NAME
Acme::CPANModules::OrderedHash - List of modules that provide ordered hash data type
VERSION
This document describes version 0.003 of Acme::CPANModules::OrderedHash (from Perl distribution Acme-CPANModules-OrderedHash), released on 2023-10-06.
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 bencher or run bencher --help
.
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:
Tie::SortHash - will automatically sort keys when you call keys()
, values()
, each()
. But this module does not maintain insertion order.
ACME::CPANMODULES ENTRIES
- Tie::IxHash
-
Author: CHORNY
- Hash::Ordered
-
Author: DAGOLDEN
- Tie::Hash::Indexed
-
Author: MHX
Provides two interfaces: tied hash and OO.
- Tie::LLHash
-
Author: XAERXESS
- Tie::StoredOrderHash
-
Author: TFM
- Array::OrdHash
-
Author: WOWASURIN
Provide something closest to PHP's associative array, where you can refer elements by key or by numeric index, and insertion order is remembered.
- List::Unique::DeterministicOrder
-
Author: SLAFFAN
Provide a list, not hash.
BENCHMARKED MODULES
Version numbers shown below are the versions used when running the sample benchmark.
Tie::IxHash 1.23
Hash::Ordered 0.014
Tie::Hash::Indexed 0.08
Tie::LLHash 1.004
Tie::StoredOrderHash 0.22
Array::OrdHash 1.03
List::Unique::DeterministicOrder 0.004
BENCHMARK PARTICIPANTS
Tie::IxHash (perl_code)
Hash::Ordered (perl_code)
Tie::Hash::Indexed (perl_code)
Tie::LLHash (perl_code)
Tie::StoredOrderHash (perl_code)
Array::OrdHash (perl_code)
List::Unique::DeterministicOrder (perl_code) [no_iterate]
BENCHMARK DATASETS
insert 1000 pairs
insert 1000 pairs + delete
insert 1000 pairs + return keys 100 times
insert 1000 pairs + iterate 10 times
BENCHMARK SAMPLE RESULTS
Sample benchmark #1
Run on: perl: v5.38.0, CPU: Intel(R) Core(TM) i5-7200U CPU @ 2.50GHz (2 cores), OS: GNU/Linux Ubuntu version 20.04, OS kernel: Linux version 5.4.0-91-generic.
Benchmark command (default options):
% bencher --cpanmodules-module OrderedHash
Result formatted as table (split, part 1 of 4):
#table1#
{dataset=>"insert 1000 pairs"}
+----------------------------------+------------+-----------+-----------+-----------------------+-----------------------+---------+---------+
| participant | p_tags | rate (/s) | time (ms) | pct_faster_vs_slowest | pct_slower_vs_fastest | errors | samples |
+----------------------------------+------------+-----------+-----------+-----------------------+-----------------------+---------+---------+
| Tie::StoredOrderHash | | 360 | 2.78 | 0.00% | 197.99% | 1.1e-06 | 20 |
| Tie::LLHash | | 380 | 2.6 | 6.60% | 179.55% | 1.3e-05 | 20 |
| Array::OrdHash | | 540 | 1.9 | 49.87% | 98.83% | 3.2e-06 | 20 |
| Tie::Hash::Indexed | | 700 | 2 | 81.84% | 63.87% | 7.2e-05 | 22 |
| Tie::IxHash | | 676 | 1.48 | 87.57% | 58.87% | 9.9e-07 | 20 |
| Hash::Ordered | | 884 | 1.13 | 145.25% | 21.50% | 1.1e-06 | 21 |
| List::Unique::DeterministicOrder | no_iterate | 1070 | 0.931 | 197.99% | 0.00% | 8e-07 | 21 |
+----------------------------------+------------+-----------+-----------+-----------------------+-----------------------+---------+---------+
The above result formatted in Benchmark.pm style:
Rate T:S T:L TH:I A:O T:I H:O LU:D no_iterate
T:S 360/s -- -6% -28% -31% -46% -59% -66%
T:L 380/s 6% -- -23% -26% -43% -56% -64%
TH:I 700/s 38% 30% -- -5% -26% -43% -53%
A:O 540/s 46% 36% 5% -- -22% -40% -51%
T:I 676/s 87% 75% 35% 28% -- -23% -37%
H:O 884/s 146% 130% 76% 68% 30% -- -17%
LU:D no_iterate 1070/s 198% 179% 114% 104% 58% 21% --
Legends:
A:O : p_tags= participant=Array::OrdHash
H:O : p_tags= participant=Hash::Ordered
LU:D no_iterate: p_tags=no_iterate participant=List::Unique::DeterministicOrder
T:I : p_tags= participant=Tie::IxHash
T:L : p_tags= participant=Tie::LLHash
T:S : p_tags= participant=Tie::StoredOrderHash
TH:I : p_tags= participant=Tie::Hash::Indexed
The above result presented as chart:
Result formatted as table (split, part 2 of 4):
#table2#
{dataset=>"insert 1000 pairs + delete"}
+----------------------------------+------------+-----------+-----------+-----------------------+-----------------------+---------+---------+
| participant | p_tags | rate (/s) | time (ms) | pct_faster_vs_slowest | pct_slower_vs_fastest | errors | samples |
+----------------------------------+------------+-----------+-----------+-----------------------+-----------------------+---------+---------+
| Tie::IxHash | | 17 | 58.8 | 0.00% | 3799.19% | 4.1e-05 | 20 |
| Tie::StoredOrderHash | | 200 | 5 | 1070.77% | 233.04% | 1.1e-05 | 20 |
| Tie::LLHash | | 220 | 4.6 | 1191.67% | 201.87% | 1.4e-05 | 21 |
| Array::OrdHash | | 279 | 3.59 | 1537.64% | 138.10% | 2.8e-06 | 21 |
| Hash::Ordered | | 370 | 2.7 | 2087.76% | 78.23% | 4.9e-06 | 20 |
| List::Unique::DeterministicOrder | no_iterate | 604 | 1.66 | 3450.01% | 9.84% | 5.1e-07 | 20 |
| Tie::Hash::Indexed | | 663 | 1.51 | 3799.19% | 0.00% | 6e-07 | 20 |
+----------------------------------+------------+-----------+-----------+-----------------------+-----------------------+---------+---------+
The above result formatted in Benchmark.pm style:
Rate T:I T:S T:L A:O H:O LU:D no_iterate TH:I
T:I 17/s -- -91% -92% -93% -95% -97% -97%
T:S 200/s 1076% -- -8% -28% -46% -66% -69%
T:L 220/s 1178% 8% -- -21% -41% -63% -67%
A:O 279/s 1537% 39% 28% -- -24% -53% -57%
H:O 370/s 2077% 85% 70% 32% -- -38% -44%
LU:D no_iterate 604/s 3442% 201% 177% 116% 62% -- -9%
TH:I 663/s 3794% 231% 204% 137% 78% 9% --
Legends:
A:O : p_tags= participant=Array::OrdHash
H:O : p_tags= participant=Hash::Ordered
LU:D no_iterate: p_tags=no_iterate participant=List::Unique::DeterministicOrder
T:I : p_tags= participant=Tie::IxHash
T:L : p_tags= participant=Tie::LLHash
T:S : p_tags= participant=Tie::StoredOrderHash
TH:I : p_tags= participant=Tie::Hash::Indexed
The above result presented as chart:
Result formatted as table (split, part 3 of 4):
#table3#
{dataset=>"insert 1000 pairs + iterate 10 times"}
+----------------------+-----------+-----------+-----------------------+-----------------------+---------+---------+
| participant | rate (/s) | time (ms) | pct_faster_vs_slowest | pct_slower_vs_fastest | errors | samples |
+----------------------+-----------+-----------+-----------------------+-----------------------+---------+---------+
| Tie::LLHash | 45 | 22 | 0.00% | 206.84% | 4.1e-05 | 21 |
| Tie::StoredOrderHash | 46 | 21.7 | 2.02% | 200.75% | 9.4e-06 | 20 |
| Array::OrdHash | 51.4 | 19.5 | 13.93% | 169.32% | 1.4e-05 | 21 |
| Tie::IxHash | 65.1 | 15.4 | 44.41% | 112.47% | 9.4e-06 | 20 |
| Tie::Hash::Indexed | 97.5 | 10.3 | 116.20% | 41.93% | 9.3e-06 | 20 |
| Hash::Ordered | 140 | 7.2 | 206.84% | 0.00% | 6.4e-05 | 20 |
+----------------------+-----------+-----------+-----------------------+-----------------------+---------+---------+
The above result formatted in Benchmark.pm style:
Rate T:L T:S A:O T:I TH:I H:O
T:L 45/s -- -1% -11% -29% -53% -67%
T:S 46/s 1% -- -10% -29% -52% -66%
A:O 51.4/s 12% 11% -- -21% -47% -63%
T:I 65.1/s 42% 40% 26% -- -33% -53%
TH:I 97.5/s 113% 110% 89% 49% -- -30%
H:O 140/s 205% 201% 170% 113% 43% --
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
The above result presented as chart:
Result formatted as table (split, part 4 of 4):
#table4#
{dataset=>"insert 1000 pairs + return keys 100 times"}
+----------------------------------+------------+-----------+-----------+-----------------------+-----------------------+-----------+---------+
| participant | p_tags | rate (/s) | time (ms) | pct_faster_vs_slowest | pct_slower_vs_fastest | errors | samples |
+----------------------------------+------------+-----------+-----------+-----------------------+-----------------------+-----------+---------+
| Tie::StoredOrderHash | | 10.7 | 93.2 | 0.00% | 845.55% | 5.8e-05 | 20 |
| Tie::LLHash | | 12 | 86 | 8.76% | 769.40% | 0.00011 | 20 |
| Array::OrdHash | | 14 | 70 | 32.35% | 614.46% | 0.0001 | 20 |
| Tie::IxHash | | 16.2 | 61.8 | 50.70% | 527.45% | 5.4e-05 | 20 |
| Tie::Hash::Indexed | | 24 | 41 | 124.79% | 320.64% | 0.0001 | 20 |
| Hash::Ordered | | 78.3 | 12.8 | 629.18% | 29.67% | 4.2e-06 | 20 |
| List::Unique::DeterministicOrder | no_iterate | 101 | 9.85 | 845.55% | 0.00% | 2.2e-06 | 22 |
+----------------------------------+------------+-----------+-----------+-----------------------+-----------------------+-----------+---------+
The above result formatted in Benchmark.pm style:
Rate T:S T:L A:O T:I TH:I H:O LU:D no_iterate
T:S 10.7/s -- -7% -24% -33% -56% -86% -89%
T:L 12/s 8% -- -18% -28% -52% -85% -88%
A:O 14/s 33% 22% -- -11% -41% -81% -85%
T:I 16.2/s 50% 39% 13% -- -33% -79% -84%
TH:I 24/s 127% 109% 70% 50% -- -68% -75%
H:O 78.3/s 628% 571% 446% 382% 220% -- -23%
LU:D no_iterate 101/s 846% 773% 610% 527% 316% 29% --
Legends:
A:O : p_tags= participant=Array::OrdHash
H:O : p_tags= participant=Hash::Ordered
LU:D no_iterate: p_tags=no_iterate participant=List::Unique::DeterministicOrder
T:I : p_tags= participant=Tie::IxHash
T:L : p_tags= participant=Tie::LLHash
T:S : p_tags= participant=Tie::StoredOrderHash
TH:I : p_tags= participant=Tie::Hash::Indexed
The above result presented as chart:
Sample benchmark #2
Benchmark command (benchmarking module startup overhead):
% bencher --cpanmodules-module OrderedHash --module-startup
Result formatted as table:
#table5#
+----------------------------------+-----------+-------------------+-----------------------+-----------------------+---------+---------+
| participant | time (ms) | mod_overhead_time | pct_faster_vs_slowest | pct_slower_vs_fastest | errors | samples |
+----------------------------------+-----------+-------------------+-----------------------+-----------------------+---------+---------+
| List::Unique::DeterministicOrder | 16.2 | 8.5 | 0.00% | 110.26% | 7.7e-06 | 20 |
| Hash::Ordered | 15.9 | 8.2 | 1.50% | 107.15% | 6e-06 | 20 |
| Tie::Hash::Indexed | 15.5 | 7.8 | 4.57% | 101.06% | 4.9e-06 | 22 |
| Array::OrdHash | 15 | 7.3 | 7.86% | 94.94% | 1.1e-05 | 20 |
| Tie::IxHash | 14.9 | 7.2 | 8.49% | 93.81% | 9e-06 | 20 |
| Tie::LLHash | 13.6 | 5.9 | 18.93% | 76.79% | 7.4e-06 | 20 |
| Tie::StoredOrderHash | 10.7 | 3 | 51.34% | 38.93% | 5.9e-06 | 20 |
| perl -e1 (baseline) | 7.7 | 0 | 110.26% | 0.00% | 3.4e-05 | 20 |
+----------------------------------+-----------+-------------------+-----------------------+-----------------------+---------+---------+
The above result formatted in Benchmark.pm style:
Rate LU:D H:O TH:I A:O T:I T:L T:S perl -e1 (baseline)
LU:D 61.7/s -- -1% -4% -7% -8% -16% -33% -52%
H:O 62.9/s 1% -- -2% -5% -6% -14% -32% -51%
TH:I 64.5/s 4% 2% -- -3% -3% -12% -30% -50%
A:O 66.7/s 7% 6% 3% -- 0% -9% -28% -48%
T:I 67.1/s 8% 6% 4% 0% -- -8% -28% -48%
T:L 73.5/s 19% 16% 13% 10% 9% -- -21% -43%
T:S 93.5/s 51% 48% 44% 40% 39% 27% -- -28%
perl -e1 (baseline) 129.9/s 110% 106% 101% 94% 93% 76% 38% --
Legends:
A:O: mod_overhead_time=7.3 participant=Array::OrdHash
H:O: mod_overhead_time=8.2 participant=Hash::Ordered
LU:D: mod_overhead_time=8.5 participant=List::Unique::DeterministicOrder
T:I: mod_overhead_time=7.2 participant=Tie::IxHash
T:L: mod_overhead_time=5.9 participant=Tie::LLHash
T:S: mod_overhead_time=3 participant=Tie::StoredOrderHash
TH:I: mod_overhead_time=7.8 participant=Tie::Hash::Indexed
perl -e1 (baseline): mod_overhead_time=0 participant=perl -e1 (baseline)
The above result presented as chart:
To display as an interactive HTML table on a browser, you can add option --format html+datatables
.
BENCHMARK NOTES
Hash::Ordered has strong performance in iterating and returning keys, while List::Unique::DeterministicOrder is strong in insertion and deletion (or Tie::Hash::Indexed if you're looking for actual hash type).
FAQ
What is an Acme::CPANModules::* module?
An Acme::CPANModules::* module, like this module, contains just a list of module names that share a common characteristics. It is a way to categorize modules and document CPAN. See Acme::CPANModules for more details.
What are ways to use this Acme::CPANModules module?
Aside from reading this Acme::CPANModules module's POD documentation, you can install all the listed modules (entries) using cpanm-cpanmodules script (from App::cpanm::cpanmodules distribution):
% cpanm-cpanmodules -n OrderedHash
Alternatively you can use the cpanmodules CLI (from App::cpanmodules distribution):
% cpanmodules ls-entries OrderedHash | cpanm -n
or Acme::CM::Get:
% perl -MAcme::CM::Get=OrderedHash -E'say $_->{module} for @{ $LIST->{entries} }' | cpanm -n
or directly:
% perl -MAcme::CPANModules::OrderedHash -E'say $_->{module} for @{ $Acme::CPANModules::OrderedHash::LIST->{entries} }' | cpanm -n
This Acme::CPANModules module contains benchmark instructions. You can run a benchmark for some/all the modules listed in this Acme::CPANModules module using the bencher CLI (from Bencher distribution):
% bencher --cpanmodules-module OrderedHash
This Acme::CPANModules module also helps lcpan produce a more meaningful result for lcpan related-mods
command when it comes to finding related modules for the modules listed in this Acme::CPANModules module. See App::lcpan::Cmd::related_mods for more details on how "related modules" are found.
HOMEPAGE
Please visit the project's homepage at https://metacpan.org/release/Acme-CPANModules-OrderedHash.
SOURCE
Source repository is at https://github.com/perlancar/perl-Acme-CPANModules-OrderedHash.
SEE ALSO
Acme::CPANModules::HashUtilities
Acme::CPANModules - about the Acme::CPANModules namespace
cpanmodules - CLI tool to let you browse/view the lists
AUTHOR
perlancar <perlancar@cpan.org>
CONTRIBUTING
To contribute, you can send patches by email/via RT, or send pull requests on GitHub.
Most of the time, you don't need to build the distribution yourself. You can simply modify the code, then test via:
% prove -l
If you want to build the distribution (e.g. to try to install it locally on your system), you can install Dist::Zilla, Dist::Zilla::PluginBundle::Author::PERLANCAR, Pod::Weaver::PluginBundle::Author::PERLANCAR, and sometimes one or two other Dist::Zilla- and/or Pod::Weaver plugins. Any additional steps required beyond that are considered a bug and can be reported to me.
COPYRIGHT AND LICENSE
This software is copyright (c) 2023 by perlancar <perlancar@cpan.org>.
This is free software; you can redistribute it and/or modify it under the same terms as the Perl 5 programming language system itself.
BUGS
Please report any bugs or feature requests on the bugtracker website https://rt.cpan.org/Public/Dist/Display.html?Name=Acme-CPANModules-OrderedHash
When submitting a bug or request, please include a test-file or a patch to an existing test-file that illustrates the bug or desired feature.