aboutsummaryrefslogtreecommitdiffstats
path: root/yardstick/benchmark/runners/iteration.py
blob: 15dad2cd5a9060798cd8625175d622c7750ce75d (plain)
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
# 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 traceback

import os

from yardstick.benchmark.runners import base
from yardstick.common import exceptions as y_exc

LOG = logging.getLogger(__name__)


QUEUE_PUT_TIMEOUT = 10


def _worker_process(queue, cls, method_name, scenario_cfg,
                    context_cfg, aborted, output_queue):

    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()

    scenario_output = base.ScenarioOutput(queue, sequence=1, errors="")
    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": scenario_output.sequence})

            scenario_output.clear()
            scenario_output.errors = ""
            benchmark.pre_run_wait_time(interval)

            try:
                result = method(scenario_output)
            except y_exc.SLAValidationError as error:
                # 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", error.args)
                    scenario_output.errors = error.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
                    scenario_output.sequence = 1
                    continue
            except Exception:  # pylint: disable=broad-except
                scenario_output.errors = traceback.format_exc()
                LOG.exception("")
                raise
            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)

            benchmark.post_run_wait_time(interval)

            if scenario_output:
                scenario_output.push()

            LOG.debug("runner=%(runner)s seq=%(sequence)s END",
                      {"runner": runner_cfg["runner_id"],
                       "sequence": scenario_output.sequence})

            scenario_output.sequence += 1

            if (scenario_output.errors and sla_action is None) or \
                    (scenario_output.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()