import asyncio import json import logging import os import signal import subprocess import sys import traceback from asyncio.tasks import FIRST_COMPLETED from typing import Any, Dict, List, Optional import ray import ray._private.ray_constants as ray_constants from ray._common.filters import CoreContextFilter from ray._common.formatters import JSONFormatter, TextFormatter from ray._common.network_utils import build_address from ray._private.accelerators.npu import NOSET_ASCEND_RT_VISIBLE_DEVICES_ENV_VAR from ray._private.accelerators.nvidia_gpu import NOSET_CUDA_VISIBLE_DEVICES_ENV_VAR from ray._private.runtime_env.constants import RAY_JOB_CONFIG_JSON_ENV_VAR from ray._private.utils import remove_ray_internal_flags_from_env from ray._raylet import GcsClient from ray.actor import ActorHandle from ray.dashboard.modules.job.common import ( JOB_ID_METADATA_KEY, JOB_NAME_METADATA_KEY, JobInfoStorageClient, ) from ray.dashboard.modules.job.job_log_storage_client import JobLogStorageClient from ray.job_submission import JobErrorType, JobStatus import psutil # asyncio python version compatibility try: create_task = asyncio.create_task except AttributeError: create_task = asyncio.ensure_future # Windows requires additional packages for proper process control. if sys.platform == "win32": try: import win32api import win32con import win32job except (ModuleNotFoundError, ImportError) as e: win32api = None win32con = None win32job = None logger = logging.getLogger(__name__) logger.warning( "Failed to Import win32api. For best usage experience run " f"'conda install pywin32'. Import error: {e}" ) class JobSupervisor: """ Ray actor created by JobManager for each submitted job, responsible to setup runtime_env, execute given shell command in subprocess, update job status, persist job logs and manage subprocess group cleaning. One job supervisor actor maps to one subprocess, for one job_id. Job supervisor actor should fate share with subprocess it created. """ DEFAULT_RAY_JOB_STOP_WAIT_TIME_S = 3 SUBPROCESS_POLL_PERIOD_S = 0.1 VALID_STOP_SIGNALS = ["SIGINT", "SIGTERM"] def __init__( self, job_id: str, entrypoint: str, user_metadata: Dict[str, str], gcs_address: str, cluster_id_hex: str, logs_dir: Optional[str] = None, ): self._job_id = job_id gcs_client = GcsClient(address=gcs_address, cluster_id=cluster_id_hex) self._job_info_client = JobInfoStorageClient(gcs_client, logs_dir) self._log_client = JobLogStorageClient() self._entrypoint = entrypoint # Default metadata if not passed by the user. self._metadata = {JOB_ID_METADATA_KEY: job_id, JOB_NAME_METADATA_KEY: job_id} self._metadata.update(user_metadata) # Event used to signal that a job should be stopped. # Set in the `stop_job` method. self._stop_event = asyncio.Event() # Windows Job Object used to handle stopping the child processes. self._win32_job_object = None # Logger object to persist JobSupervisor logs in separate file. self._logger = logging.getLogger(f"{__name__}.supervisor-{job_id}") self._configure_logger() def _configure_logger(self) -> None: """ Configure self._logger object to write logs to file based on job submission ID and to console. """ supervisor_log_file_name = os.path.join( ray._private.worker._global_node.get_logs_dir_path(), f"jobs/supervisor-{self._job_id}.log", ) os.makedirs(os.path.dirname(supervisor_log_file_name), exist_ok=True) self._logger.addFilter(CoreContextFilter()) stream_handler = logging.StreamHandler() file_handler = logging.FileHandler(supervisor_log_file_name) formatter = TextFormatter() if ray_constants.env_bool(ray_constants.RAY_BACKEND_LOG_JSON_ENV_VAR, False): formatter = JSONFormatter() stream_handler.setFormatter(formatter) file_handler.setFormatter(formatter) self._logger.addHandler(stream_handler) self._logger.addHandler(file_handler) self._logger.propagate = False def _get_driver_runtime_env( self, resources_specified: bool = False ) -> Dict[str, Any]: """Get the runtime env that should be set in the job driver. Args: resources_specified: Whether the user specified resources (CPUs, GPUs, custom resources) in the submit_job request. If so, we will skip the workaround for GPU detection introduced in #24546, so that the behavior matches that of the user specifying resources for any other actor. Returns: The runtime env that should be set in the job driver. """ # Get the runtime_env set for the supervisor actor. curr_runtime_env = dict(ray.get_runtime_context().runtime_env) if resources_specified: return curr_runtime_env # Allow CUDA_VISIBLE_DEVICES to be set normally for the driver's tasks # & actors. env_vars = curr_runtime_env.get("env_vars", {}) env_vars.pop(NOSET_CUDA_VISIBLE_DEVICES_ENV_VAR) env_vars.pop(NOSET_ASCEND_RT_VISIBLE_DEVICES_ENV_VAR) env_vars.pop(ray_constants.RAY_WORKER_NICENESS) curr_runtime_env["env_vars"] = env_vars return curr_runtime_env def ping(self): """Used to check the health of the actor.""" pass def _exec_entrypoint(self, env: dict, logs_path: str) -> subprocess.Popen: """ Runs the entrypoint command as a child process, streaming stderr & stdout to given log files. Unix systems: Meanwhile we start a demon process and group driver subprocess in same pgid, such that if job actor dies, entire process group also fate share with it. Windows systems: A jobObject is created to enable fate sharing for the entire process group. Args: env: Environment variables passed through to the driver subprocess. logs_path: File path on head node's local disk to store driver command's stdout & stderr. Returns: child_process: Child process that runs the driver command. Can be terminated or killed upon user calling stop(). """ # Open in append mode to avoid overwriting runtime_env setup logs for the # supervisor actor, which are also written to the same file. with open(logs_path, "a") as logs_file: logs_file.write( f"Running entrypoint for job {self._job_id}: {self._entrypoint}\n" ) child_process = subprocess.Popen( self._entrypoint, shell=True, start_new_session=True, stdout=logs_file, stderr=subprocess.STDOUT, env=env, # Ray intentionally blocks SIGINT in all processes, so if the user wants # to stop job through SIGINT, we need to unblock it in the child process preexec_fn=( ( lambda: signal.pthread_sigmask( signal.SIG_UNBLOCK, {signal.SIGINT} ) ) if sys.platform != "win32" and os.environ.get("RAY_JOB_STOP_SIGNAL") == "SIGINT" else None ), ) parent_pid = os.getpid() child_pid = child_process.pid # Create new pgid with new subprocess to execute driver command if sys.platform != "win32": try: child_pgid = os.getpgid(child_pid) except ProcessLookupError: # Process died before we could get its pgid. return child_process # Open a new subprocess to kill the child process when the parent # process dies kill -s 0 parent_pid will succeed if the parent is # alive. If it fails, SIGKILL the child process group and exit subprocess.Popen( f"while kill -s 0 {parent_pid}; do sleep 1; done; kill -9 -{child_pgid}", # noqa: E501 shell=True, # Suppress output stdout=subprocess.DEVNULL, stderr=subprocess.DEVNULL, ) elif sys.platform == "win32" and win32api: # Create a JobObject to which the child process (and its children) # will be connected. This job object can be used to kill the child # processes explicitly or when the jobObject gets deleted during # garbage collection. self._win32_job_object = win32job.CreateJobObject(None, "") win32_job_info = win32job.QueryInformationJobObject( self._win32_job_object, win32job.JobObjectExtendedLimitInformation ) win32_job_info["BasicLimitInformation"][ "LimitFlags" ] = win32job.JOB_OBJECT_LIMIT_KILL_ON_JOB_CLOSE win32job.SetInformationJobObject( self._win32_job_object, win32job.JobObjectExtendedLimitInformation, win32_job_info, ) child_handle = win32api.OpenProcess( win32con.PROCESS_TERMINATE | win32con.PROCESS_SET_QUOTA, False, child_pid, ) win32job.AssignProcessToJobObject(self._win32_job_object, child_handle) return child_process def _get_driver_env_vars(self, resources_specified: bool) -> Dict[str, str]: """Returns environment variables that should be set in the driver.""" # RAY_ADDRESS may be the dashboard URL but not the gcs address, # so when the environment variable is not empty, we force set RAY_ADDRESS # to "auto" to avoid function `canonicalize_bootstrap_address_or_die` returning # the wrong GCS address. # TODO(Jialing He, Archit Kulkarni): Definition of Specification RAY_ADDRESS if ray_constants.RAY_ADDRESS_ENVIRONMENT_VARIABLE in os.environ: os.environ[ray_constants.RAY_ADDRESS_ENVIRONMENT_VARIABLE] = "auto" ray_addr = ray._private.services.canonicalize_bootstrap_address_or_die( "auto", ray._private.worker._global_node._ray_params.temp_dir ) assert ray_addr is not None return { # Set JobConfig for the child process (runtime_env, metadata). RAY_JOB_CONFIG_JSON_ENV_VAR: json.dumps( { "runtime_env": self._get_driver_runtime_env(resources_specified), "metadata": self._metadata, } ), # Always set RAY_ADDRESS as find_bootstrap_address address for # job submission. In case of local development, prevent user from # re-using http://{address}:{dashboard_port} to interact with # jobs SDK. # TODO:(mwtian) Check why "auto" does not work in entrypoint script ray_constants.RAY_ADDRESS_ENVIRONMENT_VARIABLE: ray_addr, # Set PYTHONUNBUFFERED=1 to stream logs during the job instead of # only streaming them upon completion of the job. "PYTHONUNBUFFERED": "1", } async def _polling(self, child_process: subprocess.Popen) -> int: while child_process is not None: return_code = child_process.poll() if return_code is not None: # subprocess finished with return code return return_code else: # still running, yield control, 0.1s by default await asyncio.sleep(self.SUBPROCESS_POLL_PERIOD_S) async def _poll_all(self, processes: List[psutil.Process]): """Poll processes until all are completed.""" while True: (_, alive) = psutil.wait_procs(processes, timeout=0) if len(alive) == 0: return else: await asyncio.sleep(self.SUBPROCESS_POLL_PERIOD_S) def _kill_processes(self, processes: List[psutil.Process], sig: signal.Signals): """Ensure each process is already finished or send a kill signal.""" for proc in processes: try: os.kill(proc.pid, sig) except ProcessLookupError: # Process is already dead pass async def run( self, # Signal actor used in testing to capture PENDING -> RUNNING cases _start_signal_actor: Optional[ActorHandle] = None, resources_specified: bool = False, ): """ Stop and start both happen asynchronously, coordinated by asyncio event and coroutine, respectively. 1) Sets job status as running 2) Pass runtime env and metadata to subprocess as serialized env variables. 3) Handle concurrent events of driver execution and """ curr_info = await self._job_info_client.get_info(self._job_id) if curr_info is None: raise RuntimeError(f"Status could not be retrieved for job {self._job_id}.") curr_status = curr_info.status curr_message = curr_info.message if curr_status == JobStatus.RUNNING: raise RuntimeError( f"Job {self._job_id} is already in RUNNING state. " f"JobSupervisor.run() should only be called once. " ) if curr_status != JobStatus.PENDING: raise RuntimeError( f"Job {self._job_id} is not in PENDING state. " f"Current status is {curr_status} with message {curr_message}." ) if _start_signal_actor: # Block in PENDING state until start signal received. await _start_signal_actor.wait.remote() node = ray._private.worker.global_worker.node driver_agent_http_address = f"http://{build_address(node.node_ip_address, node.dashboard_agent_listen_port)}" driver_node_id = ray.get_runtime_context().get_node_id() await self._job_info_client.put_status( self._job_id, JobStatus.RUNNING, jobinfo_replace_kwargs={ "driver_agent_http_address": driver_agent_http_address, "driver_node_id": driver_node_id, }, ) try: # Configure environment variables for the child process. env = os.environ.copy() # Remove internal Ray flags. They present because JobSuperVisor itself is # a Ray worker process but we don't want to pass them to the driver. remove_ray_internal_flags_from_env(env) # These will *not* be set in the runtime_env, so they apply to the driver # only, not its tasks & actors. env.update(self._get_driver_env_vars(resources_specified)) self._logger.info( "Submitting job with RAY_ADDRESS = " f"{env[ray_constants.RAY_ADDRESS_ENVIRONMENT_VARIABLE]}" ) log_path = self._log_client.get_log_file_path(self._job_id) child_process = self._exec_entrypoint(env, log_path) child_pid = child_process.pid polling_task = create_task(self._polling(child_process)) finished, _ = await asyncio.wait( [polling_task, create_task(self._stop_event.wait())], return_when=FIRST_COMPLETED, ) if self._stop_event.is_set(): polling_task.cancel() if sys.platform == "win32" and self._win32_job_object: win32job.TerminateJobObject(self._win32_job_object, -1) elif sys.platform != "win32": stop_signal = os.environ.get("RAY_JOB_STOP_SIGNAL", "SIGTERM") if stop_signal not in self.VALID_STOP_SIGNALS: self._logger.warning( f"{stop_signal} not a valid stop signal. Terminating " "job with SIGTERM." ) stop_signal = "SIGTERM" job_process = psutil.Process(child_pid) proc_to_kill = [job_process] + job_process.children(recursive=True) # Send stop signal and wait for job to terminate gracefully, # otherwise SIGKILL job forcefully after timeout. self._kill_processes(proc_to_kill, getattr(signal, stop_signal)) try: stop_job_wait_time = int( os.environ.get( "RAY_JOB_STOP_WAIT_TIME_S", self.DEFAULT_RAY_JOB_STOP_WAIT_TIME_S, ) ) poll_job_stop_task = create_task(self._poll_all(proc_to_kill)) await asyncio.wait_for(poll_job_stop_task, stop_job_wait_time) self._logger.info( f"Job {self._job_id} has been terminated gracefully " f"with {stop_signal}." ) except asyncio.TimeoutError: self._logger.warning( f"Attempt to gracefully terminate job {self._job_id} " f"through {stop_signal} has timed out after " f"{stop_job_wait_time} seconds. Job is now being " "force-killed with SIGKILL." ) self._kill_processes(proc_to_kill, signal.SIGKILL) await self._job_info_client.put_status(self._job_id, JobStatus.STOPPED) else: # Child process finished execution and no stop event is set # at the same time assert len(finished) == 1, "Should have only one coroutine done" [child_process_task] = finished return_code = child_process_task.result() self._logger.info( f"Job {self._job_id} entrypoint command " f"exited with code {return_code}" ) if return_code == 0: await self._job_info_client.put_status( self._job_id, JobStatus.SUCCEEDED, driver_exit_code=return_code, ) else: log_tail = await self._log_client.get_last_n_log_lines(self._job_id) if log_tail is not None and log_tail != "": message = ( "Job entrypoint command " f"failed with exit code {return_code}, " "last available logs (truncated to 20,000 chars):\n" + log_tail ) else: message = ( "Job entrypoint command " f"failed with exit code {return_code}. No logs available." ) await self._job_info_client.put_status( self._job_id, JobStatus.FAILED, message=message, driver_exit_code=return_code, error_type=JobErrorType.JOB_ENTRYPOINT_COMMAND_ERROR, ) except Exception: self._logger.error( "Got unexpected exception while trying to execute driver " f"command. {traceback.format_exc()}" ) try: await self._job_info_client.put_status( self._job_id, JobStatus.FAILED, message=traceback.format_exc(), error_type=JobErrorType.JOB_ENTRYPOINT_COMMAND_START_ERROR, ) except Exception: self._logger.error( "Failed to update job status to FAILED. " f"Exception: {traceback.format_exc()}" ) finally: # clean up actor after tasks are finished ray.actor.exit_actor() def stop(self): """Set step_event and let run() handle the rest in its asyncio.wait().""" self._stop_event.set()