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)
self._working_dir_uri_cache = URICache(
self._working_dir_manager.delete_uri, WORKING_DIR_CACHE_SIZE_BYTES)
self._py_modules_uri_cache = URICache(
self._py_modules_manager.delete_uri, PY_MODULES_CACHE_SIZE_BYTES)
self._conda_uri_cache = URICache(self._conda_manager.delete_uri,
CONDA_CACHE_SIZE_BYTES)
self._pip_uri_cache = URICache(self._pip_manager.delete_uri,
PIP_CACHE_SIZE_BYTES)
self._logger = default_logger
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()
_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._java_jars_manager = JavaJarsManager(self._runtime_env_dir)
self._working_dir_manager = WorkingDirManager(self._runtime_env_dir)
self._container_manager = ContainerManager(dashboard_agent.temp_dir)
self._reference_table = ReferenceTable(
self.uris_parser,
self.unused_uris_processor,
self.unused_runtime_env_processor,
)
self._working_dir_uri_cache = URICache(
self._working_dir_manager.delete_uri, WORKING_DIR_CACHE_SIZE_BYTES)
self._py_modules_uri_cache = URICache(
self._py_modules_manager.delete_uri, PY_MODULES_CACHE_SIZE_BYTES)
self._java_jars_uri_cache = URICache(
self._java_jars_manager.delete_uri, JAVA_JARS_CACHE_SIZE_BYTES)
self._conda_uri_cache = URICache(self._conda_manager.delete_uri,
CONDA_CACHE_SIZE_BYTES)
self._pip_uri_cache = URICache(self._pip_manager.delete_uri,
PIP_CACHE_SIZE_BYTES)
self._logger = default_logger
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._working_dir_uri_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._conda_manager = CondaManager(self._runtime_env_dir)
self._working_dir_manager = WorkingDirManager(self._runtime_env_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: dict = json.loads(serialized_runtime_env or "{}")
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.get("env_vars"))
self._conda_manager.setup(runtime_env,
context,
logger=per_job_logger)
self._working_dir_manager.setup(runtime_env,
context,
logger=per_job_logger)
# Add the mapping of URIs -> the serialized environment to be
# used for cache invalidation.
for uri in runtime_env.get("uris", []):
self._working_dir_uri_to_envs[uri].add(
serialized_runtime_env)
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}.")
# Only a single URI is currently supported.
assert len(request.uris) == 1
uri = request.uris[0]
# Invalidate the env cache for any environments that contain this URI.
for env in self._working_dir_uri_to_envs.get(uri, []):
if env in self._env_cache:
del self._env_cache[env]
if self._working_dir_manager.delete_uri(uri):
return runtime_env_agent_pb2.DeleteURIsReply(
status=agent_manager_pb2.AGENT_RPC_STATUS_OK)
else:
return runtime_env_agent_pb2.DeleteURIsReply(
status=agent_manager_pb2.AGENT_RPC_STATUS_FAILED,
error_message=f"Local file for URI {uri} not found.")
async def run(self, server):
runtime_env_agent_pb2_grpc.add_RuntimeEnvServiceServicer_to_server(
self, server)
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()
_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._java_jars_manager = JavaJarsManager(self._runtime_env_dir)
self._working_dir_manager = WorkingDirManager(self._runtime_env_dir)
self._container_manager = ContainerManager(dashboard_agent.temp_dir)
self._reference_table = ReferenceTable(
self.uris_parser,
self.unused_uris_processor,
self.unused_runtime_env_processor,
)
self._working_dir_uri_cache = URICache(
self._working_dir_manager.delete_uri, WORKING_DIR_CACHE_SIZE_BYTES)
self._py_modules_uri_cache = URICache(
self._py_modules_manager.delete_uri, PY_MODULES_CACHE_SIZE_BYTES)
self._java_jars_uri_cache = URICache(
self._java_jars_manager.delete_uri, JAVA_JARS_CACHE_SIZE_BYTES)
self._conda_uri_cache = URICache(self._conda_manager.delete_uri,
CONDA_CACHE_SIZE_BYTES)
self._pip_uri_cache = URICache(self._pip_manager.delete_uri,
PIP_CACHE_SIZE_BYTES)
self._logger = default_logger
def uris_parser(self, runtime_env):
result = list()
uri = self._working_dir_manager.get_uri(runtime_env)
if uri:
result.append((uri, UriType.WORKING_DIR))
uris = self._py_modules_manager.get_uris(runtime_env)
for uri in uris:
result.append((uri, UriType.PY_MODULES))
uri = self._pip_manager.get_uri(runtime_env)
if uri:
result.append((uri, UriType.PIP))
uri = self._conda_manager.get_uri(runtime_env)
if uri:
result.append((uri, UriType.CONDA))
return result
def unused_uris_processor(self, unused_uris: List[Tuple[str,
UriType]]) -> None:
for uri, uri_type in unused_uris:
if uri_type == UriType.WORKING_DIR:
self._working_dir_uri_cache.mark_unused(uri)
elif uri_type == UriType.PY_MODULES:
self._py_modules_uri_cache.mark_unused(uri)
elif uri_type == UriType.JAVA_JARS:
self._java_jars_uri_cache.mark_unused(uri)
elif uri_type == UriType.CONDA:
self._conda_uri_cache.mark_unused(uri)
elif uri_type == UriType.PIP:
self._pip_uri_cache.mark_unused(uri)
def unused_runtime_env_processor(self, unused_runtime_env: str) -> None:
def delete_runtime_env():
del self._env_cache[unused_runtime_env]
self._logger.info("Runtime env %s deleted.", unused_runtime_env)
if unused_runtime_env in self._env_cache:
if not self._env_cache[unused_runtime_env].success:
loop = asyncio.get_event_loop()
# Cache the bad runtime env result by ttl seconds.
loop.call_later(
dashboard_consts.BAD_RUNTIME_ENV_CACHE_TTL_SECONDS,
delete_runtime_env,
)
else:
delete_runtime_env()
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 GetOrCreateRuntimeEnv(self, request, context):
self._logger.debug(
f"Got request from {request.source_process} to increase "
"reference for runtime env: "
f"{request.serialized_runtime_env}.")
async def _setup_runtime_env(runtime_env, serialized_runtime_env,
serialized_allocated_resource_instances):
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())
await self._container_manager.setup(runtime_env,
context,
logger=per_job_logger)
for (manager, uri_cache) in [
(self._working_dir_manager, self._working_dir_uri_cache),
(self._conda_manager, self._conda_uri_cache),
(self._pip_manager, self._pip_uri_cache),
]:
uri = manager.get_uri(runtime_env)
if uri is not None:
if uri not in uri_cache:
per_job_logger.debug(f"Cache miss for URI {uri}.")
size_bytes = await manager.create(
uri, runtime_env, context, logger=per_job_logger)
uri_cache.add(uri, size_bytes, logger=per_job_logger)
else:
per_job_logger.debug(f"Cache hit for URI {uri}.")
uri_cache.mark_used(uri, logger=per_job_logger)
manager.modify_context(uri, runtime_env, context)
# Set up py_modules. For now, py_modules uses multiple URIs so
# the logic is slightly different from working_dir, conda, and
# pip above.
for (manager, uri_cache) in [
(self._java_jars_manager, self._java_jars_uri_cache),
(self._py_modules_manager, self._py_modules_uri_cache),
]:
uris = manager.get_uris(runtime_env)
if uris is not None:
per_job_logger.debug(f"URIs is not None, URI {uris}.")
for uri in uris:
if uri not in uri_cache:
per_job_logger.debug(f"Cache miss for URI {uri}.")
size_bytes = await manager.create(
uri,
runtime_env,
context,
logger=per_job_logger)
uri_cache.add(uri,
size_bytes,
logger=per_job_logger)
else:
per_job_logger.debug(f"Cache hit for URI {uri}.")
uri_cache.mark_used(uri, logger=per_job_logger)
manager.modify_context(uris, runtime_env, context)
def setup_plugins():
# Run setup function from all the plugins
for plugin_class_path, config in runtime_env.plugins():
per_job_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)
loop = asyncio.get_event_loop()
# Plugins setup method is sync process, running in other threads
# is to avoid blocks asyncio loop
await loop.run_in_executor(None, setup_plugins)
return context
async def _create_runtime_env_with_retry(
runtime_env,
serialized_runtime_env,
serialized_allocated_resource_instances,
setup_timeout_seconds,
) -> Tuple[bool, str, str]:
"""
Create runtime env with retry times. This function won't raise exceptions.
Args:
runtime_env(RuntimeEnv): The instance of RuntimeEnv class.
serialized_runtime_env(str): The serialized runtime env.
serialized_allocated_resource_instances(str): The serialized allocated
resource instances.
setup_timeout_seconds(int): The timeout of runtime environment creation.
Returns:
a tuple which contains result(bool), runtime env context(str), error
message(str).
"""
self._logger.info(
f"Creating runtime env: {serialized_env} with timeout "
f"{setup_timeout_seconds} seconds.")
serialized_context = None
error_message = None
for _ in range(runtime_env_consts.RUNTIME_ENV_RETRY_TIMES):
try:
# python 3.6 requires the type of input is `Future`,
# python 3.7+ only requires the type of input is `Awaitable`
# TODO(Catch-Bull): remove create_task when ray drop python 3.6
runtime_env_setup_task = create_task(
_setup_runtime_env(
runtime_env,
serialized_env,
request.serialized_allocated_resource_instances,
))
runtime_env_context = await asyncio.wait_for(
runtime_env_setup_task, timeout=setup_timeout_seconds)
serialized_context = runtime_env_context.serialize()
error_message = None
break
except Exception as e:
err_msg = f"Failed to create runtime env {serialized_env}."
self._logger.exception(err_msg)
error_message = "".join(
traceback.format_exception(type(e), e,
e.__traceback__))
await asyncio.sleep(
runtime_env_consts.RUNTIME_ENV_RETRY_INTERVAL_MS / 1000
)
if error_message:
self._logger.error(
"Runtime env creation failed for %d times, "
"don't retry any more.",
runtime_env_consts.RUNTIME_ENV_RETRY_TIMES,
)
return False, None, error_message
else:
self._logger.info(
"Successfully created runtime env: %s, the context: %s",
serialized_env,
serialized_context,
)
return True, serialized_context, None
try:
serialized_env = request.serialized_runtime_env
runtime_env = RuntimeEnv.deserialize(serialized_env)
except Exception as e:
self._logger.exception("[Increase] Failed to parse runtime env: "
f"{serialized_env}")
return runtime_env_agent_pb2.GetOrCreateRuntimeEnvReply(
status=agent_manager_pb2.AGENT_RPC_STATUS_FAILED,
error_message="".join(
traceback.format_exception(type(e), e, e.__traceback__)),
)
# Increase reference
self._reference_table.increase_reference(runtime_env, serialized_env,
request.source_process)
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
self._logger.info("Runtime env already created "
f"successfully. Env: {serialized_env}, "
f"context: {context}")
return runtime_env_agent_pb2.GetOrCreateRuntimeEnvReply(
status=agent_manager_pb2.AGENT_RPC_STATUS_OK,
serialized_runtime_env_context=context,
)
else:
error_message = result.result
self._logger.info("Runtime env already failed. "
f"Env: {serialized_env}, "
f"err: {error_message}")
# Recover the reference.
self._reference_table.decrease_reference(
runtime_env, serialized_env, request.source_process)
return runtime_env_agent_pb2.GetOrCreateRuntimeEnvReply(
status=agent_manager_pb2.AGENT_RPC_STATUS_FAILED,
error_message=error_message,
)
if SLEEP_FOR_TESTING_S:
self._logger.info(f"Sleeping for {SLEEP_FOR_TESTING_S}s.")
time.sleep(int(SLEEP_FOR_TESTING_S))
runtime_env_config = RuntimeEnvConfig.from_proto(
request.runtime_env_config)
# accroding to the document of `asyncio.wait_for`,
# None means disable timeout logic
setup_timeout_seconds = (
None if runtime_env_config["setup_timeout_seconds"] == -1 else
runtime_env_config["setup_timeout_seconds"])
start = time.perf_counter()
(
successful,
serialized_context,
error_message,
) = await _create_runtime_env_with_retry(
runtime_env,
serialized_env,
request.serialized_allocated_resource_instances,
setup_timeout_seconds,
)
creation_time_ms = int(
round((time.perf_counter() - start) * 1000, 0))
if not successful:
# Recover the reference.
self._reference_table.decrease_reference(
runtime_env, serialized_env, request.source_process)
# Add the result to env cache.
self._env_cache[serialized_env] = CreatedEnvResult(
successful,
serialized_context if successful else error_message,
creation_time_ms,
)
# Reply the RPC
return runtime_env_agent_pb2.GetOrCreateRuntimeEnvReply(
status=agent_manager_pb2.AGENT_RPC_STATUS_OK
if successful else agent_manager_pb2.AGENT_RPC_STATUS_FAILED,
serialized_runtime_env_context=serialized_context,
error_message=error_message,
)
async def DeleteRuntimeEnvIfPossible(self, request, context):
self._logger.info(
f"Got request from {request.source_process} to decrease "
"reference for runtime env: "
f"{request.serialized_runtime_env}.")
try:
runtime_env = RuntimeEnv.deserialize(
request.serialized_runtime_env)
except Exception as e:
self._logger.exception("[Decrease] Failed to parse runtime env: "
f"{request.serialized_runtime_env}")
return runtime_env_agent_pb2.GetOrCreateRuntimeEnvReply(
status=agent_manager_pb2.AGENT_RPC_STATUS_FAILED,
error_message="".join(
traceback.format_exception(type(e), e, e.__traceback__)),
)
self._reference_table.decrease_reference(
runtime_env, request.serialized_runtime_env,
request.source_process)
return runtime_env_agent_pb2.DeleteRuntimeEnvIfPossibleReply(
status=agent_manager_pb2.AGENT_RPC_STATUS_OK)
async def GetRuntimeEnvsInfo(self, request, context):
"""Return the runtime env information of the node."""
# TODO(sang): Currently, it only includes runtime_env information.
# We should include the URI information which includes,
# URIs
# Caller
# Ref counts
# Cache information
# Metrics (creation time & success)
# Deleted URIs
runtime_env_states = defaultdict(ProtoRuntimeEnvState)
runtime_env_refs = self._reference_table.runtime_env_refs
for runtime_env, ref_cnt in runtime_env_refs.items():
runtime_env_states[runtime_env].runtime_env = runtime_env
runtime_env_states[runtime_env].ref_cnt = ref_cnt
for runtime_env, result in self._env_cache.items():
runtime_env_states[runtime_env].runtime_env = runtime_env
runtime_env_states[runtime_env].success = result.success
if not result.success:
runtime_env_states[runtime_env].error = result.result
runtime_env_states[
runtime_env].creation_time_ms = result.creation_time_ms
reply = runtime_env_agent_pb2.GetRuntimeEnvsInfoReply()
for runtime_env_state in runtime_env_states.values():
reply.runtime_env_states.append(runtime_env_state)
return reply
async def run(self, server):
if server:
runtime_env_agent_pb2_grpc.add_RuntimeEnvServiceServicer_to_server(
self, server)
@staticmethod
def is_minimal_module():
return True