async def list_placement_groups(self, *, option: ListApiOptions) -> ListApiResponse: """List all placement group information from the cluster. Returns: {pg_id -> pg_data_in_dict} pg_data_in_dict's schema is in PlacementGroupState """ try: reply = await self._client.get_all_placement_group_info( timeout=option.timeout ) except DataSourceUnavailable: raise DataSourceUnavailable(GCS_QUERY_FAILURE_WARNING) result = [] for message in reply.placement_group_table_data: data = self._message_to_dict( message=message, fields_to_decode=["placement_group_id"], ) result.append(data) result = self._filter(result, option.filters, PlacementGroupState) # Sort to make the output deterministic. result.sort(key=lambda entry: entry["placement_group_id"]) return ListApiResponse(result=list(islice(result, option.limit)))
async def list_workers(self, *, option: ListApiOptions) -> ListApiResponse: """List all worker information from the cluster. Returns: {worker_id -> worker_data_in_dict} worker_data_in_dict's schema is in WorkerState """ try: reply = await self._client.get_all_worker_info( timeout=option.timeout) except DataSourceUnavailable: raise DataSourceUnavailable(GCS_QUERY_FAILURE_WARNING) result = [] for message in reply.worker_table_data: data = self._message_to_dict( message=message, fields_to_decode=["worker_id", "raylet_id"]) data["worker_id"] = data["worker_address"]["worker_id"] data["node_id"] = data["worker_address"]["raylet_id"] data["ip"] = data["worker_address"]["ip_address"] result.append(data) result = self._filter(result, option.filters, WorkerState, option.detail) # Sort to make the output deterministic. result.sort(key=lambda entry: entry["worker_id"]) result = list(islice(result, option.limit)) return ListApiResponse( result=result, total=reply.total, )
async def list_nodes(self, *, option: ListApiOptions) -> ListApiResponse: """List all node information from the cluster. Returns: {node_id -> node_data_in_dict} node_data_in_dict's schema is in NodeState """ try: reply = await self._client.get_all_node_info(timeout=option.timeout ) except DataSourceUnavailable: raise DataSourceUnavailable(GCS_QUERY_FAILURE_WARNING) result = [] for message in reply.node_info_list: data = self._message_to_dict(message=message, fields_to_decode=["node_id"]) data["node_ip"] = data["node_manager_address"] result.append(data) result = self._filter(result, option.filters, NodeState, option.detail) # Sort to make the output deterministic. result.sort(key=lambda entry: entry["node_id"]) total_nodes = len(result) result = list(islice(result, option.limit)) return ListApiResponse( result=result, # No reason to truncate node because they are usually small. total=total_nodes, )
def list_jobs(self, *, option: ListApiOptions) -> ListApiResponse: # TODO(sang): Support limit & timeout & async calls. try: result = self._client.get_job_info() except DataSourceUnavailable: raise DataSourceUnavailable(GCS_QUERY_FAILURE_WARNING) return ListApiResponse(result=result)
async def list_nodes(self, *, option: ListApiOptions) -> ListApiResponse: """List all node information from the cluster. Returns: {node_id -> node_data_in_dict} node_data_in_dict's schema is in NodeState """ try: reply = await self._client.get_all_node_info(timeout=option.timeout ) except DataSourceUnavailable: raise DataSourceUnavailable(GCS_QUERY_FAILURE_WARNING) result = [] for message in reply.node_info_list: data = self._message_to_dict(message=message, fields_to_decode=["node_id"]) result.append(data) result = self._filter(result, option.filters, NodeState) # Sort to make the output deterministic. result.sort(key=lambda entry: entry["node_id"]) return ListApiResponse( result={d["node_id"]: d for d in islice(result, option.limit)})
def list_jobs(self, *, option: ListApiOptions) -> ListApiResponse: # TODO(sang): Support limit & timeout & async calls. try: result = [] job_info = self._client.get_job_info() for job_id, data in job_info.items(): data = asdict(data) data["job_id"] = job_id result.append(data) except DataSourceUnavailable: raise DataSourceUnavailable(GCS_QUERY_FAILURE_WARNING) return ListApiResponse(result=result)
async def list_runtime_envs(self, *, option: ListApiOptions) -> ListApiResponse: """List all runtime env information from the cluster. Returns: A list of runtime env information in the cluster. The schema of returned "dict" is equivalent to the `RuntimeEnvState` protobuf message. We don't have id -> data mapping like other API because runtime env doesn't have unique ids. """ agent_ids = self._client.get_all_registered_agent_ids() replies = await asyncio.gather( *[ self._client.get_runtime_envs_info(node_id, timeout=option.timeout) for node_id in agent_ids ], return_exceptions=True, ) result = [] unresponsive_nodes = 0 for node_id, reply in zip(self._client.get_all_registered_agent_ids(), replies): if isinstance(reply, DataSourceUnavailable): unresponsive_nodes += 1 continue elif isinstance(reply, Exception): raise reply states = reply.runtime_env_states for state in states: data = self._message_to_dict(message=state, fields_to_decode=[]) # Need to deseiralize this field. data["runtime_env"] = RuntimeEnv.deserialize( data["runtime_env"] ).to_dict() data["node_id"] = node_id result.append(data) partial_failure_warning = None if len(agent_ids) > 0 and unresponsive_nodes > 0: warning_msg = NODE_QUERY_FAILURE_WARNING.format( type="agent", total=len(agent_ids), network_failures=unresponsive_nodes, log_command="dashboard_agent.log", ) if unresponsive_nodes == len(agent_ids): raise DataSourceUnavailable(warning_msg) partial_failure_warning = ( f"The returned data may contain incomplete result. {warning_msg}" ) result = self._filter(result, option.filters, RuntimeEnvState) # Sort to make the output deterministic. def sort_func(entry): # If creation time is not there yet (runtime env is failed # to be created or not created yet, they are the highest priority. # Otherwise, "bigger" creation time is coming first. if "creation_time_ms" not in entry: return float("inf") elif entry["creation_time_ms"] is None: return float("inf") else: return float(entry["creation_time_ms"]) result.sort(key=sort_func, reverse=True) return ListApiResponse( result=list(islice(result, option.limit)), partial_failure_warning=partial_failure_warning, )
async def list_objects(self, *, option: ListApiOptions) -> ListApiResponse: """List all object information from the cluster. Returns: {object_id -> object_data_in_dict} object_data_in_dict's schema is in ObjectState """ raylet_ids = self._client.get_all_registered_raylet_ids() replies = await asyncio.gather( *[ self._client.get_object_info(node_id, timeout=option.timeout) for node_id in raylet_ids ], return_exceptions=True, ) unresponsive_nodes = 0 worker_stats = [] for reply, _ in zip(replies, raylet_ids): if isinstance(reply, DataSourceUnavailable): unresponsive_nodes += 1 continue elif isinstance(reply, Exception): raise reply for core_worker_stat in reply.core_workers_stats: # NOTE: Set preserving_proto_field_name=False here because # `construct_memory_table` requires a dictionary that has # modified protobuf name # (e.g., workerId instead of worker_id) as a key. worker_stats.append( self._message_to_dict( message=core_worker_stat, fields_to_decode=["object_id"], preserving_proto_field_name=False, ) ) partial_failure_warning = None if len(raylet_ids) > 0 and unresponsive_nodes > 0: warning_msg = NODE_QUERY_FAILURE_WARNING.format( type="raylet", total=len(raylet_ids), network_failures=unresponsive_nodes, log_command="raylet.out", ) if unresponsive_nodes == len(raylet_ids): raise DataSourceUnavailable(warning_msg) partial_failure_warning = ( f"The returned data may contain incomplete result. {warning_msg}" ) result = [] memory_table = memory_utils.construct_memory_table(worker_stats) for entry in memory_table.table: data = entry.as_dict() # `construct_memory_table` returns object_ref field which is indeed # object_id. We do transformation here. # TODO(sang): Refactor `construct_memory_table`. data["object_id"] = data["object_ref"] del data["object_ref"] result.append(data) result = self._filter(result, option.filters, ObjectState) # Sort to make the output deterministic. result.sort(key=lambda entry: entry["object_id"]) return ListApiResponse( result=list(islice(result, option.limit)), partial_failure_warning=partial_failure_warning, )
async def list_tasks(self, *, option: ListApiOptions) -> ListApiResponse: """List all task information from the cluster. Returns: {task_id -> task_data_in_dict} task_data_in_dict's schema is in TaskState """ raylet_ids = self._client.get_all_registered_raylet_ids() replies = await asyncio.gather( *[ self._client.get_task_info(node_id, timeout=option.timeout) for node_id in raylet_ids ], return_exceptions=True, ) unresponsive_nodes = 0 running_task_id = set() successful_replies = [] for reply in replies: if isinstance(reply, DataSourceUnavailable): unresponsive_nodes += 1 continue elif isinstance(reply, Exception): raise reply successful_replies.append(reply) for task_id in reply.running_task_ids: running_task_id.add(binary_to_hex(task_id)) partial_failure_warning = None if len(raylet_ids) > 0 and unresponsive_nodes > 0: warning_msg = NODE_QUERY_FAILURE_WARNING.format( type="raylet", total=len(raylet_ids), network_failures=unresponsive_nodes, log_command="raylet.out", ) if unresponsive_nodes == len(raylet_ids): raise DataSourceUnavailable(warning_msg) partial_failure_warning = ( f"The returned data may contain incomplete result. {warning_msg}" ) result = [] for reply in successful_replies: assert not isinstance(reply, Exception) tasks = reply.owned_task_info_entries for task in tasks: data = self._message_to_dict( message=task, fields_to_decode=["task_id"], ) if data["task_id"] in running_task_id: data["scheduling_state"] = TaskStatus.DESCRIPTOR.values_by_number[ TaskStatus.RUNNING ].name result.append(data) result = self._filter(result, option.filters, TaskState) # Sort to make the output deterministic. result.sort(key=lambda entry: entry["task_id"]) return ListApiResponse( result=list(islice(result, option.limit)), partial_failure_warning=partial_failure_warning, )