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In this book, I ll show how to use object-oriented concepts to help separate the business logic from the UI. It is important to recognize that a typical application will use business logic in a couple different ways. Most applications have some user interaction, such as forms in which the user views or enters data into the system. Most applications also have some very non-interactive processes, such as posting invoices, relieving inventory, or calculating insurance rates. Ideally, the Business Logic layer will be used in a very rich and interactive way when the user is directly entering data into the application. For instance, when a user is entering a sales order, he or she expects that the validation of data, the calculation of tax, and the subtotaling of the order will happen literally as they type. This implies that the business layer can be physically deployed on the client workstation or on the web server to provide the high levels of interactivity users desire. To support non-interactive processes, on the other hand, the Business Logic layer often needs to be deployed onto an application server, or as close to the database server as possible. For instance, the calculation of an insurance rate can involve extensive database lookups along with quite a bit of complex business processing. This is the kind of thing that should occur behind the scenes on a server, not on a user s desktop. Fortunately, it is possible to deploy a logical layer on multiple physical tiers. Doing this does require some up-front planning and technical design, as you ll see in 2. The end result, however, is a single business layer that is potentially deployed on both the client workstation (or web server) and on the application server. This allows the application to provide high levels of interactivity when the user is working directly with the application, and efficient back-end processing for non-interactive processes.
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Figure 6-23. Configuring WSE support from within Visual Studio .NET 2005 Selecting this option brings up a dialog with many tabs. Support for WSE is enabled when you select the check boxes (see Figure 6-24).
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CHAPTER 22: Social Networking
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Remember, even though these activities are sequential for any particular row of data, from a systemwide perspective they are all happening at once, during the same second in time. Minute after minute. Hour after hour. Day after day. Month after month. A relentless tide of data, washing back and forth like the waves on a beach, except picture in your mind tsunamis, not just waves suitable for surfing and wading. So, if you add up all these estimates of the throughput demands on I/O resulting from the activities listed, the original stated workload of 660Mbps of data balloons to a more realistic workload of almost 10 gigabytes per second (GBps)! Minute after minute. Hour after hour. Day after day. Month after month. This is a 15:1 ratio for every byte of data loaded, we can prove that 15 bytes or more will be read or written, at a minimum, during the lifetime of the data. So, after we consider the full range of activities involving I/O performed with relational database systems, the true problem is actually that of supporting I/O throughput of 10GBps using storage devices that can sustain maximum throughput of 150 200MBps. Infinity isn t just numbers that exceed the imagination. Anybody can imagine 50TB a day. Infinity is anything that is beyond your grasp. This theoretical example is still apparently years beyond our grasp with standard storage options. But what can we do to improve this situation Even with new storage options such as Exadata, which is already promising to meet the storage throughput requirements illustrated here, does it make sense to simply rely on sheer processing and storage power to save the day Or, can we push the requirements back down, reduce the requirements, to meet the state of the art as it improves to meet us Pushing the horizon of infinity further has to be accomplished step by step. If the entire task is considered in its entirety only, it might well be impossible. But if you take the big problem, break it down into chunks, and attack each chunk, you can achieve success in the face of the most extreme requirements. You can reach 50TB a day. In fact, it is already here. In mid-2009, I was contracted to begin implementation of a data warehouse that was expected to reach a size of 9PB after 12 months. A little basic math shows that as loading approximately 25TB per day. The scope of the project was later scaled way back, and the data volumes hacked to a fraction of that total, but the mission and the data to support it is still out there, waiting to be loaded and exploited. The future is now. And obscenely large Oracle databases are up and running right this minute, and more are being built. Here is how they become feasible.
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Windows Live Services is a collection of pretty much any other web-based service Microsoft has ever provided and is now held under the umbrella of Windows Live Services and accessed using the Live SDK. At the time of writing the SDK documentation and Azure site listed the following services (some of which are not yet complete): Advertising Alerts Live Messenger FeedSync
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