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I hope this chapter and the provided GameKitHelper class help you get comfortable with Game Center programming. Sure, network programming is no easy task, but I ve laid a lot of the groundwork for you, and even block objects are no longer foreign territory for you. In particular, the checklist of tasks to enable Game Center support for your game should help you avoid a lot of the initial pitfalls faced by developers. Over the course of this chapter, you ve become comfortable using the leaderboard and achievement features of Game Center. Those alone bring your game to a new level. And with the user interface provided by Game Center, you don t even have to write your own user interface to display leaderboards and achievements. I then introduced you to the matchmaking features of Game Center, which allow you to invite friends to join your game, find random players on the Internet, and allow them to send and receive data. With this chapter, I already departed a little from pure cocos2d programming; in fact, you can apply what you just learned about Game Center to any iOS game engine. In the next chapter, I ll depart even further from cocos2d game engine programming. I ll show you where to go from here, where to find help, and where all the useful resources are. What s more, I ll delve into marketing, public relations, and publishers. Understanding these topics can help you sell more units and connect with more developers and fans.

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To match more carefully, you could use the \d (digit) specifier, with the whole expression written as follows: \:\s( <date>\d\d\d\d-\d\d-\d\d)\s That covers the simple regular expression. You can use a more complex regular expression to match each line of the log file. Because of the regularity of the line, we could have used Split(), but that wouldn t have been as illustrative. The clauses of the regular expression are as follows: ( <time>(\d|\:)+)\s ( <ip>(\d|\.)+)\s ( <method>\S+)\s ( <uri>\S+)\s ( <status>\d+) // // // // // match digit or : to extract time match digit or . to get IP address any nonwhitespace for method any nonwhitespace for uri any digit for status

Although this is not a performance optimization suggestion, it is an important consideration for tempdb integrity. Starting with SQL Server 2008, the CHECKSUM database

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function Get-Types ($Pattern=".") { Get-Assemblies | %{ $_.GetExportedTypes() } | where {$_ -match $Pattern} }

Here s what happens when main() calls DrawDots(): On the calling side, the expression passed as an argument to DrawDots() is resolved to a single value. In this case, the expression is simply the variable numDots. The value of the expression is the value of numDots, which is 30. On the receiving side, when DrawDots() gets called, memory is allocated for its parameters as well as for its local variables. This means that memory is allocated for DrawDots() s copy of numDots, as well as for its copy of i. The value passed in to DrawDots() from main() (in this case, 30) is copied into the memory allocated to DrawDots() s copy of numDots. It is important to understand that whatever main() passes in to DrawDots() is copied into DrawDots() s local copy of the parameter. Think of DrawDots() s copy of numDots as just another local variable that will disappear when DrawDots() exits. DrawDots() can do whatever it likes to its copy of the parameter. Since it is just a local copy, any changes will have absolutely no effect on the variable main() passes in as an argument.

Loading XML from a web site (or any URL) is also supported by the Load method. To load the RSS feed from the MSDN web site, we can alter the Load method to take in a URL instead of a file path.

And then a new ITunesFinder is created:

A common performance-tuning recommendation is to create tables on one filegroup and indexes on another (or some other combination), with each filegroup containing files on dedicated disks. For example, Filegroup 1 (tables) contains files on a RAID volume containing 10 disks with Filegroup 2 (indexes) containing files on a separate RAID volume, also containing 10 disks. The theory behind such configurations is that groups of disks will operate in parallel to improve throughput. For example, disks 1 10 will be dedicated to table scans and seeks while index scans and seeks can operate in parallel on another dedicated group of disks. Although it s true that this can improve performance in some cases, it s also true that in most cases it s a much better option to have simpler filegroup structures containing more disks. In the previous example, the alternative to two filegroups each containing 10 disks is to have one filegroup containing 20. In simpler configurations such as this, each database object has more disk spindles to be striped across. Generally speaking, unless the data access patterns are very well known, simpler filegroup structures are almost always a better alternative, unless alternate configurations can be proven in load-testing environments. Another common use for filegroups is for backup and restore flexibility.

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