NAME Bencher::Scenario::SortingByKey - Benchmark various techniques to sort array by some computed key VERSION This document describes version 0.002 of Bencher::Scenario::SortingByKey (from Perl distribution Bencher-Scenario-SortingByKey), released on 2019-12-25. SYNOPSIS To run benchmark with default option: % bencher -m SortingByKey To run module startup overhead benchmark: % bencher --module-startup -m SortingByKey For more options (dump scenario, list/include/exclude/add participants, list/include/exclude/add datasets, etc), see bencher or run "bencher --help". DESCRIPTION Packaging a benchmark script as a Bencher scenario makes it convenient to include/exclude/add participants/datasets (either via CLI or Perl code), send the result to a central repository, among others . See Bencher and bencher (CLI) for more details. BENCHMARKED MODULES Version numbers shown below are the versions used when running the sample benchmark. Sort::Key 1.33 BENCHMARK PARTICIPANTS * uncached (perl_code) Code template: state $array=; sort { -$a <=> -$b } @$array This technique does not cache the sort key and computes it everytime they are compared. This performance of this technique depends on how expensive the computation of key is. (In this benchmark, the computation is very cheap.) In Perl code: @sorted = sort { GEN_KEY($a) cmp GEN_KEY($b) } @array; * ST (perl_code) Code template: state $array=; map { $_->[0] } sort { $a->[1] <=> $b->[1] } map { [$_, -$_] } @$array Schwartzian transform (also known as map/sort/map technique) caches the sort key in an arrayref. It works by constructing, for each array element, a container record (most often anonymous arrayref) containing the original element and the key to be sorted. Later after the sort, it discards the anonymous arrayrefs. The arrayref construction is a significant part of the total cost, especially for larger arrays. In Perl code: @sorted = map { $_->[0] } sort { $a->[1] <=> $b->[1] } map { [$_, GEN_KEY($_)] } @array; * GRT (perl_code) Code template: state $array=; map { $_->[0] } sort { $a->[1] <=> $b->[1] } map { [$_, -$_] } @$array Guttman-Rosler transform, another map/sort/map technique, is similar to ST. The difference is, the computed key is transformed into a fixed-length string that can be compared lexicographically (thus eliminating the need for the Perl custom sort block). The original element is also transformed as a string and concatenated into the string. Thus, GRT avoids the construction of the anonymous arrayrefs. As a downside, the construction of the key string can be tricky. In Perl code (assuming the compute key is transformed into a fixed 4-byte string: @sorted = map { substr($_, 4) } sort map { pack("NN", -$_, $_) } @array; * 2array (perl_code) Code template: state $array=; my @keys = map { -$_ } @$array; my @indexes = 0..$#{$array}; map { $array->[$_] } sort { $keys[$a] <=> $keys[$b] } @indexes This technique caches the compute key in a single array. It also constructs an array of indexes, sorts the array according to the array keys, then constructs the final sorted array using the sorted indexes. Compared to GRT, it constructs far fewer anonymous arrayrefs. But it still requires Perl custom sort block. In Perl code: @indexes = 0 .. $#array; @keys = map { GEN_KEY($_) } @array; @sorted = map { $array[$_] } sort { $keys[$a] <=> $keys[$b] } @indexes; * Sort::Key::nkeysort (perl_code) Code template: state $array=; Sort::Key::nkeysort(sub { -$_ }, @$array) This module also caches the compute keys. It's faster because it's implemented in XS. The compute key must be string (to be compared lexicographically) or numeric. BENCHMARK DATASETS * 10 * 100 * 1000 * 10000 SAMPLE BENCHMARK RESULTS Run on: perl: *v5.30.0*, CPU: *Intel(R) Core(TM) i5-7200U CPU @ 2.50GHz (2 cores)*, OS: *GNU/Linux Ubuntu version 19.04*, OS kernel: *Linux version 5.0.0-37-generic*. Benchmark with default options ("bencher -m SortingByKey"): #table1# {dataset=>10} +---------------------+-----------+-----------+------------+---------+---------+ | participant | rate (/s) | time (μs) | vs_slowest | errors | samples | +---------------------+-----------+-----------+------------+---------+---------+ | GRT | 203230 | 4.9206 | 1 | 5.8e-12 | 20 | | ST | 207000 | 4.84 | 1.02 | 1.5e-09 | 26 | | 2array | 320000 | 3.13 | 1.57 | 1.6e-09 | 23 | | Sort::Key::nkeysort | 506900 | 1.973 | 2.494 | 2.3e-11 | 22 | | uncached | 25000000 | 0.04 | 123 | 2.3e-11 | 20 | +---------------------+-----------+-----------+------------+---------+---------+ #table2# {dataset=>100} +---------------------+-----------+-----------+------------+---------+---------+ | participant | rate (/s) | time (μs) | vs_slowest | errors | samples | +---------------------+-----------+-----------+------------+---------+---------+ | GRT | 13000 | 75 | 1 | 2.1e-07 | 20 | | ST | 13000 | 75 | 1 | 1.3e-07 | 20 | | 2array | 23400 | 42.8 | 1.75 | 1.2e-08 | 26 | | Sort::Key::nkeysort | 51900 | 19.3 | 3.88 | 5.2e-09 | 33 | | uncached | 9830000 | 0.102 | 736 | 5.2e-11 | 20 | +---------------------+-----------+-----------+------------+---------+---------+ #table3# {dataset=>1000} +---------------------+-----------+-----------+------------+---------+---------+ | participant | rate (/s) | time (μs) | vs_slowest | errors | samples | +---------------------+-----------+-----------+------------+---------+---------+ | GRT | 930 | 1100 | 1 | 1.7e-06 | 20 | | ST | 940 | 1100 | 1 | 2e-06 | 21 | | 2array | 1580 | 634 | 1.69 | 2.1e-07 | 20 | | Sort::Key::nkeysort | 3820 | 261 | 4.1 | 5.3e-08 | 20 | | uncached | 1456000 | 0.687 | 1561 | 1.7e-11 | 20 | +---------------------+-----------+-----------+------------+---------+---------+ #table4# {dataset=>10000} +---------------------+-----------+-------------+------------+---------+---------+ | participant | rate (/s) | time (ms) | vs_slowest | errors | samples | +---------------------+-----------+-------------+------------+---------+---------+ | GRT | 67.6 | 14.8 | 1 | 1.3e-05 | 20 | | ST | 67.9 | 14.7 | 1 | 7e-06 | 20 | | 2array | 122 | 8.22 | 1.8 | 1.8e-06 | 20 | | Sort::Key::nkeysort | 320 | 3.1 | 4.8 | 6e-06 | 20 | | uncached | 149191 | 0.00670284 | 2206.16 | 5.7e-12 | 20 | +---------------------+-----------+-------------+------------+---------+---------+ Benchmark module startup overhead ("bencher -m SortingByKey --module-startup"): #table5# +---------------------+-----------+------------------------+------------+---------+---------+ | participant | time (ms) | mod_overhead_time (ms) | vs_slowest | errors | samples | +---------------------+-----------+------------------------+------------+---------+---------+ | Sort::Key | 13.4 | 7.4 | 1 | 9.4e-06 | 20 | | perl -e1 (baseline) | 6 | 0 | 2.2 | 9.4e-06 | 20 | +---------------------+-----------+------------------------+------------+---------+---------+ To display as an interactive HTML table on a browser, you can add option "--format html+datatables". HOMEPAGE Please visit the project's homepage at . SOURCE Source repository is at . BUGS Please report any bugs or feature requests on the bugtracker website 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. SEE ALSO Guttman, U., & Rosler, L. (2003). A fresh look at efficient perl sorting. . This is the original paper that mentions GRT. Sort::Maker, also by Uri Guttman, describes the various sort techniques (ST, GRT, etc). Sort::Key by Salvador Fandiño García. AUTHOR perlancar COPYRIGHT AND LICENSE This software is copyright (c) 2019 by 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.