airflow.providers.google.cloud.sensors.bigtable

This module contains Google Cloud Bigtable sensor.

Module Contents

class airflow.providers.google.cloud.sensors.bigtable.BigtableTableReplicationCompletedSensor(*, instance_id: str, table_id: str, project_id: Optional[str] = None, gcp_conn_id: str = 'google_cloud_default', impersonation_chain: Optional[Union[str, Sequence[str]]] = None, **kwargs)[source]

Bases: airflow.sensors.base.BaseSensorOperator, airflow.providers.google.cloud.operators.bigtable.BigtableValidationMixin

Sensor that waits for Cloud Bigtable table to be fully replicated to its clusters. No exception will be raised if the instance or the table does not exist.

For more details about cluster states for a table, have a look at the reference: https://googleapis.github.io/google-cloud-python/latest/bigtable/table.html#google.cloud.bigtable.table.Table.get_cluster_states

See also

For more information on how to use this operator, take a look at the guide: BigtableTableReplicationCompletedSensor

Parameters
  • instance_id (str) – The ID of the Cloud Bigtable instance.

  • table_id (str) – The ID of the table to check replication status.

  • project_id (str) – Optional, the ID of the Google Cloud project.

  • impersonation_chain (Union[str, Sequence[str]]) – Optional service account to impersonate using short-term credentials, or chained list of accounts required to get the access_token of the last account in the list, which will be impersonated in the request. If set as a string, the account must grant the originating account the Service Account Token Creator IAM role. If set as a sequence, the identities from the list must grant Service Account Token Creator IAM role to the directly preceding identity, with first account from the list granting this role to the originating account (templated).

REQUIRED_ATTRIBUTES = ['instance_id', 'table_id'][source]
template_fields = ['project_id', 'instance_id', 'table_id', 'impersonation_chain'][source]
poke(self, context: dict)[source]

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