import asyncio from collections import defaultdict from dataclasses import dataclass import json import logging import os import time from typing import Dict, Set from ray._private.utils import import_attr from ray.core.generated import runtime_env_agent_pb2 from ray.core.generated import runtime_env_agent_pb2_grpc from ray.core.generated import agent_manager_pb2 import ray.dashboard.utils as dashboard_utils import ray.dashboard.modules.runtime_env.runtime_env_consts as runtime_env_consts from ray.experimental.internal_kv import ( _internal_kv_initialized, _initialize_internal_kv, ) from ray._private.ray_logging import setup_component_logger from ray._private.runtime_env.pip import PipManager from ray._private.runtime_env.conda import CondaManager from ray._private.runtime_env.context import RuntimeEnvContext from ray._private.runtime_env.py_modules import PyModulesManager from ray._private.runtime_env.working_dir import WorkingDirManager from ray._private.runtime_env.container import ContainerManager from ray._private.runtime_env.plugin import decode_plugin_uri from ray._private.runtime_env.utils import RuntimeEnv logger = logging.getLogger(__name__) # TODO(edoakes): this is used for unit tests. We should replace it with a # better pluggability mechanism once available. SLEEP_FOR_TESTING_S = os.environ.get("RAY_RUNTIME_ENV_SLEEP_FOR_TESTING_S") @dataclass class CreatedEnvResult: # Whether or not the env was installed correctly. success: bool # If success is True, will be a serialized RuntimeEnvContext # If success is False, will be an error message. result: str class RuntimeEnvAgent( dashboard_utils.DashboardAgentModule, runtime_env_agent_pb2_grpc.RuntimeEnvServiceServicer, ): """An RPC server to create and delete runtime envs. Attributes: dashboard_agent: The DashboardAgent object contains global config. """ def __init__(self, dashboard_agent): super().__init__(dashboard_agent) self._runtime_env_dir = dashboard_agent.runtime_env_dir self._logging_params = dashboard_agent.logging_params self._per_job_logger_cache = dict() # Cache the results of creating envs to avoid repeatedly calling into # conda and other slow calls. self._env_cache: Dict[str, CreatedEnvResult] = dict() # Maps a serialized runtime env to a lock that is used # to prevent multiple concurrent installs of the same env. self._env_locks: Dict[str, asyncio.Lock] = dict() # Keeps track of the URIs contained within each env so we can # invalidate the env cache when a URI is deleted. # This is a temporary mechanism until we have per-URI caching. self._uris_to_envs: Dict[str, Set[str]] = defaultdict(set) # Initialize internal KV to be used by the working_dir setup code. _initialize_internal_kv(self._dashboard_agent.gcs_client) assert _internal_kv_initialized() self._pip_manager = PipManager(self._runtime_env_dir) self._conda_manager = CondaManager(self._runtime_env_dir) self._py_modules_manager = PyModulesManager(self._runtime_env_dir) self._working_dir_manager = WorkingDirManager(self._runtime_env_dir) self._container_manager = ContainerManager(dashboard_agent.temp_dir) def get_or_create_logger(self, job_id: bytes): job_id = job_id.decode() if job_id not in self._per_job_logger_cache: params = self._logging_params.copy() params["filename"] = f"runtime_env_setup-{job_id}.log" params["logger_name"] = f"runtime_env_{job_id}" per_job_logger = setup_component_logger(**params) self._per_job_logger_cache[job_id] = per_job_logger return self._per_job_logger_cache[job_id] async def CreateRuntimeEnv(self, request, context): async def _setup_runtime_env( serialized_runtime_env, serialized_allocated_resource_instances ): # This function will be ran inside a thread def run_setup_with_logger(): runtime_env = RuntimeEnv(serialized_runtime_env=serialized_runtime_env) allocated_resource: dict = json.loads( serialized_allocated_resource_instances or "{}" ) # Use a separate logger for each job. per_job_logger = self.get_or_create_logger(request.job_id) # TODO(chenk008): Add log about allocated_resource to # avoid lint error. That will be moved to cgroup plugin. per_job_logger.debug(f"Worker has resource :" f"{allocated_resource}") context = RuntimeEnvContext(env_vars=runtime_env.env_vars()) self._pip_manager.setup(runtime_env, context, logger=per_job_logger) self._conda_manager.setup(runtime_env, context, logger=per_job_logger) self._py_modules_manager.setup( runtime_env, context, logger=per_job_logger ) self._working_dir_manager.setup( runtime_env, context, logger=per_job_logger ) self._container_manager.setup( runtime_env, context, logger=per_job_logger ) # Add the mapping of URIs -> the serialized environment to be # used for cache invalidation. if runtime_env.working_dir_uri(): uri = runtime_env.working_dir_uri() self._uris_to_envs[uri].add(serialized_runtime_env) if runtime_env.py_modules_uris(): for uri in runtime_env.py_modules_uris(): self._uris_to_envs[uri].add(serialized_runtime_env) if runtime_env.conda_uri(): uri = runtime_env.conda_uri() self._uris_to_envs[uri].add(serialized_runtime_env) if runtime_env.pip_uri(): uri = runtime_env.pip_uri() self._uris_to_envs[uri].add(serialized_runtime_env) if runtime_env.plugin_uris(): for uri in runtime_env.plugin_uris(): self._uris_to_envs[uri].add(serialized_runtime_env) # Run setup function from all the plugins for plugin_class_path, config in runtime_env.plugins(): logger.debug(f"Setting up runtime env plugin {plugin_class_path}") plugin_class = import_attr(plugin_class_path) # TODO(simon): implement uri support plugin_class.create( "uri not implemented", json.loads(config), context ) plugin_class.modify_context( "uri not implemented", json.loads(config), context ) return context loop = asyncio.get_event_loop() return await loop.run_in_executor(None, run_setup_with_logger) serialized_env = request.serialized_runtime_env if serialized_env not in self._env_locks: # async lock to prevent the same env being concurrently installed self._env_locks[serialized_env] = asyncio.Lock() async with self._env_locks[serialized_env]: if serialized_env in self._env_cache: serialized_context = self._env_cache[serialized_env] result = self._env_cache[serialized_env] if result.success: context = result.result logger.info( "Runtime env already created successfully. " f"Env: {serialized_env}, context: {context}" ) return runtime_env_agent_pb2.CreateRuntimeEnvReply( status=agent_manager_pb2.AGENT_RPC_STATUS_OK, serialized_runtime_env_context=context, ) else: error_message = result.result logger.info( "Runtime env already failed. " f"Env: {serialized_env}, err: {error_message}" ) return runtime_env_agent_pb2.CreateRuntimeEnvReply( status=agent_manager_pb2.AGENT_RPC_STATUS_FAILED, error_message=error_message, ) if SLEEP_FOR_TESTING_S: logger.info(f"Sleeping for {SLEEP_FOR_TESTING_S}s.") time.sleep(int(SLEEP_FOR_TESTING_S)) logger.info(f"Creating runtime env: {serialized_env}") runtime_env_context: RuntimeEnvContext = None error_message = None for _ in range(runtime_env_consts.RUNTIME_ENV_RETRY_TIMES): try: runtime_env_context = await _setup_runtime_env( serialized_env, request.serialized_allocated_resource_instances ) break except Exception as ex: logger.exception("Runtime env creation failed.") error_message = str(ex) await asyncio.sleep( runtime_env_consts.RUNTIME_ENV_RETRY_INTERVAL_MS / 1000 ) if error_message: logger.error( "Runtime env creation failed for %d times, " "don't retry any more.", runtime_env_consts.RUNTIME_ENV_RETRY_TIMES, ) self._env_cache[serialized_env] = CreatedEnvResult(False, error_message) return runtime_env_agent_pb2.CreateRuntimeEnvReply( status=agent_manager_pb2.AGENT_RPC_STATUS_FAILED, error_message=error_message, ) serialized_context = runtime_env_context.serialize() self._env_cache[serialized_env] = CreatedEnvResult(True, serialized_context) logger.info( "Successfully created runtime env: %s, the context: %s", serialized_env, serialized_context, ) return runtime_env_agent_pb2.CreateRuntimeEnvReply( status=agent_manager_pb2.AGENT_RPC_STATUS_OK, serialized_runtime_env_context=serialized_context, ) async def DeleteURIs(self, request, context): logger.info(f"Got request to delete URIs: {request.uris}.") failed_uris = [] # URIs that we failed to delete. for plugin_uri in request.uris: plugin, uri = decode_plugin_uri(plugin_uri) # Invalidate the env cache for any envs that contain this URI. for env in self._uris_to_envs.get(uri, []): if env in self._env_cache: del self._env_cache[env] if plugin == "working_dir": if not self._working_dir_manager.delete_uri(uri): failed_uris.append(uri) elif plugin == "py_modules": if not self._py_modules_manager.delete_uri(uri): failed_uris.append(uri) elif plugin == "conda": if not self._conda_manager.delete_uri(uri): failed_uris.append(uri) elif plugin == "pip": if not self._pip_manager.delete_uri(uri): failed_uris.append(uri) else: raise ValueError( "RuntimeEnvAgent received DeleteURI request " f"for unsupported plugin {plugin}. URI: {uri}" ) if failed_uris: return runtime_env_agent_pb2.DeleteURIsReply( status=agent_manager_pb2.AGENT_RPC_STATUS_FAILED, error_message="Local files for URI(s) " f"{failed_uris} not found.", ) else: return runtime_env_agent_pb2.DeleteURIsReply( status=agent_manager_pb2.AGENT_RPC_STATUS_OK ) async def run(self, server): runtime_env_agent_pb2_grpc.add_RuntimeEnvServiceServicer_to_server(self, server) @staticmethod def is_minimal_module(): return True