NAME¶
perlthrtut - Tutorial on threads in Perl
DESCRIPTION¶
This tutorial describes the use of Perl interpreter threads (sometimes referred
to as
ithreads) that was first introduced in Perl 5.6.0. 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
ithreads uses
the threads class.
NOTE: 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.
What Is A Thread Anyway?¶
A thread is a flow of control through a program with a single execution point.
Sounds an awful lot like a process, doesn't it? Well, it should. Threads are one
of the pieces of a process. Every process has at least one thread and, up
until now, every process running Perl had only one thread. With 5.8, though,
you can create extra threads. We're going to show you how, when, and why.
Threaded Program Models¶
There are three basic ways that you can structure a threaded program. Which
model you choose depends on what you need your program to do. For many
non-trivial threaded programs, you'll need to choose different models for
different pieces of your program.
Boss/Worker¶
The boss/worker model usually has one
boss thread and one or more
worker threads. The boss thread gathers or generates tasks that need to
be done, then parcels those tasks out to the appropriate worker thread.
This model is common in GUI and server programs, where a main thread waits for
some event and then passes that event to the appropriate worker threads for
processing. Once the event has been passed on, the boss thread goes back to
waiting for another event.
The boss thread does relatively little work. While tasks aren't necessarily
performed faster than with any other method, it tends to have the best
user-response times.
Work Crew¶
In the work crew model, several threads are created that do essentially the same
thing to different pieces of data. It closely mirrors classical parallel
processing and vector processors, where a large array of processors do the
exact same thing to many pieces of data.
This model is particularly useful if the system running the program will
distribute multiple threads across different processors. It can also be useful
in ray tracing or rendering engines, where the individual threads can pass on
interim results to give the user visual feedback.
Pipeline¶
The pipeline model divides up a task into a series of steps, and passes the
results of one step on to the thread processing the next. Each thread does one
thing to each piece of data and passes the results to the next thread in line.
This model makes the most sense if you have multiple processors so two or more
threads will be executing in parallel, though it can often make sense in other
contexts as well. It tends to keep the individual tasks small and simple, as
well as allowing some parts of the pipeline to block (on I/O or system calls,
for example) while other parts keep going. If you're running different parts
of the pipeline on different processors you may also take advantage of the
caches on each processor.
This model is also handy for a form of recursive programming where, rather than
having a subroutine call itself, it instead creates another thread. Prime and
Fibonacci generators both map well to this form of the pipeline model. (A
version of a prime number generator is presented later on.)
What kind of threads are Perl threads?¶
If you have experience with other thread implementations, you might find that
things aren't quite what you expect. It's very important to remember when
dealing with Perl threads that
Perl Threads Are Not X Threads
for all values of X. They aren't POSIX threads, or DecThreads, or Java's Green
threads, or Win32 threads. There are similarities, and the broad concepts are
the same, but if you start looking for implementation details you're going to
be either disappointed or confused. Possibly both.
This is not to say that Perl threads are completely different from everything
that's ever come before. They're not. Perl's threading model owes a lot to
other thread models, especially POSIX. Just as Perl is not C, though, Perl
threads are not POSIX threads. So if you find yourself looking for mutexes, or
thread priorities, it's time to step back a bit and think about what you want
to do and how Perl can do it.
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.
Perl Threads Are Different.
Thread-Safe Modules¶
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".
Thread Basics¶
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.
Basic Thread Support¶
Thread support is a Perl compile-time option. It's something that's turned on or
off when Perl is built at your site, rather than when your programs are
compiled. If your Perl wasn't compiled with thread support enabled, then any
attempt to use threads will fail.
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.
A Note about the Examples¶
In a real situation, care should be taken that all threads are finished
executing before the program exits. That care has
not been taken in
these examples in the interest of simplicity. Running these examples
as
is 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.
Creating Threads¶
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 $thr3 = threads->create(\&sub1, qw(Param1 Param2 Param3));
sub sub1 {
my @InboundParameters = @_;
print("In the thread\n");
print('Got parameters >', join('<>', @InboundParameters), "<\n");
}
The last example illustrates another feature of threads. You can spawn off
several threads using the same subroutine. Each thread executes the same
subroutine, but in a separate thread with a separate environment and
potentially separate arguments.
"new()" is a synonym for "create()".
Waiting For A Thread To Exit¶
Since threads are also subroutines, they can return values. To wait for a thread
to exit and extract any values it might return, you can use the
"join()" method:
use threads;
my ($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->
join()" in threads and
"THREAD CONTEXT" in threads for more details on thread context and
return values.
Ignoring A Thread¶
"join()" does three things: it waits for a thread to exit, cleans up
after it, and returns any data the thread may have produced. But what if
you're not interested in the thread's return values, and you don't really care
when the thread finishes? All you want is for the thread to get cleaned up
after when it's done.
In this case, you use the "detach()" method. Once a thread is
detached, it'll run until it's finished; then Perl will clean up after it
automatically.
use 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 {
$a = 0;
while (1) {
$a++;
print("\$a is $a\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
}
Process and Thread Termination¶
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
all running threads.
die() and
exit() 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.
Threads And Data¶
Now that we've covered the basics of threads, it's time for our next topic:
Data. Threading introduces a couple of complications to data access that
non-threaded programs never need to worry about.
Shared And Unshared Data¶
The biggest difference between Perl
ithreads 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.
Thread Pitfalls: Races¶
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 $a :shared = 1;
my $thr1 = threads->create(\&sub1);
my $thr2 = threads->create(\&sub2);
$thr1->join();
$thr2->join();
print("$a\n");
sub sub1 { my $foo = $a; $a = $foo + 1; }
sub sub2 { my $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 threads;
my $a :shared = 2;
my $b :shared;
my $c :shared;
my $thr1 = threads->create(sub { $b = $a; $a = $b + 1; });
my $thr2 = threads->create(sub { $c = $a; $a = $c + 1; });
$thr1->join();
$thr2->join();
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 $c could be 2 or 3.
Even "$a += 5" or "$a++" 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.
Synchronization and control¶
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.
Controlling access: lock()¶
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.
A Thread Pitfall: Deadlocks¶
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 $a :shared = 4;
my $b :shared = 'foo';
my $thr1 = threads->create(sub {
lock($a);
sleep(20);
lock($b);
});
my $thr2 = threads->create(sub {
lock($b);
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 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 $a, then, after a pause during which the
second thread has probably had time to do some work, 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.
The other synchronization primitives described below can suffer from similar
problems.
Queues: Passing Data Around¶
A queue is a special thread-safe object that lets you put data in one end and
take it out the other without having to worry about synchronization issues.
They're pretty straightforward, and look like this:
use 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.
Semaphores: Synchronizing Data Access¶
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
lock
at any one time.
Basic semaphores¶
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.
Advanced Semaphores¶
By default, semaphores behave like locks, letting only one thread
"down()" them at a time. However, there are other uses for
semaphores.
Each semaphore has a counter attached to it. 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.
Waiting for a Condition¶
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.
Giving up control¶
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.
On many operating systems, yield() is a
no-op. 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.
General Thread Utility Routines¶
We've covered the workhorse parts of Perl's threading package, and with these
tools you should be well on your way to writing threaded code and packages.
There are a few useful little pieces that didn't really fit in anyplace else.
What Thread Am I In?¶
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.
Thread IDs¶
"tid()" is a thread object method that returns the thread ID of the
thread the object represents. Thread IDs are integers, with the main thread in
a program being 0. Currently Perl assigns a unique TID to every thread ever
created in your program, assigning the first thread to be created a TID of 1,
and increasing the TID by 1 for each new thread that's created. When used as a
class method, "threads->tid()" can be used by a thread to get its
own TID.
Are These Threads The Same?¶
The "equal()" method takes two thread objects and returns true if the
objects represent the same thread, and false if they don't.
Thread objects also have an overloaded "==" comparison so that you can
do comparison on them as you would with normal objects.
What Threads Are Running?¶
"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()) {
$thr->join();
}
If some threads have not finished running when the main Perl thread ends, Perl
will warn you about it and die, since it is impossible for Perl to clean up
itself while other threads are running.
NOTE: The main Perl thread (thread 0) is in a
detached state, and so does
not appear in the list returned by "threads->list()".
A Complete Example¶
Confused yet? It's time for an example program to show some of the things we've
covered. This program finds prime numbers using threads.
1 #!/usr/bin/perl
2 # prime-pthread, courtesy of Tom Christiansen
3
4 use strict;
5 use warnings;
6
7 use threads;
8 use Thread::Queue;
9
10 sub check_num {
11 my ($upstream, $cur_prime) = @_;
12 my $kid;
13 my $downstream = Thread::Queue->new();
14 while (my $num = $upstream->dequeue()) {
15 next unless ($num % $cur_prime);
16 if ($kid) {
17 $downstream->enqueue($num);
18 } else {
19 print("Found prime: $num\n");
20 $kid = threads->create(\&check_num, $downstream, $num);
21 if (! $kid) {
22 warn("Sorry. Ran out of threads.\n");
23 last;
24 }
25 }
26 }
27 if ($kid) {
28 $downstream->enqueue(undef);
29 $kid->join();
30 }
31 }
32
33 my $stream = Thread::Queue->new(3..1000, undef);
34 check_num($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. After pulling in the input queue and the prime that the subroutine is
checking (line 11), we create a new queue (line 13) and reserve a scalar for
the thread that we're likely to create later (line 12).
The while loop from line 14 to line 26 grabs a scalar off the input queue and
checks against the prime this thread is responsible for. Line 15 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 17) or
create a new thread if we haven't.
The new thread creation is line 20. We pass on to it a reference to the queue
we've created, and the prime number we've found. In lines 21 through 24, 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 27 and 30).
Meanwhile, back in the main thread, we first create a queue (line 33) 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 34).
That's how it works. It's pretty simple; as with many Perl programs, the
explanation is much longer than the program.
Different implementations of threads¶
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 "$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.)
Most modern operating systems support preemptive multitasking nowadays.
The main thing to bear in mind when comparing Perl's
ithreads 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.
Process-scope Changes¶
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.)
Thread-Safety of System Libraries¶
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.
Conclusion¶
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.
SEE ALSO¶
Annotated POD for threads:
<
http://annocpan.org/?mode=search&field=Module&name=threads>
Latest version of threads on CPAN:
<
http://search.cpan.org/search?module=threads>
Annotated POD for threads::shared:
<
http://annocpan.org/?mode=search&field=Module&name=threads%3A%3Ashared>
Latest version of threads::shared on CPAN:
<
http://search.cpan.org/search?module=threads%3A%3Ashared>
Perl threads mailing list:
<
http://lists.cpan.org/showlist.cgi?name=iThreads>
Bibliography¶
Here's a short bibliography courtesy of Juergen Christoffel:
Introductory Texts¶
Birrell, Andrew D. An Introduction to Programming with Threads. Digital
Equipment Corporation, 1989, DEC-SRC Research Report #35 online as
ftp://ftp.dec.com/pub/DEC/SRC/research-reports/SRC-035.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).
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
Other References¶
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/
<
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>
Acknowledgements¶
Thanks (in no particular order) to Chaim Frenkel, Steve Fink, Gurusamy Sarathy,
Ilya Zakharevich, Benjamin Sugars, Juergen 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.
AUTHOR¶
Dan Sugalski <dan@sidhe.org<gt>
Slightly modified by Arthur Bergman to fit the new thread model/module.
Reworked slightly by Joerg Walter <jwalt@cpan.org<gt> to be more
concise about thread-safety of Perl code.
Rearranged slightly by Elizabeth Mattijsen <liz@dijkmat.nl<gt> to put
less emphasis on
yield().
Copyrights¶
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.
