-##############################################################################
-# Copyright (c) 2015 Ericsson AB and others.
+# Copyright 2014: Mirantis Inc.
+# All Rights Reserved.
#
-# All rights reserved. This program and the accompanying materials
-# are made available under the terms of the Apache License, Version 2.0
-# which accompanies this distribution, and is available at
-# http://www.apache.org/licenses/LICENSE-2.0
-##############################################################################
+# 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.
-'''A runner that every run arithmetically steps specified input value(s) to
+# yardstick comment: this is a modified copy of
+# rally/rally/benchmark/runners/constant.py
+
+"""A runner that every run arithmetically steps specified input value(s) to
the scenario. This just means step value(s) is added to the previous value(s).
It is possible to combine several named input values and run with those either
as nested for loops or combine each i:th index of each "input value list"
until the end of the shortest list is reached (optimally all lists should be
defined with the same number of values when using such iter_type).
-'''
+"""
-import os
-import multiprocessing
+from __future__ import absolute_import
+
+import itertools
import logging
-import traceback
+import multiprocessing
+import os
import time
-import itertools
+import traceback
+
+import six
+from six.moves import range
from yardstick.benchmark.runners import base
def _worker_process(queue, cls, method_name, scenario_cfg,
- context_cfg, aborted):
+ context_cfg, aborted, output_queue):
sequence = 1
benchmark.setup()
method = getattr(benchmark, method_name)
- queue.put({'runner_id': runner_cfg['runner_id'],
- 'scenario_cfg': scenario_cfg,
- 'context_cfg': context_cfg})
-
sla_action = None
if "sla" in scenario_cfg:
sla_action = scenario_cfg["sla"].get("action", "assert")
# To both be able to include the stop value and handle backwards stepping
- margin = lambda start, stop: -1 if start > stop else 1
+ def margin(start, stop):
+ return -1 if start > stop else 1
param_iters = \
- [xrange(d['start'], d['stop'] + margin(d['start'], d['stop']),
- d['step']) for d in runner_cfg['iterators']]
+ [range(d['start'], d['stop'] + margin(d['start'], d['stop']),
+ d['step']) for d in runner_cfg['iterators']]
param_names = [d['name'] for d in runner_cfg['iterators']]
iter_type = runner_cfg.get("iter_type", "nested_for_loops")
loop_iter = itertools.product(*param_iters)
elif iter_type == 'tuple_loops':
# Combine each i;th index of respective parameter list
- loop_iter = itertools.izip(*param_iters)
+ loop_iter = six.moves.zip(*param_iters)
else:
LOG.warning("iter_type unrecognized: %s", iter_type)
- raise
+ raise TypeError("iter_type unrecognized: %s", iter_type)
# Populate options and run the requested method for each value combination
for comb_values in loop_iter:
if aborted.is_set():
break
- LOG.debug("runner=%(runner)s seq=%(sequence)s START" %
+ LOG.debug("runner=%(runner)s seq=%(sequence)s START",
{"runner": runner_cfg["runner_id"], "sequence": sequence})
for i, value in enumerate(comb_values):
errors = ""
try:
- method(data)
+ 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)
+ LOG.warning("SLA validation failed: %s", assertion.args)
errors = assertion.args
except Exception as e:
errors = traceback.format_exc()
LOG.exception(e)
+ else:
+ if result:
+ output_queue.put(result)
time.sleep(interval)
'errors': errors
}
- record = {'runner_id': runner_cfg['runner_id'],
- 'benchmark': benchmark_output}
-
- queue.put(record)
+ queue.put(benchmark_output)
- LOG.debug("runner=%(runner)s seq=%(sequence)s END" %
+ LOG.debug("runner=%(runner)s seq=%(sequence)s END",
{"runner": runner_cfg["runner_id"], "sequence": sequence})
sequence += 1
- if errors:
+ if errors and sla_action is None:
break
- benchmark.teardown()
+ 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.info("worker END")
+ LOG.debug("queue.qsize() = %s", queue.qsize())
+ LOG.debug("output_queue.qsize() = %s", output_queue.qsize())
class ArithmeticRunner(base.Runner):
- '''Run a scenario arithmetically stepping input value(s)
+ """Run a scenario arithmetically stepping input value(s)
Parameters
interval - time to wait between each scenario invocation
default: none
-
name - and so on......
- '''
+ """
__execution_type__ = 'Arithmetic'
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))
+ context_cfg, self.aborted, self.output_queue))
self.process.start()
Code Review / yardstick.git / blobdiff