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Before I go too deeply into the specifics of views, I want to quickly review some of what I discussed in s 2 and 3. A view, as you might recall, is one of three types of tables supported by SQL, along with base tables and derived tables. Most base tables are schema objects and come in four types: persistent base tables, global temporary tables, created local temporary tables, and declared local temporary tables. Of these four types, it is the persistent base tables that hold the actual SQL data. Derived tables, on the other hand, are merely the results you see when you query data from the database. For example, if you request data from the COMPACT_DISCS table, the results of your request are displayed in a table-like format, which is known as the derived table. In some ways, a view is a cross between a persistent base table and a derived table. It is like a persistent base table in that the view definition is stored as a schema object using a unique name (within the schema) that can be accessed as you would a base table. However, a view is like a derived table in that no data is stored in association with the view. Both derived tables and views are types of virtual tables. The data is selected from one or more base tables when you invoke the view. In fact, you can think of a view as merely a named derived table, with the view definition stored in the schema. The data results that you see when you call a view are not stored anywhere but are derived from existing base tables. Views can be useful tools when accessing different types of data. One of the main advantages of using views is that you can define complex queries and store them within the view definition. Instead of recreating those queries every time you need them, you can simply
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invoke the view. Moreover, views can be a handy way to present information to users without providing them with more information than they need or information they should not see. For example, you might want users in your organization to have access to certain employee records, but you might not want information such as Social Security numbers or pay rates available to those users, so you can create a view that provides only the information that they should see. Views can also be used to synthesize complex structures and present information in a way that is easier for some users to understand, which in effect hides the underlying structure and complexity of the database from the users. Now that you have an overview of what views are, let s take a look at a few examples that illustrate how data is extracted from base tables into the type of derived table that is presented by a view definition. The first example we ll look at, shown in Figure 5-1, is based on the COMPACT_DISC_INVENTORY table, which includes six columns. Suppose you want to view only the CD_TITLE, COPYRIGHT, and IN_STOCK columns. You can create a view that extracts these three columns from the table and organizes them as if the data existed in its own table, as shown in Figure 5-1. The COMPACT_DISCS_IN_STOCK view contains a query that defines exactly what data should be returned by the view. You might have noticed that the column names in the view are different from the column names of the COMPACT_DISC_INVENTORY table, even though the data within the columns is the same. This is because you can assign names to view columns that are different from the originating table if you wish. If you don t assign any names, the view columns inherit the names from the originating table. The same is true of data types. The view columns inherit their data types from their respective table columns. For example, the COMPACT_DISC column in the COMPACT_DISCS_IN_STOCK view inherits the VARCHAR(60) data type from the CD_TITLE column of the COMPACT_DISC_INVENTORY table. You don t specify the VARCHAR(60) data type anywhere within the view definition. As you can see, a view allows you to define which columns are returned when you invoke the view. The definition for the COMPACT_DISCS_IN_STOCK view specifies three columns; however, it could have specified any of the columns from the COMPACT_DISC_INVENTORY table. In addition to columns, a view definition can specify which rows are returned. For example, Figure 5-2 shows the CDS_IN_STOCK_1990S view. Notice that it contains the same columns as the COMPACT_DISCS_IN_STOCK view (shown in Figure 5-1), but there are fewer rows. In this case, the view definition not only specifies the same three columns from the COMPACT_DISC_INVENTORY table, but also specifies that only rows with values between 1990 and 1999 (inclusive) in the COPYRIGHT column fall are to be returned. In the previous two examples, we looked at views that derive data from only one table; however, you can create views based on multiple tables. This is particularly useful if you want to display related information that spans more than one table. Let s take a look at Figure 5-3, which includes the CD_INVENTORY table and the LABELS table. The CD_INVENTORY table contains a list of CDs in your inventory, and the LABELS table contains a list of companies that publish CDs. I am briefly introducing multiple table access here because it is a great way to demonstrate how well views can hide query complexity. The topic is covered in detail in 11.
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