Acme-CPANModules-OrderedHash
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lib/Acme/CPANModules/OrderedHash.pm view on Meta::CPAN
for (1..$numrep) { my @keys = $hash->keys }
} elsif ($op eq 'iterate') {
for (1..$numrep) { while (my ($k,$v) = each %$hash) {} }
}
},
},
{
module => 'Tree::RB::XS',
description => <<'MARKDOWN',
Multi-purpose tree data structure which can record insertion order and act as an
ordered hash. Use `track_recent => 1, keys_in_recent_order => 1` options. Can
be used as a tied hash, or as an object (faster).
MARKDOWN
bench_code => sub {
my ($op, $numkeys, $numrep) = @_;
my $tree= Tree::RB::XS->new(compare_fn => 'str', track_recent => 1, keys_in_recent_order => 1);
for (1..$numkeys) { $tree->insert("key$_") }
if ($op eq 'delete') {
for (1..$numkeys) { $tree->delete("key$_") }
} elsif ($op eq 'keys') {
for (1..$numrep) { my @keys= $tree->keys }
} elsif ($op eq 'iterate') {
for (1..$numrep) { my $iter = $tree->iter; while (my $v = $iter->next) {} }
}
},
},
],
bench_datasets => [
{name=>'insert 1000 pairs', argv => ['insert', 1000]},
{name=>'insert 1000 pairs + delete', argv => ['delete', 1000]},
{name=>'insert 1000 pairs + return keys 100 times', argv => ['keys', 1000, 100]},
{name=>'insert 1000 pairs + iterate 10 times', argv => ['iterate', 1000, 10], exclude_participant_tags => ['no_iterate']},
],
};
1;
# ABSTRACT: List of modules that provide ordered hash data type
__END__
=pod
=encoding UTF-8
=head1 NAME
Acme::CPANModules::OrderedHash - List of modules that provide ordered hash data type
=head1 VERSION
This document describes version 0.004 of Acme::CPANModules::OrderedHash (from Perl distribution Acme-CPANModules-OrderedHash), released on 2025-04-15.
=head1 SYNOPSIS
To run benchmark with default option:
% bencher --cpanmodules-module OrderedHash
To run module startup overhead benchmark:
% bencher --module-startup --cpanmodules-module OrderedHash
For more options (dump scenario, list/include/exclude/add participants, list/include/exclude/add datasets, etc), see L<bencher> or run C<bencher --help>.
=head1 DESCRIPTION
When you ask a Perl's hash for the list of keys, the answer comes back
unordered. In fact, Perl explicitly randomizes the order of keys it returns
everytime. The random ordering is a (security) feature, not a bug. However,
sometimes you want to know the order of insertion. These modules provide you
with an ordered hash; most of them implement it by recording the order of
insertion of keys in an additional array.
Other related modules:
L<Tie::SortHash> - will automatically sort keys when you call C<keys()>,
C<values()>, C<each()>. But this module does not maintain insertion order.
=head1 ACME::CPANMODULES ENTRIES
=over
=item L<Tie::IxHash>
=item L<Hash::Ordered>
=item L<Tie::Hash::Indexed>
Provides two interfaces: tied hash and OO.
=item L<Tie::LLHash>
=item L<Tie::StoredOrderHash>
=item L<Array::OrdHash>
Provide something closest to PHP's associative array, where you can refer
elements by key or by numeric index, and insertion order is remembered.
=item L<List::Unique::DeterministicOrder>
Provide a list, not hash.
=item L<Tree::RB::XS>
Multi-purpose tree data structure which can record insertion order and act as an
ordered hash. Use C<< track_recent =E<gt> 1, keys_in_recent_order =E<gt> 1 >> options. Can
be used as a tied hash, or as an object (faster).
=back
lib/Acme/CPANModules/OrderedHash.pm view on Meta::CPAN
=item * Hash::Ordered (perl_code)
L<Hash::Ordered>
=item * Tie::Hash::Indexed (perl_code)
L<Tie::Hash::Indexed>
=item * Tie::LLHash (perl_code)
L<Tie::LLHash>
=item * Tie::StoredOrderHash (perl_code)
L<Tie::StoredOrderHash>
=item * Array::OrdHash (perl_code)
L<Array::OrdHash>
=item * Tree::RB::XS (perl_code)
L<Tree::RB::XS>
=back
=head1 BENCHMARK DATASETS
=over
=item * insert 1000 pairs
=item * insert 1000 pairs + delete
=item * insert 1000 pairs + return keys 100 times
=item * insert 1000 pairs + iterate 10 times
=back
=head1 BENCHMARK SAMPLE RESULTS
=head2 Sample benchmark #1
Run on: perl: I<< v5.40.1 >>, CPU: I<< AMD Ryzen 5 7535HS with Radeon Graphics (6 cores) >>, OS: I<< GNU/Linux Ubuntu version 24.10 >>, OS kernel: I<< Linux version 6.11.0-8-generic >>.
Benchmark command (default options):
% bencher --cpanmodules-module OrderedHash
Result formatted as table (split, part 1 of 4):
#table1#
{dataset=>"insert 1000 pairs"}
+----------------------+-----------+-----------+-----------------------+-----------------------+---------+---------+
| participant | rate (/s) | time (ms) | pct_faster_vs_slowest | pct_slower_vs_fastest | errors | samples |
+----------------------+-----------+-----------+-----------------------+-----------------------+---------+---------+
| Tie::StoredOrderHash | 539 | 1.85 | 0.00% | 528.45% | 1.4e-06 | 22 |
| Tie::LLHash | 640 | 1.6 | 19.19% | 427.28% | 3.4e-06 | 20 |
| Array::OrdHash | 889 | 1.12 | 64.84% | 281.24% | 9.6e-07 | 20 |
| Tie::IxHash | 1080 | 0.928 | 99.73% | 214.65% | 6.1e-07 | 20 |
| Hash::Ordered | 1460 | 0.684 | 170.98% | 131.92% | 4.1e-07 | 20 |
| Tie::Hash::Indexed | 1600 | 0.62 | 196.91% | 111.67% | 9.6e-07 | 20 |
| Tree::RB::XS | 3400 | 0.3 | 528.45% | 0.00% | 5.4e-07 | 21 |
+----------------------+-----------+-----------+-----------------------+-----------------------+---------+---------+
The above result formatted in L<Benchmark.pm|Benchmark> style:
Rate T:S T:L A:O T:I H:O TH:I TR:X
T:S 539/s -- -13% -39% -49% -63% -66% -83%
T:L 640/s 15% -- -29% -42% -57% -61% -81%
A:O 889/s 65% 42% -- -17% -38% -44% -73%
T:I 1080/s 99% 72% 20% -- -26% -33% -67%
H:O 1460/s 170% 133% 63% 35% -- -9% -56%
TH:I 1600/s 198% 158% 80% 49% 10% -- -51%
TR:X 3400/s 516% 433% 273% 209% 128% 106% --
Legends:
A:O: participant=Array::OrdHash
H:O: participant=Hash::Ordered
T:I: participant=Tie::IxHash
T:L: participant=Tie::LLHash
T:S: participant=Tie::StoredOrderHash
TH:I: participant=Tie::Hash::Indexed
TR:X: participant=Tree::RB::XS
The above result presented as chart:
=begin html
<img src="data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAtAAAAH4CAMAAABUnipoAAAAIGNIUk0AAHomAACAhAAA+gAAAIDoAAB1MAAA6mAAADqYAAAXcJy6UTwAAADDUExURf///wAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA...
=end html
Result formatted as table (split, part 2 of 4):
#table2#
{dataset=>"insert 1000 pairs + delete"}
+----------------------+-----------+-----------+-----------------------+-----------------------+---------+---------+
| participant | rate (/s) | time (ms) | pct_faster_vs_slowest | pct_slower_vs_fastest | errors | samples |
+----------------------+-----------+-----------+-----------------------+-----------------------+---------+---------+
| Tie::IxHash | 31 | 32 | 0.00% | 5838.76% | 4.8e-05 | 21 |
| Tie::StoredOrderHash | 310 | 3.3 | 875.00% | 509.10% | 8.6e-06 | 21 |
| Tie::LLHash | 376 | 2.66 | 1098.31% | 395.59% | 2.5e-06 | 20 |
| Array::OrdHash | 440 | 2.3 | 1289.81% | 327.31% | 6.1e-06 | 20 |
| Hash::Ordered | 610 | 1.6 | 1854.01% | 203.93% | 1.9e-06 | 20 |
( run in 0.912 second using v1.01-cache-2.11-cpan-140bd7fdf52 )