- Tests were run in single-user mode, one at a time.
- Data was read from and written to tmpfs.
- borg-1.1rc2 seems about 10% slower than borg-1.0.11 (many possible reasons, borg-1.1rc2 binary comes from GitHub but 1.0.11 from the Arch repos)
- Still making sense of the auto,X,Y compression modes
Last active
May 31, 2024 19:32
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Save Artefact2/eb4b47d8c3310ad537547c2c445446f5 to your computer and use it in GitHub Desktop.
Borg compression benchmark/comparison
Benchmark date: 2017-09-09
Borg version: borg-linux64 1.1.0rc2
Python version: Python 3.6.2
Kernel version: Linux 4.12.8-2-ARCH
CPU model: AMD FX(tm)-8150 Eight-Core Processor
Borg init command: %s init --error -e repokey %s
Borg create command: %s create --error -C %s %s::foo %s
Dataset path: /tmp/borg-dataset (tmpfs)
Repository path: /tmp/borg-repo (tmpfs)
Averaging algos over 1 run(s)
algo | cputime | reposize | bytes/s | timeratio | compratio
----------------+------------+-----------+-----------+-----------+----------
none | 31.10 | 792.654M | 25.487M | 1.00 | 1.000
lz4 | 29.54 | 311.050M | 26.833M | 0.95 | 0.392
zlib,0 | 33.00 | 793.244M | 24.020M | 1.06 | 1.001
zlib,1 | 36.82 | 228.762M | 21.528M | 1.18 | 0.289
zlib,2 | 37.74 | 221.245M | 21.003M | 1.21 | 0.279
zlib,3 | 39.05 | 216.240M | 20.298M | 1.26 | 0.273
zlib,4 | 41.51 | 205.451M | 19.095M | 1.33 | 0.259
zlib,5 | 44.57 | 199.655M | 17.784M | 1.43 | 0.252
zlib,6 | 50.48 | 197.501M | 15.702M | 1.62 | 0.249
zlib,7 | 55.10 | 196.702M | 14.386M | 1.77 | 0.248
zlib,8 | 66.13 | 196.170M | 11.986M | 2.13 | 0.247
zlib,9 | 66.77 | 196.137M | 11.871M | 2.15 | 0.247
lzma,0 | 79.57 | 201.884M | 9961.717K | 2.56 | 0.255
lzma,1 | 96.85 | 195.178M | 8184.345K | 3.11 | 0.246
lzma,2 | 114.55 | 192.754M | 6919.719K | 3.68 | 0.243
lzma,3 | 154.87 | 191.959M | 5118.188K | 4.98 | 0.242
lzma,4 | 307.70 | 189.075M | 2576.060K | 9.89 | 0.239
lzma,5 | 487.64 | 185.676M | 1625.489K | 15.68 | 0.234
lzma,6 | 543.37 | 184.078M | 1458.773K | 17.47 | 0.232
lzma,7 | 764.68 | 184.058M | 1036.582K | 24.59 | 0.232
lzma,8 | 1218.62 | 184.082M | 650.452K | 39.18 | 0.232
lzma,9 | 1218.07 | 184.095M | 650.745K | 39.17 | 0.232
auto,lz4 | 32.19 | 311.050M | 24.624M | 1.04 | 0.392
auto,zlib,0 | 36.56 | 793.240M | 21.681M | 1.18 | 1.001
auto,zlib,1 | 39.51 | 228.762M | 20.062M | 1.27 | 0.289
auto,zlib,2 | 41.02 | 221.250M | 19.324M | 1.32 | 0.279
auto,zlib,3 | 41.67 | 216.248M | 19.022M | 1.34 | 0.273
auto,zlib,4 | 44.01 | 205.447M | 18.011M | 1.42 | 0.259
auto,zlib,5 | 47.52 | 199.660M | 16.680M | 1.53 | 0.252
auto,zlib,6 | 53.45 | 197.497M | 14.830M | 1.72 | 0.249
auto,zlib,7 | 57.71 | 196.706M | 13.735M | 1.86 | 0.248
auto,zlib,8 | 67.28 | 196.162M | 11.781M | 2.16 | 0.247
auto,zlib,9 | 69.64 | 196.141M | 11.382M | 2.24 | 0.247
auto,lzma,0 | 82.29 | 201.830M | 9632.444K | 2.65 | 0.255
auto,lzma,1 | 100.03 | 195.105M | 7924.160K | 3.22 | 0.246
auto,lzma,2 | 116.15 | 192.668M | 6824.397K | 3.73 | 0.243
auto,lzma,3 | 159.19 | 192.012M | 4979.294K | 5.12 | 0.242
auto,lzma,4 | 314.17 | 189.080M | 2523.009K | 10.10 | 0.239
auto,lzma,5 | 486.67 | 185.709M | 1628.729K | 15.65 | 0.234
auto,lzma,6 | 542.93 | 184.013M | 1459.955K | 17.46 | 0.232
auto,lzma,7 | 763.56 | 184.054M | 1038.102K | 24.55 | 0.232
auto,lzma,8 | 1207.50 | 184.029M | 656.442K | 38.83 | 0.232
auto,lzma,9 | 1205.69 | 184.001M | 657.427K | 38.77 | 0.232
Benchmark date: 2017-09-10
Borg version: borg-linux64 1.1.0rc2
Python version: Python 3.6.2
Kernel version: Linux 4.12.8-2-ARCH
CPU model: AMD FX(tm)-8150 Eight-Core Processor
Borg init command: %s init --error -e repokey %s
Borg create command: %s create --error -C %s %s::foo %s
Dataset path: /tmp/borg-dataset (tmpfs)
Repository path: /tmp/borg-repo (tmpfs)
Averaging algos over 1 run(s)
algo | cputime | reposize | bytes/s | timeratio | compratio
----------------+------------+-----------+-----------+-----------+----------
none | 12.06 | 682.570M | 56.598M | 1.00 | 1.000
lz4 | 10.04 | 222.540M | 67.985M | 0.83 | 0.326
zlib,0 | 14.91 | 682.672M | 45.779M | 1.24 | 1.000
zlib,1 | 15.61 | 154.948M | 43.726M | 1.29 | 0.227
zlib,2 | 16.50 | 150.839M | 41.368M | 1.37 | 0.221
zlib,3 | 18.30 | 147.550M | 37.299M | 1.52 | 0.216
zlib,4 | 21.61 | 136.143M | 31.586M | 1.79 | 0.199
zlib,5 | 25.56 | 128.610M | 26.705M | 2.12 | 0.188
zlib,6 | 31.23 | 126.640M | 21.856M | 2.59 | 0.186
zlib,7 | 36.63 | 125.997M | 18.634M | 3.04 | 0.185
zlib,8 | 51.20 | 124.961M | 13.331M | 4.25 | 0.183
zlib,9 | 53.49 | 124.903M | 12.761M | 4.44 | 0.183
lzma,0 | 43.15 | 125.125M | 15.819M | 3.58 | 0.183
lzma,1 | 47.43 | 115.737M | 14.391M | 3.93 | 0.170
lzma,2 | 59.86 | 111.706M | 11.403M | 4.96 | 0.164
lzma,3 | 77.78 | 109.818M | 8775.645K | 6.45 | 0.161
lzma,4 | 129.02 | 98.345M | 5290.417K | 10.70 | 0.144
lzma,5 | 174.62 | 94.564M | 3908.886K | 14.48 | 0.139
lzma,6 | 320.48 | 89.686M | 2129.835K | 26.57 | 0.131
lzma,7 | 322.40 | 89.711M | 2117.151K | 26.73 | 0.131
lzma,8 | 326.85 | 89.489M | 2088.327K | 27.10 | 0.131
lzma,9 | 329.77 | 89.518M | 2069.835K | 27.34 | 0.131
auto,lz4 | 11.78 | 222.540M | 57.943M | 0.98 | 0.326
auto,zlib,0 | 16.60 | 682.672M | 41.119M | 1.38 | 1.000
auto,zlib,1 | 17.35 | 154.952M | 39.341M | 1.44 | 0.227
auto,zlib,2 | 18.13 | 150.847M | 37.649M | 1.50 | 0.221
auto,zlib,3 | 20.02 | 147.522M | 34.094M | 1.66 | 0.216
auto,zlib,4 | 23.53 | 136.163M | 29.008M | 1.95 | 0.199
auto,zlib,5 | 26.54 | 128.618M | 25.719M | 2.20 | 0.188
auto,zlib,6 | 34.28 | 126.648M | 19.912M | 2.84 | 0.186
auto,zlib,7 | 37.69 | 125.989M | 18.110M | 3.13 | 0.185
auto,zlib,8 | 53.51 | 124.953M | 12.756M | 4.44 | 0.183
auto,zlib,9 | 55.94 | 124.891M | 12.202M | 4.64 | 0.183
auto,lzma,0 | 45.07 | 125.088M | 15.145M | 3.74 | 0.183
auto,lzma,1 | 49.24 | 115.806M | 13.862M | 4.08 | 0.170
auto,lzma,2 | 61.87 | 111.907M | 11.032M | 5.13 | 0.164
auto,lzma,3 | 78.91 | 110.121M | 8649.977K | 6.54 | 0.161
auto,lzma,4 | 135.67 | 97.944M | 5031.102K | 11.25 | 0.143
auto,lzma,5 | 173.32 | 94.376M | 3938.205K | 14.37 | 0.138
auto,lzma,6 | 321.33 | 89.723M | 2124.201K | 26.64 | 0.131
auto,lzma,7 | 324.67 | 89.477M | 2102.349K | 26.92 | 0.131
auto,lzma,8 | 325.54 | 89.559M | 2096.730K | 26.99 | 0.131
auto,lzma,9 | 327.80 | 89.825M | 2082.274K | 27.18 | 0.132
Benchmark date: 2017-09-10
Borg version: borg-linux64 1.1.0rc2
Python version: Python 3.6.2
Kernel version: Linux 4.12.8-2-ARCH
CPU model: AMD FX(tm)-8150 Eight-Core Processor
Borg init command: %s init --error -e repokey %s
Borg create command: %s create --error -C %s %s::foo %s
Dataset path: /tmp/borg-dataset (tmpfs)
Repository path: /tmp/borg-repo (tmpfs)
Averaging algos over 1 run(s)
algo | cputime | reposize | bytes/s | timeratio | compratio
----------------+------------+-----------+-----------+-----------+----------
none | 10.08 | 552.243M | 54.786M | 1.00 | 1.000
lz4 | 10.51 | 553.198M | 52.545M | 1.04 | 1.002
zlib,0 | 12.31 | 552.329M | 44.861M | 1.22 | 1.000
zlib,1 | 31.31 | 541.327M | 17.638M | 3.11 | 0.980
zlib,2 | 30.76 | 541.123M | 17.953M | 3.05 | 0.980
zlib,3 | 32.22 | 541.028M | 17.140M | 3.20 | 0.980
zlib,4 | 32.63 | 541.639M | 16.924M | 3.24 | 0.981
zlib,5 | 33.09 | 541.610M | 16.689M | 3.28 | 0.981
zlib,6 | 34.04 | 541.594M | 16.223M | 3.38 | 0.981
zlib,7 | 32.58 | 541.594M | 16.950M | 3.23 | 0.981
zlib,8 | 33.74 | 541.594M | 16.368M | 3.35 | 0.981
zlib,9 | 32.60 | 541.598M | 16.940M | 3.23 | 0.981
lzma,0 | 114.12 | 539.759M | 4839.144K | 11.32 | 0.977
lzma,1 | 128.01 | 539.451M | 4314.062K | 12.70 | 0.977
lzma,2 | 139.48 | 539.443M | 3959.300K | 13.84 | 0.977
lzma,3 | 144.05 | 539.423M | 3833.691K | 14.29 | 0.977
lzma,4 | 152.77 | 536.760M | 3614.866K | 15.16 | 0.972
lzma,5 | 150.73 | 536.711M | 3663.790K | 14.95 | 0.972
lzma,6 | 150.52 | 536.781M | 3668.902K | 14.93 | 0.972
lzma,7 | 148.66 | 536.748M | 3714.806K | 14.75 | 0.972
lzma,8 | 149.84 | 536.805M | 3685.552K | 14.87 | 0.972
lzma,9 | 149.07 | 536.736M | 3704.589K | 14.79 | 0.972
auto,lz4 | 10.69 | 551.404M | 51.660M | 1.06 | 0.998
auto,zlib,0 | 10.99 | 552.255M | 50.250M | 1.09 | 1.000
auto,zlib,1 | 13.00 | 546.533M | 42.480M | 1.29 | 0.990
auto,zlib,2 | 13.37 | 545.362M | 41.305M | 1.33 | 0.988
auto,zlib,3 | 13.57 | 545.980M | 40.696M | 1.35 | 0.989
auto,zlib,4 | 14.26 | 545.980M | 38.727M | 1.41 | 0.989
auto,zlib,5 | 15.30 | 544.649M | 36.094M | 1.52 | 0.986
auto,zlib,6 | 13.90 | 546.619M | 39.730M | 1.38 | 0.990
auto,zlib,7 | 14.00 | 546.296M | 39.446M | 1.39 | 0.989
auto,zlib,8 | 13.67 | 546.947M | 40.398M | 1.36 | 0.990
auto,zlib,9 | 14.01 | 546.161M | 39.418M | 1.39 | 0.989
auto,lzma,0 | 21.26 | 544.084M | 25.976M | 2.11 | 0.985
auto,lzma,1 | 23.84 | 544.461M | 23.165M | 2.37 | 0.986
auto,lzma,2 | 24.53 | 544.211M | 22.513M | 2.43 | 0.985
auto,lzma,3 | 25.64 | 544.330M | 21.538M | 2.54 | 0.986
auto,lzma,4 | 31.46 | 542.163M | 17.554M | 3.12 | 0.982
auto,lzma,5 | 28.74 | 542.806M | 19.215M | 2.85 | 0.983
auto,lzma,6 | 27.20 | 543.543M | 20.303M | 2.70 | 0.984
auto,lzma,7 | 25.30 | 544.756M | 21.828M | 2.51 | 0.986
auto,lzma,8 | 26.69 | 543.953M | 20.691M | 2.65 | 0.985
auto,lzma,9 | 27.53 | 542.675M | 20.060M | 2.73 | 0.983
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| #!/usr/bin/env php | |
| <?php | |
| /* Author: Romain "Artefact2" Dal Maso <[email protected]> */ | |
| /* This program is free software. It comes without any warranty, to the | |
| * extent permitted by applicable law. You can redistribute it and/or | |
| * modify it under the terms of the Do What The Fuck You Want To Public | |
| * License, Version 2, as published by Sam Hocevar. See | |
| * http://sam.zoy.org/wtfpl/COPYING for more details. */ | |
| const BORG_BINARY = '/home/romain/Downloads/borg-linux64'; | |
| const DATASET_DIR = '/tmp/borg-dataset'; | |
| const BORG_REPO = '/tmp/borg-repo'; | |
| const STATE_FILE = '/tmp/borg-compressbench.state'; | |
| const INIT_COMMAND = '%s init --error -e repokey %s'; | |
| const CREATE_COMMAND = '%s create --error -C %s %s::foo %s'; | |
| const RUNS = 1; | |
| $compressions = [ 'lz4' ]; | |
| foreach([ 'zlib', 'lzma' ] as $algo) { | |
| foreach(range(0, 9) as $level) { | |
| $compressions[] = $algo.','.$level; | |
| } | |
| } | |
| foreach($compressions as $comp) { | |
| $compressions[] = 'auto,'.$comp; | |
| } | |
| array_unshift($compressions, 'none'); | |
| printf("Benchmark date: %s\n", gmdate('Y-m-d')); | |
| printf("Borg version: %s", shell_exec(sprintf('%s --version', escapeshellarg(BORG_BINARY)))); | |
| printf("Python version: %s", shell_exec('python --version')); | |
| printf("Kernel version: %s", shell_exec('uname -sr')); | |
| printf("CPU model: %s", shell_exec('grep "model name" /proc/cpuinfo | head -n1 | cut -d\' \' -f3-')); | |
| printf("\nBorg init command: %s\n", INIT_COMMAND); | |
| printf("Borg create command: %s\n", CREATE_COMMAND); | |
| printf("Dataset path: %s (%s)\n", DATASET_DIR, find_mountpoint(DATASET_DIR)); | |
| printf("Repository path: %s (%s)\n", BORG_REPO, find_mountpoint(BORG_REPO)); | |
| printf("\nAveraging algos over %d run(s)\n", RUNS); | |
| putenv('BORG_PASSPHRASE=foobar'); | |
| if(file_exists(STATE_FILE)) { | |
| $results = json_decode(file_get_contents(STATE_FILE), true); | |
| fprintf(STDERR, "\nWARNING: resuming progress from state file %s\nDelete file if you want to start over.\n", STATE_FILE); | |
| } else { | |
| $results = [];; | |
| } | |
| const FORMAT = "%15s | %10s | %9s | %9s | %9s | %9s\n"; | |
| const IFORMAT = "%15s | %10.2f | %9s | %9s | %9.2f | %9.3f\n"; | |
| printf("\n".FORMAT, "algo", "cputime", "reposize", "bytes/s", "timeratio", "compratio"); | |
| echo strtr(sprintf(FORMAT, '', '', '', '', '', '', '', ''), ' |', '-+'); | |
| foreach($compressions as $comp) { | |
| if(!isset($results[$comp])) { | |
| $results[$comp] = [ | |
| 'runs' => 0, | |
| 'cpu' => 0, | |
| 'size' => 0, | |
| ]; | |
| } | |
| while($results[$comp]['runs'] < RUNS) { | |
| passthru(sprintf('rm -Rf %s', escapeshellarg(BORG_REPO))); | |
| passthru(sprintf(INIT_COMMAND, | |
| escapeshellarg(BORG_BINARY), | |
| escapeshellarg(BORG_REPO))); | |
| $times = shell_exec('bash -c '.escapeshellarg( | |
| sprintf('time -p '.CREATE_COMMAND, | |
| escapeshellarg(BORG_BINARY), | |
| escapeshellarg($comp), | |
| escapeshellarg(BORG_REPO), | |
| escapeshellarg(DATASET_DIR)) | |
| ).' 2>&1'); | |
| preg_match_all('%^(real|user|sys) (?<time>.+)$%m', $times, $matches); | |
| $results[$comp]['cpu'] += floatval($matches['time'][1]); | |
| $results[$comp]['cpu'] += floatval($matches['time'][2]); | |
| $du = shell_exec(sprintf('du -B 1 -s %s', escapeshellarg(BORG_REPO))); | |
| preg_match('%^(?<total>[0-9]+)\s%m', $du, $match); | |
| $results[$comp]['size'] += intval($match['total']); | |
| ++$results[$comp]['runs']; | |
| $f = fopen(STATE_FILE, 'wb'); | |
| fwrite($f, json_encode($results)); | |
| fflush($f); | |
| fclose($f); | |
| } | |
| printf( | |
| IFORMAT, | |
| $comp, | |
| $results[$comp]['cpu'] / $results[$comp]['runs'], | |
| format_bytes($results[$comp]['size'] / $results[$comp]['runs']), | |
| format_bytes(($results['none']['size'] / $results['none']['runs']) / ($results[$comp]['cpu'] / $results[$comp]['runs'])), | |
| ($results[$comp]['cpu'] / $results[$comp]['runs']) / ($results['none']['cpu'] / $results['none']['runs']), | |
| ($results[$comp]['size'] / $results[$comp]['runs']) / ($results['none']['size'] / $results['none']['runs']) | |
| ); | |
| } | |
| function format_bytes(int $b, string $prec = '8.3') { | |
| static $suffixes = [ 'B', 'K', 'M', 'G', 'T', 'P', 'E' ]; | |
| list($total, $decimals) = explode('.', $prec); | |
| $cutoff = pow(10, $total - $decimals - 1); | |
| $i = 0; | |
| while($b >= $cutoff) { | |
| $b /= 1000; | |
| ++$i; | |
| } | |
| return sprintf("%".$prec."f%s", $b, $suffixes[$i]); | |
| } | |
| function find_mountpoint($path) { | |
| if($del = !file_exists($path)) { | |
| touch($path); | |
| } | |
| $dev = shell_exec(sprintf('df %s | tail -n1 | cut -d\' \' -f1', escapeshellarg($path))); | |
| if($del) unlink($path); | |
| return substr($dev, 0, -1); | |
| } |
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| #!/bin/sh | |
| # Run me in single-user mode: | |
| # systemctl isolate rescue.target | |
| for i in 1 2 3; do | |
| rm -Rf /tmp/borg-dataset /tmp/borg-repo /tmp/borg-compressbench.state | |
| cp -a /tmp/borg-dataset$i /tmp/borg-dataset | |
| ./borg-compressbench | tee bcb$i.txt | |
| mv /tmp/borg-compressbench.state bcb$i.state | |
| done |
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Thanks for the work! I created a plot of your comparison within my fork. What do you think about adding it here? :-)