Source code for tests.system.providers.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 airflow import models
from airflow.decorators import task
from airflow.providers.google.cloud.operators.dataproc import (
    DataprocCreateClusterOperator,
    DataprocDeleteClusterOperator,
    DataprocSubmitJobOperator,
)
from airflow.providers.google.cloud.operators.gcs import (
    GCSCreateBucketOperator,
    GCSDeleteBucketOperator,
)
from airflow.providers.google.cloud.transfers.local_to_gcs import LocalFilesystemToGCSOperator
from airflow.utils.trigger_rule import TriggerRule


[docs]ENV_ID = os.environ.get("SYSTEM_TESTS_ENV_ID")


[docs]DAG_ID = "dataproc_sparkr"


[docs]PROJECT_ID = os.environ.get("SYSTEM_TESTS_GCP_PROJECT")



[docs]BUCKET_NAME = f"bucket_{DAG_ID}_{ENV_ID}"


[docs]CLUSTER_NAME = f"cluster-{ENV_ID}-{DAG_ID}".replace("_", "-")


[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": 1024},
    },
    "worker_config": {
        "num_instances": 2,
        "machine_type_uri": "n1-standard-4",
        "disk_config": {"boot_disk_type": "pd-standard", "boot_disk_size_gb": 1024},
    },
}



[docs]JOB_FILE_NAME = "dataproc-sparkr-job.r"


[docs]JOB_FILE_LOCAL_PATH = f"/tmp/{JOB_FILE_NAME}"


[docs]JOB_FILE_CONTENT = """library(SparkR)
sparkR.session()
df <- as.DataFrame(faithful)
head(df)
"""


# 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": f"gs://{BUCKET_NAME}/{JOB_FILE_NAME}"},
}

# [END how_to_cloud_dataproc_sparkr_config]


with models.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
    )


    @task
    def create_job_file():
        with open(JOB_FILE_LOCAL_PATH, "w") as job_file:
            job_file.write(JOB_FILE_CONTENT)

    create_job_file_task = create_job_file()

    upload_file = LocalFilesystemToGCSOperator(
        task_id="upload_file",
        src=JOB_FILE_LOCAL_PATH,
        dst=JOB_FILE_NAME,
        bucket=BUCKET_NAME,
    )

    create_cluster = DataprocCreateClusterOperator(
        task_id="create_cluster",
        project_id=PROJECT_ID,
        cluster_config=CLUSTER_CONFIG,
        region=REGION,
        cluster_name=CLUSTER_NAME,
    )

    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
    )

    @task(trigger_rule=TriggerRule.ALL_DONE)
    def delete_job_file():
        try:
            os.remove(JOB_FILE_LOCAL_PATH)
        except FileNotFoundError:
            pass

    delete_job_file_task = delete_job_file()

    # TEST SETUP
    [create_bucket, create_job_file_task] >> upload_file
    # TEST BODY
    [upload_file, create_cluster] >> sparkr_task
    # TEST TEARDOWN
    sparkr_task >> [delete_cluster, delete_bucket, delete_job_file_task]

    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)

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