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"""This module contains Databricks sensors."""
from __future__ import annotations
from functools import cached_property
from typing import TYPE_CHECKING, Any, Callable, Iterable, Sequence
from airflow.exceptions import AirflowException, AirflowSkipException
from airflow.providers.common.sql.hooks.sql import fetch_all_handler
from airflow.providers.databricks.hooks.databricks_sql import DatabricksSqlHook
from airflow.sensors.base import BaseSensorOperator
if TYPE_CHECKING:
from airflow.utils.context import Context
[docs]class DatabricksSqlSensor(BaseSensorOperator):
"""
Sensor that runs a SQL query on Databricks.
:param databricks_conn_id: Reference to :ref:`Databricks
connection id<howto/connection:databricks>` (templated), defaults to
DatabricksSqlHook.default_conn_name.
:param sql_warehouse_name: Optional name of Databricks SQL warehouse. If not specified, ``http_path``
must be provided as described below, defaults to None
:param http_path: Optional string specifying HTTP path of Databricks SQL warehouse or All Purpose cluster.
If not specified, it should be either specified in the Databricks connection's
extra parameters, or ``sql_warehouse_name`` must be specified.
:param session_configuration: An optional dictionary of Spark session parameters. If not specified,
it could be specified in the Databricks connection's extra parameters, defaults to None
:param http_headers: An optional list of (k, v) pairs
that will be set as HTTP headers on every request. (templated).
:param catalog: An optional initial catalog to use.
Requires Databricks Runtime version 9.0+ (templated), defaults to ""
:param schema: An optional initial schema to use.
Requires Databricks Runtime version 9.0+ (templated), defaults to "default"
:param sql: SQL statement to be executed.
:param handler: Handler for DbApiHook.run() to return results, defaults to fetch_all_handler
:param client_parameters: Additional parameters internal to Databricks SQL connector parameters.
"""
[docs] template_fields: Sequence[str] = (
"databricks_conn_id",
"sql",
"catalog",
"schema",
"http_headers",
)
[docs] template_ext: Sequence[str] = (".sql",)
[docs] template_fields_renderers = {"sql": "sql"}
def __init__(
self,
*,
databricks_conn_id: str = DatabricksSqlHook.default_conn_name,
http_path: str | None = None,
sql_warehouse_name: str | None = None,
session_configuration=None,
http_headers: list[tuple[str, str]] | None = None,
catalog: str = "",
schema: str = "default",
sql: str | Iterable[str],
handler: Callable[[Any], Any] = fetch_all_handler,
client_parameters: dict[str, Any] | None = None,
**kwargs,
) -> None:
"""Create DatabricksSqlSensor object using the specified input arguments."""
self.databricks_conn_id = databricks_conn_id
self._http_path = http_path
self._sql_warehouse_name = sql_warehouse_name
self.session_config = session_configuration
self.http_headers = http_headers
self.catalog = catalog
self.schema = schema
self.sql = sql
self.caller = "DatabricksSqlSensor"
self.client_parameters = client_parameters or {}
self.hook_params = kwargs.pop("hook_params", {})
self.handler = handler
super().__init__(**kwargs)
@cached_property
[docs] def hook(self) -> DatabricksSqlHook:
"""Creates and returns a DatabricksSqlHook object."""
return DatabricksSqlHook(
self.databricks_conn_id,
self._http_path,
self._sql_warehouse_name,
self.session_config,
self.http_headers,
self.catalog,
self.schema,
self.caller,
**self.client_parameters,
**self.hook_params,
)
def _get_results(self) -> bool:
"""Use the Databricks SQL hook and run the specified SQL query."""
if not (self._http_path or self._sql_warehouse_name):
# TODO: remove this if block when min_airflow_version is set to higher than 2.7.1
message = (
"Databricks SQL warehouse/cluster configuration missing. Please specify either"
" http_path or sql_warehouse_name."
)
if self.soft_fail:
raise AirflowSkipException(message)
raise AirflowException(message)
hook = self.hook
sql_result = hook.run(
self.sql,
handler=self.handler if self.do_xcom_push else None,
)
self.log.debug("SQL result: %s", sql_result)
return bool(sql_result)
[docs] def poke(self, context: Context) -> bool:
"""Sensor poke function to get and return results from the SQL sensor."""
return self._get_results()