4a16b068ef
Set the value of time the periodic task was last run to a multiple of the spacing value rather than the actual last time run. This ensures tasks runs regularly but avoids synchronizing that interval with other nodes. This patch also removes the coalescing of tasks which are _nearby_ (0.2 seconds away). 4dbd3aa Make periodic tasks run on regular spacing interval 21249f1 Fix parenthesis typo misunderstanding in periodic_task Change-Id: I8873545578f104fd204fbc25493350128b2bc8d4
207 lines
7.4 KiB
Python
207 lines
7.4 KiB
Python
#
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# Licensed under the Apache License, Version 2.0 (the "License"); you may
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# not use this file except in compliance with the License. You may obtain
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# a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS, WITHOUT
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# WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the
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# License for the specific language governing permissions and limitations
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# under the License.
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import random
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import time
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from oslo.config import cfg
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import six
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from neutron.openstack.common.gettextutils import _, _LE, _LI
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from neutron.openstack.common import log as logging
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periodic_opts = [
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cfg.BoolOpt('run_external_periodic_tasks',
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default=True,
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help='Some periodic tasks can be run in a separate process. '
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'Should we run them here?'),
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]
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CONF = cfg.CONF
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CONF.register_opts(periodic_opts)
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LOG = logging.getLogger(__name__)
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DEFAULT_INTERVAL = 60.0
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class InvalidPeriodicTaskArg(Exception):
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message = _("Unexpected argument for periodic task creation: %(arg)s.")
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def periodic_task(*args, **kwargs):
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"""Decorator to indicate that a method is a periodic task.
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This decorator can be used in two ways:
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1. Without arguments '@periodic_task', this will be run on the default
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interval of 60 seconds.
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2. With arguments:
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@periodic_task(spacing=N [, run_immediately=[True|False]])
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this will be run on approximately every N seconds. If this number is
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negative the periodic task will be disabled. If the run_immediately
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argument is provided and has a value of 'True', the first run of the
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task will be shortly after task scheduler starts. If
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run_immediately is omitted or set to 'False', the first time the
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task runs will be approximately N seconds after the task scheduler
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starts.
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"""
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def decorator(f):
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# Test for old style invocation
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if 'ticks_between_runs' in kwargs:
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raise InvalidPeriodicTaskArg(arg='ticks_between_runs')
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# Control if run at all
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f._periodic_task = True
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f._periodic_external_ok = kwargs.pop('external_process_ok', False)
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if f._periodic_external_ok and not CONF.run_external_periodic_tasks:
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f._periodic_enabled = False
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else:
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f._periodic_enabled = kwargs.pop('enabled', True)
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# Control frequency
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f._periodic_spacing = kwargs.pop('spacing', 0)
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f._periodic_immediate = kwargs.pop('run_immediately', False)
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if f._periodic_immediate:
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f._periodic_last_run = None
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else:
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f._periodic_last_run = time.time()
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return f
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# NOTE(sirp): The `if` is necessary to allow the decorator to be used with
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# and without parenthesis.
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#
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# In the 'with-parenthesis' case (with kwargs present), this function needs
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# to return a decorator function since the interpreter will invoke it like:
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#
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# periodic_task(*args, **kwargs)(f)
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#
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# In the 'without-parenthesis' case, the original function will be passed
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# in as the first argument, like:
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#
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# periodic_task(f)
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if kwargs:
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return decorator
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else:
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return decorator(args[0])
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class _PeriodicTasksMeta(type):
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def __init__(cls, names, bases, dict_):
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"""Metaclass that allows us to collect decorated periodic tasks."""
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super(_PeriodicTasksMeta, cls).__init__(names, bases, dict_)
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# NOTE(sirp): if the attribute is not present then we must be the base
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# class, so, go ahead an initialize it. If the attribute is present,
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# then we're a subclass so make a copy of it so we don't step on our
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# parent's toes.
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try:
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cls._periodic_tasks = cls._periodic_tasks[:]
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except AttributeError:
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cls._periodic_tasks = []
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try:
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cls._periodic_spacing = cls._periodic_spacing.copy()
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except AttributeError:
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cls._periodic_spacing = {}
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for value in cls.__dict__.values():
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if getattr(value, '_periodic_task', False):
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task = value
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name = task.__name__
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if task._periodic_spacing < 0:
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LOG.info(_LI('Skipping periodic task %(task)s because '
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'its interval is negative'),
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{'task': name})
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continue
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if not task._periodic_enabled:
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LOG.info(_LI('Skipping periodic task %(task)s because '
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'it is disabled'),
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{'task': name})
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continue
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# A periodic spacing of zero indicates that this task should
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# be run on the default interval to avoid running too
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# frequently.
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if task._periodic_spacing == 0:
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task._periodic_spacing = DEFAULT_INTERVAL
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cls._periodic_tasks.append((name, task))
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cls._periodic_spacing[name] = task._periodic_spacing
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def _nearest_boundary(last_run, spacing):
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"""Find nearest boundary which is in the past, which is a multiple of the
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spacing with the last run as an offset.
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Eg if last run was 10 and spacing was 7, the new last run could be: 17, 24,
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31, 38...
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0% to 5% of the spacing value will be added to this value to ensure tasks
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do not synchronize. This jitter is rounded to the nearest second, this
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means that spacings smaller than 20 seconds will not have jitter.
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"""
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current_time = time.time()
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if last_run is None:
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return current_time
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delta = current_time - last_run
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offset = delta % spacing
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# Add up to 5% jitter
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jitter = int(spacing * (random.random() / 20))
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return current_time - offset + jitter
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@six.add_metaclass(_PeriodicTasksMeta)
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class PeriodicTasks(object):
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def __init__(self):
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super(PeriodicTasks, self).__init__()
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self._periodic_last_run = {}
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for name, task in self._periodic_tasks:
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self._periodic_last_run[name] = task._periodic_last_run
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def run_periodic_tasks(self, context, raise_on_error=False):
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"""Tasks to be run at a periodic interval."""
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idle_for = DEFAULT_INTERVAL
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for task_name, task in self._periodic_tasks:
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full_task_name = '.'.join([self.__class__.__name__, task_name])
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spacing = self._periodic_spacing[task_name]
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last_run = self._periodic_last_run[task_name]
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# Check if due, if not skip
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idle_for = min(idle_for, spacing)
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if last_run is not None:
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delta = last_run + spacing - time.time()
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if delta > 0:
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idle_for = min(idle_for, delta)
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continue
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LOG.debug("Running periodic task %(full_task_name)s",
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{"full_task_name": full_task_name})
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self._periodic_last_run[task_name] = _nearest_boundary(
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last_run, spacing)
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try:
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task(self, context)
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except Exception as e:
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if raise_on_error:
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raise
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LOG.exception(_LE("Error during %(full_task_name)s: %(e)s"),
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{"full_task_name": full_task_name, "e": e})
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time.sleep(0)
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return idle_for
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