AWS Database Migration Service (DMS)¶

AWS Database Migration Service (AWS DMS) is a web service you can use to migrate data from your database that is on-premises, on an Amazon Relational Database Service (Amazon RDS) DB instance, or in a database on an Amazon Elastic Compute Cloud (Amazon EC2) instance to a database on an AWS service. These services can include a database on Amazon RDS or a database on an Amazon EC2 instance. You can also migrate a database from an AWS service to an on-premises database. You can migrate between source and target endpoints that use the same database engine, such as from an Oracle database to an Oracle database. You can also migrate between source and target endpoints that use different database engines, such as from an Oracle database to a PostgreSQL database.

Prerequisite Tasks¶

To use these operators, you must do a few things:

Create necessary resources using AWS Console or AWS CLI.
Install API libraries via pip.
pip install 'apache-airflow[amazon]'
Detailed information is available Installation of Airflow®
Setup Connection.

Generic Parameters¶

aws_conn_id

Reference to Amazon Web Services Connection ID. If this parameter is set to None then the default boto3 behaviour is used without a connection lookup. Otherwise use the credentials stored in the Connection. Default: aws_default

region_name

AWS Region Name. If this parameter is set to None or omitted then region_name from AWS Connection Extra Parameter will be used. Otherwise use the specified value instead of the connection value. Default: None

verify

Whether or not to verify SSL certificates.

False - Do not validate SSL certificates.
path/to/cert/bundle.pem - A filename of the CA cert bundle to use. You can specify this argument if you want to use a different CA cert bundle than the one used by botocore.

If this parameter is set to None or is omitted then verify from AWS Connection Extra Parameter will be used. Otherwise use the specified value instead of the connection value. Default: None

botocore_config

The provided dictionary is used to construct a botocore.config.Config. This configuration can be used to configure Avoid Throttling exceptions, timeouts, etc.

Example, for more detail about parameters please have a look botocore.config.Config¶

{
    "signature_version": "unsigned",
    "s3": {
        "us_east_1_regional_endpoint": True,
    },
    "retries": {
      "mode": "standard",
      "max_attempts": 10,
    },
    "connect_timeout": 300,
    "read_timeout": 300,
    "tcp_keepalive": True,
}

If this parameter is set to None or omitted then config_kwargs from AWS Connection Extra Parameter will be used. Otherwise use the specified value instead of the connection value. Default: None

Note

Specifying an empty dictionary, {}, will overwrite the connection configuration for botocore.config.Config

Operators¶

Create a replication task¶

To create a replication task you can use DmsCreateTaskOperator.

tests/system/amazon/aws/example_dms.py[source]

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,
    migration_type="full-load-and-cdc",
    create_task_kwargs={
        "ReplicationTaskSettings": json.dumps({"ValidationSettings": {"EnableValidation": True}})
    },
)

Modify a replication task¶

To modify an existing replication task (e.g. to update table mappings for a backfill) you can use DmsModifyTaskOperator. The task must be stopped before modification — use DmsStopTaskOperator upstream in the Dag, and DmsStartTaskOperator downstream to restart it afterwards if needed.

tests/system/amazon/aws/example_dms.py[source]

modify_task = DmsModifyTaskOperator(
    task_id="modify_task",
    replication_task_arn=task_arn,
    table_mappings={
        "rules": [
            {
                "rule-type": "selection",
                "rule-id": "1",
                "rule-name": "1",
                "object-locator": {"schema-name": "%", "table-name": "%"},
                "rule-action": "include",
            }
        ]
    },
)

Start a replication task¶

To start a replication task you can use DmsStartTaskOperator.

tests/system/amazon/aws/example_dms.py[source]

start_task = DmsStartTaskOperator(
    task_id="start_task",
    replication_task_arn=task_arn,
)

Reload tables for a replication task¶

To reload selected target tables from their source data, use DmsReloadTablesOperator. The required parameters are replication_task_arn and tables_to_reload. Each item in tables_to_reload must contain SchemaName and TableName. The optional reload_option defaults to data-reload, which reloads the data and runs validation again when it is enabled. Use validate-only to revalidate without reloading data; this option only applies when validation is enabled for the task. The replication task must be in the RUNNING state. By default, the operator waits until every requested operation completes. With data-reload, it waits for TableState to reach Table completed. With validate-only, it waits for ValidationState to reach Validated and fails if DMS reports mismatched or suspended records, a table error, or another terminal validation failure. The first waiter poll runs immediately after the request returns. Set deferrable=True to release the worker slot while waiting, or set wait_for_completion=False to return the replication task ARN immediately. Use waiter_delay and waiter_max_attempts to control subsequent polls for each table. AWS DMS accepts up to 10 unique tables per request and supports tasks using the full-load or full-load-and-cdc migration type. DMS applies the task’s TargetTablePrepMode setting before reloading each table; when it is DO_NOTHING, truncate the target table manually before reloading. See Reloading tables during a task for details.

tests/system/amazon/aws/example_dms.py[source]

reload_tables = DmsReloadTablesOperator(
    task_id="reload_tables",
    replication_task_arn=task_arn,
    tables_to_reload=[{"SchemaName": "public", "TableName": rds_table_name}],
    reload_option="data-reload",
    wait_for_completion=True,
    deferrable=True,
)
revalidate_tables = DmsReloadTablesOperator(
    task_id="revalidate_tables",
    replication_task_arn=task_arn,
    tables_to_reload=[{"SchemaName": "public", "TableName": rds_table_name}],
    reload_option="validate-only",
    wait_for_completion=True,
    deferrable=True,
)

Get details of replication tasks¶

To retrieve the details for a list of replication tasks you can use DmsDescribeTasksOperator.

tests/system/amazon/aws/example_dms.py[source]

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,
)

Stop a replication task¶

To stop a replication task you can use DmsStopTaskOperator.

tests/system/amazon/aws/example_dms.py[source]

stop_task = DmsStopTaskOperator(
    task_id="stop_task",
    replication_task_arn=task_arn,
)

Delete a replication task¶

To delete a replication task you can use DmsDeleteTaskOperator.

tests/system/amazon/aws/example_dms.py[source]

delete_task = DmsDeleteTaskOperator(
    task_id="delete_task",
    replication_task_arn=task_arn,
)

Create a serverless replication config¶

To create a serverless replication config use DmsCreateReplicationConfigOperator.

tests/system/amazon/aws/example_dms_serverless.py[source]

create_replication_config = DmsCreateReplicationConfigOperator(
    task_id="create_replication_config",
    replication_config_id=replication_id,
    source_endpoint_arn=create_assets["source_endpoint_arn"],
    target_endpoint_arn=create_assets["target_endpoint_arn"],
    compute_config={
        "MaxCapacityUnits": 4,
        "MinCapacityUnits": 1,
        "MultiAZ": False,
        "ReplicationSubnetGroupId": "default",
    },
    replication_type="full-load",
    table_mappings=json.dumps(table_mappings),
)

Describe a serverless replication config¶

To describe a serverless replication config use DmsDescribeReplicationConfigsOperator.

tests/system/amazon/aws/example_dms_serverless.py[source]

describe_replication_configs = DmsDescribeReplicationConfigsOperator(
    task_id="describe_replication_configs",
)

Start a serverless replication¶

To start a serverless replication use DmsStartReplicationOperator.

tests/system/amazon/aws/example_dms_serverless.py[source]

replicate = DmsStartReplicationOperator(
    task_id="replicate",
    replication_config_arn="{{ task_instance.xcom_pull(task_ids='create_replication_config', key='return_value') }}",
    replication_start_type="start-replication",
    wait_for_completion=True,
    waiter_delay=60,
    waiter_max_attempts=200,
)

Stop a serverless replication¶

To stop a serverless replication use DmsStopReplicationOperator.

tests/system/amazon/aws/example_dms_serverless.py[source]

stop_replication = DmsStopReplicationOperator(
    task_id="stop_replication",
    replication_config_arn="{{ task_instance.xcom_pull(task_ids='create_replication_config', key='return_value') }}",
    wait_for_completion=True,
    waiter_delay=120,
    waiter_max_attempts=200,
)

Get the status of a serverless replication¶

To get the status of a serverless replication use DmsDescribeReplicationsOperator.

tests/system/amazon/aws/example_dms_serverless.py[source]

describe_replications = DmsDescribeReplicationsOperator(
    task_id="describe_replications",
)

Delete a serverless replication configuration¶

To delete a serverless replication config use DmsDeleteReplicationConfigOperator.

tests/system/amazon/aws/example_dms_serverless.py[source]

delete_replication_config = DmsDeleteReplicationConfigOperator(
    task_id="delete_replication_config",
    waiter_max_attempts=200,
    replication_config_arn="{{ task_instance.xcom_pull(task_ids='create_replication_config', key='return_value') }}",
)

Sensors¶

Wait for a replication task to complete¶

To check the state of a replication task until it is completed, you can use DmsTaskCompletedSensor.

tests/system/amazon/aws/example_dms.py[source]

await_task_stop = DmsTaskCompletedSensor(
    task_id="await_task_stop",
    replication_task_arn=task_arn,
)

Reference¶

AWS boto3 library documentation for DMS