Source code for airflow.providers.google.cloud.sensors.bigtable
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"""This module contains Google Cloud Bigtable sensor."""
from __future__ import annotations
from typing import TYPE_CHECKING, Sequence
import google.api_core.exceptions
from google.cloud.bigtable import enums
from google.cloud.bigtable.table import ClusterState
from airflow.providers.google.cloud.hooks.bigtable import BigtableHook
from airflow.providers.google.cloud.links.bigtable import BigtableTablesLink
from airflow.providers.google.cloud.operators.bigtable import BigtableValidationMixin
from airflow.sensors.base import BaseSensorOperator
if TYPE_CHECKING:
from airflow.utils.context import Context
[docs]class BigtableTableReplicationCompletedSensor(BaseSensorOperator, 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
.. seealso::
For more information on how to use this operator, take a look at the guide:
:ref:`howto/operator:BigtableTableReplicationCompletedSensor`
:param instance_id: The ID of the Cloud Bigtable instance.
:param table_id: The ID of the table to check replication status.
:param project_id: Optional, the ID of the Google Cloud project.
:param impersonation_chain: 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).
"""
[docs] REQUIRED_ATTRIBUTES = ("instance_id", "table_id")
[docs] template_fields: Sequence[str] = (
"project_id",
"instance_id",
"table_id",
"impersonation_chain",
)
def __init__(
self,
*,
instance_id: str,
table_id: str,
project_id: str | None = None,
gcp_conn_id: str = "google_cloud_default",
impersonation_chain: str | Sequence[str] | None = None,
**kwargs,
) -> None:
self.project_id = project_id
self.instance_id = instance_id
self.table_id = table_id
self.gcp_conn_id = gcp_conn_id
self._validate_inputs()
self.impersonation_chain = impersonation_chain
super().__init__(**kwargs)
[docs] def poke(self, context: Context) -> bool:
hook = BigtableHook(
gcp_conn_id=self.gcp_conn_id,
impersonation_chain=self.impersonation_chain,
)
instance = hook.get_instance(project_id=self.project_id, instance_id=self.instance_id)
if not instance:
self.log.info("Dependency: instance '%s' does not exist.", self.instance_id)
return False
try:
cluster_states = hook.get_cluster_states_for_table(instance=instance, table_id=self.table_id)
except google.api_core.exceptions.NotFound:
self.log.info(
"Dependency: table '%s' does not exist in instance '%s'.", self.table_id, self.instance_id
)
return False
ready_state = ClusterState(enums.Table.ReplicationState.READY)
is_table_replicated = True
for cluster_id in cluster_states.keys():
if cluster_states[cluster_id] != ready_state:
self.log.info("Table '%s' is not yet replicated on cluster '%s'.", self.table_id, cluster_id)
is_table_replicated = False
if not is_table_replicated:
return False
self.log.info("Table '%s' is replicated.", self.table_id)
BigtableTablesLink.persist(context=context, task_instance=self)
return True