Source code for tests.system.providers.google.cloud.dataproc.example_dataproc_hive

#
# 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.
"""
Example Airflow DAG for DataprocSubmitJobOperator with hive job.
"""
from __future__ import annotations

import os
from datetime import datetime

from airflow import models
from airflow.providers.google.cloud.operators.dataproc import (
    DataprocCreateClusterOperator,
    DataprocDeleteClusterOperator,
    DataprocSubmitJobOperator,
)
from airflow.utils.trigger_rule import TriggerRule

[docs]ENV_ID = os.environ.get("SYSTEM_TESTS_ENV_ID")
[docs]DAG_ID = "dataproc_hive"
[docs]PROJECT_ID = os.environ.get("SYSTEM_TESTS_GCP_PROJECT", "")

[docs]CLUSTER_NAME = f"cluster-dataproc-hive-{ENV_ID}"
[docs]REGION = "europe-west1"
[docs]ZONE = "europe-west1-b"


# Cluster definition
# [START how_to_cloud_dataproc_create_cluster]

[docs]CLUSTER_CONFIG = {
    "master_config": {
        "num_instances": 1,
        "machine_type_uri": "n1-standard-4",
        "disk_config": {"boot_disk_type": "pd-standard", "boot_disk_size_gb": 1024},
    },
    "worker_config": {
        "num_instances": 2,
        "machine_type_uri": "n1-standard-4",
        "disk_config": {"boot_disk_type": "pd-standard", "boot_disk_size_gb": 1024},
    },
}

# [END how_to_cloud_dataproc_create_cluster]

[docs]TIMEOUT = {"seconds": 1 * 24 * 60 * 60}

# [START how_to_cloud_dataproc_hive_config]
[docs]HIVE_JOB = {
    "reference": {"project_id": PROJECT_ID},
    "placement": {"cluster_name": CLUSTER_NAME},
    "hive_job": {"query_list": {"queries": ["SHOW DATABASES;"]}},
}
# [END how_to_cloud_dataproc_hive_config]


with models.DAG(
    DAG_ID,
    schedule='@once',
    start_date=datetime(2021, 1, 1),
    catchup=False,
    tags=["example", "dataproc"],
) as dag:
    # [START how_to_cloud_dataproc_create_cluster_operator]
[docs]    create_cluster = DataprocCreateClusterOperator(
        task_id="create_cluster",
        project_id=PROJECT_ID,
        cluster_config=CLUSTER_CONFIG,
        region=REGION,
        cluster_name=CLUSTER_NAME,
    )
    # [END how_to_cloud_dataproc_create_cluster_operator]

    hive_task = DataprocSubmitJobOperator(
        task_id="hive_task", job=HIVE_JOB, region=REGION, project_id=PROJECT_ID
    )

    # [START how_to_cloud_dataproc_delete_cluster_operator]
    delete_cluster = DataprocDeleteClusterOperator(
        task_id="delete_cluster",
        project_id=PROJECT_ID,
        cluster_name=CLUSTER_NAME,
        region=REGION,
    )
    # [END how_to_cloud_dataproc_delete_cluster_operator]
    delete_cluster.trigger_rule = TriggerRule.ALL_DONE

    create_cluster >> hive_task >> delete_cluster

    from tests.system.utils.watcher import watcher

    # This test needs watcher in order to properly mark success/failure
    # when "teardown" task with trigger rule is part of the DAG
    list(dag.tasks) >> watcher()


from tests.system.utils import get_test_run  # noqa: E402

# Needed to run the example DAG with pytest (see: tests/system/README.md#run_via_pytest)
[docs]test_run = get_test_run(dag)