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PERLTHRTUT(1)
NAME
perlthrtut - tutorial on threads in Perl
DESCRIPTION
NOTE: this tutorial describes the new Perl threading flavour introduced in
Perl 5.6.0 called interpreter threads, or ithreads for short. In this
model each thread runs in its own Perl interpreter, and any data sharing
between threads must be explicit.
There is another older Perl threading flavour called the 5.005 model,
unsurprisingly for 5.005 versions of Perl. The old model is known to have
problems, deprecated, and will probably be removed around release 5.10. You
are strongly encouraged to migrate any existing 5.005 threads code to the
new model as soon as possible.
You can see which (or neither) threading flavour you have by running "perl
-V" and looking at the "Platform" section. If you have
"useithreads=define" you have ithreads, if you have "use5005threads=define"
you have 5.005 threads. If you have neither, you don't have any thread
support built in. If you have both, you are in trouble.
The user-level interface to the 5.005 threads was via the Threads class,
while ithreads uses the threads class. Note the change in case.
Status
The ithreads code has been available since Perl 5.6.0, and is considered
stable. The user-level interface to ithreads (the threads classes) appeared
in the 5.8.0 release, and as of this time is considered stable although it
should be treated with caution as with all new features.
What Is A Thread Anyway?
A thread is a flow of control through a program with a single execution
point.
Sounds an awful lot like a process, doesn't it? Well, it should. Threads
are one of the pieces of a process. Every process has at least one thread
and, up until now, every process running Perl had only one thread. With
5.8, though, you can create extra threads. We're going to show you how,
when, and why.
Threaded Program Models
There are three basic ways that you can structure a threaded program.
Which model you choose depends on what you need your program to do. For
many non-trivial threaded programs you'll need to choose different models
for different pieces of your program.
Boss/Worker
The boss/worker model usually has one `boss' thread and one or more
`worker' threads. The boss thread gathers or generates tasks that need to
be done, then parcels those tasks out to the appropriate worker thread.
This model is common in GUI and server programs, where a main thread waits
for some event and then passes that event to the appropriate worker threads
for processing. Once the event has been passed on, the boss thread goes
back to waiting for another event.
The boss thread does relatively little work. While tasks aren't
necessarily performed faster than with any other method, it tends to have
the best user-response times.
Work Crew
In the work crew model, several threads are created that do essentially the
same thing to different pieces of data. It closely mirrors classical
parallel processing and vector processors, where a large array of
processors do the exact same thing to many pieces of data.
This model is particularly useful if the system running the program will
distribute multiple threads across different processors. It can also be
useful in ray tracing or rendering engines, where the individual threads
can pass on interim results to give the user visual feedback.
Pipeline
The pipeline model divides up a task into a series of steps, and passes the
results of one step on to the thread processing the next. Each thread does
one thing to each piece of data and passes the results to the next thread
in line.
This model makes the most sense if you have multiple processors so two or
more threads will be executing in parallel, though it can often make sense
in other contexts as well. It tends to keep the individual tasks small and
simple, as well as allowing some parts of the pipeline to block (on I/O or
system calls, for example) while other parts keep going. If you're running
different parts of the pipeline on different processors you may also take
advantage of the caches on each processor.
This model is also handy for a form of recursive programming where, rather
than having a subroutine call itself, it instead creates another thread.
Prime and Fibonacci generators both map well to this form of the pipeline
model. (A version of a prime number generator is presented later on.)
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.
However it is important to remember that Perl threads cannot magically do
things unless your operating systems threads allows it. So if your system
blocks the entire process on sleep(), Perl usually will as well.
Perl Threads Are Different.
Thread-Safe Modules
The addition of threads has changed Perl's internals substantially. There
are implications for people who write modules with XS code or external
libraries. However, since perl data is not shared among threads by default,
Perl modules stand a high chance of being thread-safe or can be made
thread-safe easily. Modules that are not tagged as thread-safe should be
tested or code reviewed before being used in production code.
Not all modules that you might use are thread-safe, and you should always
assume a module is unsafe unless the documentation says otherwise. This
includes modules that are distributed as part of the core. Threads are a
new feature, and even some of the standard modules aren't thread-safe.
Even if a module is thread-safe, it doesn't mean that the module is
optimized to work well with threads. A module could possibly be rewritten
to utilize the new features in threaded Perl to increase performance in a
threaded environment.
If you're using a module that's not thread-safe for some reason, you can
protect yourself by using it from one, and only one thread at all. If you
need multiple threads to access such a module, you can use semaphores and
lots of programming discipline to control access to it. Semaphores are
covered in "Basic semaphores".
See also "Thread-Safety of System Libraries".
Thread Basics
The core threads module provides the basic functions you need to write
threaded programs. In the following sections we'll cover the basics,
showing you what you need to do to create a threaded program. After that,
we'll go over some of the features of the threads module that make threaded
programming easier.
Basic Thread Support
Thread support is a Perl compile-time option - it's something that's turned
on or off when Perl is built at your site, rather than when your programs
are compiled. If your Perl wasn't compiled with thread support enabled,
then any attempt to use threads will fail.
Your programs can use the Config module to check whether threads are
enabled. If your program can't run without them, you can say something
like:
$Config{useithreads} or die "Recompile Perl with threads to run this program.";
A possibly-threaded program using a possibly-threaded module might have
code like this:
use Config;
use MyMod;
BEGIN {
if ($Config{useithreads}) {
# We have threads
require MyMod_threaded;
import MyMod_threaded;
} else {
require MyMod_unthreaded;
import MyMod_unthreaded;
}
}
Since code that runs both with and without threads is usually pretty messy,
it's best to isolate the thread-specific code in its own module. In our
example above, that's what MyMod_threaded is, and it's only imported if
we're running on a threaded Perl.
A Note about the Examples
Although thread support is considered to be stable, there are still a
number of quirks that may startle you when you try out any of the examples
below. In a real situation, care should be taken that all threads are
finished executing before the program exits. That care has not been taken
in these examples in the interest of simplicity. Running these examples
"as is" will produce error messages, usually caused by the fact that there
are still threads running when the program exits. You should not be
alarmed by this. Future versions of Perl may fix this problem.
Creating Threads
The threads package provides the tools you need to create new threads.
Like any other module, you need to tell Perl that you want to use it; "use
threads" imports all the pieces you need to create basic threads.
The simplest, most straightforward way to create a thread is with new():
use threads;
$thr = threads->new(<!>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
"threads::new" call, like this:
use threads;
$Param3 = "foo";
$thr = threads->new(<!>sub1, "Param 1", "Param 2", $Param3);
$thr = threads->new(<!>sub1, @ParamList);
$thr = threads->new(<!>sub1, qw(Param1 Param2 Param3));
sub sub1 {
my @InboundParameters = @_;
print "In the thread\n";
print "got parameters >", join("<>", @InboundParameters), "<\n";
}
The last example illustrates another feature of threads. You can spawn off
several threads using the same subroutine. Each thread executes the same
subroutine, but in a separate thread with a separate environment and
potentially separate arguments.
"create()" is a synonym for "new()".
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 processor-intensive and want to make sure that the user-
interface thread gets called frequently. Regardless, there are times that
you might want a thread to give up the processor.
Perl's threading package provides the yield() function that does this.
yield() is pretty straightforward, and works like this:
use threads;
sub loop {
my $thread = shift;
my $foo = 50;
while($foo--) { print "in thread $thread\n" }
threads->yield;
$foo = 50;
while($foo--) { print "in thread $thread\n" }
}
my $thread1 = threads->new(<!>loop, 'first');
my $thread2 = threads->new(<!>loop, 'second');
my $thread3 = threads->new(<!>loop, 'third');
It is important to remember that yield() is only a hint to give up the CPU,
it depends on your hardware, OS and threading libraries what actually
happens. Therefore it is important to note that one should not build the
scheduling of the threads around yield() calls. It might work on your
platform but it won't work on another platform.
Waiting For A Thread To Exit
Since threads are also subroutines, they can return values. To wait for a
thread to exit and extract any values it might return, you can use the
join() method:
use threads;
$thr = threads->new(<!>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, as described next.
Ignoring A Thread
join() does three things: it waits for a thread to exit, cleans up after
it, and returns any data the thread may have produced. But what if you're
not interested in the thread's return values, and you don't really care
when the thread finishes? All you want is for the thread to get cleaned up
after when it's done.
In this case, you use the detach() method. Once a thread is detached,
it'll run until it's finished, then Perl will clean up after it
automatically.
use threads;
$thr = threads->new(<!>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 return data 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 biggest difference between Perl ithreads and the old 5.005 style
threading, or for that matter, to most other threading systems out there,
is that by default, no data is shared. When a new perl thread is created,
all the data associated with the current thread is copied to the new
thread, and is subsequently private to that new thread! This is similar in
feel to what happens when a UNIX process forks, except that in this case,
the data is just copied to a different part of memory within the same
process rather than a real fork taking place.
To make use of threading however, one usually wants the threads to share at
least some data between themselves. This is done with the threads::shared
module and the " : shared" attribute:
use threads;
use threads::shared;
my $foo : shared = 1;
my $bar = 1;
threads->new(sub { $foo++; $bar++ })->join;
print "$foo\n"; #prints 2 since $foo is shared
print "$bar\n"; #prints 1 since $bar is not shared
In the case of a shared array, all the array's elements are shared, and for
a shared hash, all the keys and values are shared. This places restrictions
on what may be assigned to shared array and hash elements: only simple
values or references to shared variables are allowed - this is so that a
private variable can't accidentally become shared. A bad assignment will
cause the thread to die. For example:
use threads;
use threads::shared;
my $var = 1;
my $svar : shared = 2;
my %hash : shared;
... create some threads ...
$hash{a} = 1; # all threads see exists($hash{a}) and $hash{a} == 1
$hash{a} = $var # okay - copy-by-value: same effect as previous
$hash{a} = $svar # okay - copy-by-value: same effect as previous
$hash{a} = \$svar # okay - a reference to a shared variable
$hash{a} = \$var # This will die
delete $hash{a} # okay - all threads will see !exists($hash{a})
Note that a shared variable guarantees that if two or more threads try to
modify it at the same time, the internal state of the variable will not
become corrupted. However, there are no guarantees beyond this, as
explained in the next section.
Thread Pitfalls: Races
While threads bring a new set of useful tools, they also bring a number of
pitfalls. One pitfall is the race condition:
use threads;
use threads::shared;
my $a : shared = 1;
$thr1 = threads->new(<!>sub1);
$thr2 = threads->new(<!>sub2);
$thr1->join;
$thr2->join;
print "$a\n";
sub sub1 { my $foo = $a; $a = $foo + 1; }
sub sub2 { my $bar = $a; $a = $bar + 1; }
What do you think $a will be? The answer, unfortunately, is "it depends."
Both sub1() and sub2() access the global variable $a, once to read and once
to write. Depending on factors ranging from your thread implementation's
scheduling algorithm to the phase of the moon, $a can be 2 or 3.
Race conditions are caused by unsynchronized access to shared data.
Without explicit synchronization, there's no way to be sure that nothing
has happened to the shared data between the time you access it and the time
you update it. Even this simple code fragment has the possibility of
error:
use threads;
my $a : shared = 2;
my $b : shared;
my $c : shared;
my $thr1 = threads->create(sub { $b = $a; $a = $b + 1; });
my $thr2 = threads->create(sub { $c = $a; $a = $c + 1; });
$thr1->join;
$thr2->join;
Two threads both access $a. Each thread can potentially be interrupted at
any point, or be executed in any order. At the end, $a could be 3 or 4,
and both $b and $c could be 2 or 3.
Even "$a += 5" or "$a++" are not guaranteed to be atomic.
Whenever your program accesses data or resources that can be accessed by
other threads, you must take steps to coordinate access or risk data
inconsistency and race conditions. Note that Perl will protect its
internals from your race conditions, but it won't protect you from you.
Synchronization and control
Perl provides a number of mechanisms to coordinate the interactions between
themselves and their data, to avoid race conditions and the like. Some of
these are designed to resemble the common techniques used in thread
libraries such as "pthreads"; others are Perl-specific. Often, the standard
techniques are clumsy and difficult to get right (such as condition waits).
Where possible, it is usually easier to use Perlish techniques such as
queues, which remove some of the hard work involved.
Controlling access: lock()
The lock() function takes a shared variable and puts a lock on it. No other
thread may lock the variable until the the variable is unlocked by the
thread holding the lock. Unlocking happens automatically when the locking
thread exits the outermost block that contains "lock()" function. Using
lock() is straightforward: this example has several threads doing some
calculations in parallel, and occasionally updating a running total:
use threads;
use threads::shared;
my $total : shared = 0;
sub calc {
for (;;) {
my $result;
# (... do some calculations and set $result ...)
{
lock($total); # block until we obtain the lock
$total += $result;
} # lock implicitly released at end of scope
last if $result == 0;
}
}
my $thr1 = threads->new(<!>calc);
my $thr2 = threads->new(<!>calc);
my $thr3 = threads->new(<!>calc);
$thr1->join;
$thr2->join;
$thr3->join;
print "total=$total\n";
lock() blocks the thread until the variable being locked is available.
When lock() returns, your thread can be sure that no other thread can lock
that variable until the outermost block containing the lock exits.
It's important to note that locks don't prevent access to the variable in
question, only lock attempts. This is in keeping with Perl's longstanding
tradition of courteous programming, and the advisory file locking that
flock() gives you.
You may lock arrays and hashes as well as scalars. Locking an array,
though, will not block subsequent locks on array elements, just lock
attempts on the array itself.
Locks are recursive, which means it's okay for a thread to lock a variable
more than once. The lock will last until the outermost lock() on the
variable goes out of scope. For example:
my $x : shared;
doit();
sub doit {
{
{
lock($x); # wait for lock
lock($x); # NOOP - we already have the lock
{
lock($x); # NOOP
{
lock($x); # NOOP
lockit_some_more();
}
}
} # *** implicit unlock here ***
}
}
sub lockit_some_more {
lock($x); # NOOP
} # nothing happens here
Note that there is no unlock() function - the only way to unlock a variable
is to allow it to go out of scope.
A lock can either be used to guard the data contained within the variable
being locked, or it can be used to guard something else, like a section of
code. In this latter case, the variable in question does not hold any
useful data, and exists only for the purpose of being locked. In this
respect, the variable behaves like the mutexes and basic semaphores of
traditional thread libraries.
A Thread Pitfall: Deadlocks
Locks are a handy tool to synchronize access to data, and using them
properly is the key to safe shared data. Unfortunately, locks aren't
without their dangers, especially when multiple locks are involved.
Consider the following code:
use threads;
my $a : shared = 4;
my $b : shared = "foo";
my $thr1 = threads->new(sub {
lock($a);
threads->yield;
sleep 20;
lock($b);
});
my $thr2 = threads->new(sub {
lock($b);
threads->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 threads acquires both locks first. A
guaranteed-to-hang version is more complicated, but the principle is the
same.
The first thread will grab a lock on $a, then, after a pause during which
the second thread has probably had time to do some work, try to grab a lock
on $b. Meanwhile, the second thread grabs a lock on $b, then later tries
to grab a lock on $a. The second lock attempt for both threads will block,
each waiting for the other to release its lock.
This condition is called a deadlock, and it occurs whenever two or more
threads are trying to get locks on resources that the others own. Each
thread will block, waiting for the other to release a lock on a resource.
That never happens, though, since the thread with the resource is itself
waiting for a lock to be released.
There are a number of ways to handle this sort of problem. The best way is
to always have all threads acquire locks in the exact same order. If, for
example, you lock variables $a, $b, and $c, always lock $a before $b, and
$b before $c. It's also best to hold on to locks for as short a period of
time to minimize the risks of deadlock.
The other synchronization primitives described below can suffer from
similar problems.
Queues: Passing Data Around
A queue is a special thread-safe object that lets you put data in one end
and take it out the other without having to worry about synchronization
issues. They're pretty straightforward, and look like this:
use threads;
use Thread::Queue;
my $DataQueue = Thread::Queue->new;
$thr = threads->new(sub {
while ($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);
$thr->join;
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.
Semaphores: Synchronizing Data Access
Semaphores are a kind of generic locking mechanism. In their most basic
form, they behave very much like lockable scalars, except that thay can't
hold data, and that they must be explicitly unlocked. In their advanced
form, they act like a kind of counter, and can allow multiple threads to
have the 'lock' at any one time.
Basic semaphores
Semaphores have two methods, down() and up(): down() decrements the
resource count, while up increments it. Calls to down() will block if the
semaphore's current count would decrement below zero. This program gives a
quick demonstration:
use threads qw(yield);
use Thread::Semaphore;
my $semaphore = new Thread::Semaphore;
my $GlobalVariable : shared = 0;
$thr1 = new threads <!>sample_sub, 1;
$thr2 = new threads <!>sample_sub, 2;
$thr3 = new threads <!>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;
}
}
$thr1->join;
$thr2->join;
$thr3->join;
The three invocations of the subroutine all operate in sync. The
semaphore, though, makes sure that only one thread is accessing the global
variable at once.
Advanced Semaphores
By default, semaphores behave like locks, letting only one thread down()
them at a time. However, there are other uses for semaphores.
Each semaphore has a counter attached to it. By default, semaphores are
created with the counter set to one, down() decrements the counter by one,
and up() increments by one. However, we can override any or all of these
defaults simply by passing in different values:
use threads;
use Thread::Semaphore;
my $semaphore = Thread::Semaphore->new(5);
# Creates a semaphore with the counter set to five
$thr1 = threads->new(<!>sub1);
$thr2 = threads->new(<!>sub1);
sub sub1 {
$semaphore->down(5); # Decrements the counter by five
# Do stuff here
$semaphore->up(5); # Increment the counter by five
}
$thr1->detach;
$thr2->detach;
If down() attempts to decrement the counter below zero, it blocks until the
counter is large enough. Note that while a semaphore can be created with a
starting count of zero, any up() or down() always changes the counter by at
least one, and so $semaphore->down(0) is the same as $semaphore->down(1).
The question, of course, is why would you do something like this? Why
create a semaphore with a starting count that's not one, or why
decrement/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.
cond_wait() and cond_signal()
These two functions can be used in conjunction with locks to notify co-
operating threads that a resource has become available. They are very
similar in use to the functions found in "pthreads". However for most
purposes, queues are simpler to use and more intuitive. See threads::shared
for more details.
General Thread Utility Routines
We've covered the workhorse parts of Perl's threading package, and with
these tools you should be well on your way to writing threaded code and
packages. There are a few useful little pieces that didn't really fit in
anyplace else.
What Thread Am I In?
The "threads->self" class method provides your program with a way to get an
object representing the thread it's currently in. You can use this object
in the same way as the ones returned from thread creation.
Thread IDs
tid() is a thread object method that returns the thread ID of the thread
the object represents. Thread IDs are integers, with the main thread in a
program being 0. Currently Perl assigns a unique tid to every thread ever
created in your program, assigning the first thread to be created a tid of
1, and increasing the tid by 1 for each new thread that's created.
Are These Threads The Same?
The equal() method takes two thread objects and returns true if the objects
represent the same thread, and false if they don't.
Thread objects also have an overloaded == comparison so that you can do
comparison on them as you would with normal objects.
What Threads Are Running?
"threads->list" returns a list of thread objects, one for each thread
that's currently running and not detached. Handy for a number of things,
including cleaning up at the end of your program:
# Loop through all the threads
foreach $thr (threads->list) {
# Don't join the main thread or ourselves
if ($thr->tid && !threads::equal($thr, threads->self)) {
$thr->join;
}
}
If some threads have not finished running when the main Perl thread ends,
Perl will warn you about it and die, since it is impossible for Perl to
clean up itself while other threads are running
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 threads;
7 use Thread::Queue;
8
9 my $stream = new Thread::Queue;
10 my $kid = new threads(<!>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 threads(<!>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 into which it
funnels numbers that have failed the check. If the thread has a number
that's failed its check and there's no child thread, then the thread must
have found a new prime number. In that case, a new child thread is created
for that prime and stuck on the end of the pipeline.
This probably sounds a bit more confusing than it really is, so let's go
through this program piece by piece and see what it does. (For those of
you who might be trying to remember exactly what a prime number is, it's a
number that's only evenly divisible by itself and 1)
The bulk of the work is done by the check_num() subroutine, which takes a
reference to its input queue and a prime number that it's responsible for.
After pulling in the input queue and the prime that the subroutine'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.
Performance considerations
The main thing to bear in mind when comparing ithreads to other threading
models is the fact that for each new thread created, a complete copy of all
the variables and data of the parent thread has to be taken. Thus thread
creation can be quite expensive, both in terms of memory usage and time
spent in creation. The ideal way to reduce these costs is to have a
relatively short number of long-lived threads, all created fairly early on
- before the base thread has accumulated too much data. Of course, this
may not always be possible, so compromises have to be made. However, after
a thread has been created, its performance and extra memory usage should be
little different than ordinary code.
Also note that under the current implementation, shared variables use a
little more memory and are a little slower than ordinary variables.
Process-scope Changes
Note that while threads themselves are separate execution threads and Perl
data is thread-private unless explicitly shared, the threads can affect
process-scope state, affecting all the threads.
The most common example of this is changing the current working directory
using chdir(). One thread calls chdir(), and the working directory of all
the threads changes.
Even more drastic example of a process-scope change is chroot(): the root
directory of all the threads changes, and no thread can undo it (as opposed
to chdir()).
Further examples of process-scope changes include umask() and changing
uids/gids.
Thinking of mixing fork() and threads? Please lie down and wait until the
feeling passes-- but in case you really want to know, the semantics is that
fork() duplicates all the threads. (In UNIX, at least, other platforms
will do something different.)
Similarly, mixing signals and threads should not be attempted.
Implementations are platform-dependent, and even the POSIX semantics may
not be what you expect (and Perl doesn't even give you the full POSIX API).
Thread-Safety of System Libraries
Whether various library calls are thread-safe is outside the control of
Perl. Calls often suffering from not being thread-safe include:
localtime(), gmtime(), get{gr,host,net,proto,serv,pw}*(), readdir(),
rand(), and srand() -- in general, calls that depend on some global
external state.
If the system Perl is compiled in has thread-safe variants of such calls,
they will be used. Beyond that, Perl is at the mercy of the thread-safety
or -unsafety of the calls. Please consult your C library call
documentation.
In some platforms the thread-safe interfaces may fail if the result buffer
is too small (for example getgrent() may return quite large group member
lists). Perl will retry growing the result buffer a few times, but only up
to 64k (for safety reasons).
Conclusion
A complete thread tutorial could fill a book (and has, many times), but
with what we've covered in this introduction, you should be well on your
way to becoming a threaded Perl expert.
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://gatekeeper.dec.com/pub/DEC/SRC/research-reports/abstracts/src-rr-035.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.
comp.programming.threads FAQ, <http://www.serpentine.com/~bos/threads-faq/>
Le Sergent, T. and B. Berthomieu. "Incremental MultiThreaded Garbage
Collection on Virtually Shared Memory Architectures" in Memory Management:
Proc. of the International Workshop IWMM 92, St. Malo, France, September
1992, Yves Bekkers and Jacques Cohen, eds. Springer, 1992, ISBN
3540-55940-X (real-life thread applications).
Artur Bergman, "Where Wizards Fear To Tread", June 11, 2002,
<http://www.perl.com/pub/a/2002/06/11/threads.html>
Acknowledgements
Thanks (in no particular order) to Chaim Frenkel, Steve Fink, Gurusamy
Sarathy, Ilya Zakharevich, Benjamin Sugars, 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 <dan@sidhe.org<gt>
Slightly modified by Arthur Bergman to fit the new thread model/module.
Reworked slightly by Jrg Walter <jwalt@cpan.org<gt> to be more concise
about thread-safety of perl code.
Copyrights
The original version of this article originally appeared in The Perl
Journal #10, and is copyright 1998 The Perl Journal. It appears courtesy of
Jon Orwant and The Perl Journal. This document may be distributed under
the same terms as Perl itself.
For more information please see threads and threads::shared.
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