def run_scenario(self,
scenario,
auth_kwargs,
run_results,
noop=False,
with_profiling=False,
keep_objects=False,
batch_size=1):
"""
Runs a CRUD scenario, given cluster parameters and a Scenario object.
:param scenario: Scenario object describing the benchmark run
:param auth_kwargs: All-you-can-eat dictionary of
authentication-related arguments.
:param run_results: RunResults objects for the run
:param noop: Run in no-op mode?
:param with_profiing: Profile the run?
:param keep_objects: Keep uploaded objects instead of deleting them?
:param batch_size: Send this many bench jobs per packet to workers
:param returns: Collected result records from workers
"""
run_state = RunState()
logging.info(u'Starting scenario run for "%s"', scenario.name)
raise_file_descriptor_limit()
# Construct auth_kwargs appropriate for client.get_auth()
if auth_kwargs.get('token'):
auth_kwargs = {
'storage_urls': auth_kwargs['storage_urls'],
'token': auth_kwargs['token'],
}
# Ensure containers exist
if not noop:
storage_urls, c_token = self._authenticate(auth_kwargs)
logging.info(
'Ensuring %d containers (%s_*) exist; '
'concurrency=%d...', len(scenario.containers),
scenario.container_base, scenario.container_concurrency)
pool = gevent.pool.Pool(scenario.container_concurrency)
for container in scenario.containers:
pool.spawn(_container_creator,
storage_urls,
c_token,
container,
policy=scenario.policy)
pool.join()
# Enqueue initialization jobs
if not noop:
logging.info(
'Initializing cluster with stock data (up to %d '
'concurrent workers)', scenario.user_count)
self.do_a_run(scenario.user_count,
scenario.initial_jobs(),
run_state.handle_initialization_result,
auth_kwargs,
batch_size=batch_size)
logging.info('Starting benchmark run (up to %d concurrent '
'workers)', scenario.user_count)
if noop:
logging.info(' (not actually talking to Swift cluster!)')
if with_profiling:
import cProfile
prof = cProfile.Profile()
prof.enable()
self.do_a_run(scenario.user_count,
scenario.bench_jobs(),
run_state.handle_run_result,
auth_kwargs,
mapper_fn=run_state.fill_in_job,
label='Benchmark Run:',
noop=noop,
batch_size=batch_size,
run_results=run_results)
if with_profiling:
prof.disable()
prof_output_path = '/tmp/do_a_run.%d.prof' % os.getpid()
prof.dump_stats(prof_output_path)
logging.info('PROFILED main do_a_run to %s', prof_output_path)
if not noop and not keep_objects:
logging.info('Deleting population objects from cluster')
self.do_a_run(scenario.user_count,
run_state.cleanup_object_infos(),
lambda *_: None,
auth_kwargs,
mapper_fn=_gen_cleanup_job,
batch_size=batch_size)
elif keep_objects:
logging.info('NOT deleting any objects due to -k/--keep-objects')
def setUp(self):
self.run_state = RunState()
