| #!/usr/bin/env python | |
| # | |
| # Simple benchmarking framework | |
| # | |
| # Copyright (c) 2019 Virtuozzo International GmbH. | |
| # | |
| # This program is free software; you can redistribute it and/or modify | |
| # it under the terms of the GNU General Public License as published by | |
| # the Free Software Foundation; either version 2 of the License, or | |
| # (at your option) any later version. | |
| # | |
| # This program is distributed in the hope that it will be useful, | |
| # but WITHOUT ANY WARRANTY; without even the implied warranty of | |
| # MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the | |
| # GNU General Public License for more details. | |
| # | |
| # You should have received a copy of the GNU General Public License | |
| # along with this program. If not, see <http://www.gnu.org/licenses/>. | |
| # | |
| import statistics | |
| import subprocess | |
| import time | |
| def do_drop_caches(): | |
| subprocess.run('sync; echo 3 > /proc/sys/vm/drop_caches', shell=True, | |
| check=True) | |
| def bench_one(test_func, test_env, test_case, count=5, initial_run=True, | |
| slow_limit=100, drop_caches=False): | |
| """Benchmark one test-case | |
| test_func -- benchmarking function with prototype | |
| test_func(env, case), which takes test_env and test_case | |
| arguments and on success returns dict with 'seconds' or | |
| 'iops' (or both) fields, specifying the benchmark result. | |
| If both 'iops' and 'seconds' provided, the 'iops' is | |
| considered the main, and 'seconds' is just an additional | |
| info. On failure test_func should return {'error': str}. | |
| Returned dict may contain any other additional fields. | |
| test_env -- test environment - opaque first argument for test_func | |
| test_case -- test case - opaque second argument for test_func | |
| count -- how many times to call test_func, to calculate average | |
| initial_run -- do initial run of test_func, which don't get into result | |
| slow_limit -- stop at slow run (that exceedes the slow_limit by seconds). | |
| (initial run is not measured) | |
| drop_caches -- drop caches before each run | |
| Returns dict with the following fields: | |
| 'runs': list of test_func results | |
| 'dimension': dimension of results, may be 'seconds' or 'iops' | |
| 'average': average value (iops or seconds) per run (exists only if at | |
| least one run succeeded) | |
| 'stdev': standard deviation of results | |
| (exists only if at least one run succeeded) | |
| 'n-failed': number of failed runs (exists only if at least one run | |
| failed) | |
| """ | |
| if initial_run: | |
| print(' #initial run:') | |
| do_drop_caches() | |
| print(' ', test_func(test_env, test_case)) | |
| runs = [] | |
| for i in range(count): | |
| t = time.time() | |
| print(' #run {}'.format(i+1)) | |
| do_drop_caches() | |
| res = test_func(test_env, test_case) | |
| print(' ', res) | |
| runs.append(res) | |
| if time.time() - t > slow_limit: | |
| print(' - run is too slow, stop here') | |
| break | |
| count = len(runs) | |
| result = {'runs': runs} | |
| succeeded = [r for r in runs if ('seconds' in r or 'iops' in r)] | |
| if succeeded: | |
| if 'iops' in succeeded[0]: | |
| assert all('iops' in r for r in succeeded) | |
| dim = 'iops' | |
| else: | |
| assert all('seconds' in r for r in succeeded) | |
| assert all('iops' not in r for r in succeeded) | |
| dim = 'seconds' | |
| result['dimension'] = dim | |
| result['average'] = statistics.mean(r[dim] for r in succeeded) | |
| if len(succeeded) == 1: | |
| result['stdev'] = 0 | |
| else: | |
| result['stdev'] = statistics.stdev(r[dim] for r in succeeded) | |
| if len(succeeded) < count: | |
| result['n-failed'] = count - len(succeeded) | |
| return result | |
| def bench(test_func, test_envs, test_cases, *args, **vargs): | |
| """Fill benchmark table | |
| test_func -- benchmarking function, see bench_one for description | |
| test_envs -- list of test environments, see bench_one | |
| test_cases -- list of test cases, see bench_one | |
| args, vargs -- additional arguments for bench_one | |
| Returns dict with the following fields: | |
| 'envs': test_envs | |
| 'cases': test_cases | |
| 'tab': filled 2D array, where cell [i][j] is bench_one result for | |
| test_cases[i] for test_envs[j] (i.e., rows are test cases and | |
| columns are test environments) | |
| """ | |
| tab = {} | |
| results = { | |
| 'envs': test_envs, | |
| 'cases': test_cases, | |
| 'tab': tab | |
| } | |
| n = 1 | |
| n_tests = len(test_envs) * len(test_cases) | |
| for env in test_envs: | |
| for case in test_cases: | |
| print('Testing {}/{}: {} :: {}'.format(n, n_tests, | |
| env['id'], case['id'])) | |
| if case['id'] not in tab: | |
| tab[case['id']] = {} | |
| tab[case['id']][env['id']] = bench_one(test_func, env, case, | |
| *args, **vargs) | |
| n += 1 | |
| print('Done') | |
| return results |