code: def test_default_config_cluster(ray_start_cluster_enabled):
      cluster = ray_start_cluster_enabled
      cluster.add_node(num_cpus=0)
      ray.init(cluster.address)
      worker_nodes = []
      worker_nodes.append(
          cluster.add_node(
              num_cpus=1, object_store_memory=75 * 1024 * 1024
          )
      )
      cluster.wait_for_nodes()
  
      # Run the basic spilling workload on both
      # worker nodes and make sure they are working.
      @ray.remote
      def task():
          arr = np.random.rand(5 * 1024 * 1024)  # 40 MB
          refs = []
          refs.append([ray.put(arr) for _ in range(2)])
          ray.get(ray.put(arr))
  
      ray.get([task.remote() for _ in range(2)])
  
imports: import copy
  import json
  import platform
  import random
  import sys
  from datetime import datetime, timedelta
  from unittest.mock import patch
  import numpy
  import pytest
  import ray
  from ray._private.external_storage import create_url_with_offset, parse_url_with_offset, _get_unique_spill_filename, FileSystemStorage, ExternalStorageSmartOpenImpl
  from ray._private.internal_api import memory_summary
  from ray._private.test_utils import wait_for_condition
  from ray._raylet import GcsClientOptions
  from ray.tests.conftest import buffer_object_spilling_config, file_system_object_spilling_config, mock_distributed_fs_object_spilling_config
label_desc: Use image node_id 9 for calling a global function with example usage: test_default_config_cluster(ray_start_cluster_enabled) without return types