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airflow.providers.apache.hive.transfers.vertica_to_hive

This module contains operator to move data from Vertica to Hive.

Module Contents

class airflow.providers.apache.hive.transfers.vertica_to_hive.VerticaToHiveOperator(*, sql, hive_table, create=True, recreate=False, partition=None, delimiter=chr(1), vertica_conn_id='vertica_default', hive_cli_conn_id='hive_cli_default', **kwargs)[source]

Bases: airflow.models.BaseOperator

Moves data from Vertica to Hive. The operator runs your query against Vertica, 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.

Parameters
  • sql (str) -- SQL query to execute against the Vertica database. (templated)

  • hive_table (str) -- target Hive table, use dot notation to target a specific database. (templated)

  • create (bool) -- whether to create the table if it doesn't exist

  • recreate (bool) -- whether to drop and recreate the table at every execution

  • partition (dict) -- target partition as a dict of partition columns and values. (templated)

  • delimiter (str) -- field delimiter in the file

  • vertica_conn_id (str) -- source Vertica connection

  • hive_cli_conn_id (str) -- Reference to the Hive CLI connection id.

template_fields = ['sql', 'partition', 'hive_table'][source]
template_ext = ['.sql'][source]
ui_color = #b4e0ff[source]
classmethod type_map(cls, vertica_type)[source]

Vertica-python datatype.py does not provide the full type mapping access. Manual hack. Reference: https://github.com/uber/vertica-python/blob/master/vertica_python/vertica/column.py

execute(self, context)[source]

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