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diff --git a/pod/perlthrtut.pod b/pod/perlthrtut.pod new file mode 100644 index 0000000000..db2a319093 --- /dev/null +++ b/pod/perlthrtut.pod @@ -0,0 +1,1063 @@ +=head1 NAME + +perlthrtut - tutorial on threads in Perl + +=head1 DESCRIPTION + +One of the most prominent new features of Perl 5.005 is the inclusion +of threads. Threads make a number of things a lot easier, and are a +very useful addition to your bag of programming tricks. + +=head1 What Is A Thread Anyway? + +A thread is a flow of control through a program with a single +execution point. + +Sounds an awful lot like a process, doesn't it? Well, it should. +Threads are one of the pieces of a process. Every process has at least +one thread and, up until now, every process running Perl had only one +thread. With 5.005, though, you can create extra threads. We're going +to show you how, when, and why. + +=head1 Threaded Program Models + +There are three basic ways that you can structure a threaded +program. Which model you choose depends on what you need your program +to do. For many non-trivial threaded programs you'll need to choose +different models for different pieces of your program. + +=head2 Boss/Worker + +The boss/worker model usually has one `boss' thread and one or more +`worker' threads. The boss thread gathers or generates tasks that need +to be done, then parcels those tasks out to the appropriate worker +thread. + +This model is common in GUI and server programs, where a main thread +waits for some event and then passes that event to the appropriate +worker threads for processing. Once the event has been passed on, the +boss thread goes back to waiting for another event. + +The boss thread does relatively little work. While tasks aren't +necessarily performed faster than with any other method, it tends to +have the best user-response times. + +=head2 Work Crew + +In the work crew model, several threads are created that do +essentially the same thing to different pieces of data. It closely +mirrors classical parallel processing and vector processors, where a +large array of processors do the exact same thing to many pieces of +data. + +This model is particularly useful if the system running the program +will distribute multiple threads across different processors. It can +also be useful in ray tracing or rendering engines, where the +individual threads can pass on interim results to give the user visual +feedback. + +=head2 Pipeline + +The pipeline model divides up a task into a series of steps, and +passes the results of one step on to the thread processing the +next. Each thread does one thing to each piece of data and passes the +results to the next thread in line. + +This model makes the most sense if you have multiple processors so two +or more threads will be executing in parallel, though it can often +make sense in other contexts as well. It tends to keep the individual +tasks small and simple, as well as allowing some parts of the pipeline +to block (on I/O or system calls, for example) while other parts keep +going. If you're running different parts of the pipeline on different +processors you may also take advantage of the caches on each +processor. + +This model is also handy for a form of recursive programming where, +rather than having a subroutine call itself, it instead creates +another thread. Prime and Fibonacci generators both map well to this +form of the pipeline model. (A version of a prime number generator is +presented later on.) + +=head1 Native threads + +There are several different ways to implement threads on a system. How +threads are implemented depends both on the vendor and, in some cases, +the version of the operating system. Often the first implementation +will be relatively simple, but later versions of the OS will be more +sophisticated. + +While the information in this section is useful, it's not necessary, +so you can skip it if you don't feel up to it. + +There are three basic categories of threads-user-mode threads, kernel +threads, and multiprocessor kernel threads. + +User-mode threads are threads that live entirely within a program and +its libraries. In this model, the OS knows nothing about threads. As +far as it's concerned, your process is just a process. + +This is the easiest way to implement threads, and the way most OSes +start. The big disadvantage is that, since the OS knows nothing about +threads, if one thread blocks they all do. Typical blocking activities +include most system calls, most I/O, and things like sleep(). + +Kernel threads are the next step in thread evolution. The OS knows +about kernel threads, and makes allowances for them. The main +difference between a kernel thread and a user-mode thread is +blocking. With kernel threads, things that block a single thread don't +block other threads. This is not the case with user-mode threads, +where the kernel blocks at the process level and not the thread level. + +This is a big step forward, and can give a threaded program quite a +performance boost over non-threaded programs. Threads that block +performing I/O, for example, won't block threads that are doing other +things. Each process still has only one thread running at once, +though, regardless of how many CPUs a system might have. + +Since kernel threading can interrupt a thread at any time, they will +uncover some of the implicit locking assumptions you may make in your +program. For example, something as simple as C<$a = $a + 2> can behave +unpredictably with kernel threads if C<$a> is visible to other +threads, as another thread may have changed C<$a> between the time it +was fetched on the right hand side and the time the new value is +stored. + +Multiprocessor Kernel Threads are the final step in thread +support. With multiprocessor kernel threads on a machine with multiple +CPUs, the OS may schedule two or more threads to run simultaneously on +different CPUs. + +This can give a serious performance boost to your threaded program, +since more than one thread will be executing at the same time. As a +tradeoff, though, any of those nagging synchronization issues that +might not have shown with basic kernel threads will appear with a +vengeance. + +In addition to the different levels of OS involvement in threads, +different OSes (and different thread implementations for a particular +OS) allocate CPU cycles to threads in different ways. + +Cooperative multitasking systems have running threads give up control +if one of two things happen. If a thread calls a yield function, it +gives up control. It also gives up control if the thread does +something that would cause it to block, such as perform I/O. In a +cooperative multitasking implementation, one thread can starve all the +others for CPU time if it so chooses. + +Preemptive multitasking systems interrupt threads at regular intervals +while the system decides which thread should run next. In a preemptive +multitasking system, one thread usually won't monopolize the CPU. + +On some systems, there can be cooperative and preemptive threads +running simultaneously. (Threads running with realtime priorities +often behave cooperatively, for example, while threads running at +normal priorities behave preemptively.) + +=head1 What kind of threads are perl threads? + +If you have experience with other thread implementations, you might +find that things aren't quite what you expect. It's very important to +remember when dealing with Perl threads that Perl Threads Are Not X +Threads, for all values of X. They aren't POSIX threads, or +DecThreads, or Java's Green threads, or Win32 threads. There are +similarities, and the broad concepts are the same, but if you start +looking for implementation details you're going to be either +disappointed or confused. Possibly both. + +This is not to say that Perl threads are completely different from +everything that's ever come before--they're not. Perl's threading +model owes a lot to other thread models, especially POSIX. Just as +Perl is not C, though, Perl threads are not POSIX threads. So if you +find yourself looking for mutexes, or thread priorities, it's time to +step back a bit and think about what you want to do and how Perl can +do it. + +=head1 Threadsafe Modules + +The addition of threads has changed Perl's internals +substantially. There are implications for people who write +modules--especially modules with XS code or external libraries. While +most modules won't encounter any problems, modules that aren't +explicitly tagged as thread-safe should be tested before being used in +production code. + +Not all modules that you might use are thread-safe, and you should +always assume a module is unsafe unless the documentation says +otherwise. This includes modules that are distributed as part of the +core. Threads are a beta feature, and even some of the standard +modules aren't thread-safe. + +If you're using a module that's not thread-safe for some reason, you +can protect yourself by using semaphores and lots of programming +discipline to control access to the module. Semaphores are covered +later in the article. Perl Threads Are Different + +=head1 Thread Basics + +The core Thread module provides the basic functions you need to write +threaded programs. In the following sections we'll cover the basics, +showing you what you need to do to create a threaded program. After +that, we'll go over some of the features of the Thread module that +make threaded programming easier. + +=head2 Basic Thread Support + +Thread support is a Perl compile-time option-it's something that's +turned on or off when Perl is built at your site, rather than when +your programs are compiled. If your Perl wasn't compiled with thread +support enabled, then any attempt to use threads will fail. + +Remember that the threading support in 5.005 is in beta release, and +should be treated as such. You should expect that it may not function +entirely properly, and the thread interface may well change some +before it is a fully supported, production release. The beta version +shouldn't be used for mission-critical projects. Having said that, +threaded Perl is pretty nifty, and worth a look. + +Your programs can use the Config module to check whether threads are +enabled. If your program can't run without them, you can say something +like: + + $Config{usethreads} or die "Recompile Perl with threads to run this program."; + +A possibly-threaded program using a possibly-threaded module might +have code like this: + + use Config; + use MyMod; + + if ($Config{usethreads}) { + # We have threads + require MyMod_threaded; + import MyMod_threaded; + } else { + require MyMod_unthreaded; + import MyMod_unthreaded; + } + +Since code that runs both with and without threads is usually pretty +messy, it's best to isolate the thread-specific code in its own +module. In our example above, that's what MyMod_threaded is, and it's +only imported if we're running on a threaded Perl. + +=head2 Creating Threads + +The Thread package provides the tools you need to create new +threads. Like any other module, you need to tell Perl you want to use +it; use Thread imports all the pieces you need to create basic +threads. + +The simplest, straightforward way to create a thread is with new(): + + use Thread; + + $thr = new Thread \&sub1; + + sub sub1 { + print "In the thread\n"; + } + +The new() method takes a reference to a subroutine and creates a new +thread, which starts executing in the referenced subroutine. Control +then passes both to the subroutine and the caller. + +If you need to, your program can pass parameters to the subroutine as +part of the thread startup. Just include the list of parameters as +part of the C<Thread::new> call, like this: + + use Thread; + $Param3 = "foo"; + $thr = new Thread \&sub1, "Param 1", "Param 2", $Param3; + $thr = new Thread \&sub1, @ParamList; + $thr = new Thread \&sub1, qw(Param1 Param2 $Param3); + + sub sub1 { + my @InboundParameters = @_; + print "In the thread\n"; + print "got parameters >", join("<>", @InboundParameters), "<\n"; + } + + +The subroutine runs like a normal Perl subroutine, and the call to new +Thread returns whatever the subroutine returns. + +The last example illustrates another feature of threads. You can spawn +off several threads using the same subroutine. Each thread executes +the same subroutine, but in a separate thread with a separate +environment and potentially separate arguments. + +The other way to spawn a new thread is with async(), which is a way to +spin off a chunk of code like eval(), but into its own thread: + + use Thread qw(async); + + $LineCount = 0; + + $thr = async { + while(<>) {$LineCount++} + print "Got $LineCount lines\n"; + }; + + print "Waiting for the linecount to end\n"; + $thr->join; + print "All done\n"; + +You'll notice we did a use Thread qw(async) in that example. async is +not exported by default, so if you want it, you'll either need to +import it before you use it or fully qualify it as +Thread::async. You'll also note that there's a semicolon after the +closing brace. That's because async() treats the following block as an +anonymous subroutine, so the semicolon is necessary. + +Like eval(), the code executes in the same context as it would if it +weren't spun off. Since both the code inside and after the async start +executing, you need to be careful with any shared resources. Locking +and other synchronization techniques are covered later. + +=head2 Giving up control + +There are times when you may find it useful to have a thread +explicitly give up the CPU to another thread. Your threading package +might not support preemptive multitasking for threads, for example, or +you may be doing something compute-intensive and want to make sure +that the user-interface thread gets called frequently. Regardless, +there are times that you might want a thread to give up the processor. + +Perl's threading package provides the yield() function that does +this. yield() is pretty straightforward, and works like this: + + use Thread qw(yield async); + async { + my $foo = 50; + while ($foo--) { print "first async\n" } + yield; + $foo = 50; + while ($foo--) { print "first async\n" } + }; + async { + my $foo = 50; + while ($foo--) { print "second async\n" } + yield; + $foo = 50; + while ($foo--) { print "second async\n" } + }; + +=head2 Waiting For A Thread To Exit + +Since threads are also subroutines, they can return values. To wait +for a thread to exit and extract any scalars it might return, you can +use the join() method. + + use Thread; + $thr = new Thread \&sub1; + + @ReturnData = $thr->join; + print "Thread returned @ReturnData"; + + sub sub1 { return "Fifty-six", "foo", 2; } + +In the example above, the join() method returns as soon as the thread +ends. In addition to waiting for a thread to finish and gathering up +any values that the thread might have returned, join() also performs +any OS cleanup necessary for the thread. That cleanup might be +important, especially for long-running programs that spawn lots of +threads. If you don't want the return values and don't want to wait +for the thread to finish, you should call the detach() method +instead. detach() is covered later in the article. + +=head2 Errors In Threads + +So what happens when an error occurs in a thread? Any errors that +could be caught with eval() are postponed until the thread is +joined. If your program never joins, the errors appear when your +program exits. + +Errors deferred until a join() can be caught with eval(): + + use Thread qw(async); + $thr = async {$b = 3/0}; # Divide by zero error + $foo = eval {$thr->join}; + if ($@) { + print "died with error $@\n"; + } else { + print "Hey, why aren't you dead?\n"; + } + +eval() passes any results from the joined thread back unmodified, so +if you want the return value of the thread, this is your only chance +to get them. + +=head2 Ignoring A Thread + +join() does three things:it waits for a thread to exit, cleans up +after it, and returns any data the thread may have produced. But what +if you're not interested in the thread's return values, and you don't +really care when the thread finishes? All you want is for the thread +to get cleaned up after when it's done. + +In this case, you use the detach() method. Once a thread is detached, +it'll run until it's finished, then Perl will clean up after it +automatically. + + use Thread; + $thr = new Thread \&sub1; # Spawn the thread + + $thr->detach; # Now we officially don't care any more + + sub sub1 { + $a = 0; + while (1) { + $a++; + print "\$a is $a\n"; + sleep 1; + } + } + + +Once a thread is detached, it may not be joined, and any output that +it might have produced (if it was done and waiting for a join) is +lost. + +=head1 Threads And Data + +Now that we've covered the basics of threads, it's time for our next +topic: data. Threading introduces a couple of complications to data +access that non-threaded programs never need to worry about. + +=head2 Shared And Unshared Data + +The single most important thing to remember when using threads is that +all threads potentially have access to all the data anywhere in your +program. While this is true with a nonthreaded Perl program as well, +it's especially important to remember with a threaded program, since +more than one thread can be accessing this data at once. + +Perl's scoping rules don't change because you're using threads. If a +subroutine (or block, in the case of async()) could see a variable if +you weren't running with threads, it can see it if you are. This is +especially important for the subroutines that create, and makes my +variables even more important. Remember--if your variables aren't +lexically scoped (declared with C<my>) you're probably sharing it between +threads. + +=head2 Thread Pitfall: Races + +While threads bring a new set of useful tools, they also bring a +number of pitfalls. One pitfall is the race condition: + + use Thread; + $a = 1; + $thr1 = Thread->new(\&sub1); + $thr2 = Thread->new(\&sub2); + + sleep 10; + print "$a\n"; + + sub sub1 { $foo = $a; $a = $foo + 1; } + sub sub2 { $bar = $a; $a = $bar + 1; } + +What do you think $a will be? The answer, unfortunately, is "it +depends." Both sub1() and sub2() access the global variable $a, once +to read and once to write. Depending on factors ranging from your +thread implementation's scheduling algorithm to the phase of the moon, +$a can be 2 or 3. + +Race conditions are caused by unsynchronized access to shared +data. Without explicit synchronization, there's no way to be sure that +nothing has happened to the shared data between the time you access it +and the time you update it. Even this simple code fragment has the +possibility of error: + + use Thread qw(async); + $a = 2; + async{ $b = $a; $a = $b + 1; }; + async{ $c = $a; $a = $c + 1; }; + +Two threads both access $a. Each thread can potentially be interrupted +at any point, or be executed in any order. At the end, $a could be 3 +or 4, and both $b and $c could be 2 or 3. + +Whenever your program accesses data or resources that can be accessed +by other threads, you must take steps to coordinate access or risk +data corruption and race conditions. + +=head2 Controlling access: lock() + +The lock() function takes a variable (or subroutine, but we'll get to +that later) and puts a lock on it. No other thread may lock the +variable until the locking thread exits the innermost block containing +the lock. Using lock() is straightforward: + + use Thread qw(async); + $a = 4; + $thr1 = async { + $foo = 12; + { + lock ($a); # Block until we get access to $a + $b = $a; + $a = $b * $foo; + } + print "\$foo was $foo\n"; + }; + $thr2 = async { + $bar = 7; + { + lock ($a); # Block until we can get access to $a + $c = $a; + $a = $c * $bar; + } + print "\$bar was $bar\n"; + }; + $thr1->join; + $thr2->join; + print "\$a is $a\n"; + +lock() blocks the thread until the variable being locked is +available. When lock() returns, your thread can be sure that no other +thread can lock that variable until the innermost block containing the +lock exits. + +It's important to note that locks don't prevent access to the variable +in question, only lock attempts. This is in keeping with Perl's +longstanding tradition of courteous programming, and the advisory file +locking that flock() gives you. Locked subroutines behave differently, +however. We'll cover that later in the article. + +You may lock arrays and hashes as well as scalars. Locking an array, +though, will not block subsequent locks on array elements, just lock +attempts on the array itself. + +Finally, locks are recursive, which means it's okay for a thread to +lock a variable more than once. The lock will last until the outermost +lock() on the variable goes out of scope. + +=head2 Thread Pitfall: Deadlocks + +Locks are a handy tool to synchronize access to data. Using them +properly is the key to safe shared data. Unfortunately, locks aren't +without their dangers. Consider the following code: + + use Thread qw(async yield); + $a = 4; + $b = "foo"; + async { + lock($a); + yield; + sleep 20; + lock ($b); + }; + async { + lock($b); + yield; + sleep 20; + lock ($a); + }; + +This program will probably hang until you kill it. The only way it +won't hang is if one of the two async() routines acquires both locks +first. A guaranteed-to-hang version is more complicated, but the +principle is the same. + +The first thread spawned by async() will grab a lock on $a then, a +second or two later, try to grab a lock on $b. Meanwhile, the second +thread grabs a lock on $b, then later tries to grab a lock on $a. The +second lock attempt for both threads will block, each waiting for the +other to release its lock. + +This condition is called a deadlock, and it occurs whenever two or +more threads are trying to get locks on resources that the others +own. Each thread will block, waiting for the other to release a lock +on a resource. That never happens, though, since the thread with the +resource is itself waiting for a lock to be released. + +There are a number of ways to handle this sort of problem. The best +way is to always have all threads acquire locks in the exact same +order. If, for example, you lock variables $a, $b, and $c, always lock +$a before $b, and $b before $c. It's also best to hold on to locks for +as short a period of time to minimize the risks of deadlock. + +=head2 Queues: Passing Data Around + +A queue is a special thread-safe object that lets you put data in one +end and take it out the other without having to worry about +synchronization issues. They're pretty straightforward, and look like +this: + + use Thread qw(async); + use Thread::Queue; + + my $DataQueue = new Thread::Queue; + $thr = async { + while ($DataElement = $DataQueue->dequeue) { + print "Popped $DataElement off the queue\n"; + } + }; + + $DataQueue->enqueue(12); + $DataQueue->enqueue("A", "B", "C"); + $DataQueue->enqueue(\$thr); + sleep 10; + $DataQueue->enqueue(undef); + +You create the queue with new Thread::Queue. Then you can add lists of +scalars onto the end with enqueue(), and pop scalars off the front of +it with dequeue(). A queue has no fixed size, and can grow as needed +to hold everything pushed on to it. + +If a queue is empty, dequeue() blocks until another thread enqueues +something. This makes queues ideal for event loops and other +communications between threads. + +=head1 Threads And Code + +In addition to providing thread-safe access to data via locks and +queues, threaded Perl also provides general-purpose semaphores for +coarser synchronization than locks provide and thread-safe access to +entire subroutines. + +=head2 Semaphores: Synchronizing Data Access + +Semaphores are a kind of generic locking mechanism. Unlike lock, which +gets a lock on a particular scalar, Perl doesn't associate any +particular thing with a semaphore so you can use them to control +access to anything you like. In addition, semaphores can allow more +than one thread to access a resource at once, though by default +semaphores only allow one thread access at a time. + +=over 4 + +=item Basic semaphores + +Semaphores have two methods, down and up. down decrements the resource +count, while up increments it. down calls will block if the +semaphore's current count would decrement below zero. This program +gives a quick demonstration: + + use Thread qw(yield); + use Thread::Semaphore; + my $semaphore = new Thread::Semaphore; + $GlobalVariable = 0; + + $thr1 = new Thread \&sample_sub, 1; + $thr2 = new Thread \&sample_sub, 2; + $thr3 = new Thread \&sample_sub, 3; + + sub sample_sub { + my $SubNumber = shift @_; + my $TryCount = 10; + my $LocalCopy; + sleep 1; + while ($TryCount--) { + $semaphore->down; + $LocalCopy = $GlobalVariable; + print "$TryCount tries left for sub $SubNumber (\$GlobalVariable is $GlobalVariable)\n"; + yield; + sleep 2; + $LocalCopy++; + $GlobalVariable = $LocalCopy; + $semaphore->up; + } + } + +The three invocations of the subroutine all operate in sync. The +semaphore, though, makes sure that only one thread is accessing the +global variable at once. + +=item Advanced Semaphores + +By default, semaphores behave like locks, letting only one thread +down() them at a time. However, there are other uses for semaphores. + +Each semaphore has a counter attached to it. down() decrements the +counter and up() increments the counter. By default, semaphores are +created with the counter set to one, down() decrements by one, and +up() increments by one. If down() attempts to decrement the counter +below zero, it blocks until the counter is large enough. Note that +while a semaphore can be created with a starting count of zero, any +up() or down() always changes the counter by at least +one. $semaphore->down(0) is the same as $semaphore->down(1). + +The question, of course, is why would you do something like this? Why +create a semaphore with a starting count that's not one, or why +decrement/increment it by more than one? The answer is resource +availability. Many resources that you want to manage access for can be +safely used by more than one thread at once. + +For example, let's take a GUI driven program. It has a semaphore that +it uses to synchronize access to the display, so only one thread is +ever drawing at once. Handy, but of course you don't want any thread +to start drawing until things are properly set up. In this case, you +can create a semaphore with a counter set to zero, and up it when +things are ready for drawing. + +Semaphores with counters greater than one are also useful for +establishing quotas. Say, for example, that you have a number of +threads that can do I/O at once. You don't want all the threads +reading or writing at once though, since that can potentially swamp +your I/O channels, or deplete your process' quota of filehandles. You +can use a semaphore initialized to the number of concurrent I/O +requests (or open files) that you want at any one time, and have your +threads quietly block and unblock themselves. + +Larger increments or decrements are handy in those cases where a +thread needs to check out or return a number of resources at once. + +=back + +=head2 Attributes: Restricting Access To Subroutines + +In addition to synchronizing access to data or resources, you might +find it useful to synchronize access to subroutines. You may be +accessing a singular machine resource (perhaps a vector processor), or +find it easier to serialize calls to a particular subroutine than to +have a set of locks and sempahores. + +One of the additions to Perl 5.005 is subroutine attributes. The +Thread package uses these to provide several flavors of +serialization. It's important to remember that these attributes are +used in the compilation phase of your program so you can't change a +subroutine's behavior while your program is actually running. + +=head2 Subroutine Locks + +The basic subroutine lock looks like this: + + sub test_sub { + use attrs qw(locked); + } + +This ensures that only one thread will be executing this subroutine at +any one time. Once a thread calls this subroutine, any other thread +that calls it will block until the thread in the subroutine exits +it. A more elaborate example looks like this: + + use Thread qw(yield); + + new Thread \&thread_sub, 1; + new Thread \&thread_sub, 2; + new Thread \&thread_sub, 3; + new Thread \&thread_sub, 4; + + sub sync_sub { + use attrs qw(locked); + my $CallingThread = shift @_; + print "In sync_sub for thread $CallingThread\n"; + yield; + sleep 3; + print "Leaving sync_sub for thread $CallingThread\n"; + } + + sub thread_sub { + my $ThreadID = shift @_; + print "Thread $ThreadID calling sync_sub\n"; + sync_sub($ThreadID); + print "$ThreadID is done with sync_sub\n"; + } + +The use attrs qw(locked) locks sync_sub(), and if you run this, you +can see that only one thread is in it at any one time. + +=head2 Methods + +Locking an entire subroutine can sometimes be overkill, especially +when dealing with Perl objects. When calling a method for an object, +for example, you want to serialize calls to a method, so that only one +thread will be in the subroutine for a particular object, but threads +calling that subroutine for a different object aren't blocked. The +method attribute indicates whether the subroutine is really a method. + + use Thread; + + sub tester { + my $thrnum = shift @_; + my $bar = new Foo; + foreach (1..10) { + print "$thrnum calling per_object\n"; + $bar->per_object($thrnum); + print "$thrnum out of per_object\n"; + yield; + print "$thrnum calling one_at_a_time\n"; + $bar->one_at_a_time($thrnum); + print "$thrnum out of one_at_a_time\n"; + yield; + } + } + + foreach my $thrnum (1..10) { + new Thread \&tester, $thrnum; + } + + package Foo; + sub new { + my $class = shift @_; + return bless [@_], $class; + } + + sub per_object { + use attrs qw(locked method); + my ($class, $thrnum) = @_; + print "In per_object for thread $thrnum\n"; + yield; + sleep 2; + print "Exiting per_object for thread $thrnum\n"; + } + + sub one_at_a_time { + use attrs qw(locked); + my ($class, $thrnum) = @_; + print "In one_at_a_time for thread $thrnum\n"; + yield; + sleep 2; + print "Exiting one_at_a_time for thread $thrnum\n"; + } + +As you can see from the output (omitted for brevity; it's 800 lines) +all the threads can be in per_object() simultaneously, but only one +thread is ever in one_at_a_time() at once. + +=head2 Locking A Subroutine + +You can lock a subroutine as you would lock a variable. Subroutine +locks work the same as a C<use attrs qw(locked)> in the subroutine, +and block all access to the subroutine for other threads until the +lock goes out of scope. When the subroutine isn't locked, any number +of threads can be in it at once, and getting a lock on a subroutine +doesn't affect threads already in the subroutine. Getting a lock on a +subroutine looks like this: + + lock(\&sub_to_lock); + +Simple enough. Unlike use attrs, which is a compile time option, +locking and unlocking a subroutine can be done at runtime at your +discretion. There is some runtime penalty to using lock(\&sub) instead +of use attrs qw(locked), so make sure you're choosing the proper +method to do the locking. + +You'd choose lock(\&sub) when writing modules and code to run on both +threaded and unthreaded Perl, especially for code that will run on +5.004 or earlier Perls. In that case, it's useful to have subroutines +that should be serialized lock themselves if they're running threaded, +like so: + + package Foo; + use Config; + $Running_Threaded = 0; + + BEGIN { $Running_Threaded = $Config{'usethreaded'} } + + sub sub1 { lock(\&sub1) if $Running_Threaded } + + +This way you can ensure single-threadedness regardless of which +version of Perl you're running. + +=head1 General Thread Utility Routines + +We've covered the workhorse parts of Perl's threading package, and +with these tools you should be well on your way to writing threaded +code and packages. There are a few useful little pieces that didn't +really fit in anyplace else. + +=head2 What Thread Am I In? + +The Thread->self method provides your program with a way to get an +object representing the thread it's currently in. You can use this +object in the same way as the ones returned from the thread creation. + +=head2 Thread IDs + +tid() is a thread object method that returns the thread ID of the +thread the object represents. Thread IDs are integers, with the main +thread in a program being 0. Currently Perl assigns a unique tid to +every thread ever created in your program, assigning the first thread +to be created a tid of 1, and increasing the tid by 1 for each new +thread that's created. + +=head2 Are These Threads The Same? + +The equal() method takes two thread objects and returns true +if the objects represent the same thread, and false if they don't. + +=head2 What Threads Are Running? + +Thread->list returns a list of thread objects, one for each thread +that's currently running. Handy for a number of things, including +cleaning up at the end of your program: + + # Loop through all the threads + foreach $thr (Thread->list) { + # Don't join the main thread or ourselves + if ($thr->tid && !Thread::equal($thr, Thread->self)) { + $thr->join; + } + } + +The example above is just for illustration. It isn't strictly +necessary to join all the threads you create, since Perl detaches all +the threads before it exits. + +=head1 A Complete Example + +Confused yet? It's time for an example program to show some of the +things we've covered. This program finds prime numbers using threads. + + 1 #!/usr/bin/perl -w + 2 # prime-pthread, courtesy of Tom Christiansen + 3 + 4 use strict; + 5 + 6 use Thread; + 7 use Thread::Queue; + 8 + 9 my $stream = new Thread::Queue; + 10 my $kid = new Thread(\&check_num, $stream, 2); + 11 + 12 for my $i ( 3 .. 1000 ) { + 13 $stream->enqueue($i); + 14 } + 15 + 16 $stream->enqueue(undef); + 17 $kid->join(); + 18 + 19 sub check_num { + 20 my ($upstream, $cur_prime) = @_; + 21 my $kid; + 22 my $downstream = new Thread::Queue; + 23 while (my $num = $upstream->dequeue) { + 24 next unless $num % $cur_prime; + 25 if ($kid) { + 26 $downstream->enqueue($num); + 27 } else { + 28 print "Found prime $num\n"; + 29 $kid = new Thread(\&check_num, $downstream, $num); + 30 } + 31 } + 32 $downstream->enqueue(undef) if $kid; + 33 $kid->join() if $kid; + 34 } + +This program uses the pipeline model to generate prime numbers. Each +thread in the pipeline has an input queue that feeds numbers to be +checked, a prime number that it's responsible for, and an output queue +that it funnels numbers that have failed the check into. If the thread +has a number that's failed its check and there's no child thread, then +the thread must have found a new prime number. In that case, a new +child thread is created for that prime and stuck on the end of the +pipeline. + +This probably sounds a bit more confusing than it really is, so lets +go through this program piece by piece and see what it does. (For +those of you who might be trying to remember exactly what a prime +number is, it's a number that's only evenly divisible by itself and 1) + +The bulk of the work is done by the check_num() subroutine, which +takes a reference to its input queue and a prime number that it's +responsible for. After pulling in the input queue and the prime that +the subroutine's checking (line 20), we create a new queue (line 22) +and reserve a scalar for the thread that we're likely to create later +(line 21). + +The while loop from lines 23 to line 31 grabs a scalar off the input +queue and checks against the prime this thread is responsible +for. Line 24 checks to see if there's a remainder when we modulo the +number to be checked against our prime. If there is one, the number +must not be evenly divisible by our prime, so we need to either pass +it on to the next thread if we've created one (line 26) or create a +new thread if we haven't. + +The new thread creation is line 29. We pass on to it a reference to +the queue we've created, and the prime number we've found. + +Finally, once the loop terminates (because we got a 0 or undef in the +queue, which serves as a note to die), we pass on the notice to our +child and wait for it to exit if we've created a child (Lines 32 and +37). + +Meanwhile, back in the main thread, we create a queue (line 9) and the +initial child thread (line 10), and pre-seed it with the first prime: +2. Then we queue all the numbers from 3 to 1000 for checking (lines +12-14), then queue a die notice (line 16) and wait for the first child +thread to terminate (line 17). Because a child won't die until its +child has died, we know that we're done once we return from the join. + +That's how it works. It's pretty simple; as with many Perl programs, +the explanation is much longer than the program. + +=head1 Conclusion + +A complete thread tutorial could fill a book (and has, many times), +but this should get you well on your way. The final authority on how +Perl's threads behave is the documention bundled with the Perl +distribution, but with what we've covered in this article, you should +be well on your way to becoming a threaded Perl expert. + +=head1 Bibliography + +Here's a short bibliography courtesy of Jürgen Christoffel: + +=head2 Introductory Texts + +Birrell, Andrew D. An Introduction to Programming with +Threads. Digital Equipment Corporation, 1989, DEC-SRC Research Report +#35 online as +http://www.research.digital.com/SRC/staff/birrell/bib.html (highly +recommended) + +Robbins, Kay. A., and Steven Robbins. Practical Unix Programming: A +Guide to Concurrency, Communication, and +Multithreading. Prentice-Hall, 1996. + +Lewis, Bill, and Daniel J. Berg. Multithreaded Programming with +Pthreads. Prentice Hall, 1997, ISBN 0-13-443698-9 (a well-written +introduction to threads). + +Nelson, Greg (editor). Systems Programming with Modula-3. Prentice +Hall, 1991, ISBN 0-13-590464-1. + +Nichols, Bradford, Dick Buttlar, and Jacqueline Proulx Farrell. +Pthreads Programming. O'Reilly & Associates, 1996, ISBN 156592-115-1 +(covers POSIX threads). + +=head2 OS-Related References + +Boykin, Joseph, David Kirschen, Alan Langerman, and Susan +LoVerso. Programming under Mach. Addison-Wesley, 1994, ISBN +0-201-52739-1. + +Tanenbaum, Andrew S. Distributed Operating Systems. Prentice Hall, +1995, ISBN 0-13-143934-0 (great textbook). + +Silberschatz, Abraham, and Peter B. Galvin. Operating System Concepts, +4th ed. Addison-Wesley, 1995, ISBN 0-201-59292-4 + +=head2 Other References + +Arnold, Ken and James Gosling. The Java Programming Language, 2nd +ed. Addison-Wesley, 1998, ISBN 0-201-31006-6. + +Le Sergent, T. and B. Berthomieu. "Incremental MultiThreaded Garbage +Collection on Virtually Shared Memory Architectures" in Memory +Management: Proc. of the International Workshop IWMM 92, St. Malo, +France, September 1992, Yves Bekkers and Jacques Cohen, eds. Springer, +1992, ISBN 3540-55940-X (real-life thread applications). + +=head1 Acknowledgements + +Thanks (in no particular order) to Chaim Frenkel, Steve Fink, Gurusamy +Sarathy, Ilya Zakharevich, Benjamin Sugars, Jürgen Christoffel, Joshua +Pritikin, and Alan Burlison, for their help in reality-checking and +polishing this article. Big thanks to Tom Christiansen for his rewrite +of the prime number generator. + +=head1 AUTHOR + +Dan Sugalski E<lt>sugalskd@ous.eduE<gt> + +=head1 Copyrights + +This article originally appeared in The Perl Journal #10, and is +copyright 1998 The Perl Journal. It appears courtesy of Jon Orwant and +The Perl Journal. This document may be distributed under the same terms +as Perl itself. + + |