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PR-URL: https://github.com/nodejs/node/pull/44741 Fixes: https://github.com/nodejs/node/issues/44650 Fixes: https://github.com/nodejs/node/issues/37472 Reviewed-By: Ben Noordhuis <info@bnoordhuis.nl> Reviewed-By: Jiawen Geng <technicalcute@gmail.com> Reviewed-By: James M Snell <jasnell@gmail.com>
402 lines
12 KiB
Python
402 lines
12 KiB
Python
#!/usr/bin/env python3
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# Copyright 2014 the V8 project authors. All rights reserved.
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# Use of this source code is governed by a BSD-style license that can be
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# found in the LICENSE file.
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import collections
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import logging
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import os
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import signal
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import threading
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import traceback
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from contextlib import contextmanager
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from multiprocessing import Process, Queue
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from queue import Empty
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def setup_testing():
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"""For testing only: Use threading under the hood instead of multiprocessing
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to make coverage work.
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"""
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global Queue
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global Process
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del Queue
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del Process
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from queue import Queue
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from threading import Thread as Process
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# Monkeypatch os.kill and add fake pid property on Thread.
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os.kill = lambda *args: None
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Process.pid = property(lambda self: None)
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class AbortException(Exception):
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"""Indicates early abort on SIGINT, SIGTERM or internal hard timeout."""
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pass
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class NormalResult():
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def __init__(self, result):
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self.result = result
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self.exception = None
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class ExceptionResult():
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def __init__(self, exception):
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self.exception = exception
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class MaybeResult():
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def __init__(self, heartbeat, value):
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self.heartbeat = heartbeat
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self.value = value
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@staticmethod
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def create_heartbeat():
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return MaybeResult(True, None)
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@staticmethod
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def create_result(value):
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return MaybeResult(False, value)
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def Worker(fn, work_queue, done_queue,
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process_context_fn=None, process_context_args=None):
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"""Worker to be run in a child process.
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The worker stops when the poison pill "STOP" is reached.
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"""
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# Install a default signal handler for SIGTERM that stops the processing
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# loop below on the next occasion. The job function "fn" is supposed to
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# register their own handler to avoid blocking, but still chain to this
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# handler on SIGTERM to terminate the loop quickly.
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stop = [False]
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def handler(signum, frame):
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stop[0] = True
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signal.signal(signal.SIGTERM, handler)
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try:
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kwargs = {}
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if process_context_fn and process_context_args is not None:
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kwargs.update(process_context=process_context_fn(*process_context_args))
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for args in iter(work_queue.get, "STOP"):
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if stop[0]:
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# SIGINT, SIGTERM or internal hard timeout caught outside the execution
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# of "fn".
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break
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try:
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done_queue.put(NormalResult(fn(*args, **kwargs)))
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except AbortException:
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# SIGINT, SIGTERM or internal hard timeout caught during execution of
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# "fn".
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break
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except Exception as e:
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logging.exception('Unhandled error during worker execution.')
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done_queue.put(ExceptionResult(e))
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except KeyboardInterrupt:
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assert False, 'Unreachable'
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@contextmanager
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def without_sig():
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int_handler = signal.signal(signal.SIGINT, signal.SIG_IGN)
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term_handler = signal.signal(signal.SIGTERM, signal.SIG_IGN)
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try:
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yield
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finally:
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signal.signal(signal.SIGINT, int_handler)
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signal.signal(signal.SIGTERM, term_handler)
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@contextmanager
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def drain_queue_async(queue):
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"""Drains a queue in a background thread until the wrapped code unblocks.
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This can be used to unblock joining a child process that might still write
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to the queue. The join should be wrapped by this context manager.
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"""
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keep_running = True
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def empty_queue():
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elem_count = 0
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while keep_running:
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try:
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while True:
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queue.get(True, 0.1)
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elem_count += 1
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if elem_count < 200:
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logging.info('Drained an element from queue.')
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except Empty:
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pass
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except:
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logging.exception('Error draining queue.')
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emptier = threading.Thread(target=empty_queue)
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emptier.start()
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yield
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keep_running = False
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emptier.join()
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class ContextPool():
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def __init__(self):
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self.abort_now = False
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def init(self, num_workers, heartbeat_timeout=1, notify_function=None):
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"""
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Delayed initialization. At context creation time we have no access to the
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below described parameters.
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Args:
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num_workers: Number of worker processes to run in parallel.
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heartbeat_timeout: Timeout in seconds for waiting for results. Each time
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the timeout is reached, a heartbeat is signalled and timeout is reset.
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notify_function: Callable called to signal some events like termination. The
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event name is passed as string.
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"""
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pass
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def add_jobs(self, jobs):
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pass
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def results(self, requirement):
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pass
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def abort(self):
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self.abort_now = True
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ProcessContext = collections.namedtuple('ProcessContext', ['result_reduction'])
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class DefaultExecutionPool(ContextPool):
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"""Distributes tasks to a number of worker processes.
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New tasks can be added dynamically even after the workers have been started.
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Requirement: Tasks can only be added from the parent process, e.g. while
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consuming the results generator."""
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# Factor to calculate the maximum number of items in the work/done queue.
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# Necessary to not overflow the queue's pipe if a keyboard interrupt happens.
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BUFFER_FACTOR = 4
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def __init__(self, os_context=None):
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super(DefaultExecutionPool, self).__init__()
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self.os_context = os_context
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self.processes = []
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self.terminated = False
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# Invariant: processing_count >= #work_queue + #done_queue. It is greater
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# when a worker takes an item from the work_queue and before the result is
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# submitted to the done_queue. It is equal when no worker is working,
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# e.g. when all workers have finished, and when no results are processed.
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# Count is only accessed by the parent process. Only the parent process is
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# allowed to remove items from the done_queue and to add items to the
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# work_queue.
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self.processing_count = 0
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# Disable sigint and sigterm to prevent subprocesses from capturing the
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# signals.
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with without_sig():
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self.work_queue = Queue()
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self.done_queue = Queue()
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def init(self, num_workers=1, heartbeat_timeout=1, notify_function=None):
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"""
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Args:
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num_workers: Number of worker processes to run in parallel.
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heartbeat_timeout: Timeout in seconds for waiting for results. Each time
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the timeout is reached, a heartbeat is signalled and timeout is reset.
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notify_function: Callable called to signal some events like termination. The
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event name is passed as string.
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"""
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self.num_workers = num_workers
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self.heartbeat_timeout = heartbeat_timeout
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self.notify = notify_function or (lambda x: x)
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def add_jobs(self, jobs):
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self.add(jobs)
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def results(self, requirement):
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return self.imap_unordered(
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fn=run_job,
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gen=[],
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process_context_fn=ProcessContext,
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process_context_args=[requirement],
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)
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def imap_unordered(self, fn, gen,
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process_context_fn=None, process_context_args=None):
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"""Maps function "fn" to items in generator "gen" on the worker processes
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in an arbitrary order. The items are expected to be lists of arguments to
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the function. Returns a results iterator. A result value of type
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MaybeResult either indicates a heartbeat of the runner, i.e. indicating
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that the runner is still waiting for the result to be computed, or it wraps
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the real result.
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Args:
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process_context_fn: Function executed once by each worker. Expected to
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return a process-context object. If present, this object is passed
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as additional argument to each call to fn.
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process_context_args: List of arguments for the invocation of
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process_context_fn. All arguments will be pickled and sent beyond the
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process boundary.
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"""
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if self.terminated:
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return
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try:
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internal_error = False
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gen = iter(gen)
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self.advance = self._advance_more
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# Disable sigint and sigterm to prevent subprocesses from capturing the
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# signals.
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with without_sig():
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for w in range(self.num_workers):
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p = Process(target=Worker, args=(fn,
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self.work_queue,
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self.done_queue,
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process_context_fn,
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process_context_args))
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p.start()
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self.processes.append(p)
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self.advance(gen)
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while self.processing_count > 0:
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while True:
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try:
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# Read from result queue in a responsive fashion. If available,
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# this will return a normal result immediately or a heartbeat on
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# heartbeat timeout (default 1 second).
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result = self._get_result_from_queue()
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except:
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# TODO(machenbach): Handle a few known types of internal errors
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# gracefully, e.g. missing test files.
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logging.exception('Internal error in a worker process.')
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internal_error = True
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continue
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finally:
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if self.abort_now:
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# SIGINT, SIGTERM or internal hard timeout.
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return
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yield result
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break
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self.advance(gen)
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except KeyboardInterrupt:
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assert False, 'Unreachable'
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except Exception:
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logging.exception('Unhandled error during pool execution.')
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finally:
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self._terminate()
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if internal_error:
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raise Exception('Internal error in a worker process.')
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def _advance_more(self, gen):
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while self.processing_count < self.num_workers * self.BUFFER_FACTOR:
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try:
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self.work_queue.put(next(gen))
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self.processing_count += 1
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except StopIteration:
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self.advance = self._advance_empty
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break
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def _advance_empty(self, gen):
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pass
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def add(self, args):
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"""Adds an item to the work queue. Can be called dynamically while
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processing the results from imap_unordered."""
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assert not self.terminated
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self.work_queue.put(args)
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self.processing_count += 1
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def abort(self):
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"""Schedules abort on next queue read.
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This is safe to call when handling SIGINT, SIGTERM or when an internal
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hard timeout is reached.
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"""
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self.abort_now = True
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def _terminate_processes(self):
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for p in self.processes:
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self.os_context.terminate_process(p)
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def _terminate(self):
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"""Terminates execution and cleans up the queues.
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If abort() was called before termination, this also terminates the
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subprocesses and doesn't wait for ongoing tests.
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"""
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if self.terminated:
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return
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self.terminated = True
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# Drain out work queue from tests
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try:
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while True:
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self.work_queue.get(True, 0.1)
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except Empty:
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pass
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# Make sure all processes stop
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for _ in self.processes:
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# During normal tear down the workers block on get(). Feed a poison pill
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# per worker to make them stop.
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self.work_queue.put("STOP")
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# Send a SIGTERM to all workers. They will gracefully terminate their
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# processing loop and if the signal is caught during job execution they
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# will try to terminate the ongoing test processes quickly.
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if self.abort_now:
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self._terminate_processes()
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self.notify("Joining workers")
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with drain_queue_async(self.done_queue):
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for p in self.processes:
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p.join()
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self.notify("Pool terminated")
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def _get_result_from_queue(self):
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"""Attempts to get the next result from the queue.
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Returns: A wrapped result if one was available within heartbeat timeout,
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a heartbeat result otherwise.
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Raises:
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Exception: If an exception occured when processing the task on the
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worker side, it is reraised here.
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"""
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while True:
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try:
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result = self.done_queue.get(timeout=self.heartbeat_timeout)
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self.processing_count -= 1
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if result.exception:
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raise result.exception
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return MaybeResult.create_result(result.result)
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except Empty:
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return MaybeResult.create_heartbeat()
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class SingleThreadedExecutionPool(ContextPool):
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def __init__(self):
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super(SingleThreadedExecutionPool, self).__init__()
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self.work_queue = []
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def add_jobs(self, jobs):
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self.work_queue.extend(jobs)
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def results(self, requirement):
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while self.work_queue and not self.abort_now:
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job = self.work_queue.pop()
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yield MaybeResult.create_result(job.run(ProcessContext(requirement)))
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# Global function for multiprocessing, because pickling a static method doesn't
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# work on Windows.
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def run_job(job, process_context):
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return job.run(process_context)
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