PERLOTHRTUT(1) Perl Programmers Reference Guide PERLOTHRTUT(1)NAMEperlothrtut - old tutorial on threads in Perl
DESCRIPTION
WARNING: This tutorial describes the old-style thread model
that was introduced in release 5.005. This model is now
deprecated, and will be removed, probably in version 5.10.
The interfaces described here were considered experimental,
and are likely to be buggy.
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.
What Is A Thread Anyway?
A thread is a flow of control through a program with a sin-
gle execution point.
Sounds an awful lot like a process, doesn't it? Well, it
should. Threads are one of the pieces of a process. Every
process has at least one thread and, up until now, every
process running Perl had only one thread. With 5.005,
though, you can create extra threads. We're going to show
you how, when, and why.
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 gen-
erates 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 wait-
ing 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.
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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 render-
ing 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 process-
ing 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 proces-
sors 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 dif-
ferent 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 genera-
tors both map well to this form of the pipeline model. (A
version of a prime number generator is presented later on.)
Native threads
There are several different ways to implement threads on a
system. How threads are implemented depends both on the
vendor and, in some cases, the version of the operating sys-
tem. Often the first implementation will be relatively sim-
ple, but later versions of the OS will be more sophisti-
cated.
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.
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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 pro-
cess 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 syn-
chronization 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 implementa-
tions 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
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yield function, it gives up control. It also gives up con-
trol 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 usu-
ally won't monopolize the CPU.
On some systems, there can be cooperative and preemptive
threads running simultaneously. (Threads running with real-
time priorities often behave cooperatively, for example,
while threads running at normal priorities behave preemp-
tively.)
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 look-
ing for implementation details you're going to be either
disappointed or confused. Possibly both.
This is not to say that Perl threads are completely dif-
ferent 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.
Threadsafe Modules
The addition of threads has changed Perl's internals sub-
stantially. There are implications for people who write
modules--especially modules with XS code or external
libraries. While most modules won't encounter any problems,
modules that aren't explicitly tagged as thread-safe should
be tested before being used in production code.
Not all modules that you might use are thread-safe, and you
should always assume a module is unsafe unless the documen-
tation says otherwise. This includes modules that are dis-
tributed as part of the core. Threads are a beta feature,
and even some of the standard modules aren't thread-safe.
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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
Thread Basics
The core Thread module provides the basic functions you need
to write threaded programs. In the following sections we'll
cover the basics, showing you what you need to do to create
a threaded program. After that, we'll go over some of the
features of the Thread module that make threaded programming
easier.
Basic Thread Support
Thread support is a Perl compile-time option-it's something
that's turned on or off when Perl is built at your site,
rather than when your programs are compiled. If your Perl
wasn't compiled with thread support enabled, then any
attempt to use threads will fail.
Remember that the threading support in 5.005 is in beta
release, and should be treated as such. You should expect
that it may not function entirely properly, and the thread
interface may well change some before it is a fully sup-
ported, 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;
}
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Since code that runs both with and without threads is usu-
ally 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.
Creating Threads
The Thread package provides the tools you need to create new
threads. Like any other module, you need to tell Perl you
want to use it; use Thread imports all the pieces you need
to create basic threads.
The simplest, straightforward way to create a thread is with
new():
use Thread;
$thr = new Thread \&sub1;
sub sub1 {
print "In the thread\n";
}
The new() method takes a reference to a subroutine and
creates a new thread, which starts executing in the refer-
enced subroutine. Control then passes both to the subrou-
tine and the caller.
If you need to, your program can pass parameters to the sub-
routine 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
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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 semi-
colon 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 synchroniza-
tion techniques are covered later.
Giving up control
There are times when you may find it useful to have a thread
explicitly give up the CPU to another thread. Your thread-
ing package might not support preemptive multitasking for
threads, for example, or you may be doing something
compute-intensive and want to make sure that the user-
interface thread gets called frequently. Regardless, there
are times that you might want a thread to give up the pro-
cessor.
Perl's threading package provides the yield() function that
does this. yield() is pretty straightforward, and works like
this:
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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" }
};
Waiting For A Thread To Exit
Since threads are also subroutines, they can return values.
To wait for a thread to exit and extract any scalars it
might return, you can use the join() method.
use Thread;
$thr = new Thread \&sub1;
@ReturnData = $thr->join;
print "Thread returned @ReturnData";
sub sub1 { return "Fifty-six", "foo", 2; }
In the example above, the join() method returns as soon as
the thread ends. In addition to waiting for a thread to
finish and gathering up any values that the thread might
have returned, join() also performs any OS cleanup necessary
for the thread. That cleanup might be important, especially
for long-running programs that spawn lots of threads. If
you don't want the return values and don't want to wait for
the thread to finish, you should call the detach() method
instead. detach() is covered later in the article.
Errors In Threads
So what happens when an error occurs in a thread? Any errors
that could be caught with eval() are postponed until the
thread is joined. If your program never joins, the errors
appear when your program exits.
Errors deferred until a join() can be caught with eval():
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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 unmo-
dified, so if you want the return value of the thread, this
is your only chance to get them.
Ignoring A Thread
join() does three things: it waits for a thread to exit,
cleans up after it, and returns any data the thread may have
produced. But what if you're not interested in the thread's
return values, and you don't really care when the thread
finishes? All you want is for the thread to get cleaned up
after when it's done.
In this case, you use the detach() method. Once a thread is
detached, it'll run until it's finished, then Perl will
clean up after it automatically.
use Thread;
$thr = new Thread \&sub1; # Spawn the thread
$thr->detach; # Now we officially don't care any more
sub sub1 {
$a = 0;
while (1) {
$a++;
print "\$a is $a\n";
sleep 1;
}
}
Once a thread is detached, it may not be joined, and any
output that it might have produced (if it was done and wait-
ing for a join) is lost.
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 com-
plications to data access that non-threaded programs never
need to worry about.
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Shared And Unshared Data
The single most important thing to remember when using
threads is that all threads potentially have access to all
the data anywhere in your program. While this is true with
a nonthreaded Perl program as well, it's especially impor-
tant to remember with a threaded program, since more than
one thread can be accessing this data at once.
Perl's scoping rules don't change because you're using
threads. If a subroutine (or block, in the case of async())
could see a variable if you weren't running with threads, it
can see it if you are. This is especially important for the
subroutines that create, and makes "my" variables even more
important. Remember--if your variables aren't lexically
scoped (declared with "my") you're probably sharing them
between threads.
Thread Pitfall: Races
While threads bring a new set of useful tools, they also
bring a number of pitfalls. One pitfall is the race condi-
tion:
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 vari-
able $a, once to read and once to write. Depending on fac-
tors 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; };
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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.
Controlling access: lock()
The lock() function takes a variable (or subroutine, but
we'll get to that later) and puts a lock on it. No other
thread may lock the variable until the locking thread exits
the innermost block containing the lock. Using lock() is
straightforward:
use Thread qw(async);
$a = 4;
$thr1 = async {
$foo = 12;
{
lock ($a); # Block until we get access to $a
$b = $a;
$a = $b * $foo;
}
print "\$foo was $foo\n";
};
$thr2 = async {
$bar = 7;
{
lock ($a); # Block until we can get access to $a
$c = $a;
$a = $c * $bar;
}
print "\$bar was $bar\n";
};
$thr1->join;
$thr2->join;
print "\$a is $a\n";
lock() blocks the thread until the variable being locked is
available. When lock() returns, your thread can be sure
that no other thread can lock that variable until the inner-
most 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 pro-
gramming, and the advisory file locking that flock() gives
you. Locked subroutines behave differently, however. We'll
cover that later in the article.
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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.
Thread Pitfall: Deadlocks
Locks are a handy tool to synchronize access to data. Using
them properly is the key to safe shared data. Unfor-
tunately, locks aren't without their dangers. Consider the
following code:
use Thread qw(async yield);
$a = 4;
$b = "foo";
async {
lock($a);
yield;
sleep 20;
lock ($b);
};
async {
lock($b);
yield;
sleep 20;
lock ($a);
};
This program will probably hang until you kill it. The only
way it won't hang is if one of the two async() routines
acquires both locks first. A guaranteed-to-hang version is
more complicated, but the principle is the same.
The first thread spawned by async() will grab a lock on $a
then, a second or two later, try to grab a lock on $b.
Meanwhile, the second thread grabs a lock on $b, then later
tries to grab a lock on $a. The second lock attempt for
both threads will block, each waiting for the other to
release its lock.
This condition is called a deadlock, and it occurs whenever
two or more threads are trying to get locks on resources
that the others own. Each thread will block, waiting for
the other to release a lock on a resource. That never hap-
pens, though, since the thread with the resource is itself
waiting for a lock to be released.
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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.
Queues: Passing Data Around
A queue is a special thread-safe object that lets you put
data in one end and take it out the other without having to
worry about synchronization issues. They're pretty
straightforward, and look like this:
use Thread qw(async);
use Thread::Queue;
my $DataQueue = new Thread::Queue;
$thr = async {
while ($DataElement = $DataQueue->dequeue) {
print "Popped $DataElement off the queue\n";
}
};
$DataQueue->enqueue(12);
$DataQueue->enqueue("A", "B", "C");
$DataQueue->enqueue(\$thr);
sleep 10;
$DataQueue->enqueue(undef);
You create the queue with new Thread::Queue. Then you can
add lists of scalars onto the end with enqueue(), and pop
scalars off the front of it with dequeue(). A queue has no
fixed size, and can grow as needed to hold everything pushed
on to it.
If a queue is empty, dequeue() blocks until another thread
enqueues something. This makes queues ideal for event loops
and other communications between threads.
Threads And Code
In addition to providing thread-safe access to data via
locks and queues, threaded Perl also provides general-
purpose semaphores for coarser synchronization than locks
provide and thread-safe access to entire subroutines.
Semaphores: Synchronizing Data Access
Semaphores are a kind of generic locking mechanism. Unlike
lock, which gets a lock on a particular scalar, Perl doesn't
associate any particular thing with a semaphore so you can
use them to control access to anything you like. In
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addition, semaphores can allow more than one thread to
access a resource at once, though by default semaphores only
allow one thread access at a time.
Basic semaphores
Semaphores have two methods, down and up. down decre-
ments the resource count, while up increments it. down
calls will block if the semaphore's current count would
decrement below zero. This program gives a quick
demonstration:
use Thread qw(yield);
use Thread::Semaphore;
my $semaphore = new Thread::Semaphore;
$GlobalVariable = 0;
$thr1 = new Thread \&sample_sub, 1;
$thr2 = new Thread \&sample_sub, 2;
$thr3 = new Thread \&sample_sub, 3;
sub sample_sub {
my $SubNumber = shift @_;
my $TryCount = 10;
my $LocalCopy;
sleep 1;
while ($TryCount--) {
$semaphore->down;
$LocalCopy = $GlobalVariable;
print "$TryCount tries left for sub $SubNumber (\$GlobalVariable is $GlobalVariable)\n";
yield;
sleep 2;
$LocalCopy++;
$GlobalVariable = $LocalCopy;
$semaphore->up;
}
}
The three invocations of the subroutine all operate in
sync. The semaphore, though, makes sure that only one
thread is accessing the global variable at once.
Advanced Semaphores
By default, semaphores behave like locks, letting only
one thread down() them at a time. However, there are
other uses for semaphores.
Each semaphore has a counter attached to it. down()
decrements the counter and up() increments the counter.
By default, semaphores are created with the counter set
to one, down() decrements by one, and up() increments by
one. If down() attempts to decrement the counter below
zero, it blocks until the counter is large enough. Note
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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 use-
ful 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 chan-
nels, 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.
Attributes: Restricting Access To Subroutines
In addition to synchronizing access to data or resources,
you might find it useful to synchronize access to subrou-
tines. You may be accessing a singular machine resource
(perhaps a vector processor), or find it easier to serialize
calls to a particular subroutine than to have a set of locks
and semaphores.
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 attri-
butes are used in the compilation phase of your program so
you can't change a subroutine's behavior while your program
is actually running.
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Subroutine Locks
The basic subroutine lock looks like this:
sub test_sub :locked {
}
This ensures that only one thread will be executing this
subroutine at any one time. Once a thread calls this sub-
routine, 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.
Methods
Locking an entire subroutine can sometimes be overkill,
especially when dealing with Perl objects. When calling a
method for an object, for example, you want to serialize
calls to a method, so that only one thread will be in the
subroutine for a particular object, but threads calling that
subroutine for a different object aren't blocked. The
method attribute indicates whether the subroutine is really
a method.
use Thread;
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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() simultane-
ously, but only one thread is ever in one_at_a_time() at
once.
Locking A Subroutine
You can lock a subroutine as you would lock a variable.
Subroutine locks work the same as specifying a "locked"
attribute for the subroutine, and block all access to the
subroutine for other threads until the lock goes out of
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scope. When the subroutine isn't locked, any number of
threads can be in it at once, and getting a lock on a sub-
routine doesn't affect threads already in the subroutine.
Getting a lock on a subroutine looks like this:
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 run-
time 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.
General Thread Utility Routines
We've covered the workhorse parts of Perl's threading pack-
age, 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 Thread->self method provides your program with a way to
get an object representing the thread it's currently in.
You can use this object in the same way as the ones returned
from the thread creation.
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
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thread that's created.
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.
What Threads Are Running?
Thread->list returns a list of thread objects, one for each
thread that's currently running. Handy for a number of
things, including cleaning up at the end of your program:
# Loop through all the threads
foreach $thr (Thread->list) {
# Don't join the main thread or ourselves
if ($thr->tid && !Thread::equal($thr, Thread->self)) {
$thr->join;
}
}
The example above is just for illustration. It isn't
strictly necessary to join all the threads you create, since
Perl detaches all the threads before it exits.
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.
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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)
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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 ter-
minate (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.
Conclusion
A complete thread tutorial could fill a book (and has, many
times), but this should get you well on your way. The final
authority on how Perl's threads behave is the documentation
bundled with the Perl distribution, but with what we've
covered in this article, you should be well on your way to
becoming a threaded Perl expert.
Bibliography
Here's a short bibliography courtesy of J|rgen Christoffel:
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Introductory Texts
Birrell, Andrew D. An Introduction to Programming with
Threads. Digital Equipment Corporation, 1989, DEC-SRC
Research Report #35 online as
http://www.research.digital.com/SRC/staff/birrell/bib.html
(highly recommended)
Robbins, Kay. A., and Steven Robbins. Practical Unix Pro-
gramming: A Guide to Concurrency, Communication, and Mul-
tithreading. 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 Far-
rell. Pthreads Programming. O'Reilly & Associates, 1996,
ISBN 156592-115-1 (covers POSIX threads).
OS-Related References
Boykin, Joseph, David Kirschen, Alan Langerman, and Susan
LoVerso. Programming under Mach. Addison-Wesley, 1994, ISBN
0-201-52739-1.
Tanenbaum, Andrew S. Distributed Operating Systems. Prentice
Hall, 1995, ISBN 0-13-219908-4 (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.
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).
Acknowledgements
Thanks (in no particular order) to Chaim Frenkel, Steve
Fink, Gurusamy Sarathy, Ilya Zakharevich, Benjamin Sugars,
J|rgen Christoffel, Joshua Pritikin, and Alan Burlison, for
their help in reality-checking and polishing this article.
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Big thanks to Tom Christiansen for his rewrite of the prime
number generator.
AUTHOR
Dan Sugalski <sugalskd@ous.edu>
Copyrights
This article originally appeared in The Perl Journal #10,
and is copyright 1998 The Perl Journal. It appears courtesy
of Jon Orwant and The Perl Journal. This document may be
distributed under the same terms as Perl itself.
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