MCE::Step - Parallel step model for building creative steps
This document describes MCE::Step version 1.900
MCE::Step is similar to MCE::Flow for writing custom apps. The main difference comes from the transparent use of queues between sub-tasks. MCE 1.7 adds mce_enq, mce_enqp, and mce_await methods described under QUEUE-LIKE FEATURES below.
It is trivial to parallelize with mce_stream shown below.
## Native map function
my @a = map { $_ * 4 } map { $_ * 3 } map { $_ * 2 } 1..10000;
## Same as with MCE::Stream (processing from right to left)
@a = mce_stream
sub { $_ * 4 }, sub { $_ * 3 }, sub { $_ * 2 }, 1..10000;
## Pass an array reference to have writes occur simultaneously
mce_stream \@a,
sub { $_ * 4 }, sub { $_ * 3 }, sub { $_ * 2 }, 1..10000;However, let's have MCE::Step compute the same in parallel. Unlike the example in MCE::Flow, the use of MCE::Queue is totally transparent. This calls for preserving output order provided by MCE::Candy.
use MCE::Step;
use MCE::Candy;Next are the 3 sub-tasks. Compare these 3 sub-tasks with the same as described in MCE::Flow. The call to MCE->step simplifies the passing of data to subsequent sub-task.
sub task_a {
my @ans; my ($mce, $chunk_ref, $chunk_id) = @_;
push @ans, map { $_ * 2 } @{ $chunk_ref };
MCE->step(\@ans, $chunk_id);
}
sub task_b {
my @ans; my ($mce, $chunk_ref, $chunk_id) = @_;
push @ans, map { $_ * 3 } @{ $chunk_ref };
MCE->step(\@ans, $chunk_id);
}
sub task_c {
my @ans; my ($mce, $chunk_ref, $chunk_id) = @_;
push @ans, map { $_ * 4 } @{ $chunk_ref };
MCE->gather($chunk_id, \@ans);
}In summary, MCE::Step builds out a MCE instance behind the scene and starts running. The task_name (shown), max_workers, and use_threads options can take an anonymous array for specifying the values uniquely per each sub-task.
The task_name option is required to use ->enq, ->enqp, and ->await.
my @a;
mce_step {
task_name => [ 'a', 'b', 'c' ],
gather => MCE::Candy::out_iter_array(\@a)
}, \&task_a, \&task_b, \&task_c, 1..10000;
print "@a\n";In the demonstration below, one may call ->gather or ->step any number of times although ->step is not allowed in the last sub-block. Data is gathered to @arr which may likely be out-of-order. Gathering data is optional. All sub-blocks receive $mce as the first argument.
First, defining 3 sub-tasks.
use MCE::Step;
sub task_a {
my ($mce, $chunk_ref, $chunk_id) = @_;
if ($_ % 2 == 0) {
MCE->gather($_);
# MCE->gather($_ * 4); ## Ok to gather multiple times
}
else {
MCE->print("a step: $_, $_ * $_\n");
MCE->step($_, $_ * $_);
# MCE->step($_, $_ * 4 ); ## Ok to step multiple times
}
}
sub task_b {
my ($mce, $arg1, $arg2) = @_;
MCE->print("b args: $arg1, $arg2\n");
if ($_ % 3 == 0) { ## $_ is the same as $arg1
MCE->gather($_);
}
else {
MCE->print("b step: $_ * $_\n");
MCE->step($_ * $_);
}
}
sub task_c {
my ($mce, $arg1) = @_;
MCE->print("c: $_\n");
MCE->gather($_);
}Next, pass MCE options, using chunk_size 1, and run all 3 tasks in parallel. Notice how max_workers and use_threads can take an anonymous array, similarly to task_name.
my @arr = mce_step {
task_name => [ 'a', 'b', 'c' ],
max_workers => [ 2, 2, 2 ],
use_threads => [ 0, 0, 0 ],
chunk_size => 1
}, \&task_a, \&task_b, \&task_c, 1..10;Finally, sort the array and display its contents.
@arr = sort { $a <=> $b } @arr;
print "\n@arr\n\n";
-- Output
a step: 1, 1 * 1
a step: 3, 3 * 3
a step: 5, 5 * 5
a step: 7, 7 * 7
a step: 9, 9 * 9
b args: 1, 1
b step: 1 * 1
b args: 3, 9
b args: 7, 49
b step: 7 * 7
b args: 5, 25
b step: 5 * 5
b args: 9, 81
c: 1
c: 49
c: 25
1 2 3 4 6 8 9 10 25 49Although MCE::Loop may be preferred for running using a single code block, the text below also applies to this module, particularly for the first block.
All models in MCE default to 'auto' for chunk_size. The arguments for the block are the same as writing a user_func block using the Core API.
Beginning with MCE 1.5, the next input item is placed into the input scalar variable $_ when chunk_size equals 1. Otherwise, $_ points to $chunk_ref containing many items. Basically, line 2 below may be omitted from your code when using $_. One can call MCE->chunk_id to obtain the current chunk id.
line 1: user_func => sub {
line 2: my ($mce, $chunk_ref, $chunk_id) = @_;
line 3:
line 4: $_ points to $chunk_ref->[0]
line 5: in MCE 1.5 when chunk_size == 1
line 6:
line 7: $_ points to $chunk_ref
line 8: in MCE 1.5 when chunk_size > 1
line 9: }Follow this synopsis when chunk_size equals one. Looping is not required from inside the first block. Hence, the block is called once per each item.
## Exports mce_step, mce_step_f, and mce_step_s
use MCE::Step;
MCE::Step->init(
chunk_size => 1
);
## Array or array_ref
mce_step sub { do_work($_) }, 1..10000;
mce_step sub { do_work($_) }, \@list;
## Important; pass an array_ref for deeply input data
mce_step sub { do_work($_) }, [ [ 0, 1 ], [ 0, 2 ], ... ];
mce_step sub { do_work($_) }, \@deeply_list;
## File path, glob ref, IO::All::{ File, Pipe, STDIO } obj, or scalar ref
## Workers read directly and not involve the manager process
mce_step_f sub { chomp; do_work($_) }, "/path/to/file"; # efficient
## Involves the manager process, therefore slower
mce_step_f sub { chomp; do_work($_) }, $file_handle;
mce_step_f sub { chomp; do_work($_) }, $io;
mce_step_f sub { chomp; do_work($_) }, \$scalar;
## Sequence of numbers (begin, end [, step, format])
mce_step_s sub { do_work($_) }, 1, 10000, 5;
mce_step_s sub { do_work($_) }, [ 1, 10000, 5 ];
mce_step_s sub { do_work($_) }, {
begin => 1, end => 10000, step => 5, format => undef
};Follow this synopsis when chunk_size equals 'auto' or greater than 1. This means having to loop through the chunk from inside the first block.
use MCE::Step;
MCE::Step->init( ## Chunk_size defaults to 'auto' when
chunk_size => 'auto' ## not specified. Therefore, the init
); ## function may be omitted.
## Syntax is shown for mce_step for demonstration purposes.
## Looping inside the block is the same for mce_step_f and
## mce_step_s.
## Array or array_ref
mce_step sub { do_work($_) for (@{ $_ }) }, 1..10000;
mce_step sub { do_work($_) for (@{ $_ }) }, \@list;
## Important; pass an array_ref for deeply input data
mce_step sub { do_work($_) for (@{ $_ }) }, [ [ 0, 1 ], [ 0, 2 ], ... ];
mce_step sub { do_work($_) for (@{ $_ }) }, \@deeply_list;
## Resembles code using the core MCE API
mce_step sub {
my ($mce, $chunk_ref, $chunk_id) = @_;
for (@{ $chunk_ref }) {
do_work($_);
}
}, 1..10000;Chunking reduces the number of IPC calls behind the scene. Think in terms of chunks whenever processing a large amount of data. For relatively small data, choosing 1 for chunk_size is fine.
The following list options which may be overridden when loading the module. The fast option is obsolete in 1.867 onwards; ignored if specified.
use Sereal qw( encode_sereal decode_sereal );
use CBOR::XS qw( encode_cbor decode_cbor );
use JSON::XS qw( encode_json decode_json );
use MCE::Step
max_workers => 8, # Default 'auto'
chunk_size => 500, # Default 'auto'
tmp_dir => "/path/to/app/tmp", # $MCE::Signal::tmp_dir
freeze => \&encode_sereal, # \&Storable::freeze
thaw => \&decode_sereal, # \&Storable::thaw
init_relay => 0, # Default undef; MCE 1.882+
use_threads => 0, # Default undef; MCE 1.882+
;From MCE 1.8 onwards, Sereal 3.015+ is loaded automatically if available. Specify Sereal => 0 to use Storable instead.
use MCE::Step Sereal => 0;The init function accepts a hash of MCE options. Unlike with MCE::Stream, both gather and bounds_only options may be specified (not shown below).
In scalar context (API available since 1.897), call MCE::Step-finish> automatically upon leaving the scope or program.
use MCE::Step;
my $guard = MCE::Step->init(
chunk_size => 1, max_workers => 4,
user_begin => sub {
print "## ", MCE->wid, " started\n";
},
user_end => sub {
print "## ", MCE->wid, " completed\n";
}
);
my %a = mce_step sub { MCE->gather($_, $_ * $_) }, 1..100;
print "\n", "@a{1..100}", "\n";
-- Output
## 3 started
## 1 started
## 4 started
## 2 started
## 3 completed
## 4 completed
## 1 completed
## 2 completed
1 4 9 16 25 36 49 64 81 100 121 144 169 196 225 256 289 324 361
400 441 484 529 576 625 676 729 784 841 900 961 1024 1089 1156
1225 1296 1369 1444 1521 1600 1681 1764 1849 1936 2025 2116 2209
2304 2401 2500 2601 2704 2809 2916 3025 3136 3249 3364 3481 3600
3721 3844 3969 4096 4225 4356 4489 4624 4761 4900 5041 5184 5329
5476 5625 5776 5929 6084 6241 6400 6561 6724 6889 7056 7225 7396
7569 7744 7921 8100 8281 8464 8649 8836 9025 9216 9409 9604 9801
10000Like with MCE::Step->init above, MCE options may be specified using an anonymous hash for the first argument. Notice how task_name, max_workers, and use_threads can take an anonymous array for setting uniquely per each code block.
Unlike MCE::Stream which processes from right-to-left, MCE::Step begins with the first code block, thus processing from left-to-right.
The following takes 9 seconds to complete. The 9 seconds is from having only 2 workers assigned for the last sub-task and waiting 1 or 2 seconds initially before calling MCE->step.
Removing both calls to MCE->step will cause the script to complete in just 1 second. The reason is due to the 2nd and subsequent sub-tasks awaiting data from an internal queue. Workers terminate upon receiving an undef.
use threads;
use MCE::Step;
my @a = mce_step {
task_name => [ 'a', 'b', 'c' ],
max_workers => [ 3, 4, 2, ],
use_threads => [ 1, 0, 0, ],
user_end => sub {
my ($mce, $task_id, $task_name) = @_;
MCE->print("$task_id - $task_name completed\n");
},
task_end => sub {
my ($mce, $task_id, $task_name) = @_;
MCE->print("$task_id - $task_name ended\n");
}
},
sub { sleep 1; MCE->step(""); }, ## 3 workers, named a
sub { sleep 2; MCE->step(""); }, ## 4 workers, named b
sub { sleep 3; }; ## 2 workers, named c
-- Output
0 - a completed
0 - a completed
0 - a completed
0 - a ended
1 - b completed
1 - b completed
1 - b completed
1 - b completed
1 - b ended
2 - c completed
2 - c completed
2 - c endedAlthough input data is optional for MCE::Step, the following assumes chunk_size equals 1 in order to demonstrate all the possibilities for providing input data.
Input data may be defined using a list, an array ref, or a hash ref.
Unlike MCE::Loop, Map, and Grep which take a block as { ... }, Step takes a sub { ... } or a code reference. The other difference is that the comma is needed after the block.
# $_ contains the item when chunk_size => 1
mce_step sub { do_work($_) }, 1..1000;
mce_step sub { do_work($_) }, \@list;
# Important; pass an array_ref for deeply input data
mce_step sub { do_work($_) }, [ [ 0, 1 ], [ 0, 2 ], ... ];
mce_step sub { do_work($_) }, \@deeply_list;
# Chunking; any chunk_size => 1 or greater
my %res = mce_step sub {
my ($mce, $chunk_ref, $chunk_id) = @_;
my %ret;
for my $item (@{ $chunk_ref }) {
$ret{$item} = $item * 2;
}
MCE->gather(%ret);
},
\@list;
# Input hash; current API available since 1.828
my %res = mce_step sub {
my ($mce, $chunk_ref, $chunk_id) = @_;
my %ret;
for my $key (keys %{ $chunk_ref }) {
$ret{$key} = $chunk_ref->{$key} * 2;
}
MCE->gather(%ret);
},
\%hash;
# Unlike MCE::Loop, MCE::Step doesn't need input to run
mce_step { max_workers => 4 }, sub {
MCE->say( MCE->wid );
};
# ... and can run multiple tasks
mce_step {
max_workers => [ 1, 3 ],
task_name => [ 'p', 'c' ]
},
sub {
# 1 producer
MCE->say( "producer: ", MCE->wid );
},
sub {
# 3 consumers
MCE->say( "consumer: ", MCE->wid );
};
# Here, options are specified via init
MCE::Step->init(
max_workers => [ 1, 3 ],
task_name => [ 'p', 'c' ]
);
mce_step \&producer, \&consumers;The fastest of these is the /path/to/file. Workers communicate the next offset position among themselves with zero interaction by the manager process.
IO::All { File, Pipe, STDIO } is supported since MCE 1.845.
# $_ contains the line when chunk_size => 1
mce_step_f sub { $_ }, "/path/to/file"; # faster
mce_step_f sub { $_ }, $file_handle;
mce_step_f sub { $_ }, $io; # IO::All
mce_step_f sub { $_ }, \$scalar;
# chunking, any chunk_size => 1 or greater
my %res = mce_step_f sub {
my ($mce, $chunk_ref, $chunk_id) = @_;
my $buf = '';
for my $line (@{ $chunk_ref }) {
$buf .= $line;
}
MCE->gather($chunk_id, $buf);
},
"/path/to/file";Sequence may be defined as a list, an array reference, or a hash reference. The functions require both begin and end values to run. Step and format are optional. The format is passed to sprintf (% may be omitted below).
my ($beg, $end, $step, $fmt) = (10, 20, 0.1, "%4.1f");
# $_ contains the sequence number when chunk_size => 1
mce_step_s sub { $_ }, $beg, $end, $step, $fmt;
mce_step_s sub { $_ }, [ $beg, $end, $step, $fmt ];
mce_step_s sub { $_ }, {
begin => $beg, end => $end,
step => $step, format => $fmt
};
# chunking, any chunk_size => 1 or greater
my %res = mce_step_s sub {
my ($mce, $chunk_ref, $chunk_id) = @_;
my $buf = '';
for my $seq (@{ $chunk_ref }) {
$buf .= "$seq\n";
}
MCE->gather($chunk_id, $buf);
},
[ $beg, $end ];The sequence engine can compute 'begin' and 'end' items only, for the chunk, and not the items in between (hence boundaries only). This option applies to sequence only and has no effect when chunk_size equals 1.
The time to run is 0.006s below. This becomes 0.827s without the bounds_only option due to computing all items in between, thus creating a very large array. Basically, specify bounds_only => 1 when boundaries is all you need for looping inside the block; e.g. Monte Carlo simulations.
Time was measured using 1 worker to emphasize the difference.
use MCE::Step;
MCE::Step->init(
max_workers => 1, chunk_size => 1_250_000,
bounds_only => 1
);
# Typically, the input scalar $_ contains the sequence number
# when chunk_size => 1, unless the bounds_only option is set
# which is the case here. Thus, $_ points to $chunk_ref.
mce_step_s sub {
my ($mce, $chunk_ref, $chunk_id) = @_;
# $chunk_ref contains 2 items, not 1_250_000
# my ( $begin, $end ) = ( $_->[0], $_->[1] );
my $begin = $chunk_ref->[0];
my $end = $chunk_ref->[1];
# for my $seq ( $begin .. $end ) {
# ...
# }
MCE->printf("%7d .. %8d\n", $begin, $end);
},
[ 1, 10_000_000 ];
-- Output
1 .. 1250000
1250001 .. 2500000
2500001 .. 3750000
3750001 .. 5000000
5000001 .. 6250000
6250001 .. 7500000
7500001 .. 8750000
8750001 .. 10000000An iterator reference may be specified for input_data. The only other way is to specify input_data via MCE::Step->init. This prevents MCE::Step from configuring the iterator reference as another user task which will not work.
Iterators are described under section "SYNTAX for INPUT_DATA" at MCE::Core.
MCE::Step->init(
input_data => iterator
);
mce_step sub { $_ };The ->step method is the simplest form for passing elements into the next sub-task.
use MCE::Step;
sub provider {
MCE->step( $_, rand ) for 10 .. 19;
}
sub consumer {
my ( $mce, @args ) = @_;
MCE->printf( "%d: %d, %03.06f\n", MCE->wid, $args[0], $args[1] );
}
MCE::Step->init(
task_name => [ 'p', 'c' ],
max_workers => [ 1 , 4 ]
);
mce_step \&provider, \&consumer;
-- Output
2: 10, 0.583551
4: 11, 0.175319
3: 12, 0.843662
4: 15, 0.748302
2: 14, 0.591752
3: 16, 0.357858
5: 13, 0.953528
4: 17, 0.698907
2: 18, 0.985448
3: 19, 0.146548The MCE 1.7 release enables finer control. Unlike ->step, which take multiple arguments, the ->enq and ->enqp methods push items at the end of the array internally. Passing multiple arguments is possible by enclosing the arguments inside an anonymous array.
The direction of flow is forward only. Thus, stepping to itself or backwards will cause an error.
use MCE::Step;
sub provider {
if ( MCE->wid % 2 == 0 ) {
MCE->enq( 'c', [ $_, rand ] ) for 10 .. 19;
} else {
MCE->enq( 'd', [ $_, rand ] ) for 20 .. 29;
}
}
sub consumer_c {
my ( $mce, $args ) = @_;
MCE->printf( "C%d: %d, %03.06f\n", MCE->wid, $args->[0], $args->[1] );
}
sub consumer_d {
my ( $mce, $args ) = @_;
MCE->printf( "D%d: %d, %03.06f\n", MCE->wid, $args->[0], $args->[1] );
}
MCE::Step->init(
task_name => [ 'p', 'c', 'd' ],
max_workers => [ 2 , 3 , 3 ]
);
mce_step \&provider, \&consumer_c, \&consumer_d;
-- Output
C4: 10, 0.527531
D6: 20, 0.420108
C5: 11, 0.839770
D8: 21, 0.386414
C3: 12, 0.834645
C4: 13, 0.191014
D6: 23, 0.924027
C5: 14, 0.899357
D8: 24, 0.706186
C4: 15, 0.083823
D7: 22, 0.479708
D6: 25, 0.073882
C3: 16, 0.207446
D8: 26, 0.560755
C5: 17, 0.198157
D7: 27, 0.324909
C4: 18, 0.147505
C5: 19, 0.318371
D6: 28, 0.220465
D8: 29, 0.630111Providers may sometime run faster than consumers. Thus, increasing memory consumption. MCE 1.7 adds the ->await method for pausing momentarily until the receiving sub-task reaches the minimum threshold for the number of items pending in its queue.
use MCE::Step;
use Time::HiRes 'sleep';
sub provider {
for ( 10 .. 29 ) {
# wait until 10 or less items pending
MCE->await( 'c', 10 );
# forward item to a later sub-task ( 'c' comes after 'p' )
MCE->enq( 'c', [ $_, rand ] );
}
}
sub consumer {
my ($mce, $args) = @_;
MCE->printf( "%d: %d, %03.06f\n", MCE->wid, $args->[0], $args->[1] );
sleep 0.05;
}
MCE::Step->init(
task_name => [ 'p', 'c' ],
max_workers => [ 1 , 4 ]
);
mce_step \&provider, \&consumer;
-- Output
3: 10, 0.527307
2: 11, 0.036193
5: 12, 0.987168
4: 13, 0.998140
5: 14, 0.219526
4: 15, 0.061609
2: 16, 0.557664
3: 17, 0.658684
4: 18, 0.240932
3: 19, 0.241042
5: 20, 0.884830
2: 21, 0.902223
4: 22, 0.699223
3: 23, 0.208270
5: 24, 0.438919
2: 25, 0.268854
4: 26, 0.596425
5: 27, 0.979818
2: 28, 0.918173
3: 29, 0.358266Unlike MCE::Map where gather and output order are done for you automatically, the gather method is used to have results sent back to the manager process.
use MCE::Step chunk_size => 1;
## Output order is not guaranteed.
my @a = mce_step sub { MCE->gather($_ * 2) }, 1..100;
print "@a\n\n";
## Outputs to a hash instead (key, value).
my %h1 = mce_step sub { MCE->gather($_, $_ * 2) }, 1..100;
print "@h1{1..100}\n\n";
## This does the same thing due to chunk_id starting at one.
my %h2 = mce_step sub { MCE->gather(MCE->chunk_id, $_ * 2) }, 1..100;
print "@h2{1..100}\n\n";The gather method may be called multiple times within the block unlike return which would leave the block. Therefore, think of gather as yielding results immediately to the manager process without actually leaving the block.
use MCE::Step chunk_size => 1, max_workers => 3;
my @hosts = qw(
hosta hostb hostc hostd hoste
);
my %h3 = mce_step sub {
my ($output, $error, $status); my $host = $_;
## Do something with $host;
$output = "Worker ". MCE->wid .": Hello from $host";
if (MCE->chunk_id % 3 == 0) {
## Simulating an error condition
local $? = 1; $status = $?;
$error = "Error from $host"
}
else {
$status = 0;
}
## Ensure unique keys (key, value) when gathering to
## a hash.
MCE->gather("$host.out", $output);
MCE->gather("$host.err", $error) if (defined $error);
MCE->gather("$host.sta", $status);
}, @hosts;
foreach my $host (@hosts) {
print $h3{"$host.out"}, "\n";
print $h3{"$host.err"}, "\n" if (exists $h3{"$host.err"});
print "Exit status: ", $h3{"$host.sta"}, "\n\n";
}
-- Output
Worker 3: Hello from hosta
Exit status: 0
Worker 2: Hello from hostb
Exit status: 0
Worker 1: Hello from hostc
Error from hostc
Exit status: 1
Worker 3: Hello from hostd
Exit status: 0
Worker 2: Hello from hoste
Exit status: 0The following uses an anonymous array containing 3 elements when gathering data. Serialization is automatic behind the scene.
my %h3 = mce_step sub {
...
MCE->gather($host, [$output, $error, $status]);
}, @hosts;
foreach my $host (@hosts) {
print $h3{$host}->[0], "\n";
print $h3{$host}->[1], "\n" if (defined $h3{$host}->[1]);
print "Exit status: ", $h3{$host}->[2], "\n\n";
}Although MCE::Map comes to mind, one may want additional control when gathering data such as retaining output order.
use MCE::Step;
sub preserve_order {
my %tmp; my $order_id = 1; my $gather_ref = $_[0];
return sub {
$tmp{ (shift) } = \@_;
while (1) {
last unless exists $tmp{$order_id};
push @{ $gather_ref }, @{ delete $tmp{$order_id++} };
}
return;
};
}
## Workers persist for the most part after running. Though, not always
## the case and depends on Perl. Pass a reference to a subroutine if
## workers must persist; e.g. mce_step { ... }, \&foo, 1..100000.
MCE::Step->init(
chunk_size => 'auto', max_workers => 'auto'
);
for (1..2) {
my @m2;
mce_step {
gather => preserve_order(\@m2)
},
sub {
my @a; my ($mce, $chunk_ref, $chunk_id) = @_;
## Compute the entire chunk data at once.
push @a, map { $_ * 2 } @{ $chunk_ref };
## Afterwards, invoke the gather feature, which
## will direct the data to the callback function.
MCE->gather(MCE->chunk_id, @a);
}, 1..100000;
print scalar @m2, "\n";
}
MCE::Step->finish;All 6 models support 'auto' for chunk_size unlike the Core API. Think of the models as the basis for providing JIT for MCE. They create the instance, tune max_workers, and tune chunk_size automatically regardless of the hardware.
The following does the same thing using the Core API. Workers persist after running.
use MCE;
sub preserve_order {
...
}
my $mce = MCE->new(
max_workers => 'auto', chunk_size => 8000,
user_func => sub {
my @a; my ($mce, $chunk_ref, $chunk_id) = @_;
## Compute the entire chunk data at once.
push @a, map { $_ * 2 } @{ $chunk_ref };
## Afterwards, invoke the gather feature, which
## will direct the data to the callback function.
MCE->gather(MCE->chunk_id, @a);
}
);
for (1..2) {
my @m2;
$mce->process({ gather => preserve_order(\@m2) }, [1..100000]);
print scalar @m2, "\n";
}
$mce->shutdown;Workers remain persistent as much as possible after running. Shutdown occurs automatically when the script terminates. Call finish when workers are no longer needed.
use MCE::Step;
MCE::Step->init(
chunk_size => 20, max_workers => 'auto'
);
mce_step sub { ... }, 1..100;
MCE::Step->finish;Mario E. Roy, <marioeroy AT gmail DOT com>