BTW. Always, the easiest, safest way to approach threading complex applications, is to write a single-threaded version that operates upon the data in a serial fashion.
Once you have that working, if the data is truly independent, parallelising it is usually quite simple.
For completeness, here is another example based on yours that uses a pool of threads. It is hardly more complicated than the first version: #! perl -slw
use strict;
use threads;
use threads::shared;
use Thread::Queue;
use Data::Dump qw[ pp ];
sub helper {
my $Q = shift;
while( my $ref = $Q->dequeue ) {;
lock $ref;
$ref->{NEW_KEY} = 1;
}
}
sub my_sub {
my( $ref, $n ) = @_;
my $Q = new Thread::Queue;
my @threads = map async( \&helper, $Q ), 1 .. $n;
$Q->enqueue( values %{ $ref } );
$Q->enqueue( (undef) x $n );
$_->join for @threads;
}
my $hoh = {
A => shared_clone( { NAME => 'aa' } ),
B => shared_clone( { NAME => 'bb' } ),
};
pp $hoh;
my_sub( $hoh, 2 );
pp $hoh;
The output is identical to the earlier version.
Examine what is said, not who speaks -- Silence betokens consent -- Love the truth but pardon error.
"Science is about questioning the status quo. Questioning authority".
In the absence of evidence, opinion is indistinguishable from prejudice.
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