Amazon Redshift (Cluster)¶

Amazon Redshift manages all the work of setting up, operating, and scaling a data warehouse: provisioning capacity, monitoring and backing up the cluster, and applying patches and upgrades to the Amazon Redshift engine. You can focus on using your data to acquire new insights for your business and customers.

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.

Operators¶

Create an Amazon Redshift cluster¶

To create an Amazon Redshift Cluster with the specified parameters you can use RedshiftCreateClusterOperator.

tests/system/providers/amazon/aws/example_redshift.py[source]

create_cluster = RedshiftCreateClusterOperator(
    task_id="create_cluster",
    cluster_identifier=redshift_cluster_identifier,
    vpc_security_group_ids=[security_group_id],
    cluster_subnet_group_name=cluster_subnet_group_name,
    publicly_accessible=False,
    cluster_type="single-node",
    node_type="dc2.large",
    master_username=DB_LOGIN,
    master_user_password=DB_PASS,
)

Resume an Amazon Redshift cluster¶

To resume a ‘paused’ Amazon Redshift cluster you can use RedshiftResumeClusterOperator You can also run this operator in deferrable mode by setting deferrable param to True. This will ensure that the task is deferred from the Airflow worker slot and polling for the task status happens on the trigger.

tests/system/providers/amazon/aws/example_redshift.py[source]

resume_cluster = RedshiftResumeClusterOperator(
    task_id="resume_cluster",
    cluster_identifier=redshift_cluster_identifier,
)

Pause an Amazon Redshift cluster¶

To pause an available Amazon Redshift cluster you can use RedshiftPauseClusterOperator. You can also run this operator in deferrable mode by setting deferrable param to True

tests/system/providers/amazon/aws/example_redshift.py[source]

pause_cluster = RedshiftPauseClusterOperator(
    task_id="pause_cluster",
    cluster_identifier=redshift_cluster_identifier,
)

Create an Amazon Redshift cluster snapshot¶

To create Amazon Redshift cluster snapshot you can use RedshiftCreateClusterSnapshotOperator

tests/system/providers/amazon/aws/example_redshift.py[source]

create_cluster_snapshot = RedshiftCreateClusterSnapshotOperator(
    task_id="create_cluster_snapshot",
    cluster_identifier=redshift_cluster_identifier,
    snapshot_identifier=redshift_cluster_snapshot_identifier,
    poll_interval=30,
    max_attempt=100,
    retention_period=1,
    wait_for_completion=True,
)

Delete an Amazon Redshift cluster snapshot¶

To delete Amazon Redshift cluster snapshot you can use RedshiftDeleteClusterSnapshotOperator

tests/system/providers/amazon/aws/example_redshift.py[source]

delete_cluster_snapshot = RedshiftDeleteClusterSnapshotOperator(
    task_id="delete_cluster_snapshot",
    cluster_identifier=redshift_cluster_identifier,
    snapshot_identifier=redshift_cluster_snapshot_identifier,
)

Delete an Amazon Redshift cluster¶

To delete an Amazon Redshift cluster you can use RedshiftDeleteClusterOperator. You can also run this operator in deferrable mode by setting deferrable param to True

tests/system/providers/amazon/aws/example_redshift.py[source]

delete_cluster = RedshiftDeleteClusterOperator(
    task_id="delete_cluster",
    cluster_identifier=redshift_cluster_identifier,
)

Sensors¶

Wait on an Amazon Redshift cluster state¶

To check the state of an Amazon Redshift Cluster until it reaches the target state or another terminal state you can use RedshiftClusterSensor.

tests/system/providers/amazon/aws/example_redshift.py[source]

wait_cluster_available = RedshiftClusterSensor(
    task_id="wait_cluster_available",
    cluster_identifier=redshift_cluster_identifier,
    target_status="available",
    poke_interval=15,
    timeout=60 * 30,
)

Reference¶

AWS boto3 library documentation for Amazon Redshift

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