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from __future__ import annotations
from typing import TYPE_CHECKING, Any, Sequence
from airflow.configuration import conf
from airflow.providers.amazon.aws.hooks.neptune import NeptuneHook
from airflow.providers.amazon.aws.operators.base_aws import AwsBaseOperator
from airflow.providers.amazon.aws.triggers.neptune import (
NeptuneClusterAvailableTrigger,
NeptuneClusterStoppedTrigger,
)
from airflow.providers.amazon.aws.utils.mixins import aws_template_fields
if TYPE_CHECKING:
from airflow.utils.context import Context
[docs]class NeptuneStartDbClusterOperator(AwsBaseOperator[NeptuneHook]):
"""Starts an Amazon Neptune DB cluster.
Amazon Neptune Database is a serverless graph database designed for superior scalability
and availability. Neptune Database provides built-in security, continuous backups, and
integrations with other AWS services
.. seealso::
For more information on how to use this operator, take a look at the guide:
:ref:`howto/operator:NeptuneStartDbClusterOperator`
:param db_cluster_id: The DB cluster identifier of the Neptune DB cluster to be started.
:param wait_for_completion: Whether to wait for the cluster to start. (default: True)
:param deferrable: If True, the operator will wait asynchronously for the cluster to start.
This implies waiting for completion. This mode requires aiobotocore module to be installed.
(default: False)
:param waiter_delay: Time in seconds to wait between status checks.
:param waiter_max_attempts: Maximum number of attempts to check for job completion.
:param aws_conn_id: The Airflow connection used for AWS credentials.
If this is ``None`` or empty then the default boto3 behaviour is used. If
running Airflow in a distributed manner and aws_conn_id is None or
empty, then default boto3 configuration would be used (and must be
maintained on each worker node).
:param region_name: AWS region_name. If not specified then the default boto3 behaviour is used.
:param botocore_config: Configuration dictionary (key-values) for botocore client. See:
https://botocore.amazonaws.com/v1/documentation/api/latest/reference/config.html
:return: dictionary with Neptune cluster id
"""
[docs] aws_hook_class = NeptuneHook
[docs] template_fields: Sequence[str] = aws_template_fields("cluster_id")
def __init__(
self,
db_cluster_id: str,
wait_for_completion: bool = True,
waiter_delay: int = 30,
waiter_max_attempts: int = 60,
deferrable: bool = conf.getboolean("operators", "default_deferrable", fallback=False),
**kwargs,
):
super().__init__(**kwargs)
self.cluster_id = db_cluster_id
self.wait_for_completion = wait_for_completion
self.deferrable = deferrable
self.delay = waiter_delay
self.max_attempts = waiter_max_attempts
[docs] def execute(self, context: Context) -> dict[str, str]:
self.log.info("Starting Neptune cluster: %s", self.cluster_id)
# Check to make sure the cluster is not already available.
status = self.hook.get_cluster_status(self.cluster_id)
if status.lower() in NeptuneHook.AVAILABLE_STATES:
self.log.info("Neptune cluster %s is already available.", self.cluster_id)
return {"db_cluster_id": self.cluster_id}
resp = self.hook.conn.start_db_cluster(DBClusterIdentifier=self.cluster_id)
status = resp.get("DBClusters", {}).get("Status", "Unknown")
if self.deferrable:
self.log.info("Deferring for cluster start: %s", self.cluster_id)
self.defer(
trigger=NeptuneClusterAvailableTrigger(
aws_conn_id=self.aws_conn_id,
db_cluster_id=self.cluster_id,
waiter_delay=self.delay,
waiter_max_attempts=self.max_attempts,
),
method_name="execute_complete",
)
elif self.wait_for_completion:
self.log.info("Waiting for Neptune cluster %s to start.", self.cluster_id)
self.hook.wait_for_cluster_availability(self.cluster_id, self.delay, self.max_attempts)
return {"db_cluster_id": self.cluster_id}
[docs] def execute_complete(self, context: Context, event: dict[str, Any] | None = None) -> dict[str, str]:
status = ""
cluster_id = ""
if event:
status = event.get("status", "")
cluster_id = event.get("cluster_id", "")
self.log.info("Neptune cluster %s available with status: %s", cluster_id, status)
return {"db_cluster_id": cluster_id}
[docs]class NeptuneStopDbClusterOperator(AwsBaseOperator[NeptuneHook]):
"""
Stops an Amazon Neptune DB cluster.
Amazon Neptune Database is a serverless graph database designed for superior scalability
and availability. Neptune Database provides built-in security, continuous backups, and
integrations with other AWS services
.. seealso::
For more information on how to use this operator, take a look at the guide:
:ref:`howto/operator:NeptuneStartDbClusterOperator`
:param db_cluster_id: The DB cluster identifier of the Neptune DB cluster to be stopped.
:param wait_for_completion: Whether to wait for cluster to stop. (default: True)
:param deferrable: If True, the operator will wait asynchronously for the cluster to stop.
This implies waiting for completion. This mode requires aiobotocore module to be installed.
(default: False)
:param waiter_delay: Time in seconds to wait between status checks.
:param waiter_max_attempts: Maximum number of attempts to check for job completion.
:param aws_conn_id: The Airflow connection used for AWS credentials.
If this is ``None`` or empty then the default boto3 behaviour is used. If
running Airflow in a distributed manner and aws_conn_id is None or
empty, then default boto3 configuration would be used (and must be
maintained on each worker node).
:param region_name: AWS region_name. If not specified then the default boto3 behaviour is used.
:param botocore_config: Configuration dictionary (key-values) for botocore client. See:
https://botocore.amazonaws.com/v1/documentation/api/latest/reference/config.html
:return: dictionary with Neptune cluster id
"""
[docs] aws_hook_class = NeptuneHook
[docs] template_fields: Sequence[str] = aws_template_fields("cluster_id")
def __init__(
self,
db_cluster_id: str,
wait_for_completion: bool = True,
waiter_delay: int = 30,
waiter_max_attempts: int = 60,
deferrable: bool = conf.getboolean("operators", "default_deferrable", fallback=False),
**kwargs,
):
super().__init__(**kwargs)
self.cluster_id = db_cluster_id
self.wait_for_completion = wait_for_completion
self.deferrable = deferrable
self.delay = waiter_delay
self.max_attempts = waiter_max_attempts
[docs] def execute(self, context: Context) -> dict[str, str]:
self.log.info("Stopping Neptune cluster: %s", self.cluster_id)
# Check to make sure the cluster is not already stopped.
status = self.hook.get_cluster_status(self.cluster_id)
if status.lower() in NeptuneHook.STOPPED_STATES:
self.log.info("Neptune cluster %s is already stopped.", self.cluster_id)
return {"db_cluster_id": self.cluster_id}
resp = self.hook.conn.stop_db_cluster(DBClusterIdentifier=self.cluster_id)
status = resp.get("DBClusters", {}).get("Status", "Unknown")
if self.deferrable:
self.log.info("Deferring for cluster stop: %s", self.cluster_id)
self.defer(
trigger=NeptuneClusterStoppedTrigger(
aws_conn_id=self.aws_conn_id,
db_cluster_id=self.cluster_id,
waiter_delay=self.delay,
waiter_max_attempts=self.max_attempts,
),
method_name="execute_complete",
)
elif self.wait_for_completion:
self.log.info("Waiting for Neptune cluster %s to start.", self.cluster_id)
self.hook.wait_for_cluster_stopped(self.cluster_id, self.delay, self.max_attempts)
return {"db_cluster_id": self.cluster_id}
[docs] def execute_complete(self, context: Context, event: dict[str, Any] | None = None) -> dict[str, str]:
status = ""
cluster_id = ""
if event:
status = event.get("status", "")
cluster_id = event.get("cluster_id", "")
self.log.info("Neptune cluster %s stopped with status: %s", cluster_id, status)
return {"db_cluster_id": cluster_id}