text: # Licensed to Modin Development Team under one or more contributor license agreements.
  # See the NOTICE file distributed with this work for additional information regarding
  # copyright ownership.  The Modin Development Team licenses this file to you under the
  # Apache License, Version 2.0 (the "License"); you may not use this file except in
  # compliance with the License.  You may obtain a copy of the License at
  #
  #     http://www.apache.org/licenses/LICENSE-2.0
  #
  # Unless required by applicable law or agreed to in writing, software distributed under
  # the License is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF
  # ANY KIND, either express or implied. See the License for the specific language
  # governing permissions and limitations under the License.
  
  
  # pip install git+https://github.com/intel-ai/ibis.git@develop
  # pip install braceexpand
  
  # NOTE: expects https://github.com/intel-ai/omniscripts checked out and in PYTHONPATH
  
  # the following import turns on experimental mode in Modin,
  # including enabling running things in remote cloud
  import modin.experimental.pandas as pd  # noqa: F401
  from modin.experimental.cloud import create_cluster
  
  from h2o import run_benchmark
  
  test_cluster = create_cluster(
      "aws",
      "aws_credentials",
      cluster_name="rayscale-test",
      region="eu-central-1",
      zone="eu-central-1b",
      image="ami-05f7491af5eef733a",
  )
  with test_cluster:
      parameters = {
          "no_pandas": False,
          "pandas_mode": "Modin_on_ray",
          "ray_tmpdir": "/tmp",
          "ray_memory": 1024 * 1024 * 1024,
          "extended_functionality": False,
      }
  
      # G1... - for groupby queries; J1... - for join queries;
      # Additional required files inside h2o-data folder:
      # - J1_1e6_1e0_0_0.csv
      # - J1_1e6_1e3_0_0.csv
      # - J1_1e6_1e6_0_0.csv
      for data_file in ["G1_5e5_1e2_0_0.csv", "J1_1e6_NA_0_0.csv"]:
          parameters["data_file"] = f"s3://modin-datasets/cloud/h2o/{data_file}"
          run_benchmark(parameters)
  