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If you have been keeping track of the ways in which a bridged dimension can factor into a query, you have noticed several exist. A quick recap: A nonbridged configuration, such as the shaded region of Figure 10-5 A looking-down configuration, such as Figure 10-7 A looking-up configuration, such as Figure 10-8 A looking-down configuration that also includes the subordinate member, such as Figure 10-11 A looking-up configuration that also includes the superior member, such as Figure 10-12 A subquery that produces a distinct list of member keys, used in a main query to qualify a fact table, as described in Avoiding Double-Counting, earlier in this chapter. This collection of possibilities means anyone writing queries or reports must really understand what they are doing. It can also pose a challenge when configuring a business intelligence tool to generate SQL. These tools typically prefer having only one method to link a given set of tables together. 16 will discuss this issue and provide some workarounds. You have also seen that in all configurations other than the first, it is of the utmost importance to qualify for or group by a single member to avoid double-counting. As already discussed, one way to avoid any issues is to make only the first configuration available to most users and developers. Only trained personnel will be able to use the bridge table.

A DAO provides resource functionality for a particular resource, implemented for a particular persistence mechanism. For example, a class can be created to encapsulate the database resource access for both single as well as multiple rows. The benefits are independence achieved at a small cost (the development required to build the DAO) that ultimately may save development time. For CMP entity beans, the EJB container automatically services all persistent storage access; therefore, applications using CMP entity beans do not need a DAO layer, since the application server transparently provides this functionality. However, DAOs may still be useful when an application has a combination of CMP for entity beans and BMP for session beans and/or servlets. DAOs add a layer of objects between the data client and the data source that requires extra effort to be designed and implemented. However, the benefit realized by choosing this approach makes up for the added effort. When a factory strategy is used, the hierarchy of concrete factories and concrete products produced by the factories requires additional design and implementation.

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Here, we review the concept of pooling resources. We explain how the EJB container uses this concept for EJBs.

This book describes a set of powerful and effective techniques for the design of analytic databases. These techniques unleash business analytics in a very simple way: they model the measurement of business processes. The dimensional model of a business process is made up of two components: measurements and their context. Known as facts and dimensions, these components are organized into a database design that facilitates a wide variety of analytic usage. Implemented in a relational database, the dimensional model is called a star schema. Implemented in a multidimensional database, it is known as a cube. If any part of your data warehouse includes a star schema or a cube, it leverages dimensional design. This chapter introduces the basic concepts of dimensional design, which arose in response to the unique requirements of analytic systems. The concept of measurement is defined in terms of facts and dimensions, and translated into a database design, or star schema. This chapter shows how basic interaction with a star schema can support a wide variety of measurement scenarios, and defines two simple guiding principles for the development of dimensional solutions.

Given that the EJB container cannot handle an unlimited number of EJBs, the classic concept of pooling is used to share the resources among multiple users. When the EJB is deployed, the deployment descriptor specifies the number of instances to pool and reuse. The cost of creating and destroying an EJBObject can be high. The application server manages a pool of EJBs that can be used throughout the application. This pool allows the application server to handle more requests, since the server does not have to spend time creating and destroying EJBObjects. Note that stateful session beans cannot be a part of this bean pool.

Information systems fall into two major categories: those that support the execution of business processes and those that support the analysis of business processes. The principles of dimensional design have evolved as a direct response to the unique requirements of analytic systems. The core of every dimensional model is a set of business metrics that captures how a process is evaluated, and a description of the context of every measurement.

You can set the state and severity of the error, record the error in the SQL Server Error Log, and even record the error in the Windows NT Error Log:

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