Parallel::Iterator(3) User Contributed Perl DocumentationParallel::Iterator(3)NAMEParallel::Iterator - Simple parallel execution
VERSION
This document describes Parallel::Iterator version 1.00
SYNOPSIS
use Parallel::Iterator qw( iterate );
# A very expensive way to double 100 numbers...
my @nums = ( 1 .. 100 );
my $iter = iterate( sub {
my ( $id, $job ) = @_;
return $job * 2;
}, \@nums );
my @out = ();
while ( my ( $index, $value ) = $iter->() ) {
$out[$index] = $value;
}
DESCRIPTION
The "map" function applies a user supplied transformation function to
each element in a list, returning a new list containing the transformed
elements.
This module provides a 'parallel map'. Multiple worker processes are
forked so that many instances of the transformation function may be
executed simultaneously.
For time consuming operations, particularly operations that spend most
of their time waiting for I/O, this is a big performance win. It also
provides a simple idiom to make effective use of multi CPU systems.
There is, however, a considerable overhead associated with forking, so
the example in the synopsis (doubling a list of numbers) is not a
sensible use of this module.
Example
Imagine you have an array of URLs to fetch:
my @urls = qw(
http://google.com/
http://hexten.net/
http://search.cpan.org/
... and lots more ...
);
Write a function that retrieves a URL and returns its contents or undef
if it can't be fetched:
sub fetch {
my $url = shift;
my $resp = $ua->get($url);
return unless $resp->is_success;
return $resp->content;
};
Now write a function to synthesize a special kind of iterator:
sub list_iter {
my @ar = @_;
my $pos = 0;
return sub {
return if $pos >= @ar;
my @r = ( $pos, $ar[$pos] ); # Note: returns ( index, value )
$pos++;
return @r;
};
}
The returned iterator will return each element of the array in turn and
then undef. Actually it returns both the index and the value of each
element in the array. Because multiple instances of the transformation
function execute in parallel the results won't necessarily come back in
order. The array index will later allow us to put completed items in
the correct place in an output array.
Get an iterator for the list of URLs:
my $url_iter = list_iter( @urls );
Then wrap it in another iterator which will return the transformed
results:
my $page_iter = iterate( \&fetch, $url_iter );
Finally loop over the returned iterator storing results:
my @out = ( );
while ( my ( $index, $value ) = $page_iter->() ) {
$out[$index] = $value;
}
Behind the scenes your program forked into ten (by default) instances
of itself and executed the page requests in parallel.
Simpler interfaces
Having to construct an iterator is a pain so "iterate" is smart enough
to do that for you. Instead of passing an iterator just pass a
reference to the array:
my $page_iter = iterate( \&fetch, \@urls );
If you pass a hash reference the iterator you get back will return key,
value pairs:
my $some_iter = iterate( \&fetch, \%some_hash );
If the returned iterator is inconvenient you can get back a hash or
array instead:
my @done = iterate_as_array( \&fetch, @urls );
my %done = iterate_as_hash( \&worker, %jobs );
How It Works
The current process is forked once for each worker. Each forked child
is connected to the parent by a pair of pipes. The child's STDIN,
STDOUT and STDERR are unaffected.
Input values are serialised (using Storable) and passed to the workers.
Completed work items are serialised and returned.
Caveats
Parallel::Iterator is designed to be simple to use - but the underlying
forking of the main process can cause mystifying problems unless you
have an understanding of what is going on behind the scenes.
Worker execution enviroment
All code apart from the worker subroutine executes in the parent
process as normal. The worker executes in a forked instance of the
parent process. That means that things like this won't work as
expected:
my %tally = ();
my @r = iterate_as_array( sub {
my ($id, $name) = @_;
$tally{$name}++; # might not do what you think it does
return reverse $name;
}, @names );
# Now print out the tally...
while ( my ( $name, $count ) = each %tally ) {
printf("%5d : %s\n", $count, $name);
}
Because the worker is a closure it can see the %tally hash from its
enclosing scope; but because it's running in a forked clone of the
parent process it modifies its own copy of %tally rather than the copy
for the parent process.
That means that after the job terminates the %tally in the parent
process will be empty.
In general you should avoid side effects in your worker subroutines.
Serialization
Values are serialised using Storable to pass to the worker subroutine
and results from the worker are again serialised before being passed
back. Be careful what your values refer to: everything has to be
serialised. If there's an indirect way to reach a large object graph
Storable will find it and performance will suffer.
To find out how large your serialised values are serialise one of them
and check its size:
use Storable qw( freeze );
my $serialized = freeze $some_obj;
print length($serialized), " bytes\n";
In your tests you may wish to guard against the possibility of a change
to the structure of your values resulting in a sudden increase in
serialized size:
ok length(freeze $some_obj) < 1000, "Object too bulky?";
See the documetation for Storable for other caveats.
Performance
Process forking is expensive. Only use Parallel::Iterator in cases
where:
the worker waits for I/O
The case of fetching web pages is a good example of this. Fetching
a page with LWP::UserAgent may take as long as a few seconds but
probably consumes only a few milliseconds of processor time.
Running many requests in parallel is a huge win - but be kind to
the server you're talking to: don't launch a lot of parallel
requests unless it's your server or you know it can handle the
load.
the worker is CPU intensive and you have multiple cores / CPUs
If the worker is doing an expensive calculation you can parallelise
that across multiple CPU cores. Benchmark first though. There's a
considerable overhead associated with Parallel::Iterator; unless
your calculations are time consuming that overhead will dwarf
whatever time they take.
INTERFACE
"iterate( [ $options ], $worker, $iterator )"
Get an iterator that applies the supplied transformation function to
each value returned by the input iterator.
Instead of an iterator you may pass an array or hash reference and
"iterate" will convert it internally into a suitable iterator.
If you are doing this you may wish to investigate "iterate_as_hash" and
"iterate_as_array".
Options
A reference to a hash of options may be supplied as the first argument.
The following options are supported:
"workers"
The number of concurrent processes to launch. Set this to 0 to
disable forking. Defaults to 10 on systems that support fork and 0
(disable forking) on those that do not.
"nowarn"
Normally "iterate" will issue a warning and fall back to single
process mode on systems on which fork is not available. This option
supresses that warning.
"batch"
Ordinarily items are passed to the worker one at a time. If you are
processing a large number of items it may be more efficient to
process them in batches. Specify the batch size using this option.
Batching is transparent from the caller's perspective. Internally
it modifies the iterators and worker (by wrapping them in
additional closures) so that they pack, process and unpack chunks
of work.
"adaptive"
Extending the idea of batching a number of work items to amortize
the overhead of passing work to and from parallel workers you may
also ask "iterate" to heuristically determine the batch size by
setting the "adaptive" option to a numeric value.
The batch size will be computed as
<number of items seen> / <number of workers> / <adaptive>
A larger value for "adaptive" will reduce the rate at which the
batch size increases. Good values tend to be in the range 1 to 2.
You can also specify lower and, optionally, upper bounds on the
batch size by passing an reference to an array containing ( lower
bound, growth ratio, upper bound ). The upper bound may be omitted.
my $iter = iterate(
{ adaptive => [ 5, 2, 100 ] },
$worker, \@stuff );
"onerror"
The action to take when an error is thrown in the iterator.
Possible values are 'die', 'warn' or a reference to a subroutine
that will be called with the index of the job that threw the
exception and the value of $@ thrown.
iterate( {
onerror => sub {
my ($id, $err) = @_;
$self->log( "Error for index $id: $err" );
},
$worker,
\@jobs
);
The default is 'die'.
"iterate_as_array"
As "iterate" but instead of returning an iterator returns an array
containing the collected output from the iterator. In a scalar context
returns a reference to the same array.
For this to work properly the input iterator must return (index, value)
pairs. This allows the results to be placed in the correct slots in the
output array. The simplest way to do this is to pass an array reference
as the input iterator:
my @output = iterate_as_array( \&some_handler, \@input );
"iterate_as_hash"
As "iterate" but instead of returning an iterator returns a hash
containing the collected output from the iterator. In a scalar context
returns a reference to the same hash.
For this to work properly the input iterator must return (key, value)
pairs. This allows the results to be placed in the correct slots in the
output hash. The simplest way to do this is to pass a hash reference as
the input iterator:
my %output = iterate_as_hash( \&some_handler, \%input );
CONFIGURATION AND ENVIRONMENTParallel::Iterator requires no configuration files or environment
variables.
DEPENDENCIES
None.
INCOMPATIBILITIES
None reported.
BUGS AND LIMITATIONS
No bugs have been reported.
Please report any bugs or feature requests to
"bug-parallel-iterator@rt.cpan.org", or through the web interface at
<http://rt.cpan.org>.
AUTHOR
Andy Armstrong "<andy@hexten.net>"
THANKS
Aristotle Pagaltzis for the END handling suggestion and patch.
LICENCE AND COPYRIGHT
Copyright (c) 2007, Andy Armstrong "<andy@hexten.net>". All rights
reserved.
This module is free software; you can redistribute it and/or modify it
under the same terms as Perl itself. See perlartistic.
DISCLAIMER OF WARRANTY
BECAUSE THIS SOFTWARE IS LICENSED FREE OF CHARGE, THERE IS NO WARRANTY
FOR THE SOFTWARE, TO THE EXTENT PERMITTED BY APPLICABLE LAW. EXCEPT
WHEN OTHERWISE STATED IN WRITING THE COPYRIGHT HOLDERS AND/OR OTHER
PARTIES PROVIDE THE SOFTWARE "AS IS" WITHOUT WARRANTY OF ANY KIND,
EITHER EXPRESSED OR IMPLIED, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED
WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE. THE
ENTIRE RISK AS TO THE QUALITY AND PERFORMANCE OF THE SOFTWARE IS WITH
YOU. SHOULD THE SOFTWARE PROVE DEFECTIVE, YOU ASSUME THE COST OF ALL
NECESSARY SERVICING, REPAIR, OR CORRECTION.
IN NO EVENT UNLESS REQUIRED BY APPLICABLE LAW OR AGREED TO IN WRITING
WILL ANY COPYRIGHT HOLDER, OR ANY OTHER PARTY WHO MAY MODIFY AND/OR
REDISTRIBUTE THE SOFTWARE AS PERMITTED BY THE ABOVE LICENCE, BE LIABLE
TO YOU FOR DAMAGES, INCLUDING ANY GENERAL, SPECIAL, INCIDENTAL, OR
CONSEQUENTIAL DAMAGES ARISING OUT OF THE USE OR INABILITY TO USE THE
SOFTWARE (INCLUDING BUT NOT LIMITED TO LOSS OF DATA OR DATA BEING
RENDERED INACCURATE OR LOSSES SUSTAINED BY YOU OR THIRD PARTIES OR A
FAILURE OF THE SOFTWARE TO OPERATE WITH ANY OTHER SOFTWARE), EVEN IF
SUCH HOLDER OR OTHER PARTY HAS BEEN ADVISED OF THE POSSIBILITY OF SUCH
DAMAGES.
perl v5.14.1 2011-06-20 Parallel::Iterator(3)
