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from __future__ import annotations
import os
from datetime import datetime
import yandex.cloud.dataproc.v1.cluster_pb2 as cluster_pb
import yandex.cloud.dataproc.v1.cluster_service_pb2 as cluster_service_pb
import yandex.cloud.dataproc.v1.cluster_service_pb2_grpc as cluster_service_grpc_pb
import yandex.cloud.dataproc.v1.common_pb2 as common_pb
import yandex.cloud.dataproc.v1.job_pb2 as job_pb
import yandex.cloud.dataproc.v1.job_service_pb2 as job_service_pb
import yandex.cloud.dataproc.v1.job_service_pb2_grpc as job_service_grpc_pb
import yandex.cloud.dataproc.v1.subcluster_pb2 as subcluster_pb
from google.protobuf.json_format import MessageToDict
from airflow import DAG
from airflow.decorators import task
from airflow.providers.yandex.hooks.yandex import YandexCloudBaseHook
[docs]ENV_ID = os.environ.get("SYSTEM_TESTS_ENV_ID")
[docs]DAG_ID = "example_yandexcloud_hook"
# Fill it with your identifiers
[docs]YC_S3_BUCKET_NAME = "" # Fill to use S3 instead of HFDS
[docs]YC_FOLDER_ID = None # Fill to override default YC folder from connection data
[docs]YC_ZONE_NAME = "ru-central1-b"
[docs]YC_SUBNET_ID = None # Fill if you have more than one VPC subnet in given folder and zone
[docs]YC_SERVICE_ACCOUNT_ID = None # Fill if you have more than one YC service account in given folder
[docs]def create_cluster_request(
folder_id: str,
cluster_name: str,
cluster_desc: str,
zone: str,
subnet_id: str,
service_account_id: str,
ssh_public_key: str,
resources: common_pb.Resources,
):
return cluster_service_pb.CreateClusterRequest(
folder_id=folder_id,
name=cluster_name,
description=cluster_desc,
bucket=YC_S3_BUCKET_NAME,
config_spec=cluster_service_pb.CreateClusterConfigSpec(
hadoop=cluster_pb.HadoopConfig(
services=("SPARK", "YARN"),
ssh_public_keys=[ssh_public_key],
),
subclusters_spec=[
cluster_service_pb.CreateSubclusterConfigSpec(
name="master",
role=subcluster_pb.Role.MASTERNODE,
resources=resources,
subnet_id=subnet_id,
hosts_count=1,
),
cluster_service_pb.CreateSubclusterConfigSpec(
name="compute",
role=subcluster_pb.Role.COMPUTENODE,
resources=resources,
subnet_id=subnet_id,
hosts_count=1,
),
],
),
zone_id=zone,
service_account_id=service_account_id,
)
@task
[docs]def create_cluster(
yandex_conn_id: str | None = None,
folder_id: str | None = None,
network_id: str | None = None,
subnet_id: str | None = None,
zone: str = YC_ZONE_NAME,
service_account_id: str | None = None,
ssh_public_key: str | None = None,
*,
dag: DAG | None = None,
ts_nodash: str | None = None,
) -> str:
hook = YandexCloudBaseHook(yandex_conn_id=yandex_conn_id)
folder_id = folder_id or hook.default_folder_id
if subnet_id is None:
network_id = network_id or hook.sdk.helpers.find_network_id(folder_id)
subnet_id = hook.sdk.helpers.find_subnet_id(folder_id=folder_id, zone_id=zone, network_id=network_id)
service_account_id = service_account_id or hook.sdk.helpers.find_service_account_id()
ssh_public_key = ssh_public_key or hook.default_public_ssh_key
dag_id = dag and dag.dag_id or "dag"
request = create_cluster_request(
folder_id=folder_id,
subnet_id=subnet_id,
zone=zone,
cluster_name=f"airflow_{dag_id}_{ts_nodash}"[:62],
cluster_desc="Created via Airflow custom hook task",
service_account_id=service_account_id,
ssh_public_key=ssh_public_key,
resources=common_pb.Resources(
resource_preset_id="s2.micro",
disk_type_id="network-ssd",
),
)
operation = hook.sdk.client(cluster_service_grpc_pb.ClusterServiceStub).Create(request)
operation_result = hook.sdk.wait_operation_and_get_result(
operation, response_type=cluster_pb.Cluster, meta_type=cluster_service_pb.CreateClusterMetadata
)
return operation_result.response.id
@task
[docs]def run_spark_job(
cluster_id: str,
yandex_conn_id: str | None = None,
):
hook = YandexCloudBaseHook(yandex_conn_id=yandex_conn_id)
request = job_service_pb.CreateJobRequest(
cluster_id=cluster_id,
name="Spark job: Find total urban population in distribution by country",
spark_job=job_pb.SparkJob(
main_jar_file_uri="file:///usr/lib/spark/examples/jars/spark-examples.jar",
main_class="org.apache.spark.examples.SparkPi",
args=["1000"],
),
)
operation = hook.sdk.client(job_service_grpc_pb.JobServiceStub).Create(request)
operation_result = hook.sdk.wait_operation_and_get_result(
operation, response_type=job_pb.Job, meta_type=job_service_pb.CreateJobMetadata
)
return MessageToDict(operation_result.response)
@task(trigger_rule="all_done")
[docs]def delete_cluster(
cluster_id: str,
yandex_conn_id: str | None = None,
):
hook = YandexCloudBaseHook(yandex_conn_id=yandex_conn_id)
operation = hook.sdk.client(cluster_service_grpc_pb.ClusterServiceStub).Delete(
cluster_service_pb.DeleteClusterRequest(cluster_id=cluster_id)
)
hook.sdk.wait_operation_and_get_result(
operation,
meta_type=cluster_service_pb.DeleteClusterMetadata,
)
with DAG(
dag_id=DAG_ID,
schedule=None,
start_date=datetime(2021, 1, 1),
tags=["example"],
) as dag:
[docs] cluster_id = create_cluster(
folder_id=YC_FOLDER_ID,
subnet_id=YC_SUBNET_ID,
zone=YC_ZONE_NAME,
service_account_id=YC_SERVICE_ACCOUNT_ID,
)
spark_job = run_spark_job(cluster_id=cluster_id)
delete_task = delete_cluster(cluster_id=cluster_id)
spark_job >> delete_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)