Source code for tests.system.google.cloud.dataproc.example_dataproc_sparkr

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"""
Example Airflow DAG for DataprocSubmitJobOperator with sparkr job.
"""

from __future__ import annotations

import os
from datetime import datetime

from google.api_core.retry import Retry

from airflow.models.dag import DAG
from airflow.providers.google.cloud.operators.dataproc import (
    DataprocCreateClusterOperator,
    DataprocDeleteClusterOperator,
    DataprocSubmitJobOperator,
)
from airflow.providers.google.cloud.operators.gcs import (
    GCSCreateBucketOperator,
    GCSDeleteBucketOperator,
    GCSSynchronizeBucketsOperator,
)
from airflow.utils.trigger_rule import TriggerRule

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_sparkr"
[docs]PROJECT_ID = os.environ.get("SYSTEM_TESTS_GCP_PROJECT") or DEFAULT_GCP_SYSTEM_TEST_PROJECT_ID
[docs]BUCKET_NAME = f"bucket_{DAG_ID}_{ENV_ID}"
[docs]RESOURCE_DATA_BUCKET = "airflow-system-tests-resources"
[docs]JOB_FILE = "dataproc-sparkr-job.r"
[docs]GCS_JOB_FILE = f"gs://{BUCKET_NAME}/dataproc/{JOB_FILE}"
[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]REGION = "europe-west1"
# Cluster definition
[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}, }, "software_config": { "image_version": "2.0.116-debian10", }, }
# Jobs definitions # [START how_to_cloud_dataproc_sparkr_config]
[docs]SPARKR_JOB = { "reference": {"project_id": PROJECT_ID}, "placement": {"cluster_name": CLUSTER_NAME}, "spark_r_job": {"main_r_file_uri": GCS_JOB_FILE}, }
# [END how_to_cloud_dataproc_sparkr_config] with DAG( DAG_ID, schedule="@once", start_date=datetime(2021, 1, 1), catchup=False, tags=["example", "dataproc", "sparkr"], ) as dag:
[docs] create_bucket = GCSCreateBucketOperator( task_id="create_bucket", bucket_name=BUCKET_NAME, project_id=PROJECT_ID )
move_job_file = GCSSynchronizeBucketsOperator( task_id="move_job_file", source_bucket=RESOURCE_DATA_BUCKET, source_object="dataproc/sparkr", destination_bucket=BUCKET_NAME, destination_object="dataproc", recursive=True, ) create_cluster = DataprocCreateClusterOperator( task_id="create_cluster", project_id=PROJECT_ID, cluster_config=CLUSTER_CONFIG, region=REGION, cluster_name=CLUSTER_NAME, retry=Retry(maximum=100.0, initial=10.0, multiplier=1.0), num_retries_if_resource_is_not_ready=3, ) sparkr_task = DataprocSubmitJobOperator( task_id="sparkr_task", job=SPARKR_JOB, region=REGION, project_id=PROJECT_ID ) delete_cluster = DataprocDeleteClusterOperator( task_id="delete_cluster", project_id=PROJECT_ID, cluster_name=CLUSTER_NAME, region=REGION, trigger_rule=TriggerRule.ALL_DONE, ) delete_bucket = GCSDeleteBucketOperator( task_id="delete_bucket", bucket_name=BUCKET_NAME, trigger_rule=TriggerRule.ALL_DONE ) ( # TEST SETUP create_bucket >> move_job_file >> create_cluster # TEST BODY >> sparkr_task # TEST TEARDOWN >> delete_cluster >> delete_bucket ) 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)

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