:py:mod:`astronomer.providers.apache.hive.sensors.hive_partition`
=================================================================

.. py:module:: astronomer.providers.apache.hive.sensors.hive_partition


Module Contents
---------------

Classes
~~~~~~~

.. autoapisummary::

   astronomer.providers.apache.hive.sensors.hive_partition.HivePartitionSensorAsync




.. py:class:: HivePartitionSensorAsync(*, table, partition = "ds='{{ ds }}'", metastore_conn_id = 'metastore_default', schema = 'default', poke_interval = 60 * 3, **kwargs)


   Bases: :py:obj:`airflow.providers.apache.hive.sensors.hive_partition.HivePartitionSensor`

   Waits for a given partition to show up in Hive table asynchronously.

   .. note::
      HivePartitionSensorAsync uses impyla library instead of PyHive.
      The sync version of this sensor uses `PyHive <https://github.com/dropbox/PyHive>`.

      Since we use `impyla <https://github.com/cloudera/impyla>`_ library,
      please set the connection to use the port ``10000`` instead of ``9083``.
      For ``auth_mechanism='GSSAPI'`` the ticket renewal happens through command
      ``airflow kerberos`` in
      `worker/trigger <https://airflow.apache.org/docs/apache-airflow/stable/security/kerberos.html>`_.

      You may also need to allow traffic from Airflow worker/Triggerer to the Hive instance, depending on where
      they are running. For example, you might consider adding an entry in the ``etc/hosts`` file present in the
      Airflow worker/Triggerer, which maps the EMR Master node Public IP Address to its Private DNS Name to
      allow the network traffic.

      The library version of hive and hadoop in ``Dockerfile`` should match the remote
      cluster where they are running.

   :param table: the table where the partition is present.
   :param partition: The partition clause to wait for. This is passed as
       notation as in "ds='2015-01-01'"
   :param schema: database which needs to be connected in hive. By default, it is 'default'
   :param metastore_conn_id: connection string to connect to hive.
   :param polling_interval: The interval in seconds to wait between checks for partition.

   .. py:method:: execute(context)

      Airflow runs this method on the worker and defers using the trigger.


   .. py:method:: execute_complete(context, event = None)

      Callback for when the trigger fires - returns immediately.
      Relies on trigger to throw an exception, otherwise it assumes execution was
      successful.