#
# 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, Sequence
from airflow.models import BaseOperator
from airflow.providers.amazon.aws.hooks.dms import DmsHook
if TYPE_CHECKING:
from airflow.utils.context import Context
[docs]class DmsCreateTaskOperator(BaseOperator):
"""
Creates AWS DMS replication task.
.. seealso::
For more information on how to use this operator, take a look at the guide:
:ref:`howto/operator:DmsCreateTaskOperator`
:param replication_task_id: Replication task id
:param source_endpoint_arn: Source endpoint ARN
:param target_endpoint_arn: Target endpoint ARN
:param replication_instance_arn: Replication instance ARN
:param table_mappings: Table mappings
:param migration_type: Migration type ('full-load'|'cdc'|'full-load-and-cdc'), full-load by default.
:param create_task_kwargs: Extra arguments for DMS replication task creation.
: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).
"""
[docs] template_fields: Sequence[str] = (
"replication_task_id",
"source_endpoint_arn",
"target_endpoint_arn",
"replication_instance_arn",
"table_mappings",
"migration_type",
"create_task_kwargs",
)
[docs] template_ext: Sequence[str] = ()
[docs] template_fields_renderers = {
"table_mappings": "json",
"create_task_kwargs": "json",
}
def __init__(
self,
*,
replication_task_id: str,
source_endpoint_arn: str,
target_endpoint_arn: str,
replication_instance_arn: str,
table_mappings: dict,
migration_type: str = "full-load",
create_task_kwargs: dict | None = None,
aws_conn_id: str = "aws_default",
**kwargs,
):
super().__init__(**kwargs)
self.replication_task_id = replication_task_id
self.source_endpoint_arn = source_endpoint_arn
self.target_endpoint_arn = target_endpoint_arn
self.replication_instance_arn = replication_instance_arn
self.migration_type = migration_type
self.table_mappings = table_mappings
self.create_task_kwargs = create_task_kwargs or {}
self.aws_conn_id = aws_conn_id
[docs] def execute(self, context: Context):
"""
Creates AWS DMS replication task from Airflow.
:return: replication task arn
"""
dms_hook = DmsHook(aws_conn_id=self.aws_conn_id)
task_arn = dms_hook.create_replication_task(
replication_task_id=self.replication_task_id,
source_endpoint_arn=self.source_endpoint_arn,
target_endpoint_arn=self.target_endpoint_arn,
replication_instance_arn=self.replication_instance_arn,
migration_type=self.migration_type,
table_mappings=self.table_mappings,
**self.create_task_kwargs,
)
self.log.info("DMS replication task(%s) is ready.", self.replication_task_id)
return task_arn
[docs]class DmsDeleteTaskOperator(BaseOperator):
"""
Deletes AWS DMS replication task.
.. seealso::
For more information on how to use this operator, take a look at the guide:
:ref:`howto/operator:DmsDeleteTaskOperator`
:param replication_task_arn: Replication task ARN
: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).
"""
[docs] template_fields: Sequence[str] = ("replication_task_arn",)
[docs] template_ext: Sequence[str] = ()
[docs] template_fields_renderers: dict[str, str] = {}
def __init__(
self,
*,
replication_task_arn: str | None = None,
aws_conn_id: str = "aws_default",
**kwargs,
):
super().__init__(**kwargs)
self.replication_task_arn = replication_task_arn
self.aws_conn_id = aws_conn_id
[docs] def execute(self, context: Context):
"""
Deletes AWS DMS replication task from Airflow.
:return: replication task arn
"""
dms_hook = DmsHook(aws_conn_id=self.aws_conn_id)
dms_hook.delete_replication_task(replication_task_arn=self.replication_task_arn)
self.log.info("DMS replication task(%s) has been deleted.", self.replication_task_arn)
[docs]class DmsDescribeTasksOperator(BaseOperator):
"""
Describes AWS DMS replication tasks.
.. seealso::
For more information on how to use this operator, take a look at the guide:
:ref:`howto/operator:DmsDescribeTasksOperator`
:param describe_tasks_kwargs: Describe tasks command arguments
: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).
"""
[docs] template_fields: Sequence[str] = ("describe_tasks_kwargs",)
[docs] template_ext: Sequence[str] = ()
[docs] template_fields_renderers: dict[str, str] = {"describe_tasks_kwargs": "json"}
def __init__(
self,
*,
describe_tasks_kwargs: dict | None = None,
aws_conn_id: str = "aws_default",
**kwargs,
):
super().__init__(**kwargs)
self.describe_tasks_kwargs = describe_tasks_kwargs or {}
self.aws_conn_id = aws_conn_id
[docs] def execute(self, context: Context) -> tuple[str | None, list]:
"""
Describes AWS DMS replication tasks from Airflow.
:return: Marker and list of replication tasks
"""
dms_hook = DmsHook(aws_conn_id=self.aws_conn_id)
return dms_hook.describe_replication_tasks(**self.describe_tasks_kwargs)
[docs]class DmsStartTaskOperator(BaseOperator):
"""
Starts AWS DMS replication task.
.. seealso::
For more information on how to use this operator, take a look at the guide:
:ref:`howto/operator:DmsStartTaskOperator`
:param replication_task_arn: Replication task ARN
:param start_replication_task_type: Replication task start type (default='start-replication')
('start-replication'|'resume-processing'|'reload-target')
:param start_task_kwargs: Extra start replication task arguments
: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).
"""
[docs] template_fields: Sequence[str] = (
"replication_task_arn",
"start_replication_task_type",
"start_task_kwargs",
)
[docs] template_ext: Sequence[str] = ()
[docs] template_fields_renderers = {"start_task_kwargs": "json"}
def __init__(
self,
*,
replication_task_arn: str,
start_replication_task_type: str = "start-replication",
start_task_kwargs: dict | None = None,
aws_conn_id: str = "aws_default",
**kwargs,
):
super().__init__(**kwargs)
self.replication_task_arn = replication_task_arn
self.start_replication_task_type = start_replication_task_type
self.start_task_kwargs = start_task_kwargs or {}
self.aws_conn_id = aws_conn_id
[docs] def execute(self, context: Context):
"""
Starts AWS DMS replication task from Airflow.
:return: replication task arn
"""
dms_hook = DmsHook(aws_conn_id=self.aws_conn_id)
dms_hook.start_replication_task(
replication_task_arn=self.replication_task_arn,
start_replication_task_type=self.start_replication_task_type,
**self.start_task_kwargs,
)
self.log.info("DMS replication task(%s) is starting.", self.replication_task_arn)
[docs]class DmsStopTaskOperator(BaseOperator):
"""
Stops AWS DMS replication task.
.. seealso::
For more information on how to use this operator, take a look at the guide:
:ref:`howto/operator:DmsStopTaskOperator`
:param replication_task_arn: Replication task ARN
: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).
"""
[docs] template_fields: Sequence[str] = ("replication_task_arn",)
[docs] template_ext: Sequence[str] = ()
[docs] template_fields_renderers: dict[str, str] = {}
def __init__(
self,
*,
replication_task_arn: str | None = None,
aws_conn_id: str = "aws_default",
**kwargs,
):
super().__init__(**kwargs)
self.replication_task_arn = replication_task_arn
self.aws_conn_id = aws_conn_id
[docs] def execute(self, context: Context):
"""
Stops AWS DMS replication task from Airflow.
:return: replication task arn
"""
dms_hook = DmsHook(aws_conn_id=self.aws_conn_id)
dms_hook.stop_replication_task(replication_task_arn=self.replication_task_arn)
self.log.info("DMS replication task(%s) is stopping.", self.replication_task_arn)
