cc6940b42e
Partially addresses bug #1045152 On a heavily loaded compute node, it can be observed that periodic tasks take so long to run that the report_state() looping call can be blocked from running long enough that the scheduler thinks the host is dead. Reduce the chance of this happening by yielding to another greenthread after each periodic task has completed and each loop in some methods that has linear relationship with the number of instances. Change-Id: If2b125708da8298b20497e2e08e52280c102f1e1
234 lines
8.4 KiB
Python
234 lines
8.4 KiB
Python
# vim: tabstop=4 shiftwidth=4 softtabstop=4
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# Copyright 2010 United States Government as represented by the
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# Administrator of the National Aeronautics and Space Administration.
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# All Rights Reserved.
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#
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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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"""Base Manager class.
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Managers are responsible for a certain aspect of the system. It is a logical
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grouping of code relating to a portion of the system. In general other
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components should be using the manager to make changes to the components that
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it is responsible for.
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For example, other components that need to deal with volumes in some way,
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should do so by calling methods on the VolumeManager instead of directly
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changing fields in the database. This allows us to keep all of the code
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relating to volumes in the same place.
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We have adopted a basic strategy of Smart managers and dumb data, which means
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rather than attaching methods to data objects, components should call manager
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methods that act on the data.
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Methods on managers that can be executed locally should be called directly. If
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a particular method must execute on a remote host, this should be done via rpc
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to the service that wraps the manager
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Managers should be responsible for most of the db access, and
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non-implementation specific data. Anything implementation specific that can't
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be generalized should be done by the Driver.
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In general, we prefer to have one manager with multiple drivers for different
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implementations, but sometimes it makes sense to have multiple managers. You
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can think of it this way: Abstract different overall strategies at the manager
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level(FlatNetwork vs VlanNetwork), and different implementations at the driver
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level(LinuxNetDriver vs CiscoNetDriver).
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Managers will often provide methods for initial setup of a host or periodic
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tasks to a wrapping service.
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This module provides Manager, a base class for managers.
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"""
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import eventlet
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from nova.db import base
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from nova import flags
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from nova.openstack.common import log as logging
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from nova.openstack.common.plugin import pluginmanager
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from nova.openstack.common.rpc import dispatcher as rpc_dispatcher
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from nova.scheduler import rpcapi as scheduler_rpcapi
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from nova import version
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FLAGS = flags.FLAGS
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LOG = logging.getLogger(__name__)
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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 every tick
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of the periodic scheduler.
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2. With arguments, @periodic_task(ticks_between_runs=N), this will be
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run on every N ticks of the periodic scheduler.
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"""
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def decorator(f):
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f._periodic_task = True
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f._ticks_between_runs = kwargs.pop('ticks_between_runs', 0)
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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 parens.
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#
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# In the 'with-parens' case (with kwargs present), this function needs to
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# 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-parens' 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 ManagerMeta(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(ManagerMeta, 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._ticks_to_skip = cls._ticks_to_skip.copy()
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except AttributeError:
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cls._ticks_to_skip = {}
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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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cls._periodic_tasks.append((name, task))
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cls._ticks_to_skip[name] = task._ticks_between_runs
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class Manager(base.Base):
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__metaclass__ = ManagerMeta
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# Set RPC API version to 1.0 by default.
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RPC_API_VERSION = '1.0'
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def __init__(self, host=None, db_driver=None):
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if not host:
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host = FLAGS.host
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self.host = host
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self.load_plugins()
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super(Manager, self).__init__(db_driver)
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def load_plugins(self):
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pluginmgr = pluginmanager.PluginManager('nova', self.__class__)
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pluginmgr.load_plugins()
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def create_rpc_dispatcher(self):
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'''Get the rpc dispatcher for this manager.
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If a manager would like to set an rpc API version, or support more than
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one class as the target of rpc messages, override this method.
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'''
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return rpc_dispatcher.RpcDispatcher([self])
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def periodic_tasks(self, context, raise_on_error=False):
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"""Tasks to be run at a periodic 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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ticks_to_skip = self._ticks_to_skip[task_name]
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if ticks_to_skip > 0:
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LOG.debug(_("Skipping %(full_task_name)s, %(ticks_to_skip)s"
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" ticks left until next run"), locals())
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self._ticks_to_skip[task_name] -= 1
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continue
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self._ticks_to_skip[task_name] = task._ticks_between_runs
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LOG.debug(_("Running periodic task %(full_task_name)s"), locals())
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try:
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task(self, context)
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# NOTE(tiantian): After finished a task, allow manager to
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# do other work (report_state, processing AMPQ request etc.)
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eventlet.sleep(0)
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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(_("Error during %(full_task_name)s: %(e)s"),
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locals())
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def init_host(self):
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"""Handle initialization if this is a standalone service.
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Child classes should override this method.
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"""
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pass
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def service_version(self, context):
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return version.version_string()
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def service_config(self, context):
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config = {}
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for key in FLAGS:
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config[key] = FLAGS.get(key, None)
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return config
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class SchedulerDependentManager(Manager):
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"""Periodically send capability updates to the Scheduler services.
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Services that need to update the Scheduler of their capabilities
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should derive from this class. Otherwise they can derive from
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manager.Manager directly. Updates are only sent after
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update_service_capabilities is called with non-None values.
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"""
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def __init__(self, host=None, db_driver=None, service_name='undefined'):
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self.last_capabilities = None
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self.service_name = service_name
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self.scheduler_rpcapi = scheduler_rpcapi.SchedulerAPI()
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super(SchedulerDependentManager, self).__init__(host, db_driver)
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def load_plugins(self):
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pluginmgr = pluginmanager.PluginManager('nova', self.service_name)
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pluginmgr.load_plugins()
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def update_service_capabilities(self, capabilities):
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"""Remember these capabilities to send on next periodic update."""
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self.last_capabilities = capabilities
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@periodic_task
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def _publish_service_capabilities(self, context):
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"""Pass data back to the scheduler at a periodic interval."""
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if self.last_capabilities:
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LOG.debug(_('Notifying Schedulers of capabilities ...'))
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self.scheduler_rpcapi.update_service_capabilities(context,
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self.service_name, self.host, self.last_capabilities)
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