NAME¶
Parallel::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 ENVIRONMENT¶
Parallel::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
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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
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