I have a simple DAG
from airflow import DAG
from airflow.contrib.operators.bigquery_operator import BigQueryOperator
with DAG(dag_id=\'my_dags.my_dag\') as
You first need to create an Empty partitioned destination table. Follow instructions here: link to create an empty partitioned table
and then run below airflow pipeline again. You can try code:
import datetime
from airflow import DAG
from airflow.contrib.operators.bigquery_operator import BigQueryOperator
today_date = datetime.datetime.now().strftime("%Y%m%d")
table_name = 'my_dataset.my_table' + '$' + today_date
with DAG(dag_id='my_dags.my_dag') as dag:
start = DummyOperator(task_id='start')
end = DummyOperator(task_id='end')
sql = """
SELECT *
FROM 'another_dataset.another_table'
"""
bq_query = BigQueryOperator(bql=sql,
destination_dataset_table={{ params.t_name }}),
task_id='bq_query',
bigquery_conn_id='my_bq_connection',
use_legacy_sql=False,
write_disposition='WRITE_TRUNCATE',
create_disposition='CREATE_IF_NEEDED',
query_params={'t_name': table_name},
dag=dag
)
start >> bq_query >> end
So what I did is that I created a dynamic table name variable and passed to the BQ operator.