Source code for airflow.providers.google.cloud.example_dags.example_bigquery_to_gcs

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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.transfers.bigquery_to_gcs import BigQueryToGCSOperator

[docs]PROJECT_ID = os.environ.get("GCP_PROJECT_ID", "example-project")
[docs]DATASET_NAME = os.environ.get("GCP_BIGQUERY_DATASET_NAME", "test_dataset_transfer")
[docs]DATA_EXPORT_BUCKET_NAME = os.environ.get("GCP_BIGQUERY_EXPORT_BUCKET_NAME", "INVALID BUCKET NAME")
[docs]TABLE = "table_42"

with models.DAG(
    "example_bigquery_to_gcs",
    schedule_interval=None,  # Override to match your needs
    start_date=datetime(2021, 1, 1),
    catchup=False,
    tags=["example"],
) as dag:
[docs]    bigquery_to_gcs = BigQueryToGCSOperator(
        task_id="bigquery_to_gcs",
        source_project_dataset_table=f"{DATASET_NAME}.{TABLE}",
        destination_cloud_storage_uris=[f"gs://{DATA_EXPORT_BUCKET_NAME}/export-bigquery.csv"],
    )

    create_dataset = BigQueryCreateEmptyDatasetOperator(task_id="create_dataset", dataset_id=DATASET_NAME)

    create_table = BigQueryCreateEmptyTableOperator(
        task_id="create_table",
        dataset_id=DATASET_NAME,
        table_id=TABLE,
        schema_fields=[
            {"name": "emp_name", "type": "STRING", "mode": "REQUIRED"},
            {"name": "salary", "type": "INTEGER", "mode": "NULLABLE"},
        ],
    )
    create_dataset >> create_table >> bigquery_to_gcs

    delete_dataset = BigQueryDeleteDatasetOperator(
        task_id="delete_dataset", dataset_id=DATASET_NAME, delete_contents=True
    )

    bigquery_to_gcs >> delete_dataset