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This is a much nicer result in this instance. It s useful to note that the letters fill color and stroke color don t have to be the same, which can sometimes come in handy. For completeness, it s worth noting that you can also specify the stroke width for text annotations. For example, this sets the stroke width to 3 pixels: convert -pointsize 24 -stroke red -strokewidth 3 -fill red -annotate 0x0+10+30 stillhq.com input.jpg output.jpg This gives you the rather indistinct version of the text shown in Figure 7-23.

hese days, compilers are pretty smart. They can perform all sorts of code transformations from simple inlining to sophisticated register analysis that make compiled code run faster. In most situations, faster is better than smaller, because disk space and memory are quite cheap for desktop users. However, for embedded systems small is often at least as important as fast because of a commonplace environment consisting of extreme memory constraints and no disk space, making code optimization a very important task. By this point in the book, you have a pretty good grasp of how to compile your code and how to make gcc, the GCC C compiler, do as you please. The next step, accordingly, is to make your code faster or smaller, which is the topic of this chapter. Based on what you learn, you might even be able to make your next program faster and smaller. After a quick, high-level overview of compiler optimization theory, we ll discuss GCC s command-line options for code optimization, starting with general, architecture-independent optimizations and concluding with architecture-specific optimizations. While the examples in this chapter are given in the C programming language, the optimization options discussed in this chapter are independent of the programming language in which your code is written. Being able to share optimization flags across compilers for different languages is a significant advantage of using a suite of compilers, such as those provided by GCC (GNU Compiler Collection).

SELECT DeletedName, InsertedName FROM @ProductChanges The DELETE and INSERT examples were variations on the first example, where OUTPUT pushes the deleted rows (for DELETE) or the inserted rows (for INSERT) into a table variable.

I demonstrated using TOP in 1. In SQL Server 2005, TOP can also be used in DELETE, INSERT, or UPDATE statements. This recipe further demonstrates using TOP to chunk data modifications; meaning instead of executing a very large operation, you can break the modification into smaller pieces, potentially increasing performance and improving database concurrency for larger, highlyaccessed tables. This technique is often used for large data loads to reporting or data warehouse applications. Large, single set updates can cause the database transaction log to grow considerably. When processing in chunks, each chunk is committed after completion, allowing SQL Server to potentially reuse that transaction log space. In addition to transaction log space, on a very large data update, if the query must be cancelled, you may have to wait a long time while the transaction rolls back. With smaller chunks, you can continue with your update more quickly. Also, chunking allows more concurrency against the modified table, allowing user queries to jump in, instead of waiting several minutes for a large modification to complete.