text: #
  # Licensed to the Apache Software Foundation (ASF) under one
  # or more contributor license agreements.  See the NOTICE file
  # distributed with this work for additional information
  # regarding copyright ownership.  The ASF 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.
  import pytest
  
  from airflow.providers.google.cloud.example_dags.example_dataproc import BUCKET, PYSPARK_MAIN, SPARKR_MAIN
  from tests.providers.google.cloud.utils.gcp_authenticator import GCP_DATAPROC_KEY
  from tests.test_utils.gcp_system_helpers import CLOUD_DAG_FOLDER, GoogleSystemTest, provide_gcp_context
  
  GCS_URI = f"gs://{BUCKET}"
  
  pyspark_file = """
  #!/usr/bin/python
  import pyspark
  sc = pyspark.SparkContext()
  rdd = sc.parallelize(['Hello,', 'world!'])
  words = sorted(rdd.collect())
  print(words)
  """
  
  sparkr_file = """
  #!/usr/bin/r
  if (nchar(Sys.getenv("SPARK_HOME")) < 1) {
  Sys.setenv(SPARK_HOME = "/home/spark")
  }
  library(SparkR, lib.loc = c(file.path(Sys.getenv("SPARK_HOME"), "R", "lib")))
  sparkR.session()
  # Create the SparkDataFrame
  df <- as.DataFrame(faithful)
  head(summarize(groupBy(df, df$waiting), count = n(df$waiting)))
  """
  
  
  @pytest.mark.backend("mysql", "postgres")
  @pytest.mark.credential_file(GCP_DATAPROC_KEY)
  class DataprocExampleDagsTest(GoogleSystemTest):
      @provide_gcp_context(GCP_DATAPROC_KEY)
      def setUp(self):
          super().setUp()
          self.create_gcs_bucket(BUCKET)
          self.upload_content_to_gcs(lines=pyspark_file, bucket=GCS_URI, filename=PYSPARK_MAIN)
          self.upload_content_to_gcs(lines=sparkr_file, bucket=GCS_URI, filename=SPARKR_MAIN)
  
      @provide_gcp_context(GCP_DATAPROC_KEY)
      def tearDown(self):
          self.delete_gcs_bucket(BUCKET)
          super().tearDown()
  
      @provide_gcp_context(GCP_DATAPROC_KEY)
      def test_run_example_dag(self):
          self.run_dag(dag_id="example_gcp_dataproc", dag_folder=CLOUD_DAG_FOLDER)
  