearly, materializing the view contents can be a very high-overhead operation. If the typical database workload contains many queries that require view materialization, the total throughput capacity of the DBMS can be dramatically reduced. To address this problem, some commercial DBMS products support materialized views. When you define a view as a materialized view, the DBMS will carry out the query that defines the view once (typically when the materialized view is defined), store the results (i.e., the data that appears in the view) within the database, and then permanently maintain this copy of the view data. To maintain the accuracy of the materialized view data, the DBMS must automatically examine every change to the data in the underlying
Figure 14-6.
Materializing a view for query processing
14:
Views
source tables and make the corresponding changes in the materialized view data. When the DBMS must process a query against the materialized view, it has the data already at hand and can process the query very efficiently. Figure 14-7 shows DBMS operation with a materialized view. Materialized views provide a trade-off between the efficiency of updates on the data contained in the view and the efficiency of queries on the view data. In a nonmaterialized view, updates to the source tables for a view are unaffected by the view definition; they proceed at normal DBMS processing speed. However, queries against a nonmaterialized view are much less efficient than queries against ordinary database tables, since the DBMS must do a great deal of on-the-fly work to process the queries. Materialized views reverse this balance of work. When a materialized view is defined, updates to the source tables for the view are much less efficient than updates to ordinary database tables, since the DBMS must calculate the impact of the updates and change the materialized view data accordingly. However, queries against a materialized view can proceed at the same speed as queries against actual database tables, since the materialized view is represented within the database in the same form as a real table. Thus, a materialized view is most useful when the volume of updates to the underlying data is relatively small, and the volume of queries against the view is relatively high.
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