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# to you under the Apache License, Version 2.0 (the
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from __future__ import annotations
from typing import TYPE_CHECKING, Any, Sequence
from deprecated import deprecated
from airflow.exceptions import AirflowProviderDeprecationWarning
from airflow.models import BaseOperator
from airflow.providers.apache.spark.hooks.spark_sql import SparkSqlHook
if TYPE_CHECKING:
from airflow.utils.context import Context
[docs]class SparkSqlOperator(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"``)
"""
[docs] template_fields: Sequence[str] = ("sql",)
[docs] template_ext: Sequence[str] = (".sql", ".hql")
[docs] template_fields_renderers = {"sql": "sql"}
def __init__(
self,
*,
sql: str,
conf: str | None = None,
conn_id: str = "spark_sql_default",
total_executor_cores: int | None = None,
executor_cores: int | None = None,
executor_memory: str | None = None,
keytab: str | None = None,
principal: str | None = None,
master: str | None = None,
name: str = "default-name",
num_executors: int | None = None,
verbose: bool = True,
yarn_queue: str | None = None,
**kwargs: Any,
) -> None:
super().__init__(**kwargs)
self.sql = sql
self._conf = conf
self._conn_id = conn_id
self._total_executor_cores = total_executor_cores
self._executor_cores = executor_cores
self._executor_memory = executor_memory
self._keytab = keytab
self._principal = principal
self._master = master
self._name = name
self._num_executors = num_executors
self._verbose = verbose
self._yarn_queue = yarn_queue
self._hook: SparkSqlHook | None = None
@property
@deprecated(
reason="`_sql` is deprecated and will be removed in the future. Please use `sql` instead.",
category=AirflowProviderDeprecationWarning,
)
def _sql(self):
"""Alias for ``sql``, used for compatibility (deprecated)."""
return self.sql
[docs] def execute(self, context: Context) -> None:
"""Call the SparkSqlHook to run the provided sql query."""
if self._hook is None:
self._hook = self._get_hook()
self._hook.run_query()
[docs] def on_kill(self) -> None:
if self._hook is None:
self._hook = self._get_hook()
self._hook.kill()
def _get_hook(self) -> SparkSqlHook:
"""Get SparkSqlHook."""
return SparkSqlHook(
sql=self._sql,
conf=self._conf,
conn_id=self._conn_id,
total_executor_cores=self._total_executor_cores,
executor_cores=self._executor_cores,
executor_memory=self._executor_memory,
keytab=self._keytab,
principal=self._principal,
name=self._name,
num_executors=self._num_executors,
master=self._master,
verbose=self._verbose,
yarn_queue=self._yarn_queue,
)