code: def read_1gb_cloud():
      """
      Test h2o cluster read file.  Should run faster than what is observed under
      https://github.com/h2oai/h2o-3/issues/15163
      Right now this test is not run through Jenkins. Need to setup a cloud
      testing infrastructure which is a longer term project.
      You can take a look at markc_multimachine on jenkins for the current setup
      which is based on ec2
      """
  
      # file must be seen by all nodes
      df = h2o.import_file(
          "http://s3.amazonaws.com/h2o-datasets/allstate/train_set.zip"
      )
      response = "Cat1"
      predictors = ["Cat2", "Cat3", "Cat4", "Cat5"]
      df["Cat1"] = df["Cat1"].asfactor()
      df["Cat1"].summary()
      rnd = df["Cat1"].runif(seed=1234)
      train = df[rnd <= 0.8]
      test = df[rnd > 0.8]
  
label_desc: Use image node_id 1 for calling a global function with example usage: read_1gb_cloud() without return types