:py:mod:`airflow.providers.apache.spark.hooks.spark_jdbc_script`
================================================================

.. py:module:: airflow.providers.apache.spark.hooks.spark_jdbc_script


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


Functions
~~~~~~~~~

.. autoapisummary::

   airflow.providers.apache.spark.hooks.spark_jdbc_script.set_common_options
   airflow.providers.apache.spark.hooks.spark_jdbc_script.spark_write_to_jdbc
   airflow.providers.apache.spark.hooks.spark_jdbc_script.spark_read_from_jdbc


Attributes
~~~~~~~~~~

.. autoapisummary::

   airflow.providers.apache.spark.hooks.spark_jdbc_script.SPARK_WRITE_TO_JDBC
   airflow.providers.apache.spark.hooks.spark_jdbc_script.SPARK_READ_FROM_JDBC


.. py:data:: SPARK_WRITE_TO_JDBC
   :annotation: :str = spark_to_jdbc

   
.. py:data:: SPARK_READ_FROM_JDBC
   :annotation: :str = jdbc_to_spark

   
.. py:function:: set_common_options(spark_source, url = 'localhost:5432', jdbc_table = 'default.default', user = 'root', password = 'root', driver = 'driver')

   Get Spark source from JDBC connection

   :param spark_source: Spark source, here is Spark reader or writer
   :param url: JDBC resource url
   :param jdbc_table: JDBC resource table name
   :param user: JDBC resource user name
   :param password: JDBC resource password
   :param driver: JDBC resource driver


.. py:function:: spark_write_to_jdbc(spark_session, url, user, password, metastore_table, jdbc_table, driver, truncate, save_mode, batch_size, num_partitions, create_table_column_types)

   Transfer data from Spark to JDBC source


.. py:function:: spark_read_from_jdbc(spark_session, url, user, password, metastore_table, jdbc_table, driver, save_mode, save_format, fetch_size, num_partitions, partition_column, lower_bound, upper_bound)

   Transfer data from JDBC source to Spark