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Your goal is to map this flag column to a successfulBid property of the Item class To map this as an object reference, you need a literal join condition, because there is no foreign key Hibernate can use for a join In other words, for each ITEM row, you need to join a row from the BID table that has the SUCCESSFUL flag set to T If there is no such row, the anItemgetSuccessfulBid() call returns null Let s first map the Bid class and a successful boolean property to the SUCCESSFUL database column:.

In implementation, taglibs are portable across different containers, but they have their own deployment descriptors, which are extra development effort. If you do not make any special effort, then most of the validation of JSP pages and the XML metadata

There is a fundamental difference in the way you access data in Java and in a relational database. In Java, when you access a user s billing information, you call aUser.getBillingDetails().getAccountNumber() or something similar. This is the most natural way to access object-oriented data, and it s often described as walking the object network. You navigate from one object to another, following pointers between instances. Unfortunately, this isn t an efficient way to retrieve data from an SQL database. The single most important thing you can do to improve the performance of data access code is to minimize the number of requests to the database. The most obvious way to do this is to minimize the number of SQL queries. (Of course, there are other more sophisticated ways that follow as a second step.) Therefore, efficient access to relational data with SQL usually requires joins between the tables of interest. The number of tables included in the join when retrieving data determines the depth of the object network you can navigate in memory. For example, if you need to retrieve a User and aren t interested in the user s billing information, you can write this simple query:

On the other hand, if you need to retrieve a User and then subsequently visit each of the associated BillingDetails instances (let s say, to list all the user s credit cards), you write a different query:

you have to write only takes place server side. For example, you have to deploy to a server and then remember to retrieve changed JSP pages to see if the changes generate Java source that compiles. This process may work as you begin a project, but as the number of pages increases, it soon becomes unworkable. Figure 12.1 shows the typical development process of a web application. In this manual process, there are too many files that developers create by hand files only validated during and after deployment. We need to automate the tests, run them earlier in the process, and stop writing so many deployment descriptors. Our new development process will look like figure 12.2:

select * from USERS u left outer join BILLING_DETAILS bd on bd.USER_ID = u.USER_ID where u.USER_ID = 123

Tag libraries are the safest way to add code to JSP pages. That does not mean they are the easiest. Historically the creation of the XML taglib descriptor was one of those manual chores that added extra work to the build process. Like most manual stages, it is prone to error, and as it is not particularly complicated, it is an ideal target for automating. The tool for automating such a process is XDoclet. As we demonstrated in chapter 11, XDoclet is capable of examining source files and building XML, text, or source files based on tags used to mark up classes and source.

As you can see, to efficiently use joins you need to know what portion of the object network you plan to access when you retrieve the initial User this is before you start navigating the object network! On the other hand, any object persistence solution provides functionality for fetching the data of associated objects only when the object is first accessed. However, this piecemeal style of data access is fundamentally inefficient in the context of a relational database, because it requires executing one statement for each node or collection of the object network that is accessed. This is the dreaded n+1 selects problem. This mismatch in the way you access objects in Java and in a relational database is perhaps the single most common source of performance problems in Java applications. There is a natural tension between too many selects and too big