title: Airflow BigQueryOperator: how to save query result in a partitioned Table?
body: <p>I have a simple DAG </p>
  
  <pre><code>from airflow import DAG
  from airflow.contrib.operators.bigquery_operator import BigQueryOperator
  
  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='my_dataset.my_table20180524'),
                              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={})
      start &gt;&gt; bq_query &gt;&gt; end
  </code></pre>
  
  <p>When executing the <code>bq_query</code> task the SQL query gets saved in a sharded table. I want it to get saved in a daily partitioned table. In order to do so, I only changed <code>destination_dataset_table</code> to <code>my_dataset.my_table$20180524</code>. I got the error below when executing the <code>bq_task</code>:</p>
  
  <pre><code>Partitioning specification must be provided in order to create partitioned table
  </code></pre>
  
  <p>How can I specify to BigQuery to save query result to a daily partitioned table ? my first guess has been to use <code>query_params</code> in <code>BigQueryOperator</code> 
  but I didn't find any example on how to use that parameter. </p>
  
  <p><strong>EDIT:</strong></p>
  
  <p>I'm using <code>google-cloud==0.27.0</code> python client ... and it's the one used in Prod :(</p>