Source code for airflow.providers.amazon.aws.operators.redshift_data

#
# Licensed to the Apache Software Foundation (ASF) under one
# or more contributor license agreements.  See the NOTICE file
# distributed with this work for additional information
# regarding copyright ownership.  The ASF licenses this file
# to you under the Apache License, Version 2.0 (the
# "License"); you may not use this file except in compliance
# with the License.  You may obtain a copy of the License at
#
#   http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing,
# software distributed under the License is distributed on an
# "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
# KIND, either express or implied.  See the License for the
# specific language governing permissions and limitations
# under the License.
from __future__ import annotations

from typing import TYPE_CHECKING, Any

from airflow.configuration import conf
from airflow.exceptions import AirflowException
from airflow.providers.amazon.aws.hooks.redshift_data import RedshiftDataHook
from airflow.providers.amazon.aws.operators.base_aws import AwsBaseOperator
from airflow.providers.amazon.aws.triggers.redshift_data import RedshiftDataTrigger
from airflow.providers.amazon.aws.utils import validate_execute_complete_event
from airflow.providers.amazon.aws.utils.mixins import aws_template_fields

if TYPE_CHECKING:
    from mypy_boto3_redshift_data.type_defs import GetStatementResultResponseTypeDef

    from airflow.utils.context import Context


[docs]class RedshiftDataOperator(AwsBaseOperator[RedshiftDataHook]): """ Executes SQL Statements against an Amazon Redshift cluster using Redshift Data. .. seealso:: For more information on how to use this operator, take a look at the guide: :ref:`howto/operator:RedshiftDataOperator` :param database: the name of the database :param sql: the SQL statement or list of SQL statement to run :param cluster_identifier: unique identifier of a cluster :param db_user: the database username :param parameters: the parameters for the SQL statement :param secret_arn: the name or ARN of the secret that enables db access :param statement_name: the name of the SQL statement :param with_event: indicates whether to send an event to EventBridge :param wait_for_completion: indicates whether to wait for a result, if True wait, if False don't wait :param poll_interval: how often in seconds to check the query status :param return_sql_result: if True will return the result of an SQL statement, if False (default) will return statement ID :param workgroup_name: name of the Redshift Serverless workgroup. Mutually exclusive with `cluster_identifier`. Specify this parameter to query Redshift Serverless. More info https://docs.aws.amazon.com/redshift/latest/mgmt/working-with-serverless.html :param aws_conn_id: The Airflow connection used for AWS credentials. If this is ``None`` or empty then the default boto3 behaviour is used. If running Airflow in a distributed manner and aws_conn_id is None or empty, then default boto3 configuration would be used (and must be maintained on each worker node). :param region_name: AWS region_name. If not specified then the default boto3 behaviour is used. :param verify: Whether or not to verify SSL certificates. See: https://boto3.amazonaws.com/v1/documentation/api/latest/reference/core/session.html :param botocore_config: Configuration dictionary (key-values) for botocore client. See: https://botocore.amazonaws.com/v1/documentation/api/latest/reference/config.html """
[docs] aws_hook_class = RedshiftDataHook
[docs] template_fields = aws_template_fields( "cluster_identifier", "database", "sql", "db_user", "parameters", "statement_name", "workgroup_name", )
[docs] template_ext = (".sql",)
[docs] template_fields_renderers = {"sql": "sql"}
[docs] statement_id: str | None
def __init__( self, database: str, sql: str | list, cluster_identifier: str | None = None, db_user: str | None = None, parameters: list | None = None, secret_arn: str | None = None, statement_name: str | None = None, with_event: bool = False, wait_for_completion: bool = True, poll_interval: int = 10, return_sql_result: bool = False, workgroup_name: str | None = None, deferrable: bool = conf.getboolean("operators", "default_deferrable", fallback=False), **kwargs, ) -> None: super().__init__(**kwargs) self.database = database self.sql = sql self.cluster_identifier = cluster_identifier self.workgroup_name = workgroup_name self.db_user = db_user self.parameters = parameters self.secret_arn = secret_arn self.statement_name = statement_name self.with_event = with_event self.wait_for_completion = wait_for_completion if poll_interval > 0: self.poll_interval = poll_interval else: self.log.warning( "Invalid poll_interval:", poll_interval, ) self.return_sql_result = return_sql_result self.statement_id: str | None = None self.deferrable = deferrable
[docs] def execute(self, context: Context) -> GetStatementResultResponseTypeDef | str: """Execute a statement against Amazon Redshift.""" self.log.info("Executing statement: %s", self.sql) # Set wait_for_completion to False so that it waits for the status in the deferred task. wait_for_completion = self.wait_for_completion if self.deferrable and self.wait_for_completion: self.wait_for_completion = False self.statement_id = self.hook.execute_query( database=self.database, sql=self.sql, cluster_identifier=self.cluster_identifier, workgroup_name=self.workgroup_name, db_user=self.db_user, parameters=self.parameters, secret_arn=self.secret_arn, statement_name=self.statement_name, with_event=self.with_event, wait_for_completion=wait_for_completion, poll_interval=self.poll_interval, ) if self.deferrable: is_finished = self.hook.check_query_is_finished(self.statement_id) if not is_finished: self.defer( timeout=self.execution_timeout, trigger=RedshiftDataTrigger( statement_id=self.statement_id, task_id=self.task_id, poll_interval=self.poll_interval, aws_conn_id=self.aws_conn_id, region_name=self.region_name, verify=self.verify, botocore_config=self.botocore_config, ), method_name="execute_complete", ) if self.return_sql_result: result = self.hook.conn.get_statement_result(Id=self.statement_id) self.log.debug("Statement result: %s", result) return result else: return self.statement_id
[docs] def execute_complete( self, context: Context, event: dict[str, Any] | None = None ) -> GetStatementResultResponseTypeDef | str: event = validate_execute_complete_event(event) if event["status"] == "error": msg = f"context: {context}, error message: {event['message']}" raise AirflowException(msg) statement_id = event["statement_id"] if not statement_id: raise AirflowException("statement_id should not be empty.") self.log.info("%s completed successfully.", self.task_id) if self.return_sql_result: result = self.hook.conn.get_statement_result(Id=statement_id) self.log.debug("Statement result: %s", result) return result return statement_id
[docs] def on_kill(self) -> None: """Cancel the submitted redshift query.""" if self.statement_id: self.log.info("Received a kill signal.") self.log.info("Stopping Query with statementId - %s", self.statement_id) try: self.hook.conn.cancel_statement(Id=self.statement_id) except Exception as ex: self.log.error("Unable to cancel query. Exiting. %s", ex)

Was this entry helpful?