Source code for tests.system.providers.google.cloud.bigquery.example_bigquery_transfer

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"""
Example Airflow DAG for Google BigQuery service.
"""
import os
from datetime import datetime

from airflow import models
from airflow.providers.google.cloud.operators.bigquery import (
    BigQueryCreateEmptyDatasetOperator,
    BigQueryCreateEmptyTableOperator,
    BigQueryDeleteDatasetOperator,
)
from airflow.providers.google.cloud.operators.gcs import GCSCreateBucketOperator, GCSDeleteBucketOperator
from airflow.providers.google.cloud.transfers.bigquery_to_bigquery import BigQueryToBigQueryOperator
from airflow.providers.google.cloud.transfers.bigquery_to_gcs import BigQueryToGCSOperator
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_bigquery_transfer"
[docs]DATASET_NAME = f"dataset_{DAG_ID}_{ENV_ID}"
[docs]BUCKET_NAME = f"bucket_{DAG_ID}_{ENV_ID}"
[docs]ORIGIN = "origin"
[docs]TARGET = "target"
with models.DAG( DAG_ID, schedule_interval='@once', # Override to match your needs 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
) create_dataset = BigQueryCreateEmptyDatasetOperator(task_id="create_dataset", dataset_id=DATASET_NAME) create_origin_table = BigQueryCreateEmptyTableOperator( task_id=f"create_{ORIGIN}_table", dataset_id=DATASET_NAME, table_id=ORIGIN, schema_fields=[ {"name": "emp_name", "type": "STRING", "mode": "REQUIRED"}, {"name": "salary", "type": "INTEGER", "mode": "NULLABLE"}, ], ) create_target_table = BigQueryCreateEmptyTableOperator( task_id=f"create_{TARGET}_table", dataset_id=DATASET_NAME, table_id=TARGET, schema_fields=[ {"name": "emp_name", "type": "STRING", "mode": "REQUIRED"}, {"name": "salary", "type": "INTEGER", "mode": "NULLABLE"}, ], ) copy_selected_data = BigQueryToBigQueryOperator( task_id="copy_selected_data", source_project_dataset_tables=f"{DATASET_NAME}.{ORIGIN}", destination_project_dataset_table=f"{DATASET_NAME}.{TARGET}", ) bigquery_to_gcs = BigQueryToGCSOperator( task_id="bigquery_to_gcs", source_project_dataset_table=f"{DATASET_NAME}.{ORIGIN}", destination_cloud_storage_uris=[f"gs://{BUCKET_NAME}/export-bigquery.csv"], ) 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 ) ( # TEST SETUP create_bucket >> create_dataset >> create_origin_table >> create_target_table # TEST BODY >> copy_selected_data >> bigquery_to_gcs # 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/README.md#run_via_pytest)
[docs]test_run = get_test_run(dag)

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