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from __future__ import annotations
from typing import TYPE_CHECKING, Any, Sequence
from botocore.exceptions import ClientError
from airflow.configuration import conf
from airflow.exceptions import AirflowException
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,
NeptuneClusterInstancesAvailableTrigger,
NeptuneClusterStoppedTrigger,
)
from airflow.providers.amazon.aws.utils.mixins import aws_template_fields
if TYPE_CHECKING:
from airflow.utils.context import Context
[docs]def handle_waitable_exception(
operator: NeptuneStartDbClusterOperator | NeptuneStopDbClusterOperator, err: str
):
"""
Handle client exceptions for invalid cluster or invalid instance status that are temporary.
After status change, it's possible to retry. Waiter will handle terminal status.
"""
code = err
if code in ("InvalidDBInstanceStateFault", "InvalidDBInstanceState"):
if operator.deferrable:
operator.log.info("Deferring until instances become available: %s", operator.cluster_id)
operator.defer(
trigger=NeptuneClusterInstancesAvailableTrigger(
aws_conn_id=operator.aws_conn_id,
db_cluster_id=operator.cluster_id,
region_name=operator.region_name,
botocore_config=operator.botocore_config,
verify=operator.verify,
),
method_name="execute",
)
else:
operator.log.info("Need to wait for instances to become available: %s", operator.cluster_id)
operator.hook.wait_for_cluster_instance_availability(cluster_id=operator.cluster_id)
if code in ["InvalidClusterState", "InvalidDBClusterStateFault"]:
if operator.deferrable:
operator.log.info("Deferring until cluster becomes available: %s", operator.cluster_id)
operator.defer(
trigger=NeptuneClusterAvailableTrigger(
aws_conn_id=operator.aws_conn_id,
db_cluster_id=operator.cluster_id,
region_name=operator.region_name,
botocore_config=operator.botocore_config,
verify=operator.verify,
),
method_name="execute",
)
else:
operator.log.info("Need to wait for cluster to become available: %s", operator.cluster_id)
operator.hook.wait_for_cluster_availability(operator.cluster_id)
[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.waiter_delay = waiter_delay
self.waiter_max_attempts = waiter_max_attempts
[docs] def execute(self, context: Context, event: dict[str, Any] | None = None, **kwargs) -> 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}
elif status.lower() in NeptuneHook.ERROR_STATES:
# some states will not allow you to start the cluster
self.log.error(
"Neptune cluster %s is in error state %s and cannot be started", self.cluster_id, status
)
raise AirflowException(f"Neptune cluster {self.cluster_id} is in error state {status}")
"""
A cluster and its instances must be in a valid state to send the start request.
This loop covers the case where the cluster is not available and also the case where
the cluster is available, but one or more of the instances are in an invalid state.
If either are in an invalid state, wait for the availability and retry.
Let the waiters handle retries and detecting the error states.
"""
try:
self.hook.conn.start_db_cluster(DBClusterIdentifier=self.cluster_id)
except ClientError as ex:
code = ex.response["Error"]["Code"]
self.log.warning("Received client error when attempting to start the cluster: %s", code)
if code in ["InvalidDBInstanceState", "InvalidClusterState", "InvalidDBClusterStateFault"]:
handle_waitable_exception(operator=self, err=code)
else:
# re raise for any other type of client error
raise
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.waiter_delay,
waiter_max_attempts=self.waiter_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.waiter_delay, self.waiter_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.waiter_delay = waiter_delay
self.waiter_max_attempts = waiter_max_attempts
[docs] def execute(self, context: Context, event: dict[str, Any] | None = None, **kwargs) -> dict[str, str]:
self.log.info("Stopping Neptune cluster: %s", self.cluster_id)
# Check to make sure the cluster is not already stopped or that its not in a bad state
status = self.hook.get_cluster_status(self.cluster_id)
self.log.info("Current status: %s", status)
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}
elif status.lower() in NeptuneHook.ERROR_STATES:
# some states will not allow you to stop the cluster
self.log.error(
"Neptune cluster %s is in error state %s and cannot be stopped", self.cluster_id, status
)
raise AirflowException(f"Neptune cluster {self.cluster_id} is in error state {status}")
"""
A cluster and its instances must be in a valid state to send the stop request.
This loop covers the case where the cluster is not available and also the case where
the cluster is available, but one or more of the instances are in an invalid state.
If either are in an invalid state, wait for the availability and retry.
Let the waiters handle retries and detecting the error states.
"""
try:
self.hook.conn.stop_db_cluster(DBClusterIdentifier=self.cluster_id)
# cluster must be in available state to stop it
except ClientError as ex:
code = ex.response["Error"]["Code"]
self.log.warning("Received client error when attempting to stop the cluster: %s", code)
# these can be handled by a waiter
if code in [
"InvalidDBInstanceState",
"InvalidDBInstanceStateFault",
"InvalidClusterState",
"InvalidDBClusterStateFault",
]:
handle_waitable_exception(self, code)
else:
# re raise for any other type of client error
raise
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.waiter_delay,
waiter_max_attempts=self.waiter_max_attempts,
),
method_name="execute_complete",
)
elif self.wait_for_completion:
self.log.info("Waiting for Neptune cluster %s to stop.", self.cluster_id)
self.hook.wait_for_cluster_stopped(self.cluster_id, self.waiter_delay, self.waiter_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 = ""
self.log.info(event)
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}