airflow redshift_data 源码
airflow redshift_data 代码
文件路径:/airflow/providers/amazon/aws/operators/redshift_data.py
#
# 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 time import sleep
from typing import TYPE_CHECKING, Any
from airflow.compat.functools import cached_property
from airflow.models import BaseOperator
from airflow.providers.amazon.aws.hooks.redshift_data import RedshiftDataHook
from airflow.providers.amazon.aws.utils import trim_none_values
if TYPE_CHECKING:
from airflow.utils.context import Context
class RedshiftDataOperator(BaseOperator):
"""
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 await_result: 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 aws_conn_id: aws connection to use
:param region: aws region to use
"""
template_fields = (
'cluster_identifier',
'database',
'sql',
'db_user',
'parameters',
'statement_name',
'aws_conn_id',
'region',
)
template_ext = ('.sql',)
template_fields_renderers = {'sql': 'sql'}
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,
await_result: bool = True,
poll_interval: int = 10,
aws_conn_id: str = 'aws_default',
region: str | None = None,
**kwargs,
) -> None:
super().__init__(**kwargs)
self.database = database
self.sql = sql
self.cluster_identifier = cluster_identifier
self.db_user = db_user
self.parameters = parameters
self.secret_arn = secret_arn
self.statement_name = statement_name
self.with_event = with_event
self.await_result = await_result
if poll_interval > 0:
self.poll_interval = poll_interval
else:
self.log.warning(
"Invalid poll_interval:",
poll_interval,
)
self.aws_conn_id = aws_conn_id
self.region = region
self.statement_id = None
@cached_property
def hook(self) -> RedshiftDataHook:
"""Create and return an RedshiftDataHook."""
return RedshiftDataHook(aws_conn_id=self.aws_conn_id, region_name=self.region)
def execute_query(self):
kwargs: dict[str, Any] = {
"ClusterIdentifier": self.cluster_identifier,
"Database": self.database,
"Sql": self.sql,
"DbUser": self.db_user,
"Parameters": self.parameters,
"WithEvent": self.with_event,
"SecretArn": self.secret_arn,
"StatementName": self.statement_name,
}
resp = self.hook.conn.execute_statement(**trim_none_values(kwargs))
return resp['Id']
def execute_batch_query(self):
kwargs: dict[str, Any] = {
"ClusterIdentifier": self.cluster_identifier,
"Database": self.database,
"Sqls": self.sql,
"DbUser": self.db_user,
"Parameters": self.parameters,
"WithEvent": self.with_event,
"SecretArn": self.secret_arn,
"StatementName": self.statement_name,
}
resp = self.hook.conn.batch_execute_statement(**trim_none_values(kwargs))
return resp['Id']
def wait_for_results(self, statement_id):
while True:
self.log.info("Polling statement %s", statement_id)
resp = self.hook.conn.describe_statement(
Id=statement_id,
)
status = resp['Status']
if status == 'FINISHED':
return status
elif status == 'FAILED' or status == 'ABORTED':
raise ValueError(f"Statement {statement_id!r} terminated with status {status}.")
else:
self.log.info("Query %s", status)
sleep(self.poll_interval)
def execute(self, context: Context) -> None:
"""Execute a statement against Amazon Redshift"""
self.log.info("Executing statement: %s", self.sql)
if isinstance(self.sql, list):
self.statement_id = self.execute_batch_query()
else:
self.statement_id = self.execute_query()
if self.await_result:
self.wait_for_results(self.statement_id)
return self.statement_id
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)
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