Source code for airflow.providers.databricks.sensors.databricks_sql

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"""This module contains Databricks sensors."""

from __future__ import annotations

from collections.abc import Iterable, Sequence
from functools import cached_property
from typing import TYPE_CHECKING, Any, Callable

from airflow.exceptions import AirflowException
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): message = ( "Databricks SQL warehouse/cluster configuration missing. Please specify either" " http_path or sql_warehouse_name." ) 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()

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