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perlothrtut - old tutorial on threads in Perl
For information about the new interpreter threads (``ithreads'') model, see the perlthrtut tutorial, and the threads and threads::shared modules.
You are strongly encouraged to migrate any existing threads code to the new model as soon as possible.
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.
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.
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.
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.)
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 "$a = $a + 2" can behave unpredictably with kernel threads if $a is visible to other threads, as another thread may have changed $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.)
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.
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
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.
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 "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.
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" }
};
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.
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.
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.
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 "my") you're probably sharing them between threads.
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.
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.
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.
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.
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.
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.
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.
sub test_sub :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 :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 "locked" attribute tells perl to lock sync_sub(), and if you run this, you can see that only one thread is in it at any one time.
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 [@_], $class;
}
sub per_object :locked :method {
my ($class, $thrnum) = @_;
print "In per_object for thread $thrnum\n";
yield;
sleep 2;
print "Exiting per_object for thread $thrnum\n";
}
sub one_at_a_time :locked {
my ($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.
lock(\&sub_to_lock);
Simple enough. Unlike the "locked" attribute, 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 the "locked" attribute, 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{'usethreads'} }
sub sub1 { lock(\&sub1) if $Running_Threaded }
This way you can ensure single-threadedness regardless of which version of Perl you're running.
# 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.
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.
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).
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
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).
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