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

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.