docs-archive/apache-airflow-providers-apache-spark/1.0.0/_sources/_api/airflow/providers/apache/spark/hooks/spark_sql/index.rst.txt

:mod:`airflow.providers.apache.spark.hooks.spark_sql`
=====================================================

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


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

.. py:class:: SparkSqlHook(sql: str, conf: Optional[str] = None, conn_id: str = default_conn_name, total_executor_cores: Optional[int] = None, executor_cores: Optional[int] = None, executor_memory: Optional[str] = None, keytab: Optional[str] = None, principal: Optional[str] = None, master: str = 'yarn', name: str = 'default-name', num_executors: Optional[int] = None, verbose: bool = True, yarn_queue: str = 'default')

   Bases: :class:`airflow.hooks.base.BaseHook`

   This hook is a wrapper around the spark-sql binary. It requires that the
   "spark-sql" binary is in the PATH.

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

   .. attribute:: conn_name_attr
      :annotation: = conn_id

      

   .. attribute:: default_conn_name
      :annotation: = spark_sql_default

      

   .. attribute:: conn_type
      :annotation: = spark_sql

      

   .. attribute:: hook_name
      :annotation: = Spark SQL

      

   
   .. method:: get_conn(self)



   
   .. method:: _prepare_command(self, cmd: Union[str, List[str]])

      Construct the spark-sql command to execute. Verbose output is enabled
      as default.

      :param cmd: command to append to the spark-sql command
      :type cmd: str or list[str]
      :return: full command to be executed



   
   .. method:: run_query(self, cmd: str = '', **kwargs)

      Remote Popen (actually execute the Spark-sql query)

      :param cmd: command to append to the spark-sql command
      :type cmd: str or list[str]
      :param kwargs: extra arguments to Popen (see subprocess.Popen)
      :type kwargs: dict



   
   .. method:: kill(self)

      Kill Spark job