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Storing application information has always been a challenge for developers of traditional web applications. Often, implementing such storage means storing information in cookies or on the server, which requires using a postback to retrieve the data. In the case of desktop applications, implementing storage for application information is significantly easier, as developers have more access to the user s hard drive. Once again, Silverlight bridges the gap between desktop applications and web applications by offering isolated storage. Using the Silverlight classes for working with isolated storage, you can not only store settings locally, but also create files and directories, as well as read and write files within isolated storage.

Use auto_ptrs If you haven t developed the habit of using auto_ptrs, get into the habit! auto_ptrs avoid many of the memory-leakage problems associated with regular pointers by deleting memory automatically when the auto_ptr goes out of scope. Scott Meyers More Effective C++, Item #9 contains a good discussion of auto_ptr (Meyers 1996). Get smart about smart pointers Smart pointers are a replacement for regular pointers or dumb pointers (Meyers 1996). They operate similarly to regular pointers, but they provide more control over resource management, copy operations, assignment operations, object construction, and object destruction. The issues involved are specific to C++. More Effective C++, Item #28, contains a complete discussion.

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You may consider the persistence context to be a cache of managed entity instances. The persistence context isn t something you see in your application; it isn t an API you can call. In a Hibernate application, we say that one Session has one internal persistence context. In a Java Persistence application, an EntityManager has a persistence context. All entities in persistent state and managed in a unit of work are cached in this context. We walk through the Session and EntityManager APIs later in this chapter. Now you need to know what this (internal) persistence context is buying you. The persistence context is useful for several reasons:

In the Destination text box, type: 172.16.4.0.

For the sake of simplicity, I'll ignore the non-leaf page density factor, and calculate the value as floor((page_size - header_size) / non_leaf_row_size) , which in our case amounts to floor((8192 - 96) / 25) = 323 The number of levels above the leaf (call it L-1 ): This value is calculated with the following formula: ceiling(log rows_per_non_leaf_page (num_leaf_pages)) In our case, L-1 amounts to ceiling(log 323 (25000)) = 2 Obviously, you simply need to add 1 to get L , which in our case is 3 This exercise leads me to a very important point that I will rely on in my performance discussions You can play with the formula and see that with up to about several thousand rows, our index will have 2 levels Three levels would have up to about 4,000,000 rows, and 4 levels would have up to about 4,000,000,000 rows.

A Forever value You can set the animation for constant repetition by setting Forever as the repeat behavior. A discrete number of repetitions By specifying a number followed by x, you can set the number of repetitions. For example, if you want the animation to run three times, you specify the value 3x.

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Build a level of abstraction into your access routines Build access routines at the level of the problem domain rather than at the level of the implementation details. That approach buys you improved readability as well as insurance against changes in the implementation details.

With nonclustered indexes, the formulas are identical, it's just that you can fit more rows in each leaf page, as I will describe later So with nonclustered indexes, the upper bound for each number of levels covers even more rows in the table The point is that in our table all indexes have 3 levels, which is the cost you have to consider in your performance estimation when measuring the cost of a seek operation And in general, with small tables most indexes will typically have up to 2 levels, and with large tables, they will typically have 3 or 4 levels, unless the total size of the index keys is large Keep these numbers in mind for our later discussions..

Description Occurs when the page initialization step is completed. Occurs at the end of the load stage of the page s life cycle. Fires before the page begins its initialization step. This is the first event in the life of an ASP.NET 2.0 page. Fires just before the page begins loading the state information, immediately after initialization. Occurs when the prerendering phase is completed and all child controls have been created. After this event, the personalization data and the view state are saved and the page renders to HTML.

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