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 $array=<array>; sort { -$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=<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=<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 $array=<array>; my @keys = map { -$_ } @$array; my @indexes = 0..$#{$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 $array=<array>; Sort::Key::nkeysort(sub { -$_ }, @$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
<https://metacpan.org/release/Bencher-Scenario-SortingByKey>.
SOURCE
Source repository is at
<https://github.com/perlancar/perl-Bencher-Scenario-SortingByKey>.
BUGS
Please report any bugs or feature requests on the bugtracker website
<https://rt.cpan.org/Public/Dist/Display.html?Name=Bencher-Scenario-Sort
ingByKey>
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. <http://www.sysarch.com/Perl/sort_paper.html>. This is the
original paper that mentions GRT.
<https://www.perlmonks.org/?node_id=145659>
<https://www.perlmonks.org/?node_id=287149>
Sort::Maker, also by Uri Guttman, describes the various sort techniques
(ST, GRT, etc).
Sort::Key by Salvador Fandiño GarcÃa.
AUTHOR
perlancar <perlancar@cpan.org>
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.