PERLTHRTUT(1) Perl Programmers Reference Guide PERLTHRTUT(1)

PERLTHRTUT(1) Perl Programmers Reference Guide PERLTHRTUT(1) #

PERLTHRTUT(1) Perl Programmers Reference Guide PERLTHRTUT(1)

NNAAMMEE #

 perlthrtut - Tutorial on threads in Perl

DDEESSCCRRIIPPTTIIOONN #

 This tutorial describes the use of Perl interpreter threads (sometimes
 referred to as _i_t_h_r_e_a_d_s).  In this model, each thread runs in its own
 Perl interpreter, and any data sharing between threads must be explicit.
 The user-level interface for _i_t_h_r_e_a_d_s uses the threads class.

 NNOOTTEE: There was another older Perl threading flavor called the 5.005
 model that used the threads class.  This old model was known to have
 problems, is deprecated, and was removed for release 5.10.  You are
 strongly encouraged to migrate any existing 5.005 threads code to the new
 model as soon as possible.

 You can see which (or neither) threading flavour you have by running
 "perl -V" and looking at the "Platform" section.  If you have
 "useithreads=define" you have ithreads, if you have
 "use5005threads=define" you have 5.005 threads.  If you have neither, you
 don't have any thread support built in.  If you have both, you are in
 trouble.

 The threads and threads::shared modules are included in the core Perl
 distribution.  Additionally, they are maintained as a separate modules on
 CPAN, so you can check there for any updates.

WWhhaatt IIss AA TThhrreeaadd AAnnyywwaayy?? 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 5.8, though, you can create extra threads.  We're going to show you
 how, when, and why.

TThhrreeaaddeedd PPrrooggrraamm MMooddeellss 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.

BBoossss//WWoorrkkeerr The boss/worker model usually has one _b_o_s_s thread and one or more _w_o_r_k_e_r 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.

WWoorrkk CCrreeww 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.

PPiippeelliinnee 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.)

WWhhaatt kkiinndd ooff tthhrreeaaddss aarree PPeerrll tthhrreeaaddss?? 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 _P_e_r_l _T_h_r_e_a_d_s _A_r_e _N_o_t _X _T_h_r_e_a_d_s 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.

 However, it is important to remember that Perl threads cannot magically
 do things unless your operating system's threads allow it. So if your
 system blocks the entire process on "sleep()", Perl usually will, as
 well.

 PPeerrll TThhrreeaaddss AArree DDiiffffeerreenntt..

TThhrreeaadd--SSaaffee MMoodduulleess The addition of threads has changed Perl’s internals substantially. There are implications for people who write modules with XS code or external libraries. However, since Perl data is not shared among threads by default, Perl modules stand a high chance of being thread-safe or can be made thread-safe easily. Modules that are not tagged as thread-safe should be tested or code reviewed 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
 relatively new feature, and even some of the standard modules aren't
 thread-safe.

 Even if a module is thread-safe, it doesn't mean that the module is
 optimized to work well with threads. A module could possibly be rewritten
 to utilize the new features in threaded Perl to increase performance in a
 threaded environment.

 If you're using a module that's not thread-safe for some reason, you can
 protect yourself by using it from one, and only one thread at all.  If
 you need multiple threads to access such a module, you can use semaphores
 and lots of programming discipline to control access to it.  Semaphores
 are covered in "Basic semaphores".

 See also "Thread-Safety of System Libraries".

TThhrreeaadd BBaassiiccss The threads 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 threads module that make threaded programming easier.

BBaassiicc TThhrreeaadd SSuuppppoorrtt 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.

 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:

     use Config;
     $Config{useithreads} 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;

BEGIN { #

         if ($Config{useithreads}) {
             # 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.

AA NNoottee aabboouutt tthhee EExxaammpplleess In a real situation, care should be taken that all threads are finished executing before the program exits. That care has nnoott been taken in these examples in the interest of simplicity. Running these examples _a_s _i_s will produce error messages, usually caused by the fact that there are still threads running when the program exits. You should not be alarmed by this.

CCrreeaattiinngg TThhrreeaaddss The threads module provides the tools you need to create new threads. Like any other module, you need to tell Perl that you want to use it; “use threads;” imports all the pieces you need to create basic threads.

 The simplest, most straightforward way to create a thread is with
 "create()":

     use threads;

     my $thr = threads->create(\&sub1);

     sub sub1 {
         print("In the thread\n");
     }

 The "create()" method takes a reference to a subroutine and creates a new
 thread that 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 "threads->create()" call, like this:

     use threads;

     my $Param3 = 'foo';
     my $thr1 = threads->create(\&sub1, 'Param 1', 'Param 2', $Param3);
     my @ParamList = (42, 'Hello', 3.14);
     my $thr2 = threads->create(\&sub1, @ParamList);
     my $thr3 = threads->create(\&sub1, qw(Param1 Param2 Param3));

     sub sub1 {
         my @InboundParameters = @_;
         print("In the thread\n");
         print('Got parameters >', join('<>',@InboundParameters), "<\n");
     }

 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.

 "new()" is a synonym for "create()".

WWaaiittiinngg FFoorr AA TThhrreeaadd TToo EExxiitt Since threads are also subroutines, they can return values. To wait for a thread to exit and extract any values it might return, you can use the “join()” method:

     use threads;

     my ($thr) = threads->create(\&sub1);

     my @ReturnData = $thr->join();
     print('Thread returned ', join(', ', @ReturnData), "\n");

     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, as described next.

 NOTE: In the example above, the thread returns a list, thus necessitating
 that the thread creation call be made in list context (i.e., "my
 ($thr)").  See "$thr->jjooiinn(())" in threads and "THREAD CONTEXT" in threads
 for more details on thread context and return values.

IIggnnoorriinngg AA TThhrreeaadd “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 threads;

     my $thr = threads->create(\&sub1);   # Spawn the thread

     $thr->detach();   # Now we officially don't care any more

     sleep(15);        # Let thread run for awhile

     sub sub1 {
         my $count = 0;
         while (1) {
             $count++;
             print("\$count is $count\n");
             sleep(1);
         }
     }

 Once a thread is detached, it may not be joined, and any return data that
 it might have produced (if it was done and waiting for a join) is lost.

 "detach()" can also be called as a class method to allow a thread to
 detach itself:

     use threads;

     my $thr = threads->create(\&sub1);

     sub sub1 {
         threads->detach();
         # Do more work
     }

PPrroocceessss aanndd TThhrreeaadd TTeerrmmiinnaattiioonn With threads one must be careful to make sure they all have a chance to run to completion, assuming that is what you want.

 An action that terminates a process will terminate _a_l_l running threads.
 ddiiee(()) and eexxiitt(()) have this property, and perl does an exit when the main
 thread exits, perhaps implicitly by falling off the end of your code,
 even if that's not what you want.

 As an example of this case, this code prints the message "Perl exited
 with active threads: 2 running and unjoined":

     use threads;
     my $thr1 = threads->new(\&thrsub, "test1");
     my $thr2 = threads->new(\&thrsub, "test2");
     sub thrsub {
        my ($message) = @_;
        sleep 1;
        print "thread $message\n";
     }

 But when the following lines are added at the end:

     $thr1->join();
     $thr2->join();

 it prints two lines of output, a perhaps more useful outcome.

TThhrreeaaddss AAnndd DDaattaa 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.

SShhaarreedd AAnndd UUnnsshhaarreedd DDaattaa The biggest difference between Perl _i_t_h_r_e_a_d_s and the old 5.005 style threading, or for that matter, to most other threading systems out there, is that by default, no data is shared. When a new Perl thread is created, all the data associated with the current thread is copied to the new thread, and is subsequently private to that new thread! This is similar in feel to what happens when a Unix process forks, except that in this case, the data is just copied to a different part of memory within the same process rather than a real fork taking place.

 To make use of threading, however, one usually wants the threads to share
 at least some data between themselves. This is done with the
 threads::shared module and the ":shared" attribute:

     use threads;
     use threads::shared;

     my $foo :shared = 1;
     my $bar = 1;
     threads->create(sub { $foo++; $bar++; })->join();

     print("$foo\n");  # Prints 2 since $foo is shared
     print("$bar\n");  # Prints 1 since $bar is not shared

 In the case of a shared array, all the array's elements are shared, and
 for a shared hash, all the keys and values are shared. This places
 restrictions on what may be assigned to shared array and hash elements:
 only simple values or references to shared variables are allowed - this
 is so that a private variable can't accidentally become shared. A bad
 assignment will cause the thread to die. For example:

     use threads;
     use threads::shared;

     my $var          = 1;
     my $svar :shared = 2;
     my %hash :shared;

     ... create some threads ...

     $hash{a} = 1;       # All threads see exists($hash{a})
                         # and $hash{a} == 1
     $hash{a} = $var;    # okay - copy-by-value: same effect as previous
     $hash{a} = $svar;   # okay - copy-by-value: same effect as previous
     $hash{a} = \$svar;  # okay - a reference to a shared variable
     $hash{a} = \$var;   # This will die
     delete($hash{a});   # okay - all threads will see !exists($hash{a})

 Note that a shared variable guarantees that if two or more threads try to
 modify it at the same time, the internal state of the variable will not
 become corrupted. However, there are no guarantees beyond this, as
 explained in the next section.

TThhrreeaadd PPiittffaallllss:: RRaacceess While threads bring a new set of useful tools, they also bring a number of pitfalls. One pitfall is the race condition:

     use threads;
     use threads::shared;

     my $x :shared = 1;
     my $thr1 = threads->create(\&sub1);
     my $thr2 = threads->create(\&sub2);

     $thr1->join();
     $thr2->join();
     print("$x\n");

     sub sub1 { my $foo = $x; $x = $foo + 1; }
     sub sub2 { my $bar = $x; $x = $bar + 1; }

 What do you think $x will be? The answer, unfortunately, is _i_t _d_e_p_e_n_d_s.
 Both "sub1()" and "sub2()" access the global variable $x, once to read
 and once to write.  Depending on factors ranging from your thread
 implementation's scheduling algorithm to the phase of the moon, $x 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 threads;
     my $x :shared = 2;
     my $y :shared;
     my $z :shared;
     my $thr1 = threads->create(sub { $y = $x; $x = $y + 1; });
     my $thr2 = threads->create(sub { $z = $x; $x = $z + 1; });
     $thr1->join();
     $thr2->join();

 Two threads both access $x.  Each thread can potentially be interrupted
 at any point, or be executed in any order.  At the end, $x could be 3 or
 4, and both $y and $z could be 2 or 3.

 Even "$x += 5" or "$x++" are not guaranteed to be atomic.

 Whenever your program accesses data or resources that can be accessed by
 other threads, you must take steps to coordinate access or risk data
 inconsistency and race conditions. Note that Perl will protect its
 internals from your race conditions, but it won't protect you from you.

SSyynncchhrroonniizzaattiioonn aanndd ccoonnttrrooll Perl provides a number of mechanisms to coordinate the interactions between themselves and their data, to avoid race conditions and the like. Some of these are designed to resemble the common techniques used in thread libraries such as “pthreads”; others are Perl-specific. Often, the standard techniques are clumsy and difficult to get right (such as condition waits). Where possible, it is usually easier to use Perlish techniques such as queues, which remove some of the hard work involved.

CCoonnttrroolllliinngg aacccceessss:: lloocckk(()) The “lock()” function takes a shared variable and puts a lock on it. No other thread may lock the variable until the variable is unlocked by the thread holding the lock. Unlocking happens automatically when the locking thread exits the block that contains the call to the “lock()” function. Using “lock()” is straightforward: This example has several threads doing some calculations in parallel, and occasionally updating a running total:

     use threads;
     use threads::shared;

     my $total :shared = 0;

     sub calc {
         while (1) {
             my $result;
             # (... do some calculations and set $result ...)
             {
                 lock($total);  # Block until we obtain the lock
                 $total += $result;
             } # Lock implicitly released at end of scope
             last if $result == 0;
         }
     }

     my $thr1 = threads->create(\&calc);
     my $thr2 = threads->create(\&calc);
     my $thr3 = threads->create(\&calc);
     $thr1->join();
     $thr2->join();
     $thr3->join();
     print("total=$total\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 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.

 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.

 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. For example:

     my $x :shared;
     doit();

     sub doit {
         {
             {
                 lock($x); # Wait for lock
                 lock($x); # NOOP - we already have the lock
                 {
                     lock($x); # NOOP
                     {
                         lock($x); # NOOP
                         lockit_some_more();
                     }
                 }
             } # *** Implicit unlock here ***
         }
     }

     sub lockit_some_more {
         lock($x); # NOOP
     } # Nothing happens here

 Note that there is no "unlock()" function - the only way to unlock a
 variable is to allow it to go out of scope.

 A lock can either be used to guard the data contained within the variable
 being locked, or it can be used to guard something else, like a section
 of code. In this latter case, the variable in question does not hold any
 useful data, and exists only for the purpose of being locked. In this
 respect, the variable behaves like the mutexes and basic semaphores of
 traditional thread libraries.

AA TThhrreeaadd PPiittffaallll:: DDeeaaddlloocckkss Locks are a handy tool to synchronize access to data, and using them properly is the key to safe shared data. Unfortunately, locks aren’t without their dangers, especially when multiple locks are involved. Consider the following code:

     use threads;

     my $x :shared = 4;
     my $y :shared = 'foo';
     my $thr1 = threads->create(sub {
         lock($x);
         sleep(20);
         lock($y);
     });
     my $thr2 = threads->create(sub {
         lock($y);
         sleep(20);
         lock($x);
     });

 This program will probably hang until you kill it.  The only way it won't
 hang is if one of the two threads acquires both locks first.  A
 guaranteed-to-hang version is more complicated, but the principle is the
 same.

 The first thread will grab a lock on $x, then, after a pause during which
 the second thread has probably had time to do some work, try to grab a
 lock on $y.  Meanwhile, the second thread grabs a lock on $y, then later
 tries to grab a lock on $x.  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 $x, $y, and $z, always lock $x before $y,
 and $y before $z.  It's also best to hold on to locks for as short a
 period of time to minimize the risks of deadlock.

 The other synchronization primitives described below can suffer from
 similar problems.

QQuueeuueess:: PPaassssiinngg DDaattaa AArroouunndd 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 threads;
     use Thread::Queue;

     my $DataQueue = Thread::Queue->new();
     my $thr = threads->create(sub {
         while (my $DataElement = $DataQueue->dequeue()) {
             print("Popped $DataElement off the queue\n");
         }
     });

     $DataQueue->enqueue(12);
     $DataQueue->enqueue("A", "B", "C");
     sleep(10);
     $DataQueue->enqueue(undef);
     $thr->join();

 You create the queue with "Thread::Queue->new()".  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.

SSeemmaapphhoorreess:: SSyynncchhrroonniizziinngg DDaattaa AAcccceessss Semaphores are a kind of generic locking mechanism. In their most basic form, they behave very much like lockable scalars, except that they can’t hold data, and that they must be explicitly unlocked. In their advanced form, they act like a kind of counter, and can allow multiple threads to have the _l_o_c_k at any one time.

BBaassiicc sseemmaapphhoorreess Semaphores have two methods, “down()” and “up()”: “down()” decrements the resource count, while “up()” increments it. Calls to “down()” will block if the semaphore’s current count would decrement below zero. This program gives a quick demonstration:

     use threads;
     use Thread::Semaphore;

     my $semaphore = Thread::Semaphore->new();
     my $GlobalVariable :shared = 0;

     $thr1 = threads->create(\&sample_sub, 1);
     $thr2 = threads->create(\&sample_sub, 2);
     $thr3 = threads->create(\&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");
             sleep(2);
             $LocalCopy++;
             $GlobalVariable = $LocalCopy;
             $semaphore->up();
         }
     }

     $thr1->join();
     $thr2->join();
     $thr3->join();

 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.

AAddvvaanncceedd SSeemmaapphhoorreess 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. By default, semaphores are
 created with the counter set to one, "down()" decrements the counter by
 one, and "up()" increments by one. However, we can override any or all of
 these defaults simply by passing in different values:

     use threads;
     use Thread::Semaphore;

     my $semaphore = Thread::Semaphore->new(5);
                     # Creates a semaphore with the counter set to five

     my $thr1 = threads->create(\&sub1);
     my $thr2 = threads->create(\&sub1);

     sub sub1 {
         $semaphore->down(5); # Decrements the counter by five
         # Do stuff here
         $semaphore->up(5); # Increment the counter by five
     }

     $thr1->detach();
     $thr2->detach();

 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, and so "$semaphore->down(0)" is the same as
 "$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
 or 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's 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.

WWaaiittiinngg ffoorr aa CCoonnddiittiioonn The functions “cond_wait()” and “cond_signal()” can be used in conjunction with locks to notify co-operating threads that a resource has become available. They are very similar in use to the functions found in “pthreads”. However for most purposes, queues are simpler to use and more intuitive. See threads::shared for more details.

GGiivviinngg uupp ccoonnttrrooll There are times when you may find it useful to have a thread explicitly give up the CPU to another thread. You may be doing something processor- 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 threads;

     sub loop {
         my $thread = shift;
         my $foo = 50;
         while($foo--) { print("In thread $thread\n"); }
         threads->yield();
         $foo = 50;
         while($foo--) { print("In thread $thread\n"); }
     }

     my $thr1 = threads->create(\&loop, 'first');
     my $thr2 = threads->create(\&loop, 'second');
     my $thr3 = threads->create(\&loop, 'third');

 It is important to remember that "yield()" is only a hint to give up the
 CPU, it depends on your hardware, OS and threading libraries what
 actually happens.  OOnn mmaannyy ooppeerraattiinngg ssyysstteemmss,, yyiieelldd(()) iiss aa nnoo--oopp..
 Therefore it is important to note that one should not build the
 scheduling of the threads around "yield()" calls. It might work on your
 platform but it won't work on another platform.

GGeenneerraall TThhrreeaadd UUttiilliittyy RRoouuttiinneess 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.

WWhhaatt TThhrreeaadd AAmm II IInn?? The “threads->self()” class 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 thread creation.

TThhrreeaadd IIDDss “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. When used as a class method, “threads->tid()” can be used by a thread to get its own TID.

AArree TThheessee TThhrreeaaddss TThhee SSaammee?? The “equal()” method takes two thread objects and returns true if the objects represent the same thread, and false if they don’t.

 Thread objects also have an overloaded "==" comparison so that you can do
 comparison on them as you would with normal objects.

WWhhaatt TThhrreeaaddss AArree RRuunnnniinngg?? “threads->list()” returns a list of thread objects, one for each thread that’s currently running and not detached. Handy for a number of things, including cleaning up at the end of your program (from the main Perl thread, of course):

     # Loop through all the threads
     foreach my $thr (threads->list()) {
         $thr->join();
     }

 If some threads have not finished running when the main Perl thread ends,
 Perl will warn you about it and die, since it is impossible for Perl to
 clean up itself while other threads are running.

 NOTE:  The main Perl thread (thread 0) is in a _d_e_t_a_c_h_e_d state, and so
 does not appear in the list returned by "threads->list()".

AA CCoommpplleettee EExxaammppllee 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
    2 # prime-pthread, courtesy of Tom Christiansen
    3
    4 use v5.36;
    5
    6 use threads;
    7 use Thread::Queue;
    8
    9 sub check_num ($upstream, $cur_prime) {
   10     my $kid;
   11     my $downstream = Thread::Queue->new();
   12     while (my $num = $upstream->dequeue()) {
   13         next unless ($num % $cur_prime);
   14         if ($kid) {
   15             $downstream->enqueue($num);
   16         } else {
   17             print("Found prime: $num\n");
   18             $kid = threads->create(\&check_num, $downstream, $num);
   19             if (! $kid) {
   20                 warn("Sorry.  Ran out of threads.\n");
   21                 last;
   22             }
   23         }
   24     }
   25     if ($kid) {
   26         $downstream->enqueue(undef);
   27         $kid->join();
   28     }
   29 }
   30
   31 my $stream = Thread::Queue->new(3..1000, undef);
   32 check_num($stream, 2);

 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
 into which it funnels numbers that have failed the check.  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 let's 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.  We create a new queue (line 11) and reserve a scalar for the thread
 that we're likely to create later (line 10).

 The while loop from line 12 to line 24 grabs a scalar off the input queue
 and checks against the prime this thread is responsible for.  Line 13
 checks to see if there's a remainder when we divide the number to be
 checked by 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 15) or create a new thread if we
 haven't.

 The new thread creation is line 18.  We pass on to it a reference to the
 queue we've created, and the prime number we've found.  In lines 19
 through 22, we check to make sure that our new thread got created, and if
 not, we stop checking any remaining numbers in the queue.

 Finally, once the loop terminates (because we got a 0 or "undef" in the
 queue, which serves as a note to terminate), we pass on the notice to our
 child, and wait for it to exit if we've created a child (lines 25 and
 28).

 Meanwhile, back in the main thread, we first create a queue (line 31) and
 queue up all the numbers from 3 to 1000 for checking, plus a termination
 notice.  Then all we have to do to get the ball rolling is pass the queue
 and the first prime to the "check_num()" subroutine (line 32).

 That's how it works.  It's pretty simple; as with many Perl programs, the
 explanation is much longer than the program.

DDiiffffeerreenntt iimmpplleemmeennttaattiioonnss ooff tthhrreeaaddss Some background on thread implementations from the operating system viewpoint. 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 "$x = $x + 2" can behave
 unpredictably with kernel threads if $x is visible to other threads, as
 another thread may have changed $x 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.)

 Most modern operating systems support preemptive multitasking nowadays.

PPeerrffoorrmmaannccee ccoonnssiiddeerraattiioonnss The main thing to bear in mind when comparing Perl’s _i_t_h_r_e_a_d_s to other threading models is the fact that for each new thread created, a complete copy of all the variables and data of the parent thread has to be taken. Thus, thread creation can be quite expensive, both in terms of memory usage and time spent in creation. The ideal way to reduce these costs is to have a relatively short number of long-lived threads, all created fairly early on (before the base thread has accumulated too much data). Of course, this may not always be possible, so compromises have to be made. However, after a thread has been created, its performance and extra memory usage should be little different than ordinary code.

 Also note that under the current implementation, shared variables use a
 little more memory and are a little slower than ordinary variables.

PPrroocceessss--ssccooppee CChhaannggeess Note that while threads themselves are separate execution threads and Perl data is thread-private unless explicitly shared, the threads can affect process-scope state, affecting all the threads.

 The most common example of this is changing the current working directory
 using "chdir()".  One thread calls "chdir()", and the working directory
 of all the threads changes.

 Even more drastic example of a process-scope change is "chroot()": the
 root directory of all the threads changes, and no thread can undo it (as
 opposed to "chdir()").

 Further examples of process-scope changes include "umask()" and changing
 uids and gids.

 Thinking of mixing "fork()" and threads?  Please lie down and wait until
 the feeling passes.  Be aware that the semantics of "fork()" vary between
 platforms.  For example, some Unix systems copy all the current threads
 into the child process, while others only copy the thread that called
 "fork()". You have been warned!

 Similarly, mixing signals and threads may be problematic.
 Implementations are platform-dependent, and even the POSIX semantics may
 not be what you expect (and Perl doesn't even give you the full POSIX
 API).  For example, there is no way to guarantee that a signal sent to a
 multi-threaded Perl application will get intercepted by any particular
 thread.  (However, a recently added feature does provide the capability
 to send signals between threads.  See "THREAD SIGNALLING" in threads for
 more details.)

TThhrreeaadd--SSaaffeettyy ooff SSyysstteemm LLiibbrraarriieess Whether various library calls are thread-safe is outside the control of Perl. Calls often suffering from not being thread-safe include: “localtime()”, “gmtime()”, functions fetching user, group and network information (such as “getgrent()”, “gethostent()”, “getnetent()” and so on), “readdir()”, “rand()”, and “srand()”. In general, calls that depend on some global external state.

 If the system Perl is compiled in has thread-safe variants of such calls,
 they will be used.  Beyond that, Perl is at the mercy of the thread-
 safety or -unsafety of the calls.  Please consult your C library call
 documentation.

 On some platforms the thread-safe library interfaces may fail if the
 result buffer is too small (for example the user group databases may be
 rather large, and the reentrant interfaces may have to carry around a
 full snapshot of those databases).  Perl will start with a small buffer,
 but keep retrying and growing the result buffer until the result fits.
 If this limitless growing sounds bad for security or memory consumption
 reasons you can recompile Perl with "PERL_REENTRANT_MAXSIZE" defined to
 the maximum number of bytes you will allow.

CCoonncclluussiioonn A complete thread tutorial could fill a book (and has, many times), but with what we’ve covered in this introduction, you should be well on your way to becoming a threaded Perl expert.

SSEEEE AALLSSOO #

 Annotated POD for threads:
 <https://web.archive.org/web/20171028020148/http://annocpan.org/?mode=search&field=Module&name=threads>

 Latest version of threads on CPAN: <https://metacpan.org/pod/threads>

 Annotated POD for threads::shared:
 <https://web.archive.org/web/20171028020148/http://annocpan.org/?mode=search&field=Module&name=threads%3A%3Ashared>

 Latest version of threads::shared on CPAN:
 <https://metacpan.org/pod/threads::shared>

 Perl threads mailing list: <https://lists.perl.org/list/ithreads.html>

BBiibblliiooggrraapphhyy Here’s a short bibliography courtesy of Jürgen Christoffel:

IInnttrroodduuccttoorryy TTeexxttss Birrell, Andrew D. An Introduction to Programming with Threads. Digital Equipment Corporation, 1989, DEC-SRC Research Report #35 online as https://www.hpl.hp.com/techreports/Compaq-DEC/SRC-RR-35.pdf (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).

OOSS--RReellaatteedd RReeffeerreenncceess 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 0-13-219908-4 (great textbook).

 Silberschatz, Abraham, and Peter B. Galvin. Operating System Concepts,
 4th ed. Addison-Wesley, 1995, ISBN 0-201-59292-4

OOtthheerr RReeffeerreenncceess Arnold, Ken and James Gosling. The Java Programming Language, 2nd ed. Addison-Wesley, 1998, ISBN 0-201-31006-6.

 comp.programming.threads FAQ,
 <http://www.serpentine.com/~bos/threads-faq/>

 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).

 Artur Bergman, "Where Wizards Fear To Tread", June 11, 2002,
 <http://www.perl.com/pub/a/2002/06/11/threads.html>

AAcckknnoowwlleeddggeemmeennttss 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.

AAUUTTHHOORR #

 Dan Sugalski <dan@sidhe.org>

 Slightly modified by Arthur Bergman to fit the new thread model/module.

 Reworked slightly by Jörg Walter <jwalt@cpan.org> to be more concise
 about thread-safety of Perl code.

 Rearranged slightly by Elizabeth Mattijsen <liz@dijkmat.nl> to put less
 emphasis on yyiieelldd(()).

CCooppyyrriigghhttss The original version of 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.

perl v5.36.3 2023-02-15 PERLTHRTUT(1)