Source code for tests.system.google.cloud.dataproc.example_dataproc_workflow
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"""
Example Airflow DAG for Dataproc workflow operators.
"""
from __future__ import annotations
import os
from datetime import datetime
from airflow.models.dag import DAG
from airflow.providers.google.cloud.operators.dataproc import (
DataprocCreateWorkflowTemplateOperator,
DataprocInstantiateInlineWorkflowTemplateOperator,
DataprocInstantiateWorkflowTemplateOperator,
)
from providers.tests.system.google import DEFAULT_GCP_SYSTEM_TEST_PROJECT_ID
[docs]ENV_ID = os.environ.get("SYSTEM_TESTS_ENV_ID", "default")
[docs]DAG_ID = "dataproc_workflow"
[docs]PROJECT_ID = os.environ.get("SYSTEM_TESTS_GCP_PROJECT") or DEFAULT_GCP_SYSTEM_TEST_PROJECT_ID
[docs]CLUSTER_NAME_BASE = f"cluster-{DAG_ID}".replace("_", "-")
[docs]CLUSTER_NAME_FULL = CLUSTER_NAME_BASE + f"-{ENV_ID}".replace("_", "-")
[docs]CLUSTER_NAME = CLUSTER_NAME_BASE if len(CLUSTER_NAME_FULL) >= 33 else CLUSTER_NAME_FULL
[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": 32},
},
"worker_config": {
"num_instances": 2,
"machine_type_uri": "n1-standard-4",
"disk_config": {"boot_disk_type": "pd-standard", "boot_disk_size_gb": 32},
},
}
[docs]PIG_JOB = {"query_list": {"queries": ["define sin HiveUDF('sin');"]}}
[docs]WORKFLOW_NAME = "airflow-dataproc-test"
[docs]WORKFLOW_TEMPLATE = {
"id": WORKFLOW_NAME,
"placement": {
"managed_cluster": {
"cluster_name": CLUSTER_NAME,
"config": CLUSTER_CONFIG,
}
},
"jobs": [{"step_id": "pig_job_1", "pig_job": PIG_JOB}],
}
with DAG(
DAG_ID,
schedule="@once",
start_date=datetime(2021, 1, 1),
catchup=False,
tags=["example", "dataproc", "workflow"],
) as dag:
# [START how_to_cloud_dataproc_create_workflow_template]
[docs] create_workflow_template = DataprocCreateWorkflowTemplateOperator(
task_id="create_workflow_template",
template=WORKFLOW_TEMPLATE,
project_id=PROJECT_ID,
region=REGION,
)
# [END how_to_cloud_dataproc_create_workflow_template]
# [START how_to_cloud_dataproc_trigger_workflow_template]
trigger_workflow = DataprocInstantiateWorkflowTemplateOperator(
task_id="trigger_workflow", region=REGION, project_id=PROJECT_ID, template_id=WORKFLOW_NAME
)
# [END how_to_cloud_dataproc_trigger_workflow_template]
# [START how_to_cloud_dataproc_instantiate_inline_workflow_template]
instantiate_inline_workflow_template = DataprocInstantiateInlineWorkflowTemplateOperator(
task_id="instantiate_inline_workflow_template", template=WORKFLOW_TEMPLATE, region=REGION
)
# [END how_to_cloud_dataproc_instantiate_inline_workflow_template]
(
# TEST SETUP
create_workflow_template
# TEST BODY
>> trigger_workflow
# TEST TEARDOWN
>> instantiate_inline_workflow_template
)
from tests_common.test_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_common.test_utils.system_tests 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)