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YandexCloud provider: Support new Yandex SDK features for DataProc (#…
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Piatachock authored Jul 29, 2022
1 parent 9febd7f commit a61e0c1
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4 changes: 2 additions & 2 deletions airflow/providers/yandex/hooks/yandex.py
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Expand Up @@ -17,7 +17,7 @@

import json
import warnings
from typing import Any, Dict, Optional, Union
from typing import Any, Dict, Optional

import yandexcloud

Expand Down Expand Up @@ -107,7 +107,7 @@ def __init__(
# Connection id is deprecated. Use yandex_conn_id instead
connection_id: Optional[str] = None,
yandex_conn_id: Optional[str] = None,
default_folder_id: Union[dict, bool, None] = None,
default_folder_id: Optional[str] = None,
default_public_ssh_key: Optional[str] = None,
) -> None:
super().__init__()
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190 changes: 109 additions & 81 deletions airflow/providers/yandex/operators/yandexcloud_dataproc.py

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2 changes: 1 addition & 1 deletion airflow/providers/yandex/provider.yaml
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Expand Up @@ -34,7 +34,7 @@ versions:

dependencies:
- apache-airflow>=2.2.0
- yandexcloud>=0.146.0
- yandexcloud>=0.173.0

integrations:
- integration-name: Yandex.Cloud
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2 changes: 2 additions & 0 deletions generated/README.md
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Expand Up @@ -20,6 +20,8 @@
NOTE! The files in this folder are generated by pre-commit based on airflow sources. They are not
supposed to be manually modified.

You can read more about pre-commit hooks [here](../STATIC_CODE_CHECKS.rst#pre-commit-hooks).

* `provider_dependencies.json` - is generated based on `provider.yaml` files in `airflow/providers` and
based on the imports in the provider code. If you want to add new dependency to a provider, you
need to modify the corresponding `provider.yaml` file
2 changes: 1 addition & 1 deletion generated/provider_dependencies.json
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Expand Up @@ -721,7 +721,7 @@
"yandex": {
"deps": [
"apache-airflow>=2.2.0",
"yandexcloud>=0.146.0"
"yandexcloud>=0.173.0"
],
"cross-providers-deps": []
},
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18 changes: 15 additions & 3 deletions tests/providers/yandex/hooks/test_yandex.py
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Expand Up @@ -43,7 +43,11 @@ def test_client_created_without_exceptions(self, get_credentials_mock, get_conne
)
get_credentials_mock.return_value = {"token": 122323}

hook = YandexCloudBaseHook(None, default_folder_id, default_public_ssh_key)
hook = YandexCloudBaseHook(
yandex_conn_id=None,
default_folder_id=default_folder_id,
default_public_ssh_key=default_public_ssh_key,
)
assert hook.client is not None

@mock.patch('airflow.hooks.base.BaseHook.get_connection')
Expand All @@ -63,7 +67,11 @@ def test_get_credentials_raise_exception(self, get_connection_mock):
)

with pytest.raises(AirflowException):
YandexCloudBaseHook(None, default_folder_id, default_public_ssh_key)
YandexCloudBaseHook(
yandex_conn_id=None,
default_folder_id=default_folder_id,
default_public_ssh_key=default_public_ssh_key,
)

@mock.patch('airflow.hooks.base.BaseHook.get_connection')
@mock.patch('airflow.providers.yandex.hooks.yandex.YandexCloudBaseHook._get_credentials')
Expand All @@ -80,6 +88,10 @@ def test_get_field(self, get_credentials_mock, get_connection_mock):
)
get_credentials_mock.return_value = {"token": 122323}

hook = YandexCloudBaseHook(None, default_folder_id, default_public_ssh_key)
hook = YandexCloudBaseHook(
yandex_conn_id=None,
default_folder_id=default_folder_id,
default_public_ssh_key=default_public_ssh_key,
)

assert hook._get_field('one') == 'value_one'
5 changes: 5 additions & 0 deletions tests/providers/yandex/operators/test_yandexcloud_dataproc.py
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Expand Up @@ -127,6 +127,11 @@ def test_create_cluster(self, create_cluster_mock, *_):
subnet_id='my_subnet_id',
zone='ru-central1-c',
log_group_id=LOG_GROUP_ID,
properties=None,
enable_ui_proxy=False,
host_group_ids=None,
security_group_ids=None,
initialization_actions=None,
)
context['task_instance'].xcom_push.assert_has_calls(
[
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197 changes: 197 additions & 0 deletions tests/system/providers/yandex/example_yandexcloud.py
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@@ -0,0 +1,197 @@
# Licensed to the Apache Software Foundation (ASF) under one
# or more contributor license agreements. See the NOTICE file
# distributed with this work for additional information
# regarding copyright ownership. The ASF licenses this file
# to you under the Apache License, Version 2.0 (the
# "License"); you may not use this file except in compliance
# with the License. You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing,
# software distributed under the License is distributed on an
# "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
# KIND, either express or implied. See the License for the
# specific language governing permissions and limitations
# under the License.
import os
from datetime import datetime
from typing import Optional

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

ENV_ID = os.environ.get("SYSTEM_TESTS_ENV_ID")
DAG_ID = 'example_yandexcloud_hook'

# Fill it with your identifiers
YC_S3_BUCKET_NAME = '' # Fill to use S3 instead of HFDS
YC_FOLDER_ID = None # Fill to override default YC folder from connection data
YC_ZONE_NAME = 'ru-central1-b'
YC_SUBNET_ID = None # Fill if you have more than one VPC subnet in given folder and zone
YC_SERVICE_ACCOUNT_ID = None # Fill if you have more than one YC service account in given folder


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
def create_cluster(
yandex_conn_id: Optional[str] = None,
folder_id: Optional[str] = None,
network_id: Optional[str] = None,
subnet_id: Optional[str] = None,
zone: str = YC_ZONE_NAME,
service_account_id: Optional[str] = None,
ssh_public_key: Optional[str] = None,
*,
dag: Optional[DAG] = None,
ts_nodash: Optional[str] = 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
def run_spark_job(
cluster_id: str,
yandex_conn_id: Optional[str] = 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')
def delete_cluster(
cluster_id: str,
yandex_conn_id: Optional[str] = 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_interval=None,
start_date=datetime(2021, 1, 1),
tags=['example'],
) as dag:
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)
test_run = get_test_run(dag)
Original file line number Diff line number Diff line change
@@ -0,0 +1,80 @@
# Licensed to the Apache Software Foundation (ASF) under one
# or more contributor license agreements. See the NOTICE file
# distributed with this work for additional information
# regarding copyright ownership. The ASF licenses this file
# to you under the Apache License, Version 2.0 (the
# "License"); you may not use this file except in compliance
# with the License. You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing,
# software distributed under the License is distributed on an
# "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
# KIND, either express or implied. See the License for the
# specific language governing permissions and limitations
# under the License.
import os
from datetime import datetime

from airflow import DAG
from airflow.providers.yandex.operators.yandexcloud_dataproc import (
DataprocCreateClusterOperator,
DataprocCreateSparkJobOperator,
DataprocDeleteClusterOperator,
)

# Name of the datacenter where Dataproc cluster will be created
from airflow.utils.trigger_rule import TriggerRule

# should be filled with appropriate ids


AVAILABILITY_ZONE_ID = 'ru-central1-c'

# Dataproc cluster will use this bucket as distributed storage
S3_BUCKET_NAME = ''

ENV_ID = os.environ.get("SYSTEM_TESTS_ENV_ID")
DAG_ID = 'example_yandexcloud_dataproc_lightweight'

with DAG(
DAG_ID,
schedule_interval=None,
start_date=datetime(2021, 1, 1),
tags=['example'],
) as dag:
create_cluster = DataprocCreateClusterOperator(
task_id='create_cluster',
zone=AVAILABILITY_ZONE_ID,
s3_bucket=S3_BUCKET_NAME,
computenode_count=1,
datanode_count=0,
services=('SPARK', 'YARN'),
)

create_spark_job = DataprocCreateSparkJobOperator(
cluster_id=create_cluster.cluster_id,
task_id='create_spark_job',
main_jar_file_uri='file:///usr/lib/spark/examples/jars/spark-examples.jar',
main_class='org.apache.spark.examples.SparkPi',
args=['1000'],
)

delete_cluster = DataprocDeleteClusterOperator(
cluster_id=create_cluster.cluster_id,
task_id='delete_cluster',
trigger_rule=TriggerRule.ALL_DONE,
)
create_spark_job >> delete_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/README.md#run_via_pytest)
test_run = get_test_run(dag)

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