docs-archive/apache-airflow-providers-apache-spark/3.0.0/_sources/_api/airflow/providers/apache/spark/operators/spark_sql/index.rst.txt

:py:mod:`airflow.providers.apache.spark.operators.spark_sql`
============================================================

.. py:module:: airflow.providers.apache.spark.operators.spark_sql


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

Classes
~~~~~~~

.. autoapisummary::

   airflow.providers.apache.spark.operators.spark_sql.SparkSqlOperator




.. py:class:: SparkSqlOperator(*, sql, conf = None, conn_id = 'spark_sql_default', total_executor_cores = None, executor_cores = None, executor_memory = None, keytab = None, principal = None, master = None, name = 'default-name', num_executors = None, verbose = True, yarn_queue = None, **kwargs)

   Bases: :py:obj:`airflow.models.BaseOperator`

   Execute Spark SQL query

   .. seealso::
       For more information on how to use this operator, take a look at the guide:
       :ref:`howto/operator:SparkSqlOperator`

   :param sql: The SQL query to execute. (templated)
   :param conf: arbitrary Spark configuration property
   :param conn_id: connection_id string
   :param total_executor_cores: (Standalone & Mesos only) Total cores for all
       executors (Default: all the available cores on the worker)
   :param executor_cores: (Standalone & YARN only) Number of cores per
       executor (Default: 2)
   :param executor_memory: Memory per executor (e.g. 1000M, 2G) (Default: 1G)
   :param keytab: Full path to the file that contains the keytab
   :param master: spark://host:port, mesos://host:port, yarn, or local
       (Default: The ``host`` and ``port`` set in the Connection, or ``"yarn"``)
   :param name: Name of the job
   :param num_executors: Number of executors to launch
   :param verbose: Whether to pass the verbose flag to spark-sql
   :param yarn_queue: The YARN queue to submit to
       (Default: The ``queue`` value set in the Connection, or ``"default"``)

   .. py:attribute:: template_fields
      :annotation: :Sequence[str] = ['_sql']

      

   .. py:attribute:: template_ext
      :annotation: :Sequence[str] = ['.sql', '.hql']

      

   .. py:attribute:: template_fields_renderers
      

      

   .. py:method:: execute(self, context)

      Call the SparkSqlHook to run the provided sql query


   .. py:method:: on_kill(self)

      Override this method to cleanup subprocesses when a task instance
      gets killed. Any use of the threading, subprocess or multiprocessing
      module within an operator needs to be cleaned up or it will leave
      ghost processes behind.