PERLTHRTUT(1) Perl Programmers Reference Guide PERLTHRTUT(1)NAMEperlthrtut - tutorial on threads in Perl
DESCRIPTION
WARNING: Threading is an experimental feature. Both the interface
and implementation are subject to change drastically. In fact, this
documentation describes the flavor of threads that was in version
5.005. Perl 5.6.0 and later have the beginnings of support for
interpreter threads, which (when finished) is expected to be
significantly different from what is described here. The information
contained here may therefore soon be obsolete. Use at your own risk!
One of the most prominent new features of Perl 5.005 is
the inclusion of threads. Threads make a number of things
a lot easier, and are a very useful addition to your bag
of programming tricks.
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 vec
tor 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 trac
ing 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 pro
cessors so two or more threads will be executing in paral
lel, 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 program
ming 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 sophis
ticated.
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 pro
gram 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, regard
less 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 ker
nel 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 nag
ging 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 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 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 multi
tasking implementation, one thread can starve all the oth
ers for CPU time if it so chooses.
Preemptive multitasking systems interrupt threads at regu
lar 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 exam
ple, 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 val
ues of X. They aren't POSIX threads, or DecThreads, or
Java's Green threads, or Win32 threads. There are simi
larities, 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 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 your
self 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 prob
lems, 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 sec
tions 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 some
thing 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:
$Config{usethreads} or die "Recompile Perl with threads to run this program.";
A possibly-threaded program using a possibly-threaded mod
ule might have code like this:
use Config;
use MyMod;
if ($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 usu
ally pretty messy, it's best to isolate the thread-spe
cific 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
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 subrou
tine. Each thread executes the same subroutine, but in a
separate thread with a separate environment and poten
tially 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 exam
ple. 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 care
ful with any shared resources. Locking and other synchro
nization 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 multitask
ing for threads, for example, or you may be doing some
thing 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 val
ues. 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 neces
sary 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 vari
ables 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 con
dition:
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 schedul
ing 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 possi
bility 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 coor
dinate 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, how
ever. We'll cover that later in the article.
You may lock arrays and hashes as well as scalars. Lock
ing 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. Con
sider 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() rou
tines 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 when
ever 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 vari
ables $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-pur
pose 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 any
thing 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 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 that while a semaphore can be cre
ated 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 draw
ing.
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 writ
ing 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 subrou
tines. You may be accessing a singular machine resource
(perhaps a vector processor), or find it easier to serial
ize 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 sev
eral 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 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;
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() simulta
neously, 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 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
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 seri
alized 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 any
place 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 inte
gers, with the main thread in a program being 0. Cur
rently Perl assigns a unique tid to every thread ever cre
ated 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 pro
gram:
# 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 num
bers 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 num
ber. 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() subrou
tine, 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 check
ing (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 Christof
fel:
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.digi
tal.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
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. Pren
tice Hall, 1995, ISBN 0-13-219908-4 (great textbook).
Silberschatz, Abraham, and Peter B. Galvin. Operating Sys
tem Concepts, 4th ed. Addison-Wesley, 1995, ISBN
0-201-59292-4
Other References
Arnold, Ken and James Gosling. The Java Programming Lan
guage, 2nd ed. Addison-Wesley, 1998, ISBN 0-201-31006-6.
Le Sergent, T. and B. Berthomieu. "Incremental Multi
Threaded Garbage Collection on Virtually Shared Memory
Architectures" in Memory Management: Proc. of the Interna
tional 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 cour
tesy of Jon Orwant and The Perl Journal. This document
may be distributed under the same terms as Perl itself.
2001-03-18 perl v5.6.1 PERLTHRTUT(1)
