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# Copyright 2016: Nokia
# All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License"); you may
# not use this file except in compliance with the License. You may obtain
# a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS, WITHOUT
# WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the
# License for the specific language governing permissions and limitations
# under the License.
# yardstick comment: this is a modified copy of
# rally/rally/benchmark/runners/constant.py
"""A runner that searches for the max throughput with binary search
"""
import os
import multiprocessing
import logging
import traceback
import time
from yardstick.benchmark.runners import base
LOG = logging.getLogger(__name__)
def _worker_process(queue, cls, method_name, scenario_cfg,
context_cfg, aborted): # pragma: no cover
runner_cfg = scenario_cfg['runner']
iterations = runner_cfg.get("iterations", 1)
interval = runner_cfg.get("interval", 1)
run_step = runner_cfg.get("run_step", "setup,run,teardown")
delta = runner_cfg.get("delta", 1000)
options_cfg = scenario_cfg['options']
initial_rate = options_cfg.get("pps", 1000000)
LOG.info("worker START, class %s", cls)
runner_cfg['runner_id'] = os.getpid()
benchmark = cls(scenario_cfg, context_cfg)
if "setup" in run_step:
benchmark.setup()
method = getattr(benchmark, method_name)
queue.put({'runner_id': runner_cfg['runner_id'],
'scenario_cfg': scenario_cfg,
'context_cfg': context_cfg})
if "run" in run_step:
iterator = 0
search_max = initial_rate
search_min = 0
while iterator < iterations:
search_min = int(search_min / 2)
scenario_cfg['options']['pps'] = search_max
search_max_found = False
max_throuput_found = False
sequence = 0
last_min_data = {}
last_min_data['packets_per_second'] = 0
while True:
sequence += 1
data = {}
errors = ""
too_high = False
LOG.debug("sequence: %s search_min: %s search_max: %s",
sequence, search_min, search_max)
try:
method(data)
except AssertionError as assertion:
LOG.warning("SLA validation failed: %s" % assertion.args)
too_high = True
except Exception as e:
errors = traceback.format_exc()
LOG.exception(e)
actual_pps = data['packets_per_second']
if too_high:
search_max = actual_pps
if not search_max_found:
search_max_found = True
else:
last_min_data = data
search_min = actual_pps
# Check if the actual rate is well below the asked rate
if scenario_cfg['options']['pps'] > actual_pps * 1.5:
search_max = actual_pps
LOG.debug("Sender reached max tput: %s", search_max)
elif not search_max_found:
search_max = int(actual_pps * 1.5)
if ((search_max - search_min) < delta) or \
(search_max <= search_min) or (10 <= sequence):
if last_min_data['packets_per_second'] > 0:
data = last_min_data
benchmark_output = {
'timestamp': time.time(),
'sequence': sequence,
'data': data,
'errors': errors
}
record = {
'runner_id': runner_cfg['runner_id'],
'benchmark': benchmark_output
}
queue.put(record)
max_throuput_found = True
if (errors) or aborted.is_set() or max_throuput_found:
LOG.info("worker END")
break
if not search_max_found:
scenario_cfg['options']['pps'] = search_max
else:
scenario_cfg['options']['pps'] = \
(search_max - search_min) / 2 + search_min
time.sleep(interval)
iterator += 1
LOG.debug("iterator: %s iterations: %s", iterator, iterations)
if "teardown" in run_step:
benchmark.teardown()
class IterationRunner(base.Runner):
'''Run a scenario to find the max throughput
If the scenario ends before the time has elapsed, it will be started again.
Parameters
interval - time to wait between each scenario invocation
type: int
unit: seconds
default: 1 sec
delta - stop condition for the search.
type: int
unit: pps
default: 1000 pps
'''
__execution_type__ = 'Dynamictp'
def _run_benchmark(self, cls, method, scenario_cfg, context_cfg):
self.process = multiprocessing.Process(
target=_worker_process,
args=(self.result_queue, cls, method, scenario_cfg,
context_cfg, self.aborted))
self.process.start()
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