22fd32fb55
Instead of providing and retaining a thread count in the worker and action engine executors and checking it and handling the none case, we can just let the future types handle this already (which they already do). And when displaying this information in the worker banner use a new future executor attribute that is the maximum number of workers that will be ever created. Change-Id: I765c22936b53cdbb8a90195a764d4c67bcc3f34b
436 lines
15 KiB
Python
436 lines
15 KiB
Python
# -*- coding: utf-8 -*-
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# Copyright (C) 2014 Yahoo! Inc. 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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import functools
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import threading
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from concurrent import futures as _futures
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from concurrent.futures import process as _process
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from concurrent.futures import thread as _thread
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from oslo_utils import importutils
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from oslo_utils import reflection
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greenpatcher = importutils.try_import('eventlet.patcher')
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greenpool = importutils.try_import('eventlet.greenpool')
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greenqueue = importutils.try_import('eventlet.queue')
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greenthreading = importutils.try_import('eventlet.green.threading')
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from taskflow.types import timing
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from taskflow.utils import eventlet_utils as eu
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from taskflow.utils import threading_utils as tu
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# NOTE(harlowja): Allows for simpler access to this type...
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Future = _futures.Future
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class _Gatherer(object):
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def __init__(self, submit_func,
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lock_cls=threading.Lock, start_before_submit=False):
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self._submit_func = submit_func
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self._stats_lock = lock_cls()
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self._stats = ExecutorStatistics()
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self._start_before_submit = start_before_submit
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@property
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def statistics(self):
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return self._stats
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def clear(self):
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with self._stats_lock:
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self._stats = ExecutorStatistics()
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def _capture_stats(self, watch, fut):
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"""Capture statistics
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:param watch: stopwatch object
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:param fut: future object
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"""
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watch.stop()
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with self._stats_lock:
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# Use a new collection and lock so that all mutations are seen as
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# atomic and not overlapping and corrupting with other
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# mutations (the clone ensures that others reading the current
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# values will not see a mutated/corrupted one). Since futures may
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# be completed by different threads we need to be extra careful to
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# gather this data in a way that is thread-safe...
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(failures, executed, runtime, cancelled) = (self._stats.failures,
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self._stats.executed,
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self._stats.runtime,
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self._stats.cancelled)
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if fut.cancelled():
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cancelled += 1
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else:
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executed += 1
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if fut.exception() is not None:
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failures += 1
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runtime += watch.elapsed()
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self._stats = ExecutorStatistics(failures=failures,
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executed=executed,
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runtime=runtime,
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cancelled=cancelled)
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def submit(self, fn, *args, **kwargs):
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"""Submit work to be executed and capture statistics."""
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watch = timing.StopWatch()
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if self._start_before_submit:
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watch.start()
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fut = self._submit_func(fn, *args, **kwargs)
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if not self._start_before_submit:
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watch.start()
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fut.add_done_callback(functools.partial(self._capture_stats, watch))
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return fut
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class ThreadPoolExecutor(_thread.ThreadPoolExecutor):
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"""Executor that uses a thread pool to execute calls asynchronously.
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It gathers statistics about the submissions executed for post-analysis...
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See: https://docs.python.org/dev/library/concurrent.futures.html
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"""
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def __init__(self, max_workers=None):
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if max_workers is None:
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max_workers = tu.get_optimal_thread_count()
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super(ThreadPoolExecutor, self).__init__(max_workers=max_workers)
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if self._max_workers <= 0:
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raise ValueError("Max workers must be greater than zero")
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self._gatherer = _Gatherer(
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# Since our submit will use this gatherer we have to reference
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# the parent submit, bound to this instance (which is what we
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# really want to use anyway).
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super(ThreadPoolExecutor, self).submit)
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@property
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def max_workers(self):
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"""The max number of workers that this executor will ever have."""
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return self._max_workers
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@property
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def statistics(self):
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""":class:`.ExecutorStatistics` about the executors executions."""
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return self._gatherer.statistics
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@property
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def alive(self):
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"""Accessor to determine if the executor is alive/active."""
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return not self._shutdown
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def submit(self, fn, *args, **kwargs):
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"""Submit some work to be executed (and gather statistics)."""
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return self._gatherer.submit(fn, *args, **kwargs)
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class ProcessPoolExecutor(_process.ProcessPoolExecutor):
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"""Executor that uses a process pool to execute calls asynchronously.
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It gathers statistics about the submissions executed for post-analysis...
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See: https://docs.python.org/dev/library/concurrent.futures.html
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"""
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def __init__(self, max_workers=None):
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if max_workers is None:
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max_workers = tu.get_optimal_thread_count()
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super(ProcessPoolExecutor, self).__init__(max_workers=max_workers)
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if self._max_workers <= 0:
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raise ValueError("Max workers must be greater than zero")
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self._gatherer = _Gatherer(
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# Since our submit will use this gatherer we have to reference
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# the parent submit, bound to this instance (which is what we
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# really want to use anyway).
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super(ProcessPoolExecutor, self).submit)
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@property
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def alive(self):
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"""Accessor to determine if the executor is alive/active."""
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return not self._shutdown_thread
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@property
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def max_workers(self):
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"""The max number of workers that this executor will ever have."""
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return self._max_workers
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@property
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def statistics(self):
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""":class:`.ExecutorStatistics` about the executors executions."""
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return self._gatherer.statistics
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def submit(self, fn, *args, **kwargs):
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"""Submit some work to be executed (and gather statistics)."""
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return self._gatherer.submit(fn, *args, **kwargs)
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class _WorkItem(object):
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def __init__(self, future, fn, args, kwargs):
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self.future = future
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self.fn = fn
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self.args = args
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self.kwargs = kwargs
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def run(self):
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if not self.future.set_running_or_notify_cancel():
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return
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try:
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result = self.fn(*self.args, **self.kwargs)
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except BaseException as e:
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self.future.set_exception(e)
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else:
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self.future.set_result(result)
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class SynchronousExecutor(_futures.Executor):
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"""Executor that uses the caller to execute calls synchronously.
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This provides an interface to a caller that looks like an executor but
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will execute the calls inside the caller thread instead of executing it
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in a external process/thread for when this type of functionality is
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useful to provide...
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It gathers statistics about the submissions executed for post-analysis...
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"""
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def __init__(self):
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self._shutoff = False
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self._gatherer = _Gatherer(self._submit,
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start_before_submit=True)
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@property
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def alive(self):
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"""Accessor to determine if the executor is alive/active."""
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return not self._shutoff
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def shutdown(self, wait=True):
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self._shutoff = True
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def restart(self):
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"""Restarts this executor (*iff* previously shutoff/shutdown).
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NOTE(harlowja): clears any previously gathered statistics.
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"""
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if self._shutoff:
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self._shutoff = False
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self._gatherer.clear()
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@property
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def statistics(self):
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""":class:`.ExecutorStatistics` about the executors executions."""
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return self._gatherer.statistics
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def submit(self, fn, *args, **kwargs):
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"""Submit some work to be executed (and gather statistics)."""
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if self._shutoff:
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raise RuntimeError('Can not schedule new futures'
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' after being shutdown')
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return self._gatherer.submit(fn, *args, **kwargs)
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def _submit(self, fn, *args, **kwargs):
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f = Future()
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runner = _WorkItem(f, fn, args, kwargs)
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runner.run()
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return f
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class _GreenWorker(object):
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def __init__(self, executor, work, work_queue):
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self.executor = executor
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self.work = work
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self.work_queue = work_queue
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def __call__(self):
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# Run our main piece of work.
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try:
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self.work.run()
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finally:
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# Consume any delayed work before finishing (this is how we finish
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# work that was to big for the pool size, but needs to be finished
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# no matter).
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while True:
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try:
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w = self.work_queue.get_nowait()
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except greenqueue.Empty:
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break
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else:
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try:
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w.run()
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finally:
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self.work_queue.task_done()
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class GreenFuture(Future):
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def __init__(self):
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super(GreenFuture, self).__init__()
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eu.check_for_eventlet(RuntimeError('Eventlet is needed to use a green'
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' future'))
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# NOTE(harlowja): replace the built-in condition with a greenthread
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# compatible one so that when getting the result of this future the
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# functions will correctly yield to eventlet. If this is not done then
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# waiting on the future never actually causes the greenthreads to run
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# and thus you wait for infinity.
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if not greenpatcher.is_monkey_patched('threading'):
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self._condition = greenthreading.Condition()
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class GreenThreadPoolExecutor(_futures.Executor):
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"""Executor that uses a green thread pool to execute calls asynchronously.
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See: https://docs.python.org/dev/library/concurrent.futures.html
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and http://eventlet.net/doc/modules/greenpool.html for information on
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how this works.
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It gathers statistics about the submissions executed for post-analysis...
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"""
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def __init__(self, max_workers=1000):
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eu.check_for_eventlet(RuntimeError('Eventlet is needed to use a green'
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' executor'))
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if max_workers <= 0:
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raise ValueError("Max workers must be greater than zero")
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self._max_workers = max_workers
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self._pool = greenpool.GreenPool(self._max_workers)
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self._delayed_work = greenqueue.Queue()
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self._shutdown_lock = greenthreading.Lock()
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self._shutdown = False
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self._gatherer = _Gatherer(self._submit,
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lock_cls=greenthreading.Lock)
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@property
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def alive(self):
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"""Accessor to determine if the executor is alive/active."""
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return not self._shutdown
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@property
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def statistics(self):
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""":class:`.ExecutorStatistics` about the executors executions."""
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return self._gatherer.statistics
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def submit(self, fn, *args, **kwargs):
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"""Submit some work to be executed (and gather statistics).
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:param args: non-keyworded arguments
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:type args: list
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:param kwargs: key-value arguments
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:type kwargs: dictionary
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"""
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with self._shutdown_lock:
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if self._shutdown:
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raise RuntimeError('Can not schedule new futures'
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' after being shutdown')
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return self._gatherer.submit(fn, *args, **kwargs)
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def _submit(self, fn, *args, **kwargs):
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f = GreenFuture()
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work = _WorkItem(f, fn, args, kwargs)
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if not self._spin_up(work):
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self._delayed_work.put(work)
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return f
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def _spin_up(self, work):
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"""Spin up a greenworker if less than max_workers.
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:param work: work to be given to the greenworker
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:returns: whether a green worker was spun up or not
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:rtype: boolean
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"""
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alive = self._pool.running() + self._pool.waiting()
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if alive < self._max_workers:
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self._pool.spawn_n(_GreenWorker(self, work, self._delayed_work))
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return True
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return False
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def shutdown(self, wait=True):
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with self._shutdown_lock:
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if not self._shutdown:
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self._shutdown = True
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shutoff = True
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else:
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shutoff = False
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if wait and shutoff:
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self._pool.waitall()
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self._delayed_work.join()
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class ExecutorStatistics(object):
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"""Holds *immutable* information about a executors executions."""
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__slots__ = ['_failures', '_executed', '_runtime', '_cancelled']
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__repr_format = ("failures=%(failures)s, executed=%(executed)s, "
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"runtime=%(runtime)s, cancelled=%(cancelled)s")
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def __init__(self, failures=0, executed=0, runtime=0.0, cancelled=0):
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self._failures = failures
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self._executed = executed
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self._runtime = runtime
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self._cancelled = cancelled
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@property
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def failures(self):
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"""How many submissions ended up raising exceptions.
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:returns: how many submissions ended up raising exceptions
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:rtype: number
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"""
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return self._failures
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@property
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def executed(self):
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"""How many submissions were executed (failed or not).
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:returns: how many submissions were executed
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:rtype: number
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"""
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return self._executed
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@property
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def runtime(self):
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"""Total runtime of all submissions executed (failed or not).
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:returns: total runtime of all submissions executed
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:rtype: number
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"""
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return self._runtime
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@property
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def cancelled(self):
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"""How many submissions were cancelled before executing.
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:returns: how many submissions were cancelled before executing
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:rtype: number
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"""
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return self._cancelled
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@property
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def average_runtime(self):
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"""The average runtime of all submissions executed.
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:returns: average runtime of all submissions executed
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:rtype: number
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:raises: ZeroDivisionError when no executions have occurred.
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"""
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return self._runtime / self._executed
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def __repr__(self):
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r = reflection.get_class_name(self, fully_qualified=False)
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r += "("
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r += self.__repr_format % ({
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'failures': self._failures,
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'executed': self._executed,
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'runtime': self._runtime,
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'cancelled': self._cancelled,
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})
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r += ")"
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return r
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