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The constant 0.01 is the desired probability (in this case, 1%) of choosing a row. The expression customerid%customerid was included to make the WHERE clause correlated and force its evaluation on each row of StoreContact. Without it, the value of the WHERE condition would be calculated just once, and either the entire table would be returned or no rows would be returned. Note that this technique will require a full table scan and can take a while with large tables. You can test it against our Orders table and see for yourself.
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For more information about command syntax for Icacls, at a command prompt, type icacls with no parameters.
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The Data Source Object Model
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In the .NET Framework 1.x, the DataSet and DataTable objects suffer from a serialization problem they always serialize themselves as XML. This means that when you store an instance of these classes in an out-of-process session or move it through .NET Remoting, a large chunk of data is moved. To get around this limitation, the .NET Framework 2.0 endows the DataTable and the DataSet objects with a new property RemotingFormat. The property accepts values from the SerializationFormat enumerated type Binary or Xml (the default). The property influences how the content of the object is serialized.
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The CLR allows fields to be marked as Static, InitOnly, or both Static and InitOnly. Note that constants (discussed in 8) are always considered Static and can t be marked with InitOnly.
Allocating Resources from the Managed Heap
The version in the Model 2 (see Figure 4-14) has an entirely different effect . In this case, the design is geared much more towards the interests of the target audience . In a public presentation (in this case, the audience consisted of sponsors and potential event organizers), there should be a clear distinction between the values that will be perceived as good and those that are merely satisfactory . Here, the designer also tried to create a lasting good impression by adding some decorative effects . It s not very difficult to reproduce this type of chart in Excel 2007 . Planning, preparation, and dedication to the task are more important than techniques in this case . We ll meet this chart again in later chapters . Here, I ve focused on describing how to add an image like this to the plot area . If you want to try this out for yourself, the relevant description is provided in the following paragraphs, and the Model 1 worksheet provides a starting point for the exercise . It may be useful to save the file to your hard disk under a different name before you start working on it . In this case, an image of the stadium to which the chart refers will provide the fill for the plot area . Graphics software was used to generate various templates of varying sizes, layouts, and colors to satisfy different requirements . The version finally used here you ll find on the CD-ROM .
This is a good example of one of the most prevalent and hazardous bits of programming folklore: that comments should be used to document especially tricky or sensitive sections of code. The reasoning is that people should know they need to be careful when they re working in certain areas. This is a scary idea. Commenting tricky code is exactly the wrong approach to take. Comments can t rescue difficult code. As Kernighan and Plauger emphasize, Don t document bad code rewrite it (1978). One study found that areas of source code with large numbers of comments also tended to have the most defects and to consume the most development effort (Lind and Vairavan 1989). The authors hypothesized that programmers tended to comment difficult code heavily. When someone says, This is really tricky code, I hear them say, This is really bad code. If something seems tricky to you, it will be incomprehensible to someone else. Even something that doesn t seem all that tricky to you can seem impossibly convoluted to another person who hasn t seen the trick before. If you have to ask yourself, Is this tricky , it is. You can always find a rewrite that s not tricky, so rewrite the code. Make your code so good that you don t need comments, and then comment it to make it even better. This advice applies mainly to code you re writing for the first time. If you re maintaining a program and don t have the latitude to rewrite bad code, commenting the tricky parts is a good practice.
Using File Server Resource Manager
Although it s easy to get started, you need to consider number of management issues when working with change data capture .
Introducing the 2007 Microsoft Office System
You can digitally sign data by adding a private key to it (such as a password), generating a hash, and including the hash with the data you store on the client. When clients submit the data and the hash, add the private key to the data and re-generate the hash to verify that the data has not been modified. For more information about generating hashes, refer to the documentation for the System.Security.Cryptography namespace on MSDN. ASP.NET view state automatically hashes data to help reduce the chance of data modification.
when addressed during the design phase. A scenario-based approach is effective as an alternative and is well suited for performance testing legacy code. Regardless of the situation, here are some helpful tips for performance testing. Establish a baseline An important aspect of defining and measuring early is establishing baselines. If performance testing starts late in the project, it is difficult to determine when any discovered performance bottlenecks were introduced. Run tests often Once you have a baseline, measure as often as possible. Measuring often is a tremendous aid in helping to diagnose exactly which code changes are contributing to performance degradation. Measure responsiveness Users don't care how long an underlying function takes to execute. What they care about is how responsive the application is. Performance tests should focus on measuring responsiveness to the user, regardless of how long the operation takes. Measure performance It is tempting to mix functionality (or other types of testing) in a performance test suite. Concentrate performance tests on measuring performance. Take advantage of performance tests The alternate side of the previous bullet is that performance tests are often useful in other testing situations. Use automated performance tests in other automated test suites whenever possible (for instance, in the stress test suite). Anticipate bottlenecks Target performance tests on areas where latency can occur, such as file and print I/O, memory functions, network operations, or any other areas where unresponsive behavior can occur. Use tools In conjunction with the preceding bullet, use tools that simulate network or I/O latency to determine the performance characteristics of the application under test in adverse situations. Remember that resource utilization is important Response time and latency are both key indicators of performance, but don't forget to monitor the load on CPU, disk or network I/O, and memory during your performance tests. For example, if you are testing a media player, in addition to responsiveness, you might want to monitor network I/O and CPU usage to ensure that the resource usage of the application does not cause adverse behaviors in other applications. Use "clean machines" and don't Partition your performance testing between clean machines (new installations of the operating systems and application under test) and computer configurations based on customer profiles. Clean machines are useful to generate consistent numbers, but those numbers can be misleading if performance is adversely affected by other applications, add-ins, or other extensions. Running performance tests on the clean machine will generate your best numbers, but running tests on a machine full of software will generate numbers closer to what your customers will see. Avoid change Resist the urge to tweak (or overhaul) your performance tests. The less the tests change, the more accurate the data will be over the long term. Performance counters are often useful in identifying performance bottlenecks in the system. Performance counters are granular measurements that reveal some performance aspect of the application or system, and they enable monitoring and analysis of these aspects. All versions of the Windows operating system include a tool (Perfmon.exe) for monitoring these performance counters, and Windows includes performance counters for many areas where bottlenecks exist, such as CPU, disk I/O, network I/O, memory statistics, and resource usage. A sample view of a Perfmon.exe counter
30.1 Design Tools
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