birt upc-a

birt upc-a

birt upc-a

birt upc-a

birt upc-a,
birt upc-a,
birt upc-a,
birt upc-a,
birt upc-a,

birt upc-a,
birt upc-a,
birt upc-a,
birt upc-a,
birt upc-a,
birt upc-a,
birt upc-a,

birt upc-a,
birt upc-a,
birt upc-a,
birt upc-a,
birt upc-a,
birt upc-a,
birt upc-a,
birt upc-a,
birt upc-a,
birt upc-a,
birt upc-a,
birt upc-a,
birt upc-a,
birt upc-a,
birt upc-a,
birt upc-a,
birt upc-a,
birt upc-a,

birt upc-a,
birt upc-a,
birt upc-a,
birt upc-a,
birt upc-a,
birt upc-a,
birt upc-a,
birt upc-a,
birt upc-a,
birt upc-a,
birt upc-a,
birt upc-a,
birt upc-a,
birt upc-a,
birt upc-a,
birt upc-a,
birt upc-a,
birt upc-a,
birt upc-a,
birt upc-a,
birt upc-a,
birt upc-a,
birt upc-a,
birt upc-a,
birt upc-a,
birt upc-a,
birt upc-a,
birt upc-a,
birt upc-a,
birt upc-a,
birt upc-a,
birt upc-a,
birt upc-a,
birt upc-a,
birt upc-a,
birt upc-a,
birt upc-a,
birt upc-a,
birt upc-a,
birt upc-a,
birt upc-a,
birt upc-a,
birt upc-a,
birt upc-a,
birt upc-a,
birt upc-a,
birt upc-a,
birt upc-a,
birt upc-a,

In the absence of optimization, GCC s goal, besides compiling code that works, is to keep compilation time to a minimum and generate code that runs predictably in a debugging environment. For example, in optimized code, a variable whose value is repeatedly computed inside a loop might be moved above the loop if the optimizer determines that its value does not change during the loop sequence. Although this is acceptable (if, of course, it does not alter the program s results), this optimization makes it impossible to debug the loop as expressed in your source code because you cannot set a breakpoint on that variable to halt execution of the loop. Without optimization, on the other hand, you can set a breakpoint on the statement computing the value of this variable, examine variables, and then continue execution. This is what is meant by code that runs predictably in a debugging environment. As is discussed in this chapter, optimization can change the flow, but not the results, of your code. For this reason, optimization is a phase of development generally best left until after you have completely written and debugged your application. Your mileage may vary, but it can be tricky to debug code that has been optimized by any of the GCC compilers.

In this recipe, I show you how to modify data in blocks of rows in multiple executions, instead of an entire result set in one large transaction. First, I create an example deletion table for this example: SELECT * INTO Production.Example_BillOfMaterials FROM Production.BillOfMaterials Next, all rows will be deleted from the table in 500 row chunks: WHILE (SELECT COUNT(*)FROM Production.Example_BillOfMaterials)> BEGIN DELETE TOP(500) FROM Production.Example_BillOfMaterials END This returns: (500 row(s) affected) (500 row(s) affected) (500 row(s) affected) (500 row(s) affected) (500 row(s) affected) (179 row(s) affected) 0

Optimization refers to analyzing a straightforward compilation s resulting code to determine how to transform it to run faster, consume fewer resources, or both Compilers that do this are known as optimizing compilers, and the resulting code is known as optimized code To produce optimized code, an optimizing compiler performs one or more transformations on the source code provided as input The purpose is to replace less efficient code with more efficient code while at the same time preserving the meaning and ultimate results of the code Throughout this section, I will use the term transformation to refer to the code modifications performed by an optimizing compiler because I want to distinguish between optimization techniques, such as loop unrolling and common subexpression elimination, and the way in which these techniques are implemented using specific code transformations Optimizing compilers use several methods to determine where generated code can be improved.

In this example, I used a WHILE condition to keep executing the DELETE while the count of rows in the table was greater than zero (see 9 for more information on WHILE): WHILE (SELECT COUNT(*)FROM Production.Example_BillOfMaterials)> BEGIN 0

One method is control flow analysis, which examines loops and other control constructs, such as if-then and case statements, to identify the execution paths a program might take and, based on this analysis, determine how the execution path can be streamlined Another typical optimization technique examines how data is used in a program, a procedure known as data flow analysis Data flow analysis examines how and when variables are used (or not) in a program and then applies various set equations to these usage patterns to derive optimization opportunities Optimization properly includes improving the algorithms that make up a program as well as the mechanical transformations described in this chapter The classic illustration of this is the performance of bubble sorts compared to, say, quick sorts or shell sorts.

You can also specify the font to use with the annotation. To do this, use the font commandline argument, which takes the name of a font as its argument. For this example, I want to use a TrueType font called Arbuckle that I downloaded from the Internet for free. The font is stored in the Arbuckle.ttf file, which means I use this command line: convert -pointsize 24 -font Arbuckle.ttf -stroke red -fill red -annotate 0x0+10+30 stillhq.com input.jpg output.jpg This gives you the new version of the annotation shown in Figure 7-24.

Next was the DELETE, followed by the TOP clause, and the row limitation in parentheses: DELETE TOP(500) FROM Production.BillOfMaterials This recipe didn't use a WHERE clause, so no filtering was applied and all rows were deleted from the table but only in 500 row chunks. Once the WHILE condition no longer evaluated to TRUE, the loop ended. After executing, the row counts affected in each batch were displayed. The first five batches deleted 500 rows, and the last batch deletes the remaining 179 rows. This chunking method can be used with INSERTs and UPDATEs too. For INSERT and UPDATE, the TOP clause follows right after the INSERT and UPDATE keyword, for example: INSERT TOP(100) ... UPDATE TOP(25) ... The expanded functionality of TOP adds a new technique for managing large data modifications against a table.