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Solid state drives change things only a little. You don t need to wait for bits of metal to lumber into position, but the fact that they are physically separate components slows things down it will take time for the disk controller hardware to send suitable messages to the drive, and for the drive to send a response. The difference between the time spent retrieving data and processing that data will not be as dramatic, but the code will still account for a small proportion. The one situation in which this particular example might be dominated by CPU usage rather than time spent waiting for I/O is if the file in question is already in the operating system s filesystem cache when the OS reads data off disk it tends to keep a copy in memory for a while just in case you need it again. In that case, the disk doesn t need to be involved at all, and it really is all CPU time. You need to be wary of this when testing performance the first time a particular file is read will be much slower than all the rest. If you run a test hundreds of times to get a good average measurement, you ll be ignoring the first and testing the all the rest case, but in a desktop application the one most users will notice is often the first case. For interactive code, the worst case can matter far more than the average.

Finally, let s compile and run the project to see the code in action. As you saw in Figure 10-3, the SearchEngine key still has the same value: http://www.google.com. Let s change the SearchEngine key to use MSN instead of Google. Enter http://www.msn.com into the textbox, and click the Update command button. The page will refresh and show the new value for the SearchEngine key to be http://www.msn.com, as shown in Figure 10-4.

applications, so they may not allow you to edit their shortcut keys. Those that are GNOME desktop applications will say so in the Help About dialog box.

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In plain English, this template is iterating over all classes (<XDtClass: forAllClasses>), and processing the class if it has our custom anttask name="" tag For each class with our tag, it writes out the value of that tag, index . in our case, an equals sign, and then the full class name of the class being processed The <configParam> child element of <template> and the corresponding <XDtConfig:configParameterValue> entry in the template file demonstrate XDoclet s ability to be customized from the Ant build itself by using the timestamp properties created by previous <tstamp/> (in our init target) This is a very simple example of XDoclet s capabilities, yet it does provide our project with a tangible benefit a programmer only needs to be aware of the XDoclet tags that need to be added to a class, method, or field.

public boolean isStopped() { return stopped; }

This metadata is only specified once and is used to dynamically generate other artifacts that require it The Pragmatic Programmer (Hunt 2000) advocates this approach with these tips: DRY Don t Repeat Yourself: For example, in the EJB domain it is common to duplicate metadata by manually creating several classes just for a single entity bean This is unnecessary duplication, which can be avoided with XDoclet Program Close to the Problem Domain Putting information directly with the classes, fields, and methods by using domain-specific terms such as @ant task enables us to be clear about meaning Write Code that Writes Code Why write a properties file that mirrors the same information that is already available in the code Let the code itself define how related artifacts are generated.

#!/usr/bin/perl -w use strict; my $archive_password = 'MYPASSWORD'; my $archive_path = '/Volumes/Data/backups/opendirectory/'; my $max_keep_time = 1; # MONTHS TO KEEP ARCHIVES AROUND my my my my @date = localtime(); $year = $date[5] + 1900; $month = sprintf("%.2d",$date[4] + 1); $day = sprintf("%.2d",$date[3]);

The numbers make the impact of the clustering_factor very obvious. Although the first set of figures shows that the range-based predicate on the first column has reduced the effectiveness of the t1_i1_good index, the reduction is minor compared with the impact caused by the enormous increase in the clustering_factor in the second set of figures. In this example, the extra resources used because we have picked the wrong index will be minimal we still visit exactly the same number of rows in the table so no extra I/O there and we happen to examine two leaf blocks rather than one when we use the wrong index. The guaranteed penalty of using the wrong index would be a little extra CPU spent scanning an unnecessary number of entries in the index. There are 500 entries in either index where clustered between 1 and 5, and we will examine about 400 of them (from (1,50) to (5,50)) if we use index t1_i1_good for our query. There are 100 entries in the index where scattered = 50, and we will examine about five of them (from (50,1) to (50,5)) if we use index t1_i2_bad. In real systems, the choice is more subtle than picking one of two indexes with the same columns in a slightly different order; the scope of the error becomes much larger with changes in complex execution plans not just a little waste of CPU.

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