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# Copyright 2014: Mirantis Inc.
# 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 runs a configurable number of times before it returns
"""
from __future__ import absolute_import
import logging
import multiprocessing
import time
import traceback
import os
from yardstick.benchmark.runners import base
LOG = logging.getLogger(__name__)
QUEUE_PUT_TIMEOUT = 10
def _worker_process(queue, cls, method_name, scenario_cfg,
context_cfg, aborted, output_queue):
sequence = 1
runner_cfg = scenario_cfg['runner']
interval = runner_cfg.get("interval", 1)
iterations = runner_cfg.get("iterations", 1)
run_step = runner_cfg.get("run_step", "setup,run,teardown")
delta = runner_cfg.get("delta", 2)
LOG.info("worker START, iterations %d times, class %s", iterations, 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)
sla_action = None
if "sla" in scenario_cfg:
sla_action = scenario_cfg["sla"].get("action", "assert")
if "run" in run_step:
while True:
LOG.debug("runner=%(runner)s seq=%(sequence)s START",
{"runner": runner_cfg["runner_id"],
"sequence": sequence})
data = {}
errors = ""
try:
result = method(data)
except AssertionError as assertion:
# SLA validation failed in scenario, determine what to do now
if sla_action == "assert":
raise
elif sla_action == "monitor":
LOG.warning("SLA validation failed: %s", assertion.args)
errors = assertion.args
elif sla_action == "rate-control":
try:
scenario_cfg['options']['rate']
except KeyError:
scenario_cfg.setdefault('options', {})
scenario_cfg['options']['rate'] = 100
scenario_cfg['options']['rate'] -= delta
sequence = 1
continue
except Exception:
errors = traceback.format_exc()
LOG.exception("")
else:
if result:
# add timeout for put so we don't block test
# if we do timeout we don't care about dropping individual KPIs
output_queue.put(result, True, QUEUE_PUT_TIMEOUT)
time.sleep(interval)
benchmark_output = {
'timestamp': time.time(),
'sequence': sequence,
'data': data,
'errors': errors
}
queue.put(benchmark_output, True, QUEUE_PUT_TIMEOUT)
LOG.debug("runner=%(runner)s seq=%(sequence)s END",
{"runner": runner_cfg["runner_id"],
"sequence": sequence})
sequence += 1
if (errors and sla_action is None) or \
(sequence > iterations or aborted.is_set()):
LOG.info("worker END")
break
if "teardown" in run_step:
try:
benchmark.teardown()
except Exception:
# catch any exception in teardown and convert to simple exception
# never pass exceptions back to multiprocessing, because some exceptions can
# be unpicklable
# https://bugs.python.org/issue9400
LOG.exception("")
raise SystemExit(1)
LOG.debug("queue.qsize() = %s", queue.qsize())
LOG.debug("output_queue.qsize() = %s", output_queue.qsize())
class IterationRunner(base.Runner):
"""Run a scenario for a configurable number of times
If the scenario ends before the time has elapsed, it will be started again.
Parameters
iterations - amount of times the scenario will be run for
type: int
unit: na
default: 1
interval - time to wait between each scenario invocation
type: int
unit: seconds
default: 1 sec
"""
__execution_type__ = 'Iteration'
def _run_benchmark(self, cls, method, scenario_cfg, context_cfg):
name = "{}-{}-{}".format(self.__execution_type__, scenario_cfg.get("type"), os.getpid())
self.process = multiprocessing.Process(
name=name,
target=_worker_process,
args=(self.result_queue, cls, method, scenario_cfg,
context_cfg, self.aborted, self.output_queue))
self.process.start()
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