3 perlthrtut - tutorial on threads in Perl
7 B<NOTE>: this tutorial describes the new Perl threading flavour
8 introduced in Perl 5.6.0 called interpreter threads, or B<ithreads>
9 for short. In this model each thread runs in its own Perl interpreter,
10 and any data sharing between threads must be explicit.
12 There is another older Perl threading flavour called the 5.005 model,
13 unsurprisingly for 5.005 versions of Perl. The old model is known to
14 have problems, deprecated, and will probably be removed around release
15 5.10. You are strongly encouraged to migrate any existing 5.005
16 threads code to the new model as soon as possible.
18 You can see which (or neither) threading flavour you have by
19 running C<perl -V> and looking at the C<Platform> section.
20 If you have C<useithreads=define> you have ithreads, if you
21 have C<use5005threads=define> you have 5.005 threads.
22 If you have neither, you don't have any thread support built in.
23 If you have both, you are in trouble.
25 The user-level interface to the 5.005 threads was via the L<Threads>
26 class, while ithreads uses the L<threads> class. Note the change in case.
30 The ithreads code has been available since Perl 5.6.0, and is considered
31 stable. The user-level interface to ithreads (the L<threads> classes)
32 appeared in the 5.8.0 release, and as of this time is considered stable,
33 although as with all new features, should be treated with caution.
35 =head1 What Is A Thread Anyway?
37 A thread is a flow of control through a program with a single
40 Sounds an awful lot like a process, doesn't it? Well, it should.
41 Threads are one of the pieces of a process. Every process has at least
42 one thread and, up until now, every process running Perl had only one
43 thread. With 5.8, though, you can create extra threads. We're going
44 to show you how, when, and why.
46 =head1 Threaded Program Models
48 There are three basic ways that you can structure a threaded
49 program. Which model you choose depends on what you need your program
50 to do. For many non-trivial threaded programs you'll need to choose
51 different models for different pieces of your program.
55 The boss/worker model usually has one `boss' thread and one or more
56 `worker' threads. The boss thread gathers or generates tasks that need
57 to be done, then parcels those tasks out to the appropriate worker
60 This model is common in GUI and server programs, where a main thread
61 waits for some event and then passes that event to the appropriate
62 worker threads for processing. Once the event has been passed on, the
63 boss thread goes back to waiting for another event.
65 The boss thread does relatively little work. While tasks aren't
66 necessarily performed faster than with any other method, it tends to
67 have the best user-response times.
71 In the work crew model, several threads are created that do
72 essentially the same thing to different pieces of data. It closely
73 mirrors classical parallel processing and vector processors, where a
74 large array of processors do the exact same thing to many pieces of
77 This model is particularly useful if the system running the program
78 will distribute multiple threads across different processors. It can
79 also be useful in ray tracing or rendering engines, where the
80 individual threads can pass on interim results to give the user visual
85 The pipeline model divides up a task into a series of steps, and
86 passes the results of one step on to the thread processing the
87 next. Each thread does one thing to each piece of data and passes the
88 results to the next thread in line.
90 This model makes the most sense if you have multiple processors so two
91 or more threads will be executing in parallel, though it can often
92 make sense in other contexts as well. It tends to keep the individual
93 tasks small and simple, as well as allowing some parts of the pipeline
94 to block (on I/O or system calls, for example) while other parts keep
95 going. If you're running different parts of the pipeline on different
96 processors you may also take advantage of the caches on each
99 This model is also handy for a form of recursive programming where,
100 rather than having a subroutine call itself, it instead creates
101 another thread. Prime and Fibonacci generators both map well to this
102 form of the pipeline model. (A version of a prime number generator is
105 =head1 Native threads
107 There are several different ways to implement threads on a system. How
108 threads are implemented depends both on the vendor and, in some cases,
109 the version of the operating system. Often the first implementation
110 will be relatively simple, but later versions of the OS will be more
113 While the information in this section is useful, it's not necessary,
114 so you can skip it if you don't feel up to it.
116 There are three basic categories of threads: user-mode threads, kernel
117 threads, and multiprocessor kernel threads.
119 User-mode threads are threads that live entirely within a program and
120 its libraries. In this model, the OS knows nothing about threads. As
121 far as it's concerned, your process is just a process.
123 This is the easiest way to implement threads, and the way most OSes
124 start. The big disadvantage is that, since the OS knows nothing about
125 threads, if one thread blocks they all do. Typical blocking activities
126 include most system calls, most I/O, and things like sleep().
128 Kernel threads are the next step in thread evolution. The OS knows
129 about kernel threads, and makes allowances for them. The main
130 difference between a kernel thread and a user-mode thread is
131 blocking. With kernel threads, things that block a single thread don't
132 block other threads. This is not the case with user-mode threads,
133 where the kernel blocks at the process level and not the thread level.
135 This is a big step forward, and can give a threaded program quite a
136 performance boost over non-threaded programs. Threads that block
137 performing I/O, for example, won't block threads that are doing other
138 things. Each process still has only one thread running at once,
139 though, regardless of how many CPUs a system might have.
141 Since kernel threading can interrupt a thread at any time, they will
142 uncover some of the implicit locking assumptions you may make in your
143 program. For example, something as simple as C<$a = $a + 2> can behave
144 unpredictably with kernel threads if $a is visible to other
145 threads, as another thread may have changed $a between the time it
146 was fetched on the right hand side and the time the new value is
149 Multiprocessor kernel threads are the final step in thread
150 support. With multiprocessor kernel threads on a machine with multiple
151 CPUs, the OS may schedule two or more threads to run simultaneously on
154 This can give a serious performance boost to your threaded program,
155 since more than one thread will be executing at the same time. As a
156 tradeoff, though, any of those nagging synchronization issues that
157 might not have shown with basic kernel threads will appear with a
160 In addition to the different levels of OS involvement in threads,
161 different OSes (and different thread implementations for a particular
162 OS) allocate CPU cycles to threads in different ways.
164 Cooperative multitasking systems have running threads give up control
165 if one of two things happen. If a thread calls a yield function, it
166 gives up control. It also gives up control if the thread does
167 something that would cause it to block, such as perform I/O. In a
168 cooperative multitasking implementation, one thread can starve all the
169 others for CPU time if it so chooses.
171 Preemptive multitasking systems interrupt threads at regular intervals
172 while the system decides which thread should run next. In a preemptive
173 multitasking system, one thread usually won't monopolize the CPU.
175 On some systems, there can be cooperative and preemptive threads
176 running simultaneously. (Threads running with realtime priorities
177 often behave cooperatively, for example, while threads running at
178 normal priorities behave preemptively.)
180 =head1 What kind of threads are Perl threads?
182 If you have experience with other thread implementations, you might
183 find that things aren't quite what you expect. It's very important to
184 remember when dealing with Perl threads that Perl Threads Are Not X
185 Threads, for all values of X. They aren't POSIX threads, or
186 DecThreads, or Java's Green threads, or Win32 threads. There are
187 similarities, and the broad concepts are the same, but if you start
188 looking for implementation details you're going to be either
189 disappointed or confused. Possibly both.
191 This is not to say that Perl threads are completely different from
192 everything that's ever come before--they're not. Perl's threading
193 model owes a lot to other thread models, especially POSIX. Just as
194 Perl is not C, though, Perl threads are not POSIX threads. So if you
195 find yourself looking for mutexes, or thread priorities, it's time to
196 step back a bit and think about what you want to do and how Perl can
199 However it is important to remember that Perl threads cannot magically
200 do things unless your operating systems threads allows it. So if your
201 system blocks the entire process on sleep(), Perl usually will as well.
203 Perl Threads Are Different.
205 =head1 Threadsafe Modules
207 The addition of threads has changed Perl's internals
208 substantially. There are implications for people who write
209 modules with XS code or external libraries. However, since the threads
210 do not share data, pure Perl modules that don't interact with external
211 systems should be safe. Modules that are not tagged as thread-safe should
212 be tested or code reviewed before being used in production code.
214 Not all modules that you might use are thread-safe, and you should
215 always assume a module is unsafe unless the documentation says
216 otherwise. This includes modules that are distributed as part of the
217 core. Threads are a new feature, and even some of the standard
218 modules aren't thread-safe.
220 Even if a module is threadsafe, it doesn't mean that the module is optimized
221 to work well with threads. A module could possibly be rewritten to utilize
222 the new features in threaded Perl to increase performance in a threaded
225 If you're using a module that's not thread-safe for some reason, you
226 can protect yourself by using semaphores and lots of programming
227 discipline to control access to the module. Semaphores are covered
228 later in the article.
230 See also L</"Threadsafety of System Libraries">.
234 The core L<threads> module provides the basic functions you need to write
235 threaded programs. In the following sections we'll cover the basics,
236 showing you what you need to do to create a threaded program. After
237 that, we'll go over some of the features of the L<threads> module that
238 make threaded programming easier.
240 =head2 Basic Thread Support
242 Thread support is a Perl compile-time option - it's something that's
243 turned on or off when Perl is built at your site, rather than when
244 your programs are compiled. If your Perl wasn't compiled with thread
245 support enabled, then any attempt to use threads will fail.
247 Your programs can use the Config module to check whether threads are
248 enabled. If your program can't run without them, you can say something
251 $Config{useithreads} or die "Recompile Perl with threads to run this program.";
253 A possibly-threaded program using a possibly-threaded module might
260 if ($Config{useithreads}) {
262 require MyMod_threaded;
263 import MyMod_threaded;
265 require MyMod_unthreaded;
266 import MyMod_unthreaded;
270 Since code that runs both with and without threads is usually pretty
271 messy, it's best to isolate the thread-specific code in its own
272 module. In our example above, that's what MyMod_threaded is, and it's
273 only imported if we're running on a threaded Perl.
275 =head2 Creating Threads
277 The L<threads> package provides the tools you need to create new
278 threads. Like any other module, you need to tell Perl you want to use
279 it; C<use threads> imports all the pieces you need to create basic
282 The simplest, straightforward way to create a thread is with new():
286 $thr = threads->new(\&sub1);
289 print "In the thread\n";
292 The new() method takes a reference to a subroutine and creates a new
293 thread, which starts executing in the referenced subroutine. Control
294 then passes both to the subroutine and the caller.
296 If you need to, your program can pass parameters to the subroutine as
297 part of the thread startup. Just include the list of parameters as
298 part of the C<threads::new> call, like this:
303 $thr = threads->new(\&sub1, "Param 1", "Param 2", $Param3);
304 $thr = threads->new(\&sub1, @ParamList);
305 $thr = threads->new(\&sub1, qw(Param1 Param2 $Param3));
308 my @InboundParameters = @_;
309 print "In the thread\n";
310 print "got parameters >", join("<>", @InboundParameters), "<\n";
314 The last example illustrates another feature of threads. You can spawn
315 off several threads using the same subroutine. Each thread executes
316 the same subroutine, but in a separate thread with a separate
317 environment and potentially separate arguments.
319 C<create()> is a synonym for C<new()>.
321 =head2 Giving up control
323 There are times when you may find it useful to have a thread
324 explicitly give up the CPU to another thread. Your threading package
325 might not support preemptive multitasking for threads, for example, or
326 you may be doing something compute-intensive and want to make sure
327 that the user-interface thread gets called frequently. Regardless,
328 there are times that you might want a thread to give up the processor.
330 Perl's threading package provides the yield() function that does
331 this. yield() is pretty straightforward, and works like this:
338 while($foo--) { print "in thread $thread\n" }
341 while($foo--) { print "in thread $thread\n" }
344 my $thread1 = threads->new(\&loop, 'first');
345 my $thread2 = threads->new(\&loop, 'second');
346 my $thread3 = threads->new(\&loop, 'third');
348 It is important to remember that yield() is only a hint to give up the CPU,
349 it depends on your hardware, OS and threading libraries what actually happens.
350 Therefore it is important to note that one should not build the scheduling of
351 the threads around yield() calls. It might work on your platform but it won't
352 work on another platform.
354 =head2 Waiting For A Thread To Exit
356 Since threads are also subroutines, they can return values. To wait
357 for a thread to exit and extract any values it might return, you can
358 use the join() method:
362 $thr = threads->new(\&sub1);
364 @ReturnData = $thr->join;
365 print "Thread returned @ReturnData";
367 sub sub1 { return "Fifty-six", "foo", 2; }
369 In the example above, the join() method returns as soon as the thread
370 ends. In addition to waiting for a thread to finish and gathering up
371 any values that the thread might have returned, join() also performs
372 any OS cleanup necessary for the thread. That cleanup might be
373 important, especially for long-running programs that spawn lots of
374 threads. If you don't want the return values and don't want to wait
375 for the thread to finish, you should call the detach() method
376 instead, as described next.
378 =head2 Ignoring A Thread
380 join() does three things: it waits for a thread to exit, cleans up
381 after it, and returns any data the thread may have produced. But what
382 if you're not interested in the thread's return values, and you don't
383 really care when the thread finishes? All you want is for the thread
384 to get cleaned up after when it's done.
386 In this case, you use the detach() method. Once a thread is detached,
387 it'll run until it's finished, then Perl will clean up after it
392 $thr = threads->new(\&sub1); # Spawn the thread
394 $thr->detach; # Now we officially don't care any more
405 Once a thread is detached, it may not be joined, and any return data
406 that it might have produced (if it was done and waiting for a join) is
409 =head1 Threads And Data
411 Now that we've covered the basics of threads, it's time for our next
412 topic: data. Threading introduces a couple of complications to data
413 access that non-threaded programs never need to worry about.
415 =head2 Shared And Unshared Data
417 The biggest difference between Perl ithreads and the old 5.005 style
418 threading, or for that matter, to most other threading systems out there,
419 is that by default, no data is shared. When a new perl thread is created,
420 all the data associated with the current thread is copied to the new
421 thread, and is subsequently private to that new thread!
422 This is similar in feel to what happens when a UNIX process forks,
423 except that in this case, the data is just copied to a different part of
424 memory within the same process rather than a real fork taking place.
426 To make use of threading however, one usually want the threads to share
427 at least some data between themselves. This is done with the
428 L<threads::shared> module and the C< : shared> attribute:
433 my $foo : shared = 1;
435 threads->new(sub { $foo++; $bar++ })->join;
437 print "$foo\n"; #prints 2 since $foo is shared
438 print "$bar\n"; #prints 1 since $bar is not shared
440 In the case of a shared array, all the array's elements are shared, and for
441 a shared hash, all the keys and values are shared. This places
442 restrictions on what may be assigned to shared array and hash elements: only
443 simple values or references to shared variables are allowed - this is
444 so that a private variable can't accidentally become shared. A bad
445 assignment will cause the thread to die. For example:
451 my $svar : shared = 2;
454 ... create some threads ...
456 $hash{a} = 1; # all threads see exists($hash{a}) and $hash{a} == 1
457 $hash{a} = $var # okay - copy-by-value: same affect as previous
458 $hash{a} = $svar # okay - copy-by-value: same affect as previous
459 $hash{a} = \$svar # okay - a reference to a shared variable
460 $hash{a} = \$var # This will die
461 delete $hash{a} # okay - all threads will see !exists($hash{a})
463 Note that a shared variable guarantees that if two or more threads try to
464 modify it at the same time, the internal state of the variable will not
465 become corrupted. However, there are no guarantees beyond this, as
466 explained in the next section.
468 =head2 Thread Pitfalls: Races
470 While threads bring a new set of useful tools, they also bring a
471 number of pitfalls. One pitfall is the race condition:
477 $thr1 = threads->new(\&sub1);
478 $thr2 = threads->new(\&sub2);
484 sub sub1 { my $foo = $a; $a = $foo + 1; }
485 sub sub2 { my $bar = $a; $a = $bar + 1; }
487 What do you think $a will be? The answer, unfortunately, is "it
488 depends." Both sub1() and sub2() access the global variable $a, once
489 to read and once to write. Depending on factors ranging from your
490 thread implementation's scheduling algorithm to the phase of the moon,
493 Race conditions are caused by unsynchronized access to shared
494 data. Without explicit synchronization, there's no way to be sure that
495 nothing has happened to the shared data between the time you access it
496 and the time you update it. Even this simple code fragment has the
497 possibility of error:
503 my $thr1 = threads->create(sub { $b = $a; $a = $b + 1; });
504 my $thr2 = threads->create(sub { $c = $a; $a = $c + 1; });
508 Two threads both access $a. Each thread can potentially be interrupted
509 at any point, or be executed in any order. At the end, $a could be 3
510 or 4, and both $b and $c could be 2 or 3.
512 Even C<$a += 5> or C<$a++> are not guaranteed to be atomic.
514 Whenever your program accesses data or resources that can be accessed
515 by other threads, you must take steps to coordinate access or risk
516 data inconsistency and race conditions. Note that Perl will protect its
517 internals from your race conditions, but it won't protect you from you.
519 =head1 Synchronization and control
521 Perl provides a number of mechanisms to coordinate the interactions
522 between themselves and their data, to avoid race conditions and the like.
523 Some of these are designed to resemble the common techniques used in thread
524 libraries such as C<pthreads>; others are Perl-specific. Often, the
525 standard techniques are clumsily and difficult to get right (such as
526 condition waits). Where possible, it is usually easier to use Perlish
527 techniques such as queues, which remove some of the hard work involved.
529 =head2 Controlling access: lock()
531 The lock() function takes a shared variable and puts a lock on it.
532 No other thread may lock the variable until the the variable is unlocked
533 by the thread holding the lock. Unlocking happens automatically
534 when the locking thread exists the outermost block that contains
535 C<lock()> function. Using lock() is straightforward: this example has
536 several threads doing some calculations in parallel, and occasionally
537 updating a running total:
542 my $total : shared = 0;
547 # (... do some calculations and set $result ...)
549 lock($total); # block until we obtain the lock
551 } # lock implicitly released at end of scope
552 last if $result == 0;
556 my $thr1 = threads->new(\&calc);
557 my $thr2 = threads->new(\&calc);
558 my $thr3 = threads->new(\&calc);
562 print "total=$total\n";
565 lock() blocks the thread until the variable being locked is
566 available. When lock() returns, your thread can be sure that no other
567 thread can lock that variable until the outermost block containing the
570 It's important to note that locks don't prevent access to the variable
571 in question, only lock attempts. This is in keeping with Perl's
572 longstanding tradition of courteous programming, and the advisory file
573 locking that flock() gives you.
575 You may lock arrays and hashes as well as scalars. Locking an array,
576 though, will not block subsequent locks on array elements, just lock
577 attempts on the array itself.
579 Locks are recursive, which means it's okay for a thread to
580 lock a variable more than once. The lock will last until the outermost
581 lock() on the variable goes out of scope. For example:
589 lock($x); # wait for lock
590 lock($x): # NOOP - we already have the lock
598 } # *** implicit unlock here ***
602 sub lockit_some_more {
604 } # nothing happens here
606 Note that there is no unlock() function - the only way to unlock a
607 variable is to allow it to go out of scope.
609 A lock can either be used to guard the data contained within the variable
610 being locked, or it can be used to guard something else, like a section
611 of code. In this latter case, the variable in question does not hold any
612 useful data, and exists only for the purpose of being locked. In this
613 respect, the variable behaves like the mutexes and basic semaphores of
614 traditional thread libraries.
616 =head2 A Thread Pitfall: Deadlocks
618 Locks are a handy tool to synchronize access to data, and using them
619 properly is the key to safe shared data. Unfortunately, locks aren't
620 without their dangers, especially when multiple locks are involved.
621 Consider the following code:
626 my $b : shared = "foo";
627 my $thr1 = threads->new(sub {
633 my $thr2 = threads->new(sub {
640 This program will probably hang until you kill it. The only way it
641 won't hang is if one of the two threads acquires both locks
642 first. A guaranteed-to-hang version is more complicated, but the
643 principle is the same.
645 The first thread will grab a lock on $a, then, after a pause during which
646 the second thread has probably had time to do some work, try to grab a
647 lock on $b. Meanwhile, the second thread grabs a lock on $b, then later
648 tries to grab a lock on $a. The second lock attempt for both threads will
649 block, each waiting for the other to release its lock.
651 This condition is called a deadlock, and it occurs whenever two or
652 more threads are trying to get locks on resources that the others
653 own. Each thread will block, waiting for the other to release a lock
654 on a resource. That never happens, though, since the thread with the
655 resource is itself waiting for a lock to be released.
657 There are a number of ways to handle this sort of problem. The best
658 way is to always have all threads acquire locks in the exact same
659 order. If, for example, you lock variables $a, $b, and $c, always lock
660 $a before $b, and $b before $c. It's also best to hold on to locks for
661 as short a period of time to minimize the risks of deadlock.
663 The other synchronization primitives described below can suffer from
666 =head2 Queues: Passing Data Around
668 A queue is a special thread-safe object that lets you put data in one
669 end and take it out the other without having to worry about
670 synchronization issues. They're pretty straightforward, and look like
674 use threads::shared::queue;
676 my $DataQueue = threads::shared::queue->new();
677 $thr = threads->new(sub {
678 while ($DataElement = $DataQueue->dequeue) {
679 print "Popped $DataElement off the queue\n";
683 $DataQueue->enqueue(12);
684 $DataQueue->enqueue("A", "B", "C");
685 $DataQueue->enqueue(\$thr);
687 $DataQueue->enqueue(undef);
690 You create the queue with C<new threads::shared::queue>. Then you can
691 add lists of scalars onto the end with enqueue(), and pop scalars off
692 the front of it with dequeue(). A queue has no fixed size, and can grow
693 as needed to hold everything pushed on to it.
695 If a queue is empty, dequeue() blocks until another thread enqueues
696 something. This makes queues ideal for event loops and other
697 communications between threads.
699 =head2 Semaphores: Synchronizing Data Access
701 Semaphores are a kind of generic locking mechanism. In their most basic
702 form, they behave very much like lockable scalars, except that thay
703 can't hold data, and that they must be explicitly unlocked. In their
704 advanced form, they act like a kind of counter, and can allow multiple
705 threads to have the 'lock' at any one time.
707 =head2 Basic semaphores
709 Semaphores have two methods, down() and up(): down() decrements the resource
710 count, while up increments it. Calls to down() will block if the
711 semaphore's current count would decrement below zero. This program
712 gives a quick demonstration:
714 use threads qw(yield);
715 use threads::shared::semaphore;
717 my $semaphore = new threads::shared::semaphore;
718 my $GlobalVariable : shared = 0;
720 $thr1 = new threads \&sample_sub, 1;
721 $thr2 = new threads \&sample_sub, 2;
722 $thr3 = new threads \&sample_sub, 3;
725 my $SubNumber = shift @_;
729 while ($TryCount--) {
731 $LocalCopy = $GlobalVariable;
732 print "$TryCount tries left for sub $SubNumber (\$GlobalVariable is $GlobalVariable)\n";
736 $GlobalVariable = $LocalCopy;
745 The three invocations of the subroutine all operate in sync. The
746 semaphore, though, makes sure that only one thread is accessing the
747 global variable at once.
749 =head2 Advanced Semaphores
751 By default, semaphores behave like locks, letting only one thread
752 down() them at a time. However, there are other uses for semaphores.
754 Each semaphore has a counter attached to it. By default, semaphores are
755 created with the counter set to one, down() decrements the counter by
756 one, and up() increments by one. However, we can override any or all
757 of these defaults simply by passing in different values:
760 use threads::shared::semaphore;
761 my $semaphore = threads::shared::semaphore->new(5);
762 # Creates a semaphore with the counter set to five
764 $thr1 = threads->new(\&sub1);
765 $thr2 = threads->new(\&sub1);
768 $semaphore->down(5); # Decrements the counter by five
770 $semaphore->up(5); # Increment the counter by five
776 If down() attempts to decrement the counter below zero, it blocks until
777 the counter is large enough. Note that while a semaphore can be created
778 with a starting count of zero, any up() or down() always changes the
779 counter by at least one, and so $semaphore->down(0) is the same as
782 The question, of course, is why would you do something like this? Why
783 create a semaphore with a starting count that's not one, or why
784 decrement/increment it by more than one? The answer is resource
785 availability. Many resources that you want to manage access for can be
786 safely used by more than one thread at once.
788 For example, let's take a GUI driven program. It has a semaphore that
789 it uses to synchronize access to the display, so only one thread is
790 ever drawing at once. Handy, but of course you don't want any thread
791 to start drawing until things are properly set up. In this case, you
792 can create a semaphore with a counter set to zero, and up it when
793 things are ready for drawing.
795 Semaphores with counters greater than one are also useful for
796 establishing quotas. Say, for example, that you have a number of
797 threads that can do I/O at once. You don't want all the threads
798 reading or writing at once though, since that can potentially swamp
799 your I/O channels, or deplete your process' quota of filehandles. You
800 can use a semaphore initialized to the number of concurrent I/O
801 requests (or open files) that you want at any one time, and have your
802 threads quietly block and unblock themselves.
804 Larger increments or decrements are handy in those cases where a
805 thread needs to check out or return a number of resources at once.
807 =head2 cond_wait() and cond_signal()
809 These two functions can be used in conjunction with locks to notify
810 co-operating threads that a resource has become available. They are
811 very similar in use to the functions found in C<pthreads>. However
812 for most purposes, queues are simpler to use and more intuitive. See
813 L<threads::shared> for more details.
815 =head1 General Thread Utility Routines
817 We've covered the workhorse parts of Perl's threading package, and
818 with these tools you should be well on your way to writing threaded
819 code and packages. There are a few useful little pieces that didn't
820 really fit in anyplace else.
822 =head2 What Thread Am I In?
824 The C<< threads->self >> class method provides your program with a way to
825 get an object representing the thread it's currently in. You can use this
826 object in the same way as the ones returned from thread creation.
830 tid() is a thread object method that returns the thread ID of the
831 thread the object represents. Thread IDs are integers, with the main
832 thread in a program being 0. Currently Perl assigns a unique tid to
833 every thread ever created in your program, assigning the first thread
834 to be created a tid of 1, and increasing the tid by 1 for each new
835 thread that's created.
837 =head2 Are These Threads The Same?
839 The equal() method takes two thread objects and returns true
840 if the objects represent the same thread, and false if they don't.
842 Thread objects also have an overloaded == comparison so that you can do
843 comparison on them as you would with normal objects.
845 =head2 What Threads Are Running?
847 C<< threads->list >> returns a list of thread objects, one for each thread
848 that's currently running and not detached. Handy for a number of things,
849 including cleaning up at the end of your program:
851 # Loop through all the threads
852 foreach $thr (threads->list) {
853 # Don't join the main thread or ourselves
854 if ($thr->tid && !threads::equal($thr, threads->self)) {
859 If some threads have not finished running when the main Perl thread
860 ends, Perl will warn you about it and die, since it is impossible for Perl
861 to clean up itself while other threads are running
863 =head1 A Complete Example
865 Confused yet? It's time for an example program to show some of the
866 things we've covered. This program finds prime numbers using threads.
869 2 # prime-pthread, courtesy of Tom Christiansen
874 7 use threads::shared::queue;
876 9 my $stream = new threads::shared::queue;
877 10 my $kid = new threads(\&check_num, $stream, 2);
879 12 for my $i ( 3 .. 1000 ) {
880 13 $stream->enqueue($i);
883 16 $stream->enqueue(undef);
887 20 my ($upstream, $cur_prime) = @_;
889 22 my $downstream = new threads::shared::queue;
890 23 while (my $num = $upstream->dequeue) {
891 24 next unless $num % $cur_prime;
893 26 $downstream->enqueue($num);
895 28 print "Found prime $num\n";
896 29 $kid = new threads(\&check_num, $downstream, $num);
899 32 $downstream->enqueue(undef) if $kid;
900 33 $kid->join() if $kid;
903 This program uses the pipeline model to generate prime numbers. Each
904 thread in the pipeline has an input queue that feeds numbers to be
905 checked, a prime number that it's responsible for, and an output queue
906 that into which it funnels numbers that have failed the check. If the thread
907 has a number that's failed its check and there's no child thread, then
908 the thread must have found a new prime number. In that case, a new
909 child thread is created for that prime and stuck on the end of the
912 This probably sounds a bit more confusing than it really is, so let's
913 go through this program piece by piece and see what it does. (For
914 those of you who might be trying to remember exactly what a prime
915 number is, it's a number that's only evenly divisible by itself and 1)
917 The bulk of the work is done by the check_num() subroutine, which
918 takes a reference to its input queue and a prime number that it's
919 responsible for. After pulling in the input queue and the prime that
920 the subroutine's checking (line 20), we create a new queue (line 22)
921 and reserve a scalar for the thread that we're likely to create later
924 The while loop from lines 23 to line 31 grabs a scalar off the input
925 queue and checks against the prime this thread is responsible
926 for. Line 24 checks to see if there's a remainder when we modulo the
927 number to be checked against our prime. If there is one, the number
928 must not be evenly divisible by our prime, so we need to either pass
929 it on to the next thread if we've created one (line 26) or create a
930 new thread if we haven't.
932 The new thread creation is line 29. We pass on to it a reference to
933 the queue we've created, and the prime number we've found.
935 Finally, once the loop terminates (because we got a 0 or undef in the
936 queue, which serves as a note to die), we pass on the notice to our
937 child and wait for it to exit if we've created a child (lines 32 and
940 Meanwhile, back in the main thread, we create a queue (line 9) and the
941 initial child thread (line 10), and pre-seed it with the first prime:
942 2. Then we queue all the numbers from 3 to 1000 for checking (lines
943 12-14), then queue a die notice (line 16) and wait for the first child
944 thread to terminate (line 17). Because a child won't die until its
945 child has died, we know that we're done once we return from the join.
947 That's how it works. It's pretty simple; as with many Perl programs,
948 the explanation is much longer than the program.
950 =head1 Performance considerations
952 The main thing to bear in mind when comparing ithreads to other threading
953 models is the fact that for each new thread created, a complete copy of
954 all the variables and data of the parent thread has to be taken. Thus
955 thread creation can be quite expensive, both in terms of memory usage and
956 time spent in creation. The ideal way to reduce these costs is to have a
957 relatively short number of long-lived threads, all created fairly early
958 on - before the base thread has accumulated too much data. Of course, this
959 may not always be possible, so compromises have to be made. However, after
960 a thread has been created, its performance and extra memory usage should
961 be little different than ordinary code.
963 Also note that under the current implementation, shared variables
964 use a little more memory and are a little slower than ordinary variables.
966 =head1 Threadsafety of System Libraries
968 Whether various library calls are threadsafe is outside the control
969 of Perl. Calls often suffering from not being threadsafe include:
970 localtime(), gmtime(), get{gr,host,net,proto,serv,pw}*(), readdir(),
971 rand(), and srand() -- in general, calls that depend on some external
974 If the system Perl is compiled in has threadsafe variants of such
975 calls, they will be used. Beyond that, Perl is at the mercy of
976 the threadsafety or unsafety of the calls. Please consult your
977 C library call documentation.
979 In some platforms the threadsafe interfaces may fail if the result
980 buffer is too small (for example getgrent() may return quite large
981 group member lists). Perl will retry growing the result buffer
982 a few times, but only up to 64k (for safety reasons).
986 A complete thread tutorial could fill a book (and has, many times),
987 but with what we've covered in this introduction, you should be well
988 on your way to becoming a threaded Perl expert.
992 Here's a short bibliography courtesy of Jürgen Christoffel:
994 =head2 Introductory Texts
996 Birrell, Andrew D. An Introduction to Programming with
997 Threads. Digital Equipment Corporation, 1989, DEC-SRC Research Report
999 http://gatekeeper.dec.com/pub/DEC/SRC/research-reports/abstracts/src-rr-035.html
1000 (highly recommended)
1002 Robbins, Kay. A., and Steven Robbins. Practical Unix Programming: A
1003 Guide to Concurrency, Communication, and
1004 Multithreading. Prentice-Hall, 1996.
1006 Lewis, Bill, and Daniel J. Berg. Multithreaded Programming with
1007 Pthreads. Prentice Hall, 1997, ISBN 0-13-443698-9 (a well-written
1008 introduction to threads).
1010 Nelson, Greg (editor). Systems Programming with Modula-3. Prentice
1011 Hall, 1991, ISBN 0-13-590464-1.
1013 Nichols, Bradford, Dick Buttlar, and Jacqueline Proulx Farrell.
1014 Pthreads Programming. O'Reilly & Associates, 1996, ISBN 156592-115-1
1015 (covers POSIX threads).
1017 =head2 OS-Related References
1019 Boykin, Joseph, David Kirschen, Alan Langerman, and Susan
1020 LoVerso. Programming under Mach. Addison-Wesley, 1994, ISBN
1023 Tanenbaum, Andrew S. Distributed Operating Systems. Prentice Hall,
1024 1995, ISBN 0-13-219908-4 (great textbook).
1026 Silberschatz, Abraham, and Peter B. Galvin. Operating System Concepts,
1027 4th ed. Addison-Wesley, 1995, ISBN 0-201-59292-4
1029 =head2 Other References
1031 Arnold, Ken and James Gosling. The Java Programming Language, 2nd
1032 ed. Addison-Wesley, 1998, ISBN 0-201-31006-6.
1034 Le Sergent, T. and B. Berthomieu. "Incremental MultiThreaded Garbage
1035 Collection on Virtually Shared Memory Architectures" in Memory
1036 Management: Proc. of the International Workshop IWMM 92, St. Malo,
1037 France, September 1992, Yves Bekkers and Jacques Cohen, eds. Springer,
1038 1992, ISBN 3540-55940-X (real-life thread applications).
1040 =head1 Acknowledgements
1042 Thanks (in no particular order) to Chaim Frenkel, Steve Fink, Gurusamy
1043 Sarathy, Ilya Zakharevich, Benjamin Sugars, Jürgen Christoffel, Joshua
1044 Pritikin, and Alan Burlison, for their help in reality-checking and
1045 polishing this article. Big thanks to Tom Christiansen for his rewrite
1046 of the prime number generator.
1050 Dan Sugalski E<lt>dan@sidhe.org<gt>
1052 Slightly modified by Arthur Bergman to fit the new thread model/module.
1056 The original version of this article originally appeared in The Perl
1057 Journal #10, and is copyright 1998 The Perl Journal. It appears courtesy
1058 of Jon Orwant and The Perl Journal. This document may be distributed
1059 under the same terms as Perl itself.
1061 For more information please see L<threads> and L<threads::shared>.