bigquery_to_gcs

Example Airflow DAG for Google BigQuery service.

Big Data & Analytics


Providers:

Run this DAG

1. Install Astronomer CLISkip if you already have the CLI

2. Initate the project:

3. Copy and paste the code below into a file in the

dags
directory.

4. Add the following to your requirements.txt file:

5. Run the DAG:

#
# 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.
"""
Example Airflow DAG for Google BigQuery service.
"""
import os
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
from airflow.utils.dates import days_ago
PROJECT_ID = os.environ.get("GCP_PROJECT_ID", "example-project")
DATASET_NAME = os.environ.get("GCP_BIGQUERY_DATASET_NAME", "test_dataset_transfer")
DATA_EXPORT_BUCKET_NAME = os.environ.get("GCP_BIGQUERY_EXPORT_BUCKET_NAME", "INVALID BUCKET NAME")
TABLE = "table_42"
with models.DAG(
"example_bigquery_to_gcs",
schedule_interval=None, # Override to match your needs
start_date=days_ago(1),
tags=["example"],
) as dag:
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