Bencher::Scenario::DataCleansing::Object - Benchmark data cleansing (unblessing object)
This document describes version 0.005 of Bencher::Scenario::DataCleansing::Object (from Perl distribution Bencher-Scenarios-DataCleansing), released on 2019-09-11.
To run benchmark with default option:
% bencher -m DataCleansing::Object
To run module startup overhead benchmark:
% bencher --module-startup -m DataCleansing::Object
For more options (dump scenario, list/include/exclude/add participants, list/include/exclude/add datasets, etc), see bencher or run bencher --help.
bencher --help
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.
Version numbers shown below are the versions used when running the sample benchmark.
Acme::Damn 0.08
Data::Clean 0.505
Data::Rmap 0.65
JSON::PP 2.27400_02
Scalar::Util 1.5
Data::Clean-inplace (perl_code) [inplace]
Code template:
state $cl = Data::Clean->new(-obj => ["unbless"]); $cl->clean_in_place(<data>)
Data::Clean-clone (perl_code)
state $cl = Data::Clean->new(-obj => ["unbless"]); $cl->clone_and_clean(<data>)
JSON::PP (perl_code)
state $json = JSON::PP->new->allow_blessed(1)->convert_blessed(1); $json->decode($json->encode(<data>))
Data::Rmap (perl_code) [inplace]
my $data = <data>; Data::Rmap::rmap_ref(sub { Acme::Damn::damn($_) if Scalar::Util::blessed($_) }, $data); $data
ary100-u1-obj
A 100-element array containing 1 "unclean" data: object
ary100-u100-obj
A 100-element array containing 100 "unclean" data: object
ary10k-u1-obj
A 10k-element array containing 1 "unclean" data: object
ary10k-u10k-obj
A 10k-element array containing 10k "unclean" data: object
Run on: perl: v5.26.1, CPU: Intel(R) Core(TM) M-5Y71 CPU @ 1.20GHz (2 cores), OS: GNU/Linux LinuxMint version 18.3, OS kernel: Linux version 4.10.0-38-generic.
Benchmark with default options (bencher -m DataCleansing::Object):
bencher -m DataCleansing::Object
#table1# +---------------------+-----------------+---------+-----------+-----------+------------+---------+---------+ | participant | dataset | p_tags | rate (/s) | time (ms) | vs_slowest | errors | samples | +---------------------+-----------------+---------+-----------+-----------+------------+---------+---------+ | JSON::PP | ary10k-u1-obj | | 156 | 6.39 | 1 | 2.5e-06 | 23 | | Data::Clean-clone | ary10k-u10k-obj | | 200 | 5 | 1 | 5.8e-05 | 20 | | Data::Rmap | ary10k-u10k-obj | inplace | 216 | 4.62 | 1.38 | 4.4e-06 | 20 | | JSON::PP | ary10k-u10k-obj | | 227 | 4.41 | 1.45 | 1.3e-06 | 22 | | Data::Rmap | ary10k-u1-obj | inplace | 419 | 2.39 | 2.68 | 2.3e-06 | 20 | | Data::Clean-inplace | ary10k-u10k-obj | inplace | 976 | 1.02 | 6.24 | 2.7e-07 | 20 | | JSON::PP | ary100-u1-obj | | 1500 | 0.67 | 9.5 | 1.3e-06 | 20 | | Data::Clean-clone | ary100-u100-obj | | 1900 | 0.52 | 12 | 6.1e-07 | 22 | | JSON::PP | ary100-u100-obj | | 2000 | 0.51 | 12 | 6.4e-07 | 20 | | Data::Rmap | ary100-u100-obj | inplace | 2150 | 0.465 | 13.8 | 4.3e-07 | 20 | | Data::Clean-clone | ary10k-u1-obj | | 2470 | 0.405 | 15.8 | 3.7e-07 | 26 | | Data::Rmap | ary100-u1-obj | inplace | 3990 | 0.25 | 25.5 | 1.9e-07 | 24 | | Data::Clean-inplace | ary10k-u1-obj | inplace | 4080 | 0.245 | 26.1 | 4.6e-08 | 27 | | Data::Clean-inplace | ary100-u100-obj | inplace | 9700 | 0.1 | 62 | 2.2e-07 | 23 | | Data::Clean-clone | ary100-u1-obj | | 15000 | 0.067 | 95 | 1.1e-07 | 20 | | Data::Clean-inplace | ary100-u1-obj | inplace | 39000 | 0.026 | 250 | 1e-07 | 25 | +---------------------+-----------------+---------+-----------+-----------+------------+---------+---------+
Benchmark module startup overhead (bencher -m DataCleansing::Object --module-startup):
bencher -m DataCleansing::Object --module-startup
#table2# +---------------------+-----------+------------------------+------------+---------+---------+ | participant | time (ms) | mod_overhead_time (ms) | vs_slowest | errors | samples | +---------------------+-----------+------------------------+------------+---------+---------+ | JSON::PP | 27 | 20 | 1 | 4.6e-05 | 22 | | Data::Rmap | 14.9 | 7.9 | 1.82 | 1.3e-05 | 20 | | Data::Clean | 11 | 4 | 2.4 | 1.4e-05 | 20 | | perl -e1 (baseline) | 7 | 0 | 3.9 | 2.7e-05 | 20 | +---------------------+-----------+------------------------+------------+---------+---------+
To display as an interactive HTML table on a browser, you can add option --format html+datatables.
--format html+datatables
Please visit the project's homepage at https://metacpan.org/release/Bencher-Scenarios-DataCleansing.
Source repository is at https://github.com/perlancar/perl-Bencher-Scenarios-DataCleansing.
Please report any bugs or feature requests on the bugtracker website https://rt.cpan.org/Public/Dist/Display.html?Name=Bencher-Scenarios-DataCleansing
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.
perlancar <perlancar@cpan.org>
This software is copyright (c) 2019, 2017, 2016 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.
To install Bencher::Scenarios::DataCleansing, copy and paste the appropriate command in to your terminal.
cpanm
cpanm Bencher::Scenarios::DataCleansing
CPAN shell
perl -MCPAN -e shell install Bencher::Scenarios::DataCleansing
For more information on module installation, please visit the detailed CPAN module installation guide.