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"""
Note: DMS requires you to configure specific IAM roles/permissions. For more information, see
https://docs.aws.amazon.com/dms/latest/userguide/CHAP_Security.html#CHAP_Security.APIRole
"""
from __future__ import annotations
import json
from datetime import datetime
from typing import cast
import boto3
from sqlalchemy import Column, MetaData, String, Table, create_engine
from airflow.decorators import task
from airflow.models.baseoperator import chain
from airflow.models.dag import DAG
from airflow.providers.amazon.aws.operators.dms import (
DmsCreateTaskOperator,
DmsDeleteTaskOperator,
DmsDescribeTasksOperator,
DmsStartTaskOperator,
DmsStopTaskOperator,
)
from airflow.providers.amazon.aws.operators.rds import (
RdsCreateDbInstanceOperator,
RdsDeleteDbInstanceOperator,
)
from airflow.providers.amazon.aws.operators.s3 import S3CreateBucketOperator, S3DeleteBucketOperator
from airflow.providers.amazon.aws.sensors.dms import DmsTaskBaseSensor, DmsTaskCompletedSensor
from airflow.utils.trigger_rule import TriggerRule
from providers.tests.system.amazon.aws.utils import ENV_ID_KEY, SystemTestContextBuilder
from providers.tests.system.amazon.aws.utils.ec2 import get_default_vpc_id
[docs]ROLE_ARN_KEY = "ROLE_ARN"
[docs]sys_test_context_task = SystemTestContextBuilder().add_variable(ROLE_ARN_KEY).build()
# Config values for setting up the "Source" database.
[docs]RDS_PROTOCOL = "postgresql"
[docs]RDS_USERNAME = "username"
# NEVER store your production password in plaintext in a DAG like this.
# Use Airflow Secrets or a secret manager for this in production.
[docs]RDS_PASSWORD = "rds_password"
[docs]SAMPLE_DATA = [
("Airflow", "2015"),
("OpenOffice", "2012"),
("Subversion", "2000"),
("NiFi", "2006"),
]
[docs]SG_IP_PERMISSION = {
"FromPort": 5432,
"IpProtocol": "All",
"IpRanges": [{"CidrIp": "0.0.0.0/0"}],
}
def _get_rds_instance_endpoint(instance_name: str):
print("Retrieving RDS instance endpoint.")
rds_client = boto3.client("rds")
response = rds_client.describe_db_instances(DBInstanceIdentifier=instance_name)
rds_instance_endpoint = response["DBInstances"][0]["Endpoint"]
return rds_instance_endpoint
@task
[docs]def create_security_group(security_group_name: str, vpc_id: str):
client = boto3.client("ec2")
security_group = client.create_security_group(
GroupName=security_group_name,
Description="Created for DMS system test",
VpcId=vpc_id,
)
client.get_waiter("security_group_exists").wait(
GroupIds=[security_group["GroupId"]],
)
client.authorize_security_group_ingress(
GroupId=security_group["GroupId"],
IpPermissions=[SG_IP_PERMISSION],
)
return security_group["GroupId"]
@task
[docs]def create_sample_table(instance_name: str, db_name: str, table_name: str):
print("Creating sample table.")
rds_endpoint = _get_rds_instance_endpoint(instance_name)
hostname = rds_endpoint["Address"]
port = rds_endpoint["Port"]
rds_url = f"{RDS_PROTOCOL}://{RDS_USERNAME}:{RDS_PASSWORD}@{hostname}:{port}/{db_name}"
engine = create_engine(rds_url)
table = Table(
table_name,
MetaData(engine),
Column(TABLE_HEADERS[0], String, primary_key=True),
Column(TABLE_HEADERS[1], String),
)
with engine.connect() as connection:
# Create the Table.
table.create()
load_data = table.insert().values(SAMPLE_DATA)
connection.execute(load_data)
# Read the data back to verify everything is working.
connection.execute(table.select())
@task(multiple_outputs=True)
[docs]def create_dms_assets(
db_name: str,
instance_name: str,
replication_instance_name: str,
bucket_name: str,
role_arn,
source_endpoint_identifier: str,
target_endpoint_identifier: str,
table_definition: dict,
):
print("Creating DMS assets.")
dms_client = boto3.client("dms")
rds_instance_endpoint = _get_rds_instance_endpoint(instance_name)
print("Creating replication instance.")
instance_arn = dms_client.create_replication_instance(
ReplicationInstanceIdentifier=replication_instance_name,
ReplicationInstanceClass="dms.t3.micro",
)["ReplicationInstance"]["ReplicationInstanceArn"]
print("Creating DMS source endpoint.")
source_endpoint_arn = dms_client.create_endpoint(
EndpointIdentifier=source_endpoint_identifier,
EndpointType="source",
EngineName=RDS_ENGINE,
Username=RDS_USERNAME,
Password=RDS_PASSWORD,
ServerName=rds_instance_endpoint["Address"],
Port=rds_instance_endpoint["Port"],
DatabaseName=db_name,
)["Endpoint"]["EndpointArn"]
print("Creating DMS target endpoint.")
target_endpoint_arn = dms_client.create_endpoint(
EndpointIdentifier=target_endpoint_identifier,
EndpointType="target",
EngineName="s3",
S3Settings={
"BucketName": bucket_name,
"BucketFolder": "folder",
"ServiceAccessRoleArn": role_arn,
"ExternalTableDefinition": json.dumps(table_definition),
},
)["Endpoint"]["EndpointArn"]
print("Awaiting replication instance provisioning.")
dms_client.get_waiter("replication_instance_available").wait(
Filters=[{"Name": "replication-instance-arn", "Values": [instance_arn]}]
)
return {
"replication_instance_arn": instance_arn,
"source_endpoint_arn": source_endpoint_arn,
"target_endpoint_arn": target_endpoint_arn,
}
@task(trigger_rule=TriggerRule.ALL_DONE)
[docs]def delete_dms_assets(
replication_instance_arn: str,
source_endpoint_arn: str,
target_endpoint_arn: str,
source_endpoint_identifier: str,
target_endpoint_identifier: str,
replication_instance_name: str,
):
dms_client = boto3.client("dms")
print("Deleting DMS assets.")
dms_client.delete_replication_instance(ReplicationInstanceArn=replication_instance_arn)
dms_client.delete_endpoint(EndpointArn=source_endpoint_arn)
dms_client.delete_endpoint(EndpointArn=target_endpoint_arn)
print("Awaiting DMS assets tear-down.")
dms_client.get_waiter("replication_instance_deleted").wait(
Filters=[{"Name": "replication-instance-id", "Values": [replication_instance_name]}]
)
dms_client.get_waiter("endpoint_deleted").wait(
Filters=[
{
"Name": "endpoint-id",
"Values": [source_endpoint_identifier, target_endpoint_identifier],
}
]
)
@task(trigger_rule=TriggerRule.ALL_DONE)
[docs]def delete_security_group(security_group_id: str, security_group_name: str):
boto3.client("ec2").delete_security_group(GroupId=security_group_id, GroupName=security_group_name)
with DAG(
DAG_ID,
schedule="@once",
start_date=datetime(2021, 1, 1),
tags=["example"],
catchup=False,
) as dag:
[docs] test_context = sys_test_context_task()
env_id = test_context[ENV_ID_KEY]
role_arn = test_context[ROLE_ARN_KEY]
bucket_name = f"{env_id}-dms-bucket"
rds_instance_name = f"{env_id}-instance"
rds_db_name = f"{env_id}_source_database" # dashes are not allowed in db name
rds_table_name = f"{env_id}-table"
dms_replication_instance_name = f"{env_id}-replication-instance"
dms_replication_task_id = f"{env_id}-replication-task"
source_endpoint_identifier = f"{env_id}-source-endpoint"
target_endpoint_identifier = f"{env_id}-target-endpoint"
security_group_name = f"{env_id}-dms-security-group"
# Sample data.
table_definition = {
"TableCount": "1",
"Tables": [
{
"TableName": rds_table_name,
"TableColumns": [
{
"ColumnName": TABLE_HEADERS[0],
"ColumnType": "STRING",
"ColumnNullable": "false",
"ColumnIsPk": "true",
},
{"ColumnName": TABLE_HEADERS[1], "ColumnType": "STRING", "ColumnLength": "4"},
],
"TableColumnsTotal": "2",
}
],
}
table_mappings = {
"rules": [
{
"rule-type": "selection",
"rule-id": "1",
"rule-name": "1",
"object-locator": {
"schema-name": "public",
"table-name": rds_table_name,
},
"rule-action": "include",
}
]
}
create_s3_bucket = S3CreateBucketOperator(task_id="create_s3_bucket", bucket_name=bucket_name)
get_vpc_id = get_default_vpc_id()
create_sg = create_security_group(security_group_name, get_vpc_id)
create_db_instance = RdsCreateDbInstanceOperator(
task_id="create_db_instance",
db_instance_identifier=rds_instance_name,
db_instance_class="db.t3.micro",
engine=RDS_ENGINE,
rds_kwargs={
"DBName": rds_db_name,
"AllocatedStorage": 20,
"MasterUsername": RDS_USERNAME,
"MasterUserPassword": RDS_PASSWORD,
"PubliclyAccessible": True,
"VpcSecurityGroupIds": [
create_sg,
],
},
)
create_assets = create_dms_assets(
db_name=rds_db_name,
instance_name=rds_instance_name,
replication_instance_name=dms_replication_instance_name,
bucket_name=bucket_name,
role_arn=role_arn,
source_endpoint_identifier=source_endpoint_identifier,
target_endpoint_identifier=target_endpoint_identifier,
table_definition=table_definition,
)
# [START howto_operator_dms_create_task]
create_task = DmsCreateTaskOperator(
task_id="create_task",
replication_task_id=dms_replication_task_id,
source_endpoint_arn=create_assets["source_endpoint_arn"],
target_endpoint_arn=create_assets["target_endpoint_arn"],
replication_instance_arn=create_assets["replication_instance_arn"],
table_mappings=table_mappings,
)
# [END howto_operator_dms_create_task]
task_arn = cast(str, create_task.output)
# [START howto_operator_dms_start_task]
start_task = DmsStartTaskOperator(
task_id="start_task",
replication_task_arn=task_arn,
)
# [END howto_operator_dms_start_task]
# [START howto_operator_dms_describe_tasks]
describe_tasks = DmsDescribeTasksOperator(
task_id="describe_tasks",
describe_tasks_kwargs={
"Filters": [
{
"Name": "replication-instance-arn",
"Values": [create_assets["replication_instance_arn"]],
}
]
},
do_xcom_push=False,
)
# [END howto_operator_dms_describe_tasks]
await_task_start = DmsTaskBaseSensor(
task_id="await_task_start",
replication_task_arn=task_arn,
target_statuses=["running"],
termination_statuses=["stopped", "deleting", "failed"],
poke_interval=10,
)
# [START howto_operator_dms_stop_task]
stop_task = DmsStopTaskOperator(
task_id="stop_task",
replication_task_arn=task_arn,
)
# [END howto_operator_dms_stop_task]
# TaskCompletedSensor actually waits until task reaches the "Stopped" state, so it will work here.
# [START howto_sensor_dms_task_completed]
await_task_stop = DmsTaskCompletedSensor(
task_id="await_task_stop",
replication_task_arn=task_arn,
)
# [END howto_sensor_dms_task_completed]
await_task_stop.poke_interval = 10
# [START howto_operator_dms_delete_task]
delete_task = DmsDeleteTaskOperator(
task_id="delete_task",
replication_task_arn=task_arn,
)
# [END howto_operator_dms_delete_task]
delete_task.trigger_rule = TriggerRule.ALL_DONE
delete_assets = delete_dms_assets(
replication_instance_arn=create_assets["replication_instance_arn"],
source_endpoint_arn=create_assets["source_endpoint_arn"],
target_endpoint_arn=create_assets["target_endpoint_arn"],
source_endpoint_identifier=source_endpoint_identifier,
target_endpoint_identifier=target_endpoint_identifier,
replication_instance_name=dms_replication_instance_name,
)
delete_db_instance = RdsDeleteDbInstanceOperator(
task_id="delete_db_instance",
db_instance_identifier=rds_instance_name,
rds_kwargs={
"SkipFinalSnapshot": True,
},
trigger_rule=TriggerRule.ALL_DONE,
)
delete_s3_bucket = S3DeleteBucketOperator(
task_id="delete_s3_bucket",
bucket_name=bucket_name,
force_delete=True,
trigger_rule=TriggerRule.ALL_DONE,
)
chain(
# TEST SETUP
test_context,
create_s3_bucket,
get_vpc_id,
create_sg,
create_db_instance,
create_sample_table(rds_instance_name, rds_db_name, rds_table_name),
create_assets,
# TEST BODY
create_task,
start_task,
describe_tasks,
await_task_start,
stop_task,
await_task_stop,
# TEST TEARDOWN
delete_task,
delete_assets,
delete_db_instance,
delete_security_group(create_sg, security_group_name),
delete_s3_bucket,
)
from tests_common.test_utils.watcher import watcher
# This test needs watcher in order to properly mark success/failure
# when "tearDown" task with trigger rule is part of the DAG
list(dag.tasks) >> watcher()
from tests_common.test_utils.system_tests import get_test_run # noqa: E402
# Needed to run the example DAG with pytest (see: tests/system/README.md#run_via_pytest)
[docs]test_run = get_test_run(dag)