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Example Airflow DAG that show how to create a Dataproc cluster in Google Kubernetes Engine.
from __future__ import annotations

import os
from datetime import datetime

from airflow import models
from import (
from import (
from airflow.utils.trigger_rule import TriggerRule

[docs]ENV_ID = os.environ.get("SYSTEM_TESTS_ENV_ID")
[docs]DAG_ID = "dataproc-gke"
[docs]PROJECT_ID = os.environ.get("SYSTEM_TESTS_GCP_PROJECT", "default")
[docs]REGION = "us-central1"
[docs]CLUSTER_NAME = f"cluster-test-build-in-gke{ENV_ID}"
[docs]GKE_CLUSTER_NAME = f"test-dataproc-gke-cluster-{ENV_ID}"
[docs]GKE_CLUSTER_CONFIG = { "name": GKE_CLUSTER_NAME, "workload_identity_config": { "workload_pool": f"{PROJECT_ID}", }, "initial_node_count": 1,
} # [START how_to_cloud_dataproc_create_cluster_in_gke_config]
[docs]VIRTUAL_CLUSTER_CONFIG = { "kubernetes_cluster_config": { "gke_cluster_config": { "gke_cluster_target": f"projects/{PROJECT_ID}/locations/{REGION}/clusters/{GKE_CLUSTER_NAME}", "node_pool_target": [ { "node_pool": f"projects/{PROJECT_ID}/locations/{REGION}/clusters/{GKE_CLUSTER_NAME}/nodePools/dp", # noqa "roles": ["DEFAULT"], } ], }, "kubernetes_software_config": {"component_version": {"SPARK": b"3"}}, }, "staging_bucket": "test-staging-bucket",
} # [END how_to_cloud_dataproc_create_cluster_in_gke_config] with models.DAG( DAG_ID, schedule="@once", start_date=datetime(2021, 1, 1), catchup=False, tags=["example"], ) as dag:
[docs] create_gke_cluster = GKECreateClusterOperator( task_id="create_gke_cluster", project_id=PROJECT_ID, location=REGION, body=GKE_CLUSTER_CONFIG,
) # [START how_to_cloud_dataproc_create_cluster_operator_in_gke] create_cluster_in_gke = DataprocCreateClusterOperator( task_id="create_cluster_in_gke", project_id=PROJECT_ID, region=REGION, cluster_name=CLUSTER_NAME, virtual_cluster_config=VIRTUAL_CLUSTER_CONFIG, ) # [END how_to_cloud_dataproc_create_cluster_operator_in_gke] delete_dataproc_cluster = DataprocDeleteClusterOperator( task_id="delete_dataproc_cluster", project_id=PROJECT_ID, cluster_name=CLUSTER_NAME, region=REGION, trigger_rule=TriggerRule.ALL_DONE, ) delete_gke_cluster = GKEDeleteClusterOperator( task_id="delete_gke_cluster", name=GKE_CLUSTER_NAME, project_id=PROJECT_ID, location=REGION, trigger_rule=TriggerRule.ALL_DONE, ) create_gke_cluster >> create_cluster_in_gke >> [delete_dataproc_cluster, delete_gke_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/
[docs]test_run = get_test_run(dag)

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