NAME
Bencher::Scenario::DataSah::Validate - Benchmark validation
VERSION
This document describes version 0.07 of Bencher::Scenario::DataSah::Validate (from Perl distribution Bencher-Scenarios-DataSah), released on 2017-01-25.
SYNOPSIS
To run benchmark with default option:
% bencher -m DataSah::ValidateFor 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.
Data::Sah 0.87
BENCHMARK PARTICIPANTS
gen_validator (perl_code)
Code template:
state $v = Data::Sah::gen_validator(<schema>, {return_type => <return_type>}); $v->(<data>)
BENCHMARK DATASETS
int
str+2clause
date (coerce to float(epoch))
SAMPLE BENCHMARK RESULTS
Run on: perl: v5.24.0, CPU: Intel(R) Core(TM) M-5Y71 CPU @ 1.20GHz (2 cores), OS: GNU/Linux LinuxMint version 17.3, OS kernel: Linux version 3.19.0-32-generic.
Benchmark with default options (bencher -m DataSah::Validate):
#table1#
[
200,
"OK",
[
{
"arg_data" : 1485329055,
"arg_return_type" : "full",
"dataset" : "date (coerce to float(epoch))",
"errors" : "5.2e-08",
"rate" : "28000",
"samples" : 21,
"time" : "35",
"vs_slowest" : "1"
},
{
"arg_data" : "CIRCULAR",
"arg_return_type" : "bool",
"dataset" : "date (coerce to float(epoch))",
"errors" : "1.2e-07",
"rate" : "29000",
"samples" : 20,
"time" : "35",
"vs_slowest" : "1"
},
{
"arg_data" : "CIRCULAR",
"arg_return_type" : "str",
"dataset" : "date (coerce to float(epoch))",
"errors" : "5.1e-08",
"rate" : "30000",
"samples" : 22,
"time" : "33",
"vs_slowest" : "1.1"
},
{
"arg_data" : "2016-05-16",
"arg_return_type" : "full",
"dataset" : "date (coerce to float(epoch))",
"errors" : "4.7e-08",
"rate" : "63000",
"samples" : 20,
"time" : "16",
"vs_slowest" : "2.2"
},
{
"arg_data" : "2016-05-16",
"arg_return_type" : "str",
"dataset" : "date (coerce to float(epoch))",
"errors" : "2.3e-08",
"rate" : "66000",
"samples" : 28,
"time" : "15",
"vs_slowest" : "2.3"
},
{
"arg_data" : "2016-05-16",
"arg_return_type" : "bool",
"dataset" : "date (coerce to float(epoch))",
"errors" : "2.7e-08",
"rate" : "68000",
"samples" : 20,
"time" : "15",
"vs_slowest" : "2.4"
},
{
"arg_data" : "abc",
"arg_return_type" : "full",
"dataset" : "date (coerce to float(epoch))",
"errors" : "1.2e-07",
"rate" : "400000",
"samples" : 23,
"time" : "2",
"vs_slowest" : "10"
},
{
"arg_data" : 1463371843,
"arg_return_type" : "full",
"dataset" : "date (coerce to float(epoch))",
"errors" : "1.7e-09",
"rate" : "750000",
"samples" : 20,
"time" : "1.3",
"vs_slowest" : "26"
},
{
"arg_data" : "a",
"arg_return_type" : "full",
"dataset" : "int",
"errors" : "4.2e-10",
"rate" : "813000",
"samples" : 21,
"time" : "1.23",
"vs_slowest" : "28.8"
},
{
"arg_data" : "",
"arg_return_type" : "full",
"dataset" : "str+2clause",
"errors" : "1.1e-11",
"rate" : "847640",
"samples" : 20,
"time" : "1.1798",
"vs_slowest" : "30.005"
},
{
"arg_data" : 1463371843,
"arg_return_type" : "str",
"dataset" : "date (coerce to float(epoch))",
"errors" : "1.7e-09",
"rate" : "920000",
"samples" : 20,
"time" : "1.1",
"vs_slowest" : "32"
},
{
"arg_data" : 1463371843,
"arg_return_type" : "bool",
"dataset" : "date (coerce to float(epoch))",
"errors" : "1.7e-09",
"rate" : "1100000",
"samples" : 20,
"time" : "0.88",
"vs_slowest" : "40"
},
{
"arg_data" : 1,
"arg_return_type" : "full",
"dataset" : "int",
"errors" : "4.3e-10",
"rate" : "1280000",
"samples" : 20,
"time" : "0.782",
"vs_slowest" : "45.3"
},
{
"arg_data" : "abc",
"arg_return_type" : "full",
"dataset" : "str+2clause",
"errors" : "3.9e-10",
"rate" : "1300000",
"samples" : 23,
"time" : "0.772",
"vs_slowest" : "45.9"
},
{
"arg_data" : "abc",
"arg_return_type" : "str",
"dataset" : "date (coerce to float(epoch))",
"errors" : "0",
"rate" : "1397030",
"samples" : 20,
"time" : "0.715803",
"vs_slowest" : "49.4527"
},
{
"arg_data" : "abc",
"arg_return_type" : "bool",
"dataset" : "date (coerce to float(epoch))",
"errors" : "8.3e-10",
"rate" : "1700000",
"samples" : 20,
"time" : "0.6",
"vs_slowest" : "59"
},
{
"arg_data" : null,
"arg_return_type" : "full",
"dataset" : "date (coerce to float(epoch))",
"errors" : "1e-09",
"rate" : "1700000",
"samples" : 20,
"time" : "0.59",
"vs_slowest" : "60"
},
{
"arg_data" : null,
"arg_return_type" : "full",
"dataset" : "str+2clause",
"errors" : "4.4e-10",
"rate" : "1710000",
"samples" : 20,
"time" : "0.583",
"vs_slowest" : "60.7"
},
{
"arg_data" : null,
"arg_return_type" : "full",
"dataset" : "int",
"errors" : "8.4e-10",
"rate" : "1700000",
"samples" : 20,
"time" : "0.58",
"vs_slowest" : "61"
},
{
"arg_data" : "a",
"arg_return_type" : "str",
"dataset" : "int",
"errors" : "2.1e-10",
"rate" : "2590000",
"samples" : 20,
"time" : "0.386",
"vs_slowest" : "91.6"
},
{
"arg_data" : "abc",
"arg_return_type" : "str",
"dataset" : "str+2clause",
"errors" : "1.9e-09",
"rate" : "2600000",
"samples" : 20,
"time" : "0.38",
"vs_slowest" : "93"
},
{
"arg_data" : 1,
"arg_return_type" : "str",
"dataset" : "int",
"errors" : "6.2e-10",
"rate" : "2700000",
"samples" : 20,
"time" : "0.37",
"vs_slowest" : "95"
},
{
"arg_data" : "",
"arg_return_type" : "str",
"dataset" : "str+2clause",
"errors" : "2.1e-10",
"rate" : "2830000",
"samples" : 20,
"time" : "0.354",
"vs_slowest" : "100"
},
{
"arg_data" : 1,
"arg_return_type" : "bool",
"dataset" : "int",
"errors" : "4.2e-10",
"rate" : "3300000",
"samples" : 20,
"time" : "0.3",
"vs_slowest" : "120"
},
{
"arg_data" : "a",
"arg_return_type" : "bool",
"dataset" : "int",
"errors" : "4.2e-10",
"rate" : "3400000",
"samples" : 20,
"time" : "0.3",
"vs_slowest" : "120"
},
{
"arg_data" : "abc",
"arg_return_type" : "bool",
"dataset" : "str+2clause",
"errors" : "3.1e-10",
"rate" : "3500000",
"samples" : 20,
"time" : "0.29",
"vs_slowest" : "120"
},
{
"arg_data" : "",
"arg_return_type" : "bool",
"dataset" : "str+2clause",
"errors" : "4.2e-10",
"rate" : "3700000",
"samples" : 20,
"time" : "0.27",
"vs_slowest" : "130"
},
{
"arg_data" : null,
"arg_return_type" : "str",
"dataset" : "str+2clause",
"errors" : "4.3e-10",
"rate" : "3900000",
"samples" : 20,
"time" : "0.25",
"vs_slowest" : "140"
},
{
"arg_data" : null,
"arg_return_type" : "str",
"dataset" : "date (coerce to float(epoch))",
"errors" : "1e-10",
"rate" : "3950000",
"samples" : 20,
"time" : "0.253",
"vs_slowest" : "140"
},
{
"arg_data" : null,
"arg_return_type" : "str",
"dataset" : "int",
"errors" : "4.2e-10",
"rate" : "4000000",
"samples" : 20,
"time" : "0.25",
"vs_slowest" : "140"
},
{
"arg_data" : null,
"arg_return_type" : "bool",
"dataset" : "int",
"errors" : "4.2e-10",
"rate" : "5500000",
"samples" : 20,
"time" : "0.18",
"vs_slowest" : "190"
},
{
"arg_data" : null,
"arg_return_type" : "bool",
"dataset" : "str+2clause",
"errors" : "4.7e-10",
"rate" : "5500000",
"samples" : 30,
"time" : "0.18",
"vs_slowest" : "200"
},
{
"arg_data" : null,
"arg_return_type" : "bool",
"dataset" : "date (coerce to float(epoch))",
"errors" : "3.7e-11",
"rate" : "5620000",
"samples" : 20,
"time" : "0.178",
"vs_slowest" : "199"
}
],
{
"func.bencher_args" : {
"action" : "bench",
"note" : "Run by Pod::Weaver::Plugin::Bencher::Scenario",
"scenario_module" : "DataSah::Validate"
},
"func.bencher_version" : null,
"func.cpu_info" : [
{
"L2_cache" : {
"max_cache_size" : "4096 KB"
},
"address_width" : "64",
"architecture" : "AMD-64",
"bus_speed" : null,
"data_width" : "64",
"family" : "6",
"flags" : [
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"xtopology",
"nonstop_tsc",
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"pni",
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"dtes64",
"monitor",
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"bmi2",
"erms",
"invpcid",
"rtm",
"rdseed",
"adx",
"smap",
"xsaveopt"
],
"manufacturer" : "GenuineIntel",
"model" : "61",
"name" : "Intel(R) Core(TM) M-5Y71 CPU @ 1.20GHz",
"number_of_cores" : "2",
"number_of_logical_processors" : 4,
"processor_id" : "0",
"speed" : "2599.953",
"stepping" : "4"
},
{
"L2_cache" : {
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},
{
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"x2apic",
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"avx",
"f16c",
"rdrand",
"lahf_lm",
"abm",
"3dnowprefetch",
"ida",
"arat",
"epb",
"pln",
"pts",
"dtherm",
"tpr_shadow",
"vnmi",
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"processor_id" : "3",
"speed" : "2605.531",
"stepping" : "4"
}
],
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"func.module_startup" : null,
"func.module_versions" : {
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"Benchmark::Dumb" : "0.10",
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"Devel::Platform::Info" : "0.16",
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"__PACKAGE__" : "1.034",
"perl" : "v5.24.0"
},
"func.note" : "Run by Pod::Weaver::Plugin::Bencher::Scenario",
"func.permute" : [
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[
"perl"
],
"participant",
[
0
],
"dataset",
[
0,
1,
2
]
],
"func.platform_info" : {
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"codename" : "rosa",
"is32bit" : 0,
"is64bit" : 1,
"kernel" : "linux-3.19.0-32-generic",
"kname" : "Linux",
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"osflag" : "linux",
"oslabel" : "LinuxMint",
"osname" : "GNU/Linux",
"osvers" : "17.3",
"source" : {
"cat /etc/.issue" : "",
"cat /etc/issue" : "Linux Mint 17.3 Rosa \\n \\l",
"lsb_release -a" : "Distributor ID:\tLinuxMint\nDescription:\tLinux Mint 17.3 Rosa\nRelease:\t17.3\nCodename:\trosa",
"uname -a" : "Linux backpacker 3.19.0-32-generic #37~14.04.1-Ubuntu SMP Thu Oct 22 09:41:40 UTC 2015 x86_64 x86_64 x86_64 GNU/Linux",
"uname -m" : "x86_64",
"uname -o" : "GNU/Linux",
"uname -r" : "3.19.0-32-generic",
"uname -s" : "Linux"
}
},
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"func.time_end" : 1485329064.2527,
"func.time_factor" : 1000000,
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"table.field_aligns" : [
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"number",
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],
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null,
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],
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]
}
]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-Scenarios-DataSah.
SOURCE
Source repository is at https://github.com/perlancar/perl-Bencher-Scenario-DataSah.
BUGS
Please report any bugs or feature requests on the bugtracker website https://rt.cpan.org/Public/Dist/Display.html?Name=Bencher-Scenarios-DataSah
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.
AUTHOR
perlancar <perlancar@cpan.org>
COPYRIGHT AND LICENSE
This software is copyright (c) 2017 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.