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Listing 29-5. Sample Reactor configuration file (version 2) <reactor> <config> <project value="Scratch" /> <dsn value="Scratch" /> <type value="mssql" /> <mapping value="/data" /> <mode value="development" /> </config> <objects> <object name="User"> <hasOne name="Address"> <relate from="addressId" to="addressId" /> </hasOne> </object> <object name="Address" /> </objects> </reactor> The objects section of the file now effectively tells Reactor that a User has one Address by virtue of the addressId column in both tables. When we make this configuration change, if we re running Reactor in development mode, the next time we request a User record, it will have two new methods: getAddress() and setAddress(). These methods get and set an Address record into the User record. With these new methods, we can do something fun, like the code in Listing 29-6. Listing 29-6. Something fun <cfset Reactor = CreateObject("Component", "reactor.reactorFactory").init(expandPath("reactor.xml"))> <cfset User = reactor.createRecord("User").load(userId=1)> <cfoutput> #User.getFirstName()# #User.getLastName()#<br> #User.getAddress().getStreet()#<br> #User.getAddress().getCity()#, #User.getAddress().getState()# #User.getAddress().getZip()# </cfoutput> The code in Listing 29-6 outputs a formatted address for the user. We used User.getAddress() to get the user s address. However, aside from the configuration change, we didn t need to write a single line of code to do that. Furthermore, Reactor caches the Address object on the first call to getAddress(). That means that the code in Listing 29-6 runs only two simple queries against our database. Reactor supports one-to-one, one-to-many, and many-to-many relationships. As an example of a one-to-many relationship, let s drop the addressId column from the User table and add a userId column to the Address table, making it a foreign key to the User table s userId column. This change lets one

Rather than focusing on the details of each, we will list only some of the main pros and cons of each engine, as a means of helping you understand their strengths and weaknesses, and choose which one you should use. Unfortunately, it s not just a simple case of saying xxx is better than yyy and making a simple recommendation; there are multiple attributes of each of these engines that make them more or less suited for certain applications. You will have to make this decision early on in your development cycle, which may significantly alter the way you not only architect your system, but also set up and deploy it too.

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We can also raise signals against other processes, either once in the same application or elsewhere Not all signals are errors On Unix platforms, for example, we can use an alarm signal to trigger an event over a period of our choosing In the main part of the chapter, we look at writing Perl applications that manage multiple concurrent strands of execution First we examine creating and handling multiple separate processes While this is chiefly of interest to Unix programmers, Perl now has quite credible emulation for multiprocessing applications under Windows too One of the major problems with multiple processes is getting information between them, so we also look at message queues, semaphores, and shared memory, three different solutions to the problem of interprocess communication After processes we look at threads, specifically the new interpreter threads introduced with Perl 58.

While processes exist in relative isolation, with completely separated data and execution environments, threads share everything within the same process This makes them very lightweight by comparison and easy to share data between In most languages, it also makes them much trickier to program since it is easy for threads to overwrite the same data However, interpreter threads enable Perl to keep data used by different threads partitioned away from each other unless we specify that data is to be shared This greatly simplifies the task of programming threads and making most Perl modules thread-compatible even if they have no special knowledge or understanding of them..

Much like hardware interrupts, signals are exceptional events that happen independently of whatever code a program happens to be executing at the time. They are said to be out of band, since they also cannot be deferred for handling at a later point in time. Either the program recipient of a thread handles it, or the operating system will handle it by terminating the program. Typically, the operating environment defines default triggers and behaviors for most signals. A Unix shell, for instance, maps some signals to key sequences, such as KILL to Ctrl-C, and STOP to Ctrl-Z. Other processes, as well as the kernel, have the ability to send signals to any designated process.

record in the User table relate to multiple addresses in the Address table. Before this change takes effect, we need to update our Reactor configuration, as shown in Listing 29-7. Listing 29-7. Sample Reactor configuration file (version 3) <reactor> <config> <project value="Scratch" /> <dsn value="Scratch" /> <type value="mssql" /> <mapping value="/data" /> <mode value="development" /> </config> <objects> <object name="User"> <hasMany name="Address"> <relate from="userId" to="userId" /> </hasMany> </object> <object name="Address" /> </objects> </reactor> This change tells Reactor that a user has many addresses. Now when we ask Reactor for a User record, it will no longer have the getAddress() and setAddress() methods. Instead, it will have a getAddressIterator() method.

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