from __future__ import annotations
import asyncio
import contextlib
import errno
import functools
import logging
import multiprocessing
import os
import shutil
import threading
import uuid
import warnings
import weakref
from collections.abc import Callable, Collection
from inspect import isawaitable
from queue import Empty
from time import sleep as sync_sleep
from typing import TYPE_CHECKING, ClassVar, Literal
from toolz import merge
from tornado.ioloop import IOLoop
import dask
from dask.system import CPU_COUNT
from dask.utils import parse_timedelta
from distributed import preloading
from distributed.comm import get_address_host
from distributed.comm.addressing import address_from_user_args
from distributed.core import (
AsyncTaskGroupClosedError,
CommClosedError,
ErrorMessage,
RPCClosed,
Status,
coerce_to_address,
error_message,
)
from distributed.diagnostics.plugin import _get_plugin_name
from distributed.metrics import time
from distributed.node import ServerNode
from distributed.process import AsyncProcess
from distributed.proctitle import enable_proctitle_on_children
from distributed.protocol import pickle
from distributed.protocol.serialize import _is_dumpable
from distributed.security import Security
from distributed.utils import (
get_ip,
get_mp_context,
json_load_robust,
log_errors,
parse_ports,
silence_logging_cmgr,
wait_for,
)
from distributed.worker import Worker, run
from distributed.worker_memory import (
DeprecatedMemoryManagerAttribute,
DeprecatedMemoryMonitor,
NannyMemoryManager,
)
if TYPE_CHECKING:
from distributed.diagnostics.plugin import NannyPlugin
logger = logging.getLogger(__name__)
[docs]class Nanny(ServerNode):
"""A process to manage worker processes
The nanny spins up Worker processes, watches them, and kills or restarts
them as necessary. It is necessary if you want to use the
``Client.restart`` method, or to restart the worker automatically if
it gets to the terminate fraction of its memory limit.
The parameters for the Nanny are mostly the same as those for the Worker
with exceptions listed below.
Parameters
----------
env: dict, optional
Environment variables set at time of Nanny initialization will be
ensured to be set in the Worker process as well. This argument allows to
overwrite or otherwise set environment variables for the Worker. It is
also possible to set environment variables using the option
``distributed.nanny.environ``. Precedence as follows
1. Nanny arguments
2. Existing environment variables
3. Dask configuration
.. note::
Some environment variables, like ``OMP_NUM_THREADS``, must be set before
importing numpy to have effect. Others, like ``MALLOC_TRIM_THRESHOLD_`` (see
:ref:`memtrim`), must be set before starting the Linux process. Such
variables would be ineffective if set here or in
``distributed.nanny.environ``; they must be set in
``distributed.nanny.pre-spawn-environ`` so that they are set before spawning
the subprocess, even if this means poisoning the process running the Nanny.
For the same reason, be warned that changing
``distributed.worker.multiprocessing-method`` from ``spawn`` to ``fork`` or
``forkserver`` may inhibit some environment variables; if you do, you should
set the variables yourself in the shell before you start ``dask-worker``.
See Also
--------
Worker
"""
_instances: ClassVar[weakref.WeakSet[Nanny]] = weakref.WeakSet()
process: WorkerProcess | None
memory_manager: NannyMemoryManager
env: dict[str, str]
pre_spawn_env: dict[str, str]
# Inputs to parse_ports()
_given_worker_port: int | str | Collection[int] | None
_start_port: int | str | Collection[int] | None
def __init__( # type: ignore[no-untyped-def]
self,
scheduler_ip=None,
scheduler_port=None,
scheduler_file=None,
worker_port: int | str | Collection[int] | None = 0,
nthreads=None,
loop=None,
local_directory=None,
services=None,
name=None,
memory_limit="auto",
reconnect=True,
validate=False,
quiet=False,
resources=None,
silence_logs=None,
death_timeout=None,
preload=None,
preload_argv=None,
preload_nanny=None,
preload_nanny_argv=None,
security=None,
contact_address=None,
listen_address=None,
worker_class=None,
env=None,
interface=None,
host=None,
port: int | str | Collection[int] | None = None,
protocol=None,
config=None,
**worker_kwargs,
):
if loop is not None:
warnings.warn(
"the `loop` kwarg to `Nanny` is ignored, and will be removed in a future release. "
"The Nanny always binds to the current loop.",
DeprecationWarning,
stacklevel=2,
)
self.__exit_stack = stack = contextlib.ExitStack()
self.process = None
self._setup_logging(logger)
self.loop = self.io_loop = IOLoop.current()
if isinstance(security, dict):
security = Security(**security)
self.security = security or Security()
assert isinstance(self.security, Security)
self.connection_args = self.security.get_connection_args("worker")
self.preload = preload
if self.preload is None:
self.preload = dask.config.get("distributed.worker.preload")
self.preload_argv = preload_argv
if self.preload_argv is None:
self.preload_argv = dask.config.get("distributed.worker.preload-argv")
if preload_nanny is None:
preload_nanny = dask.config.get("distributed.nanny.preload")
if preload_nanny_argv is None:
preload_nanny_argv = dask.config.get("distributed.nanny.preload-argv")
handlers = {
"instantiate": self.instantiate,
"kill": self.kill,
"restart": self.restart,
"get_logs": self.get_logs,
# cannot call it 'close' on the rpc side for naming conflict
"terminate": self.close,
"close_gracefully": self.close_gracefully,
"run": self.run,
"plugin_add": self.plugin_add,
"plugin_remove": self.plugin_remove,
}
super().__init__(
handlers=handlers,
connection_args=self.connection_args,
local_directory=local_directory,
needs_workdir=False,
)
self.preloads = preloading.process_preloads(
self, preload_nanny, preload_nanny_argv, file_dir=self.local_directory
)
self.death_timeout = parse_timedelta(death_timeout)
if scheduler_file:
cfg = json_load_robust(scheduler_file, timeout=self.death_timeout)
self.scheduler_addr = cfg["address"]
elif scheduler_ip is None and dask.config.get("scheduler-address"):
self.scheduler_addr = dask.config.get("scheduler-address")
elif scheduler_port is None:
self.scheduler_addr = coerce_to_address(scheduler_ip)
else:
self.scheduler_addr = coerce_to_address((scheduler_ip, scheduler_port))
if protocol is None:
protocol_address = self.scheduler_addr.split("://")
if len(protocol_address) == 2:
protocol = protocol_address[0]
self._given_worker_port = worker_port
self.nthreads: int = nthreads or CPU_COUNT
self.reconnect = reconnect
self.validate = validate
self.resources = resources
self.Worker = Worker if worker_class is None else worker_class
self.pre_spawn_env = _get_env_variables("distributed.nanny.pre-spawn-environ")
self.env = merge(
self.pre_spawn_env,
_get_env_variables("distributed.nanny.environ"),
{k: str(v) for k, v in env.items()} if env else {},
)
self.config = merge(dask.config.config, config or {})
worker_kwargs.update(
{
"port": worker_port,
"interface": interface,
"protocol": protocol,
"host": host,
}
)
self.worker_kwargs = worker_kwargs
self.contact_address = contact_address
self.services = services
self.name = name
self.quiet = quiet
if silence_logs:
stack.enter_context(silence_logging_cmgr(level=silence_logs))
self.silence_logs = silence_logs
self.plugins: dict[str, NannyPlugin] = {}
self.scheduler = self.rpc(self.scheduler_addr)
self.memory_manager = NannyMemoryManager(self, memory_limit=memory_limit)
if (
not host
and not interface
and not self.scheduler_addr.startswith("inproc://")
):
host = get_ip(get_address_host(self.scheduler.address))
self._start_port = port
self._start_host = host
self._interface = interface
self._protocol = protocol
self._listen_address = listen_address
Nanny._instances.add(self)
# Deprecated attributes; use Nanny.memory_manager.<name> instead
memory_limit = DeprecatedMemoryManagerAttribute()
memory_terminate_fraction = DeprecatedMemoryManagerAttribute()
memory_monitor = DeprecatedMemoryMonitor()
def __repr__(self):
return "<Nanny: %s, threads: %d>" % (self.worker_address, self.nthreads)
async def _unregister(self, timeout=10):
if self.process is None:
return
worker_address = self.process.worker_address
if worker_address is None:
return
try:
await wait_for(
self.scheduler.unregister(
address=self.worker_address, stimulus_id=f"nanny-close-{time()}"
),
timeout,
)
except (asyncio.TimeoutError, CommClosedError, OSError, RPCClosed):
pass
@property
def worker_address(self):
return None if self.process is None else self.process.worker_address
@property
def worker_dir(self):
return None if self.process is None else self.process.worker_dir
[docs] async def start_unsafe(self):
"""Start nanny, start local process, start watching"""
await super().start_unsafe()
ports = parse_ports(self._start_port)
for port in ports:
start_address = address_from_user_args(
host=self._start_host,
port=port,
interface=self._interface,
protocol=self._protocol,
security=self.security,
)
try:
await self.listen(
start_address, **self.security.get_listen_args("worker")
)
except OSError as e:
if len(ports) > 1 and e.errno == errno.EADDRINUSE:
continue
else:
raise
else:
self._start_address = start_address
break
else:
raise ValueError(
f"Could not start Nanny on host {self._start_host} "
f"with port {self._start_port}"
)
self.ip = get_address_host(self.address)
for preload in self.preloads:
await preload.start()
msg = await self.scheduler.register_nanny()
for name, plugin in msg["nanny-plugins"].items():
await self.plugin_add(plugin=plugin, name=name)
logger.info(" Start Nanny at: %r", self.address)
response = await self.instantiate()
if response != Status.running:
await self.close(reason="nanny-start-failed")
return
assert self.worker_address
self.start_periodic_callbacks()
return self
[docs] async def kill(self, timeout: float = 2, reason: str = "nanny-kill") -> None:
"""Kill the local worker process
Blocks until both the process is down and the scheduler is properly
informed
"""
if self.process is None:
return
deadline = time() + timeout
await self.process.kill(reason=reason, timeout=0.8 * (deadline - time()))
[docs] async def instantiate(self) -> Status:
"""Start a local worker process
Blocks until the process is up and the scheduler is properly informed
"""
if self.process is None:
worker_kwargs = dict(
scheduler_ip=self.scheduler_addr,
nthreads=self.nthreads,
local_directory=self._original_local_dir,
services=self.services,
nanny=self.address,
name=self.name,
memory_limit=self.memory_manager.memory_limit,
resources=self.resources,
validate=self.validate,
silence_logs=self.silence_logs,
death_timeout=self.death_timeout,
preload=self.preload,
preload_argv=self.preload_argv,
security=self.security,
contact_address=self.contact_address,
)
worker_kwargs.update(self.worker_kwargs)
self.process = WorkerProcess(
worker_kwargs=worker_kwargs,
silence_logs=self.silence_logs,
on_exit=self._on_worker_exit_sync,
worker=self.Worker,
env=self.env,
pre_spawn_env=self.pre_spawn_env,
config=self.config,
)
if self.death_timeout:
try:
result = await wait_for(self.process.start(), self.death_timeout)
except asyncio.TimeoutError:
logger.error(
"Timed out connecting Nanny '%s' to scheduler '%s'",
self,
self.scheduler_addr,
)
await self.close(
timeout=self.death_timeout, reason="nanny-instantiate-timeout"
)
raise
else:
try:
result = await self.process.start()
except Exception:
logger.error("Failed to start process", exc_info=True)
await self.close(reason="nanny-instantiate-failed")
raise
return result
@log_errors
async def plugin_add(self, plugin=None, name=None):
if isinstance(plugin, bytes):
plugin = pickle.loads(plugin)
if name is None:
name = _get_plugin_name(plugin)
assert name
self.plugins[name] = plugin
logger.info("Starting Nanny plugin %s" % name)
if hasattr(plugin, "setup"):
try:
result = plugin.setup(nanny=self)
if isawaitable(result):
result = await result
except Exception as e:
msg = error_message(e)
return msg
if getattr(plugin, "restart", False):
await self.restart(reason=f"nanny-plugin-{name}-restart")
return {"status": "OK"}
@log_errors
async def plugin_remove(self, name=None):
logger.info(f"Removing Nanny plugin {name}")
try:
plugin = self.plugins.pop(name)
if hasattr(plugin, "teardown"):
result = plugin.teardown(nanny=self)
if isawaitable(result):
result = await result
except Exception as e:
msg = error_message(e)
return msg
return {"status": "OK"}
async def restart(
self, timeout: float = 30, reason: str = "nanny-restart"
) -> Literal["OK", "timed out"] | ErrorMessage:
async def _():
if self.process is not None:
await self.kill(reason=reason)
await self.instantiate()
try:
await wait_for(_(), timeout)
except asyncio.TimeoutError:
logger.error(
f"Restart timed out after {timeout}s; returning before finished"
)
return "timed out"
except Exception as e:
return error_message(e)
else:
return "OK"
def is_alive(self):
return self.process is not None and self.process.is_alive()
def run(self, comm, *args, **kwargs):
return run(self, comm, *args, **kwargs)
def _on_worker_exit_sync(self, exitcode):
try:
self._ongoing_background_tasks.call_soon(self._on_worker_exit, exitcode)
except (
AsyncTaskGroupClosedError
): # Async task group has already been closed, so the nanny is already clos(ed|ing).
pass
@log_errors
async def _on_worker_exit(self, exitcode):
if self.status not in (
Status.init,
Status.closing,
Status.closed,
Status.closing_gracefully,
Status.failed,
):
try:
await self._unregister()
except OSError:
logger.exception("Failed to unregister")
if not self.reconnect:
await self.close(reason="nanny-unregister-failed")
return
try:
if self.status not in (
Status.closing,
Status.closed,
Status.closing_gracefully,
Status.failed,
):
logger.warning("Restarting worker")
await self.instantiate()
elif self.status == Status.closing_gracefully:
await self.close(reason="nanny-close-gracefully")
except Exception:
logger.error(
"Failed to restart worker after its process exited", exc_info=True
)
@property
def pid(self):
return self.process and self.process.pid
def _close(self, *args, **kwargs):
warnings.warn("Worker._close has moved to Worker.close", stacklevel=2)
return self.close(*args, **kwargs)
[docs] def close_gracefully(self, reason: str = "nanny-close-gracefully") -> None:
"""
A signal that we shouldn't try to restart workers if they go away
This is used as part of the cluster shutdown process.
"""
self.status = Status.closing_gracefully
logger.info(
"Closing Nanny gracefully at %r. Reason: %s", self.address_safe, reason
)
[docs] async def close(
self, timeout: float = 5, reason: str = "nanny-close"
) -> Literal["OK"]:
"""
Close the worker process, stop all comms.
"""
if self.status == Status.closing:
await self.finished()
assert self.status == Status.closed
if self.status == Status.closed:
return "OK"
self.status = Status.closing
logger.info("Closing Nanny at %r. Reason: %s", self.address_safe, reason)
for preload in self.preloads:
await preload.teardown()
teardowns = [
plugin.teardown(self)
for plugin in self.plugins.values()
if hasattr(plugin, "teardown")
]
await asyncio.gather(*(td for td in teardowns if isawaitable(td)))
self.stop()
try:
if self.process is not None:
await self.kill(timeout=timeout, reason=reason)
except Exception:
logger.exception("Error in Nanny killing Worker subprocess")
self.process = None
await self.rpc.close()
self.status = Status.closed
await super().close()
self.__exit_stack.__exit__(None, None, None)
return "OK"
async def _log_event(self, topic, msg):
await self.scheduler.log_event(
topic=topic,
msg=msg,
)
[docs] def log_event(self, topic, msg):
"""Log an event under a given topic
Parameters
----------
topic : str, list[str]
Name of the topic under which to log an event. To log the same
event under multiple topics, pass a list of topic names.
msg
Event message to log. Note this must be msgpack serializable.
See also
--------
Client.log_event
"""
if not _is_dumpable(msg):
raise TypeError(
f"Message must be msgpack serializable. Got {type(msg)=} instead."
)
self._ongoing_background_tasks.call_soon(self._log_event, topic, msg)
class WorkerProcess:
running: asyncio.Event
stopped: asyncio.Event
process: AsyncProcess | None
env: dict[str, str]
pre_spawn_env: dict[str, str]
# The interval how often to check the msg queue for init
_init_msg_interval = 0.05
def __init__(
self,
worker_kwargs,
silence_logs,
on_exit,
worker,
env,
pre_spawn_env,
config,
):
self.status = Status.init
self.silence_logs = silence_logs
self.worker_kwargs = worker_kwargs
self.on_exit = on_exit
self.process = None
self.Worker = worker
self.env = env
self.pre_spawn_env = pre_spawn_env
self.config = config.copy()
# Ensure default clients don't propagate to subprocesses
try:
from distributed.client import default_client
default_client()
self.config.pop("scheduler", None)
self.config.pop("shuffle", None)
except ValueError:
pass
# Initialized when worker is ready
self.worker_dir = None
self.worker_address = None
async def start(self) -> Status:
"""
Ensure the worker process is started.
"""
enable_proctitle_on_children()
if self.status == Status.running:
return self.status
if self.status == Status.starting:
await self.running.wait()
return self.status
self.init_result_q = init_q = get_mp_context().Queue()
self.child_stop_q = get_mp_context().Queue()
uid = uuid.uuid4().hex
self.process = AsyncProcess(
target=functools.partial(
self._run,
silence_logs=self.silence_logs,
init_result_q=self.init_result_q,
child_stop_q=self.child_stop_q,
uid=uid,
worker_factory=functools.partial(self.Worker, **self.worker_kwargs),
env=self.env,
config=self.config,
),
name="Dask Worker process (from Nanny)",
kwargs=dict(),
)
self.process.daemon = dask.config.get("distributed.worker.daemon", default=True)
self.process.set_exit_callback(self._on_exit)
self.running = asyncio.Event()
self.stopped = asyncio.Event()
self.status = Status.starting
# Set selected environment variables before spawning the subprocess.
# See note in Nanny docstring.
os.environ.update(self.pre_spawn_env)
try:
await self.process.start()
except OSError:
logger.exception("Nanny failed to start process", exc_info=True)
# NOTE: doesn't wait for process to terminate, just for terminate signal to be sent
await self.process.terminate()
self.status = Status.failed
try:
msg = await self._wait_until_connected(uid)
except Exception:
# NOTE: doesn't wait for process to terminate, just for terminate signal to be sent
await self.process.terminate()
self.status = Status.failed
raise
if not msg:
return self.status
self.worker_address = msg["address"]
self.worker_dir = msg["dir"]
assert self.worker_address
self.status = Status.running
self.running.set()
init_q.close()
return self.status
def _on_exit(self, proc):
if proc is not self.process:
# Ignore exit of old process instance
return
self.mark_stopped()
def _death_message(self, pid, exitcode):
assert exitcode is not None
if exitcode == 255:
return "Worker process %d was killed by unknown signal" % (pid,)
elif exitcode >= 0:
return "Worker process %d exited with status %d" % (pid, exitcode)
else:
return "Worker process %d was killed by signal %d" % (pid, -exitcode)
def is_alive(self):
return self.process is not None and self.process.is_alive()
@property
def pid(self):
return self.process.pid if self.process and self.process.is_alive() else None
def mark_stopped(self):
if self.status != Status.stopped:
assert self.process is not None
r = self.process.exitcode
assert r is not None
if r != 0:
msg = self._death_message(self.process.pid, r)
logger.info(msg)
self.status = Status.stopped
self.stopped.set()
# Release resources
self.process.close()
self.init_result_q = None
self.child_stop_q = None
self.process = None
# Best effort to clean up worker directory
if self.worker_dir and os.path.exists(self.worker_dir):
shutil.rmtree(self.worker_dir, ignore_errors=True)
self.worker_dir = None
# User hook
if self.on_exit is not None:
self.on_exit(r)
async def kill(
self,
timeout: float = 2,
executor_wait: bool = True,
reason: str = "workerprocess-kill",
) -> None:
"""
Ensure the worker process is stopped, waiting at most
``timeout * 0.8`` seconds before killing it abruptly.
When `kill` returns, the worker process has been joined.
If the worker process does not terminate within ``timeout`` seconds,
even after being killed, `asyncio.TimeoutError` is raised.
"""
deadline = time() + timeout
if self.status == Status.stopped:
return
if self.status == Status.stopping:
await self.stopped.wait()
return
# If the process is not properly up it will not watch the closing queue
# and we may end up leaking this process
# Therefore wait for it to be properly started before killing it
if self.status == Status.starting:
await self.running.wait()
assert self.status in (
Status.running,
Status.failed, # process failed to start, but hasn't been joined yet
), self.status
self.status = Status.stopping
logger.info("Nanny asking worker to close. Reason: %s", reason)
process = self.process
assert process
queue = self.child_stop_q
assert queue
wait_timeout = timeout * 0.8
queue.put(
{
"op": "stop",
"timeout": wait_timeout,
"executor_wait": executor_wait,
"reason": reason,
}
)
await asyncio.sleep(0) # otherwise we get broken pipe errors
queue.close()
del queue
try:
try:
await process.join(wait_timeout)
return
except asyncio.TimeoutError:
pass
logger.warning(
f"Worker process still alive after {wait_timeout} seconds, killing"
)
await process.kill()
await process.join(max(0, deadline - time()))
except ValueError as e:
if "invalid operation on closed AsyncProcess" in str(e):
return
raise
async def _wait_until_connected(self, uid):
while True:
if self.status != Status.starting:
return
# This is a multiprocessing queue and we'd block the event loop if
# we simply called get
try:
msg = self.init_result_q.get_nowait()
except Empty:
await asyncio.sleep(self._init_msg_interval)
continue
if msg["uid"] != uid: # ensure that we didn't cross queues
continue
if "exception" in msg:
raise msg["exception"]
else:
return msg
@classmethod
def _run(
cls,
silence_logs: bool,
init_result_q: multiprocessing.Queue,
child_stop_q: multiprocessing.Queue,
uid: str,
env: dict,
config: dict,
worker_factory: Callable[[], Worker],
) -> None: # pragma: no cover
async def do_stop(
*,
worker: Worker,
timeout: float = 5,
executor_wait: bool = True,
reason: str = "workerprocess-stop",
) -> None:
await worker.close(
nanny=False,
executor_wait=executor_wait,
timeout=timeout,
reason=reason,
)
def watch_stop_q(loop: IOLoop, worker: Worker) -> None:
"""
Wait for an incoming stop message and then stop the
worker cleanly.
"""
try:
msg = child_stop_q.get()
except (TypeError, OSError, EOFError):
logger.error("Worker process died unexpectedly")
msg = {"op": "stop"}
finally:
child_stop_q.close()
assert msg["op"] == "stop", msg
del msg["op"]
loop.add_callback(do_stop, worker=worker, **msg)
async def run() -> None:
"""
Try to start worker and inform parent of outcome.
"""
failure_type: str | None = "initialize"
try:
worker = worker_factory()
failure_type = "start"
thread = threading.Thread(
target=functools.partial(
watch_stop_q,
worker=worker,
loop=IOLoop.current(),
),
name="Nanny stop queue watch",
daemon=True,
)
thread.start()
stack.callback(thread.join, timeout=2)
async with worker:
failure_type = None
try:
assert worker.address
except ValueError:
pass
else:
init_result_q.put(
{
"address": worker.address,
"dir": worker.local_directory,
"uid": uid,
}
)
init_result_q.close()
await worker.finished()
logger.info("Worker closed")
except Exception as e:
if failure_type is None:
raise
logger.exception(f"Failed to {failure_type} worker")
init_result_q.put({"uid": uid, "exception": e})
init_result_q.close()
# If we hit an exception here we need to wait for a least
# one interval for the outside to pick up this message.
# Otherwise we arrive in a race condition where the process
# cleanup wipes the queue before the exception can be
# properly handled. See also
# WorkerProcess._wait_until_connected (the 3 is for good
# measure)
sync_sleep(cls._init_msg_interval * 3)
with contextlib.ExitStack() as stack:
@stack.callback
def close_stop_q() -> None:
try:
child_stop_q.put({"op": "stop"}) # usually redundant
except ValueError:
pass
try:
child_stop_q.close() # usually redundant
except ValueError:
pass
child_stop_q.join_thread()
os.environ.update(env)
dask.config.refresh()
dask.config.set(config)
from dask.multiprocessing import default_initializer
default_initializer()
if silence_logs:
logger.setLevel(silence_logs)
asyncio.run(run())
def _get_env_variables(config_key: str) -> dict[str, str]:
cfg = dask.config.get(config_key)
if not isinstance(cfg, dict):
raise TypeError( # pragma: nocover
f"{config_key} configuration must be of type dict. Instead got {type(cfg)}"
)
# Override dask config with explicitly defined env variables from the OS
cfg = {k: os.environ.get(k, str(v)) for k, v in cfg.items()}
return cfg