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You can see how the SQL statement in Listing 3-16 is like the calculus in that it describes what a retrieved row should be like. If you look carefully at the statement, you can pick out all the algebra operations. The second line (FROM) is a big Cartesian product, the next two lines are the join conditions (which would give us a table like the one in Figure 3-7), the final line is our select operation, and the first line tells us what columns to project. The two SQL statements in Listings 3-14 and 3-16 are equivalent. They will return the same set of rows: Listing 3-14 reflects the underlying algebra of how, and Listing 3-16 reflects the underlying calculus of what. You may be wondering why I ve been bothering with the calculus expressions and their somewhat obscure symbols like , and so on. For the particular example in this section, the calculus and SQL statements are so similar that we don t really need the intermediate step of writing the calculus statement. However, for more complicated queries, I find having a shorthand notation for describing a typical row very helpful. As you get more proficient, you will find that for many queries you can just write the SQL statement directly, but when you get stumped, the more approaches at your disposal, the more likely you will be able to find a solution.

Having seen some of the ways that a bean can be configured, you should look briefly at the life cycle of the bean factory and how that affects the life cycle of the beans that reside within it. Any bean that implements BeanFactory is expected to honor an ordered set of method calls to beans implementing standard interfaces. Table 3-3 enumerates the methods called during the initialization of a bean.

Since we named the reference sdk, that is the prefix used in defining the GridSplitter (<sdk:GridSplitter>).

This book is about queries in SQL, but most database products also provide a diagrammatic interface to express queries. Just for completeness, I ll show you what a typical diagrammatic interface looks like for retrieving the names of members who entered an Open tournament in 2006.

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Notifies the bean of its name within the factory. It is generally not recommended that a dependency be created on the bean name, but it may prove useful for logging purposes. Intended for use by classes within the framework. Allows beans to look up other beans by name from the factory. This is generally unnecessary because bean dependencies are typically received by injection. Permits resources to be looked up directly from the resource loader for example, where the name to be used is calculated as a suffix to some fixed root.

Run the application. It should look similar to Figure 4-15. Notice that you can now click and drag the GridSplitter to resize the two Grid columns.

Figure 3-10 shows the Microsoft Access interface, but most products have something very similar. The tables are represented by the rectangles in the top section with the lines showing the joins between them. The columns to be retrieved have a check mark ( ) in the row marked Show, and the select conditions are shown for the relevant fields in the row marked Criteria.

Table 3-3. Methods Called on Startup (Continued)

Figure 4-15. The completed GridSplitter application As you can see, it s quite easy to gain the rich functionality of a grid splitter in your application with the Silverlight GridSplitter control.

The joins we have been looking at in this chapter are equi-joins. An equi-join is one where the join condition has an equals as in m.MemberID = e.MemberID. This is the most common type of condition, but you can have different operators. A join is just a Cartesian product followed by a select, and the select condition can consist of different comparison operators (for example, <> or > ) and also logical operators (for example, AND or NOT). These sorts of joins don t turn up all that often. On the tables we have been looking at, I can t for the life of me think of a sensible query that would need one. The joins up to now have also been what are more accurately called inner joins. You will recall that the SQL key phrase (for example, in Listing 3-11) was INNER JOIN. There are also joins called outer joins. The best way to understand an outer join is to see where they are useful. Have a look at the (modified) Member and Type tables in Figure 3-11. You might want to produce different lists from the Member table, such as numbers and names, names and membership types, and so on. In these lists you expect to see all the members (for the table in Figure 3-11, that would be nine rows). Then you might think that as well as seeing the numbers and names in your member list, you will also include the membership fee. You join the two tables (with the condition MemberType = Type) and find that you lose one of your members Barbara Olson (Figure 3-12).

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