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There is a big assumption being made with the code above: no errors occur . But, of course, errors are always possible, and so we need a way to handle those errors . This is what the exception handling constructs and mechanisms are all about and why we need them as opposed to having methods that return true/false to indicate success/failure the way that Win32 and COM functions do . In addition to code composability, we are productive due to all kinds of great features provided by our compilers . For example, the compiler implicitly:

to the view (we discuss this later), but a more convenient approach is to leave the session open until the view is completely rendered.

10

The ConvertIList method specifies two type parameters in which the T parameter is constrained by the TBase type parameter . This means that whatever type argument is specified for T, the type argument must be compatible with whatever type argument is specified for TBase . Here is a method showing some legal and illegal calls to ConvertIList:

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second is the javaType attribute, which specifies which Java types should be handled by this TypeHandlerCallback. Finally, the third attribute, which is optional, allows you to specify the JDBC (i.e., database) type that this TypeHandlerCallback should be applied to. So in our case, we re working with a Java type of boolean and a JDBC type of VARCHAR. If we didn t specify the data type, this type handler would be used by default for all boolean types. However, it would not override any type handlers with a more specific definition. Thus the type handler registration that most specifically matches both the Java type and the JDBC type is the one that will be used. Custom type handlers are by far the most common form of extension in iBATIS. This is mostly due to the wide range of nonstandard features and data types supported by relational database systems. In the remaining sections, we discuss other forms of extension that are rarer but still useful to know about.

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One such situation is when you need to insert or modify large volumes of data and, for practical reasons, you split it into batches, modifying one subset of the data at a time. For example, purging historic data might involve deleting millions of rows of data. Unless the target table is partitioned and you can simply drop a partition, the purging process requires a DELETE statement. Deleting such a large set of rows in a single transaction has several drawbacks. A DELETE statement is fully logged, and it will require enough space in the transaction log to accommodate the whole transaction. During the delete operation (which can take a long time), no part of the log from the oldest open transaction up to the current point can be overwritten. Furthermore, if the transaction breaks in the middle for some reason, all the activity that took place to that point will be rolled back, and this will take a while. Finally, when many rows are deleted at once, SQL Server might escalate the individual locks held on the deleted rows to an exclusive table lock, preventing both read and write access to the target table until the DELETE is completed. It makes sense to break the single large DELETE transaction into several smaller ones small enough to avoid lock escalation (typically, a few thousand rows per transaction) and to allow recycling of the transaction log. You can easily verify that the number you chose doesn t cause lock escalation by testing a DELETE with the TOP option while monitoring Lock

In this chapter and throughout this book you ll see how this latest version of the Microsoft Office system is designed to help you meet your goals in a reliable, trackable, and efficient way. What s more, you ll see how the Microsoft Office system helps you get the clutter off your desktop (and out of your mind) and focus your energies on what s most important: making sound decisions, producing high-quality materials, and working effectively with others to meet and surpass the expectations of a fast-moving marketplace.

Figure 5.7 Hibernate Search queues all changes applied to the database during a flush. During the commit operation, the queue is processed and the index is updated.

Because your new PowerPoint le is such a versatile platform, you can try endless improvisation with it as long as you follow the basic BBP approach and stick to the ground rules. Following these rules keeps the presentation rmly rooted while leaving your creative options open to try new things.

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