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PERLOTHRTUT(1)
NAME
perlothrtut - 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 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
5.005, 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 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.)
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 system. Often the first implementation will be
relatively simple, but later versions of the OS will be more sophisticated.
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.)
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.
Threadsafe Modules
The addition of threads has changed Perl's internals substantially. 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 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
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 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.
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 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.
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 threading 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 processor.
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" }
};
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():
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.
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 waiting 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 complications to data access that
non-threaded programs never need to worry about.
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
important 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 condition:
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.
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 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.
Thread Pitfall: Deadlocks
Locks are a handy tool to synchronize access to data. Using them properly
is the key to safe shared data. Unfortunately, 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 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.
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 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 decrements 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 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.
Attributes: Restricting Access To Subroutines
In addition to synchronizing access to data or resources, you might find it
useful to synchronize access to subroutines. 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 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.
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 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.
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;
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.
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 scope. When the subroutine isn't locked, any number of threads can
be in it at once, and getting a lock on a subroutine 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 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.
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 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 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.
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.
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 Jrgen Christoffel:
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 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).
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, Jrgen 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 <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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