class_docstr: A streaming Dataset executor.
  
  This implementation executes Dataset DAGs in a fully streamed way. It runs
  by setting up the operator topology, and then routing blocks through operators in
  a way that maximizes throughput under resource constraints.
class_docstr_tok: ["A","streaming","Dataset","executor",".","This","implementation","executes","Dataset","DAGs","in","a","fully","streamed","way",".","It","runs","by","setting","up","the","operator","topology",",","and","then","routing","blocks","through","operators","in","a","way","that","maximizes","throughput","under","resource","constraints","."]
code: def _report_current_usage(
      self, cur_usage: TopologyResourceUsage, limits: ExecutionResources
  ) -> None:
      resources_status = (
          "Running: "
          f"{cur_usage.overall.cpu}/{limits.cpu} CPU, "
          f"{cur_usage.overall.gpu}/{limits.gpu} GPU, "
          f"{cur_usage.overall.object_store_memory_str()}/"
          f"{limits.object_store_memory_str()} object_store_memory"
      )
      if self._global_info:
          self._global_info.set_description(resources_status)
  
imports: import os
  import threading
  import time
  import uuid
  from typing import Dict, Iterator, List, Optional
  from ray.data._internal.dataset_logger import DatasetLogger
  from ray.data._internal.execution.autoscaling_requester import get_or_create_autoscaling_requester_actor
  from ray.data._internal.execution.backpressure_policy import BackpressurePolicy, get_backpressure_policies
  from ray.data._internal.execution.interfaces import ExecutionOptions, ExecutionResources, Executor, OutputIterator, PhysicalOperator, RefBundle
  from ray.data._internal.execution.operators.input_data_buffer import InputDataBuffer
  from ray.data._internal.execution.streaming_executor_state import DEFAULT_OBJECT_STORE_MEMORY_LIMIT_FRACTION, AutoscalingState, OpState, Topology, TopologyResourceUsage, build_streaming_topology, process_completed_tasks, select_operator_to_run, update_operator_states
  from ray.data._internal.progress_bar import ProgressBar
  from ray.data._internal.stats import DatasetStats, StatsManager
  from ray.data._internal.util import cluster_resources
  from ray.data.context import DataContext
label_desc: Use image node_id 11 for calling the StreamingExecutor obj's underlying member method code with example usage: obj._report_current_usage(cur_usage, limits) without return types