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:mod:`airflow.contrib.operators.vertica_to_hive`
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.. py:module:: airflow.contrib.operators.vertica_to_hive
Module Contents
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.. py:class:: VerticaToHiveTransfer(sql, hive_table, create=True, recreate=False, partition=None, delimiter=chr(1), vertica_conn_id='vertica_default', hive_cli_conn_id='hive_cli_default', *args, **kwargs)
Bases: :class:`airflow.models.BaseOperator`
Moves data from Vertia to Hive. The operator runs
your query against Vertia, stores the file locally
before loading it into a Hive table. If the ``create`` or
``recreate`` arguments are set to ``True``,
a ``CREATE TABLE`` and ``DROP TABLE`` statements are generated.
Hive data types are inferred from the cursor's metadata.
Note that the table generated in Hive uses ``STORED AS textfile``
which isn't the most efficient serialization format. If a
large amount of data is loaded and/or if the table gets
queried considerably, you may want to use this operator only to
stage the data into a temporary table before loading it into its
final destination using a ``HiveOperator``.
:param sql: SQL query to execute against the Vertia database. (templated)
:type sql: str
:param hive_table: target Hive table, use dot notation to target a
specific database. (templated)
:type hive_table: str
:param create: whether to create the table if it doesn't exist
:type create: bool
:param recreate: whether to drop and recreate the table at every execution
:type recreate: bool
:param partition: target partition as a dict of partition columns
and values. (templated)
:type partition: dict
:param delimiter: field delimiter in the file
:type delimiter: str
:param vertica_conn_id: source Vertica connection
:type vertica_conn_id: str
:param hive_conn_id: destination hive connection
:type hive_conn_id: str
.. attribute:: template_fields
:annotation: = ['sql', 'partition', 'hive_table']
.. attribute:: template_ext
:annotation: = ['.sql']
.. attribute:: ui_color
:annotation: = #b4e0ff
.. classmethod:: type_map(cls, vertica_type)
.. method:: execute(self, context)