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"""
Example Airflow DAG that creates and deletes Bigquery data transfer configurations.
"""
from __future__ import annotations
import os
import time
from datetime import datetime
from pathlib import Path
from typing import cast
from airflow.models.baseoperator import chain
from airflow.models.dag import DAG
from airflow.models.xcom_arg import XComArg
from airflow.providers.google.cloud.operators.bigquery import (
BigQueryCreateEmptyDatasetOperator,
BigQueryCreateEmptyTableOperator,
BigQueryDeleteDatasetOperator,
)
from airflow.providers.google.cloud.operators.bigquery_dts import (
BigQueryCreateDataTransferOperator,
BigQueryDataTransferServiceStartTransferRunsOperator,
BigQueryDeleteDataTransferConfigOperator,
)
from airflow.providers.google.cloud.operators.gcs import GCSCreateBucketOperator, GCSDeleteBucketOperator
from airflow.providers.google.cloud.sensors.bigquery_dts import BigQueryDataTransferServiceTransferRunSensor
from airflow.providers.google.cloud.transfers.local_to_gcs import LocalFilesystemToGCSOperator
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]PROJECT_ID = os.environ.get("SYSTEM_TESTS_GCP_PROJECT") or DEFAULT_GCP_SYSTEM_TEST_PROJECT_ID
[docs]DAG_ID = "gcp_bigquery_dts"
[docs]BUCKET_NAME = f"bucket-{DAG_ID}-{ENV_ID}"
[docs]FILE_NAME = "us-states.csv"
[docs]CURRENT_FOLDER = Path(__file__).parent
[docs]FILE_LOCAL_PATH = str(Path(CURRENT_FOLDER) / "resources" / FILE_NAME)
[docs]BUCKET_URI = f"gs://{BUCKET_NAME}/{FILE_NAME}"
[docs]DATASET_NAME = f"dataset_{DAG_ID}_{ENV_ID}"
[docs]DTS_BQ_TABLE = "DTS_BQ_TABLE"
# [START howto_bigquery_dts_create_args]
# In the case of Airflow, the customer needs to create a transfer
# config with the automatic scheduling disabled and then trigger
# a transfer run using a specialized Airflow operator
[docs]TRANSFER_CONFIG = {
"destination_dataset_id": DATASET_NAME,
"display_name": "test data transfer",
"data_source_id": "google_cloud_storage",
"schedule_options": {"disable_auto_scheduling": True},
"params": {
"field_delimiter": ",",
"max_bad_records": "0",
"skip_leading_rows": "1",
"data_path_template": BUCKET_URI,
"destination_table_name_template": DTS_BQ_TABLE,
"file_format": "CSV",
},
}
# [END howto_bigquery_dts_create_args]
with DAG(
DAG_ID,
schedule="@once",
start_date=datetime(2021, 1, 1),
catchup=False,
tags=["example", "bigquery"],
) as dag:
[docs] create_bucket = GCSCreateBucketOperator(
task_id="create_bucket", bucket_name=BUCKET_NAME, project_id=PROJECT_ID
)
upload_file = LocalFilesystemToGCSOperator(
task_id="upload_file",
src=FILE_LOCAL_PATH,
dst=FILE_NAME,
bucket=BUCKET_NAME,
)
create_dataset = BigQueryCreateEmptyDatasetOperator(task_id="create_dataset", dataset_id=DATASET_NAME)
create_table = BigQueryCreateEmptyTableOperator(
task_id="create_table",
dataset_id=DATASET_NAME,
table_id=DTS_BQ_TABLE,
schema_fields=[
{"name": "name", "type": "STRING", "mode": "REQUIRED"},
{"name": "post_abbr", "type": "STRING", "mode": "NULLABLE"},
],
)
# [START howto_bigquery_create_data_transfer]
gcp_bigquery_create_transfer = BigQueryCreateDataTransferOperator(
transfer_config=TRANSFER_CONFIG,
project_id=PROJECT_ID,
task_id="gcp_bigquery_create_transfer",
)
transfer_config_id = cast(str, XComArg(gcp_bigquery_create_transfer, key="transfer_config_id"))
# [END howto_bigquery_create_data_transfer]
# [START howto_bigquery_start_transfer]
gcp_bigquery_start_transfer = BigQueryDataTransferServiceStartTransferRunsOperator(
task_id="gcp_bigquery_start_transfer",
project_id=PROJECT_ID,
transfer_config_id=transfer_config_id,
requested_run_time={"seconds": int(time.time() + 60)},
)
# [END howto_bigquery_start_transfer]
# [START howto_bigquery_dts_sensor]
gcp_run_sensor = BigQueryDataTransferServiceTransferRunSensor(
task_id="gcp_run_sensor",
transfer_config_id=transfer_config_id,
run_id=cast(str, XComArg(gcp_bigquery_start_transfer, key="run_id")),
expected_statuses={"SUCCEEDED"},
)
# [END howto_bigquery_dts_sensor]
# [START howto_bigquery_delete_data_transfer]
gcp_bigquery_delete_transfer = BigQueryDeleteDataTransferConfigOperator(
transfer_config_id=transfer_config_id, task_id="gcp_bigquery_delete_transfer"
)
# [END howto_bigquery_delete_data_transfer]
gcp_bigquery_delete_transfer.trigger_rule = TriggerRule.ALL_DONE
delete_dataset = BigQueryDeleteDatasetOperator(
task_id="delete_dataset",
dataset_id=DATASET_NAME,
delete_contents=True,
trigger_rule=TriggerRule.ALL_DONE,
)
delete_bucket = GCSDeleteBucketOperator(
task_id="delete_bucket", bucket_name=BUCKET_NAME, trigger_rule=TriggerRule.ALL_DONE
)
# Task dependencies created via `XComArgs`:
# gcp_bigquery_create_transfer >> gcp_bigquery_start_transfer
# gcp_bigquery_create_transfer >> gcp_run_sensor
# gcp_bigquery_start_transfer >> gcp_run_sensor
# gcp_bigquery_create_transfer >> gcp_bigquery_delete_transfer
chain(
# TEST SETUP
create_bucket,
upload_file,
create_dataset,
create_table,
# TEST BODY
gcp_bigquery_create_transfer,
gcp_bigquery_start_transfer,
gcp_run_sensor,
gcp_bigquery_delete_transfer,
# TEST TEARDOWN
delete_dataset,
delete_bucket,
)
from dev.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 dev.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)