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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 import models
from airflow.models.baseoperator import chain
from airflow.models.xcom_arg import XComArg
from import (
from import (
from import GCSCreateBucketOperator, GCSDeleteBucketOperator
from import BigQueryDataTransferServiceTransferRunSensor
from import LocalFilesystemToGCSOperator
from airflow.utils.trigger_rule import TriggerRule

[docs]ENV_ID = os.environ.get("SYSTEM_TESTS_ENV_ID")
[docs]PROJECT_ID = os.environ.get("SYSTEM_TESTS_GCP_PROJECT")
[docs]DAG_ID = "example_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]DATASET_NAME = f"dataset_{DAG_ID}_{ENV_ID}"
# [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 models.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", 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 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/
[docs]test_run = get_test_run(dag)

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