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Google Cloud Storage Operators

Cloud Storage allows world-wide storage and retrieval of any amount of data at any time. You can use Cloud Storage for a range of scenarios including serving website content, storing data for archival and disaster recovery, or distributing large data objects to users via direct download.

Prerequisite Tasks

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

• Select or create a Cloud Platform project using the Cloud Console.

• Enable billing for your project, as described in the Google Cloud documentation.

• Enable the API, as described in the Cloud Console documentation.

• Install API libraries via pip.

  pip install 'apache-airflow[google]'
  

  Detailed information is available for Installation.

• Setup a Google Cloud Connection.

Operators

GCSTimeSpanFileTransformOperator

Use the GCSTimeSpanFileTransformOperator to transform files that were modified in a specific time span (the data interval). The time span is defined by the time span’s start and end timestamps. If a DAG does not have a next DAG instance scheduled, the time span end infinite, meaning the operator processes all files older than data_interval_start.

tests/system/providers/google/cloud/gcs/example_gcs_transform_timespan.py

gcs_timespan_transform_files_task = GCSTimeSpanFileTransformOperator(
    task_id="gcs_timespan_transform_files",
    source_bucket=BUCKET_NAME_SRC,
    source_prefix=SOURCE_PREFIX,
    source_gcp_conn_id=SOURCE_GCP_CONN_ID,
    destination_bucket=BUCKET_NAME_DST,
    destination_prefix=DESTINATION_PREFIX,
    destination_gcp_conn_id=DESTINATION_GCP_CONN_ID,
    transform_script=["python", TRANSFORM_SCRIPT_PATH],
)

GCSBucketCreateAclEntryOperator

Creates a new ACL entry on the specified bucket.

For parameter definition, take a look at GCSBucketCreateAclEntryOperator

Using the operator

tests/system/providers/google/cloud/gcs/example_gcs_acl.py

gcs_bucket_create_acl_entry_task = GCSBucketCreateAclEntryOperator(
    bucket=BUCKET_NAME,
    entity=GCS_ACL_ENTITY,
    role=GCS_ACL_BUCKET_ROLE,
    task_id="gcs_bucket_create_acl_entry_task",
)

Templating

template_fields: Sequence[str] = (
    "bucket",
    "entity",
    "role",
    "user_project",
    "impersonation_chain",
)

More information

See Google Cloud Storage Documentation to create a new ACL entry for a bucket.

GCSObjectCreateAclEntryOperator

Creates a new ACL entry on the specified object.

For parameter definition, take a look at GCSObjectCreateAclEntryOperator

Using the operator

tests/system/providers/google/cloud/gcs/example_gcs_acl.py

gcs_object_create_acl_entry_task = GCSObjectCreateAclEntryOperator(
    bucket=BUCKET_NAME,
    object_name=FILE_NAME,
    entity=GCS_ACL_ENTITY,
    role=GCS_ACL_OBJECT_ROLE,
    task_id="gcs_object_create_acl_entry_task",
)

Templating

template_fields: Sequence[str] = (
    "bucket",
    "object_name",
    "entity",
    "generation",
    "role",
    "user_project",
    "impersonation_chain",
)

More information

See Google Cloud Storage insert documentation to create a ACL entry for ObjectAccess.

Deleting Bucket

Deleting Bucket allows you to remove bucket object from the Google Cloud Storage. It is performed through the GCSDeleteBucketOperator operator.

tests/system/providers/google/cloud/gcs/example_gcs_upload_download.py

delete_bucket = GCSDeleteBucketOperator(task_id="delete_bucket", bucket_name=BUCKET_NAME)

You can use Jinja templating with bucket_name, gcp_conn_id, impersonation_chain, user_project parameters which allows you to dynamically determine values.

Reference

For further information, look at:

• Client Library Documentation

• Product Documentation

Sensors

GCSObjectExistenceSensor

Use the GCSObjectExistenceSensor to wait (poll) for the existence of a file in Google Cloud Storage.

tests/system/providers/google/cloud/gcs/example_gcs_sensor.py

gcs_object_exists = GCSObjectExistenceSensor(
    bucket=BUCKET_NAME,
    object=FILE_NAME,
    task_id="gcs_object_exists_task",
)

Also you can use deferrable mode in this operator if you would like to free up the worker slots while the sensor is running.

tests/system/providers/google/cloud/gcs/example_gcs_sensor.py

gcs_object_exists_defered = GCSObjectExistenceSensor(
    bucket=BUCKET_NAME, object=FILE_NAME, task_id="gcs_object_exists_defered", deferrable=True
)

GCSObjectExistenceAsyncSensor

GCSObjectExistenceAsyncSensor is deprecated and will be removed in a future release. Please use GCSObjectExistenceSensor and use the deferrable mode in that operator.

tests/system/providers/google/cloud/gcs/example_gcs_sensor.py

gcs_object_exists_async = GCSObjectExistenceAsyncSensor(
    bucket=BUCKET_NAME,
    object=FILE_NAME,
    task_id="gcs_object_exists_task_async",
)

GCSObjectsWithPrefixExistenceSensor

Use the GCSObjectsWithPrefixExistenceSensor to wait (poll) for the existence of a file with a specified prefix in Google Cloud Storage.

tests/system/providers/google/cloud/gcs/example_gcs_sensor.py

gcs_object_with_prefix_exists = GCSObjectsWithPrefixExistenceSensor(
    bucket=BUCKET_NAME,
    prefix=FILE_NAME[:5],
    task_id="gcs_object_with_prefix_exists_task",
)

You can set the deferrable param to True if you want this sensor to run asynchronously, leading to more efficient utilization of resources in your Airflow deployment. However the triggerer component needs to be enabled for this functionality to work.

tests/system/providers/google/cloud/gcs/example_gcs_sensor.py

gcs_object_with_prefix_exists_async = GCSObjectsWithPrefixExistenceSensor(
    bucket=BUCKET_NAME,
    prefix=FILE_NAME[:5],
    task_id="gcs_object_with_prefix_exists_task_async",
    deferrable=True,
)

GCSUploadSessionCompleteSensor

Use the GCSUploadSessionCompleteSensor to check for a change in the number of files with a specified prefix in Google Cloud Storage.

tests/system/providers/google/cloud/gcs/example_gcs_sensor.py

gcs_upload_session_complete = GCSUploadSessionCompleteSensor(
    bucket=BUCKET_NAME,
    prefix=FILE_NAME,
    inactivity_period=15,
    min_objects=1,
    allow_delete=True,
    previous_objects=set(),
    task_id="gcs_upload_session_complete_task",
)

You can set the parameter deferrable to True if you want the worker slots to be freed up while sensor is running.

tests/system/providers/google/cloud/gcs/example_gcs_sensor.py

gcs_upload_session_async_complete = GCSUploadSessionCompleteSensor(
    bucket=BUCKET_NAME,
    prefix=FILE_NAME,
    inactivity_period=15,
    min_objects=1,
    allow_delete=True,
    previous_objects=set(),
    task_id="gcs_upload_session_async_complete",
    deferrable=True,
)

GCSObjectUpdateSensor

Use the GCSObjectUpdateSensor to check if an object is updated in Google Cloud Storage.

tests/system/providers/google/cloud/gcs/example_gcs_sensor.py

gcs_update_object_exists = GCSObjectUpdateSensor(
    bucket=BUCKET_NAME,
    object=FILE_NAME,
    task_id="gcs_object_update_sensor_task",
)

You can set the deferrable param to True if you want this sensor to run asynchronously, leading to efficient utilization of resources in your Airflow deployment. However the triggerer component needs to be enabled for this functionality to work.

tests/system/providers/google/cloud/gcs/example_gcs_sensor.py

gcs_update_object_exists_async = GCSObjectUpdateSensor(
    bucket=BUCKET_NAME, object=FILE_NAME, task_id="gcs_object_update_sensor_task_async", deferrable=True
)

More information

Sensors have different modes that determine the behaviour of resources while the task is executing. See Airflow sensors documentation for best practices when using sensors.

Reference

For further information, look at:

• Client Library Documentation

• Product Documentation

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