Source code for airflow.providers.google.cloud.example_dags.example_dataflow_sql
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"""
Example Airflow DAG for Google Cloud Dataflow service
"""
import os
from datetime import datetime
from airflow import models
from airflow.providers.google.cloud.operators.dataflow import DataflowStartSqlJobOperator
[docs]GCP_PROJECT_ID = os.environ.get("GCP_PROJECT_ID", "example-project")
[docs]BQ_SQL_DATASET = os.environ.get("GCP_DATAFLOW_BQ_SQL_DATASET", "airflow_dataflow_samples")
[docs]BQ_SQL_TABLE_OUTPUT = os.environ.get("GCP_DATAFLOW_BQ_SQL_TABLE_OUTPUT", "beam_output")
[docs]DATAFLOW_SQL_JOB_NAME = os.environ.get("GCP_DATAFLOW_SQL_JOB_NAME", "dataflow-sql")
[docs]DATAFLOW_SQL_LOCATION = os.environ.get("GCP_DATAFLOW_SQL_LOCATION", "us-west1")
with models.DAG(
dag_id="example_gcp_dataflow_sql",
start_date=datetime(2021, 1, 1),
catchup=False,
schedule_interval='@once', # Override to match your needs
tags=['example'],
) as dag_sql:
# [START howto_operator_start_sql_job]
[docs] start_sql = DataflowStartSqlJobOperator(
task_id="start_sql_query",
job_name=DATAFLOW_SQL_JOB_NAME,
query=f"""
SELECT
sales_region as sales_region,
count(state_id) as count_state
FROM
bigquery.table.`{GCP_PROJECT_ID}`.`{BQ_SQL_DATASET}`.`{BQ_SQL_TABLE_INPUT}`
WHERE state_id >= @state_id_min
GROUP BY sales_region;
""",
options={
"bigquery-project": GCP_PROJECT_ID,
"bigquery-dataset": BQ_SQL_DATASET,
"bigquery-table": BQ_SQL_TABLE_OUTPUT,
"bigquery-write-disposition": "write-truncate",
"parameter": "state_id_min:INT64:2",
},
location=DATAFLOW_SQL_LOCATION,
do_xcom_push=True,
)
# [END howto_operator_start_sql_job]
