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Components help divide the labor of application development among specific skill sets, enabling each member of a development team to focus on his or her ability. For example, JSP templates can be created by graphic designers, their behavior can be coded by Java programming language coders, the business logic can be coded by domain experts, and application assembly and deployment can be affected by the appropriate team members. This division of labor also helps expedite application maintenance. For example, the user interface is the most dynamic part of many applications, particularly on the web. With the JEE platform, graphic designers can modify the look and feel of JSP-based user interface components without the need for programmer intervention.

Many business intelligence tools are capable of producing subqueries, which can be very powerful in qualifying analysis. For example, the business may categorize customers based on spending behavior high-volume, average volume, and low-volume customers. This categorization is based on analysis of previous spending, as recorded in a fact table somewhere. A user might want to use this categorization to filter query results. A business intelligence tool may provide the capability to define this computation so that it can easily be added to a report as a filter. When invoked by the user, it generates the necessary subquery to segment customers. However, this capability is often difficult to make use of. More importantly, it is likely to hamper response time. If it is to be commonly used, this kind of classification is better incorporated directly into the dimensional design as a behavioral dimension. As you learned in 6, behavioral dimensions precompute categorizations based on existing facts as part of the ETL process, dramatically improving performance at query time. Implemented in this manner, they will also be accessible to all users of the schema, ensuring a consistent definition is used for concepts like high-volume customer. TIP If users will use past behavior to qualify a query, don t rely on a business intelligence tool to generate subqueries. Instead, incorporate a behavioral dimension into the design. Once again, this does not mean you should completely avoid use of such features. Adding this ability within a business intelligence environment may allow for speedier deployment, since it does not impact the design of an existing schema or the alteration of an existing ETL process. In addition, computing this kind of information at query time, rather than when the schema is loaded, may make sense if it is not frequently used.

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Central to the JEE component-based development model is the notion of containers, standardized runtime environments that provide specific component services. Components can expect these services to be available on any JEE platform from any vendor. For example, all JEE web containers provide runtime support for responding to client requests, performing request-time processing (such as invoking JSP or servlet behavior), and returning results to the client. All EJB containers provide automated support for transaction and life cycle management of EJB components, as well as bean lookup and other services. Containers also provide standardized access to enterprise information systems for example, providing RDBMS access through the JDBC API (see Figure 2-9). In addition, containers provide a mechanism for selecting application behaviors at assembly or deployment time. Through the use of deployment descriptors (text files that specify component behavior in terms of well-defined XML tags), components can be configured to a specific container s environment when deployed, rather than in component code. Features that can be configured at deployment time include security checks, transaction control, and other management responsibilities. Although the JEE specification defines the component containers that must be supported, it doesn t specify or restrict the configuration of these containers. Thus,

While some business intelligence capabilities should not be used when it is possible to achieve the same thing in the schema design, there are other situations where the opportunities offered by a semantic layer are highly useful.

FIGURE 2-9

both container types can run on a single platform, web containers can live on one platform and EJB containers on another, or a JEE platform can be made up of multiple containers on multiple platforms.

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