shivaam commented on code in PR #64274: URL: https://github.com/apache/airflow/pull/64274#discussion_r3283419523
########## providers/amazon/src/airflow/providers/amazon/aws/operators/neptune_analytics.py: ########## @@ -0,0 +1,1006 @@ +# +# Licensed to the Apache Software Foundation (ASF) under one +# or more contributor license agreements. See the NOTICE file +# distributed with this work for additional information +# regarding copyright ownership. The ASF licenses this file +# to you under the Apache License, Version 2.0 (the +# "License"); you may not use this file except in compliance +# with the License. You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, +# software distributed under the License is distributed on an +# "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY +# KIND, either express or implied. See the License for the +# specific language governing permissions and limitations +# under the License. +from __future__ import annotations + +from collections.abc import Sequence +from typing import TYPE_CHECKING, Any + +from botocore.exceptions import ClientError + +from airflow.providers.amazon.aws.hooks.neptune_analytics import NeptuneAnalyticsHook +from airflow.providers.amazon.aws.links.ec2 import VpcEndpointLink +from airflow.providers.amazon.aws.links.neptune_analytics import NeptuneGraphLink, NeptuneImportTaskLink +from airflow.providers.amazon.aws.operators.base_aws import AwsBaseOperator +from airflow.providers.amazon.aws.triggers.neptune_analytics import ( + NeptuneGraphAvailableTrigger, + NeptuneGraphDeletedTrigger, + NeptuneGraphPrivateEndpointAvailableTrigger, + NeptuneGraphPrivateEndpointDeletedTrigger, + NeptuneImportTaskCancelledTrigger, + NeptuneImportTaskCompleteTrigger, +) +from airflow.providers.amazon.aws.utils.mixins import aws_template_fields +from airflow.providers.common.compat.sdk import conf + +if TYPE_CHECKING: + from airflow.sdk import Context + +from airflow.providers.amazon.aws.exceptions import ( + NeptuneGraphCreationFailedError, + NeptuneGraphDeletionFailedError, + NeptuneImportTaskCancellationFailedError, + NeptunePrivateEndpointCreationFailedError, + NeptunePrivateEndpointDeletionFailedError, +) + + +class NeptuneCreateGraphOperator(AwsBaseOperator[NeptuneAnalyticsHook]): + """ + Creates an empty Amazon Neptune Graph database. + + Neptune Analytics is a memory-optimized graph database engine for analytics. With Neptune Analytics, you can get insights and find trends by processing large amounts of graph data in seconds. + + .. seealso:: + For more information on how to use this operator, take a look at the guide: + :ref:`howto/operator:NeptuneCreateGraphOperator` + + :param graph_name: Name of Neptune graph to create + :param vector_search_config: Specifies the number of dimensions for vector embeddings that will be loaded into the graph. + :param provisioned_memory: The provisioned memory-optimized Neptune Capacity Units (m-NCUs) to use for the graph. + :param public_connectivity: Specifies whether or not the graph can be reachable over the internet. + :param replica_count: The number of replicas in other AZs. + :param deletion_protection: Indicates whether or not to enable deletion protection on the graph. + The graph can't be deleted when deletion protection is enabled. + :param kms_key_id: Specifies a KMS key to use to encrypt data in the new graph. + :param tags: Specifies metadata tags to add to the graph. + :param wait_for_completion: Whether to wait for the graph to start. (default: True) + :param deferrable: If True, the operator will wait asynchronously for the graph 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 graph id + """ + + aws_hook_class = NeptuneAnalyticsHook + template_fields: Sequence[str] = aws_template_fields( + "graph_name", "vector_search_config", "provisioned_memory" + ) + + template_fields_renderers = { + "vector_search_config": "json", + } + + operator_extra_links = (NeptuneGraphLink(),) + + def __init__( + self, + graph_name: str, + vector_search_config: dict, + provisioned_memory: int, + public_connectivity: bool | None = None, + replica_count: int | None = None, + deletion_protection: bool = False, + kms_key_id: str | None = None, + tags: dict | None = None, + 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.graph_name = graph_name + self.vector_search_config = vector_search_config + self.replica_count = replica_count + self.provisioned_memory = provisioned_memory + self.public_connectivity = public_connectivity + self.deletion_protect = deletion_protection + self.kms_key = kms_key_id + self.tags = tags + self.wait_for_completion = wait_for_completion + self.deferrable = deferrable + self.waiter_delay = waiter_delay + self.waiter_max_attempts = waiter_max_attempts + + def execute(self, context: Context) -> dict: + self.log.info("Creating graph %s", self.graph_name) + + create_params = { + "graphName": self.graph_name, + "vectorSearchConfiguration": self.vector_search_config, + "provisionedMemory": self.provisioned_memory, + **{ + k: v + for k, v in { + "replicaCount": self.replica_count, + "publicConnectivity": self.public_connectivity, + "deletionProtection": self.deletion_protect, + "kmsKeyIdentifier": self.kms_key, + "tags": self.tags, + }.items() + if v is not None + }, + } + + response = self.hook.conn.create_graph(**create_params) + + self.log.info("Graph %s in status %s", self.graph_name, response.get("status", "Unknown")) + self.graph_id = response.get("id", None) + + graph_url = NeptuneGraphLink.format_str.format( + graph_id=self.graph_id, + aws_domain=NeptuneGraphLink.get_aws_domain(self.hook.conn_partition), + region_name=self.hook.conn_region_name, + ) + + NeptuneGraphLink.persist( + context=context, + operator=self, + region_name=self.hook.conn_region_name, + aws_partition=self.hook.conn_partition, + graph_id=self.graph_id, + ) + self.log.info("You can view this Neptune Graph at : %s", graph_url) + + if self.deferrable: + self.log.info("Deferring until graph %s is available", self.graph_id) + self.defer( + trigger=NeptuneGraphAvailableTrigger( + aws_conn_id=self.aws_conn_id, + graph_id=self.graph_id, + waiter_delay=self.waiter_delay, + waiter_max_attempts=self.waiter_max_attempts, + ), + method_name="execute_complete", + ) + + if self.wait_for_completion: + self.log.info("Waiting until graph %s is available", self.graph_id) + self.hook.get_waiter("graph_available").wait( + graphIdentifier=self.graph_id, + WaiterConfig={"Delay": self.waiter_delay, "MaxAttempts": self.waiter_max_attempts}, + ) + + return {"graph_id": self.graph_id} + + def execute_complete(self, context: Context, event: dict[str, Any] | None = None) -> dict[str, Any]: + if event is None: + raise NeptuneGraphCreationFailedError( + "No event received while waiting for Neptune graph creation to complete." + ) + + if event.get("status") != "success": + raise NeptuneGraphCreationFailedError( + event.get( + "message", + f"Neptune graph {self.graph_id} creation did not complete successfully: {event}", + ) + ) + + self.log.info("Neptune graph %s complete", self.graph_id) + + return {"graph_id": self.graph_id} + + +class NeptuneCreatePrivateGraphEndpointOperator(AwsBaseOperator[NeptuneAnalyticsHook]): + """ + Creates a Neptune Graph private endpoint. + + .. seealso:: + For more information on how to use this operator, take a look at the guide: + :ref:`howto/operator:NeptuneCreatePrivateGraphEndpointOperator` + + :param graph_identifier: Neptune Graph id + :param vpc_id: VPC to create endpoint in + :param subnet_ids: Subnets in which private graph endpoint ENIs are created + :param vpc_security_group_ids: Security groups to be attached to the private graph endpoint + :param wait_for_completion: Whether to wait for the endpoint to be available. (default: True) + :param deferrable: If True, the operator will wait asynchronously for the endpoint to become available. + 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 graph id + """ + + aws_hook_class = NeptuneAnalyticsHook + template_fields: Sequence[str] = aws_template_fields( + "graph_identifier", "vpc_id", "subnet_ids", "vpc_security_group_ids" + ) + + def __init__( + self, + graph_identifier: str, + vpc_id: str | None = None, + subnet_ids: list[str] | None = None, + vpc_security_group_ids: list[str] | None = None, + 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.graph_identifier = graph_identifier + self.vpc_id = vpc_id + self.subnet_ids = subnet_ids + self.vpc_security_group_ids = vpc_security_group_ids + self.wait_for_completion = wait_for_completion + self.deferrable = deferrable + self.waiter_delay = waiter_delay + self.waiter_max_attempts = waiter_max_attempts + + def execute(self, context: Context) -> dict: + self.log.info("Creating private endpoint for graph %s", self.graph_identifier) + + create_params = { + "graphIdentifier": self.graph_identifier, + **{ + k: v + for k, v in { + "vpcId": self.vpc_id, + "subnetIds": self.subnet_ids, + "vpcSecurityGroupIds": self.vpc_security_group_ids, + }.items() + if v is not None + }, + } + + # create the endpoint + + result = self.hook.conn.create_private_graph_endpoint(**create_params) + status = result.get("status", "Unknown") + + self.log.info("Status of endpoint: %s", status) + + if status in ["FAILED"]: + raise NeptunePrivateEndpointCreationFailedError( + f"Private endpoint failed to create for graph {self.graph_identifier}" + ) + + # if VPC not provided, use the one that is returned, which is the default VPC. Required for the waiter + self.vpc_id = result.get("vpcId", self.vpc_id) + + if self.deferrable: + self.log.info("Deferring until endpoint is available") + self.defer( + trigger=NeptuneGraphPrivateEndpointAvailableTrigger( + aws_conn_id=self.aws_conn_id, + graph_id=self.graph_identifier, + vpc_id=self.vpc_id, + waiter_delay=self.waiter_delay, + waiter_max_attempts=self.waiter_max_attempts, + ), + method_name="execute_complete", + ) + + if self.wait_for_completion: + self.log.info("Waiting until endpoint is available") + self.hook.get_waiter("private_graph_endpoint_available").wait( + graphIdentifier=self.graph_identifier, + vpcId=self.vpc_id, + WaiterConfig={"Delay": self.waiter_delay, "MaxAttempts": self.waiter_max_attempts}, + ) + + endpoint_id = self._get_graph_endpoint_id() + + endpoint_url = VpcEndpointLink.format_str.format( + endpoint_id=endpoint_id, + aws_domain=VpcEndpointLink.get_aws_domain(self.hook.conn_partition), + region_name=self.hook.conn_region_name, + ) + + VpcEndpointLink.persist( + context=context, + operator=self, + region_name=self.hook.conn_region_name, + aws_partition=self.hook.conn_partition, + endpoint_id=endpoint_id, + ) + self.log.info("You can view this private endpoint at : %s", endpoint_url) + + return {"vpc_endpoint_id": endpoint_id, "graph_id": self.graph_identifier, "vpc_id": self.vpc_id} + + def _get_graph_endpoint_id(self): + """Return the vpc endpoint id for this graph.""" + result = self.hook.conn.get_private_graph_endpoint( + graphIdentifier=self.graph_identifier, vpcId=self.vpc_id + ) + return result.get("vpcEndpointId") + + def execute_complete(self, context: Context, event: dict[str, Any] | None = None) -> dict[str, Any]: + vpc_endpoint_id = self._get_graph_endpoint_id() + if event: + status = event["status"] + if status.lower() != "success": + raise NeptunePrivateEndpointCreationFailedError("Endpoint failed to create") + + return {"vpc_endpoint_id": vpc_endpoint_id, "graph_id": self.graph_identifier, "vpc_id": self.vpc_id} + + +class NeptuneDeletePrivateGraphEndpointOperator(AwsBaseOperator[NeptuneAnalyticsHook]): + """ + Deletes a Neptune Graph private endpoint. + + .. seealso:: + For more information on how to use this operator, take a look at the guide: + :ref:`howto/operator:NeptuneDeletePrivateGraphEndpointOperator` + + :param graph_identifier: Neptune Graph id + :param vpc_id: VPC where endpoint resides + :param wait_for_completion: Whether to wait for the endpoint to be deleted. (default: True) + :param deferrable: If True, the operator will wait asynchronously for the endpoint to be deleted. + 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 graph id + """ + + aws_hook_class = NeptuneAnalyticsHook + template_fields: Sequence[str] = aws_template_fields("graph_identifier", "vpc_id") + + def __init__( + self, + graph_identifier: str, + vpc_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.graph_identifier = graph_identifier + self.vpc_id = vpc_id + self.wait_for_completion = wait_for_completion + self.deferrable = deferrable + self.waiter_delay = waiter_delay + self.waiter_max_attempts = waiter_max_attempts + + def execute(self, context: Context) -> None: + self.log.info("Deleting private endpoint for graph %s", self.graph_identifier) + + result = self.hook.conn.delete_private_graph_endpoint( + graphIdentifier=self.graph_identifier, vpcId=self.vpc_id + ) + + status = result.get("status") + endpoint_id = result.get("vpcEndpointId") + + if status == "FAILED": + raise NeptunePrivateEndpointDeletionFailedError( + f"Failed to delete private endpoint {endpoint_id}" + ) + + if self.deferrable: + self.log.info("Deferring until endpoint %s is deleted", endpoint_id) + self.defer( + trigger=NeptuneGraphPrivateEndpointDeletedTrigger( + aws_conn_id=self.aws_conn_id, + graph_id=self.graph_identifier, + vpc_id=self.vpc_id, + endpoint_id=endpoint_id, + waiter_delay=self.waiter_delay, + waiter_max_attempts=self.waiter_max_attempts, + ), + method_name="execute_complete", + ) + if self.wait_for_completion: + self.log.info("Waiting until endpoint %s is deleted", endpoint_id) + self.hook.get_waiter("private_graph_endpoint_deleted").wait( + graphIdentifier=self.graph_identifier, + vpcId=self.vpc_id, + WaiterConfig={"Delay": self.waiter_delay, "MaxAttempts": self.waiter_max_attempts}, + ) + self.log.info("Endpoint %s deleted", endpoint_id) + + def execute_complete(self, context: Context, event: dict[str, Any] | None = None) -> None: + vpc_endpoint_id = "" + + if event and (event.get("status") or "").lower() == "success": + vpc_endpoint_id = event.get("endpoint_id", "Unknown") + + self.log.info("Endpoint id %s deleted", vpc_endpoint_id) + else: + raise NeptunePrivateEndpointDeletionFailedError("Endpoint failed to delete.") + + +class NeptuneDeleteGraphOperator(AwsBaseOperator[NeptuneAnalyticsHook]): + """ + Deletes an Amazon Neptune Graph database. + + Neptune Analytics is a memory-optimized graph database engine for analytics. With Neptune Analytics, you can get insights and find trends by processing large amounts of graph data in seconds. + + .. seealso:: + For more information on how to use this operator, take a look at the guide: + :ref:`howto/operator:NeptuneDeleteGraphOperator` + + :param graph_id: Name of Neptune graph to delete + :param skip_snapshot: Determines whether a final graph snapshot is created before the graph is deleted. If true is specified, no graph snapshot is created. If false is specified, a graph snapshot is created before the graph is deleted. + :param wait_for_completion: Whether to wait for the graph to delete. (default: True) + :param deferrable: If True, the operator will wait asynchronously for the graph to be deleted. + 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 graph id + """ + + aws_hook_class = NeptuneAnalyticsHook + template_fields: Sequence[str] = aws_template_fields("graph_id", "skip_snapshot") + + def __init__( + self, + graph_id: str, + skip_snapshot: bool, + 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.graph_id = graph_id + self.skip_snapshot = skip_snapshot + self.wait_for_completion = wait_for_completion + self.deferrable = deferrable + self.waiter_delay = waiter_delay + self.waiter_max_attempts = waiter_max_attempts + + def execute(self, context: Context): + self.log.info("Deleting graph %s", self.graph_id) + + try: + self.hook.conn.delete_graph(graphIdentifier=self.graph_id, skipSnapshot=self.skip_snapshot) + except ClientError as e: + # if not found, just exit because there is nothing to delete + if e.response["Error"]["Code"] == "ResourceNotFoundException": + self.log.info("Graph %s not found. Nothing to delete", self.graph_id) + return + raise NeptuneGraphDeletionFailedError(e.response["Error"]) + + if self.deferrable: + self.log.info("Deferring until graph %s is deleted", self.graph_id) + self.defer( + trigger=NeptuneGraphDeletedTrigger( + aws_conn_id=self.aws_conn_id, + graph_id=self.graph_id, + waiter_delay=self.waiter_delay, + waiter_max_attempts=self.waiter_max_attempts, + ), + method_name="execute_complete", + ) + if self.wait_for_completion: + self.log.info("Waiting to delete %s", self.graph_id) + + self.hook.get_waiter("graph_deleted").wait( + graphIdentifier=self.graph_id, + WaiterConfig={"Delay": self.waiter_delay, "MaxAttempts": self.waiter_max_attempts}, + ) + + def execute_complete(self, context: Context, event: dict[str, Any] | None = None): + if event: + graph_id = event.get("graph_id", "Unknown") + + self.log.info("Neptune graph %s deleted", graph_id) + + +class NeptuneCreateGraphWithImportOperator(AwsBaseOperator[NeptuneAnalyticsHook]): + """ + Creates a Neptune Graph and imports data into it. + + Neptune Analytics is a memory-optimized graph database engine for analytics. With Neptune Analytics, + you can get insights and find trends by processing large amounts of graph data in seconds. + + .. seealso:: + For more information on how to use this operator, take a look at the guide: + :ref:`howto/operator:NeptuneCreateGraphWithImportOperator` + + :param graph_name: Name of Neptune graph to create + :param vector_search_config: Specifies the number of dimensions for vector embeddings that will be loaded into the graph. + :param source: The source from which to import data. Can be an S3 URI or Neptune database snapshot. + :param role_arn: The ARN of the IAM role that Neptune Analytics can assume to access the data source. + :param blank_node_handling: The method to handle blank nodes in the dataset. Options include 'convertToIri' or other handling strategies. + :param parquet_type: The type of Parquet files in the data source (if applicable). + :param format: The format of the data to be imported (e.g., 'csv', 'opencypher', 'ntriples', 'nquads', 'rdfxml', 'turtle'). + :param min_provisioned_memory: The minimum provisioned memory for the graph in GBs. + :param max_provisioned_memory: The maximum provisioned memory for the graph in GBs. + :param fail_on_error: If True, the import will fail if any errors are encountered. If False, the import will continue despite errors. + :param public_connectivity: Specifies whether or not the graph can be reachable over the internet. + :param replica_count: The number of replicas in other AZs. + :param deletion_protection: Indicates whether or not to enable deletion protection on the graph. + The graph can't be deleted when deletion protection is enabled. (default: False) + :param kms_key_id: Specifies a KMS key to use to encrypt data in the new graph. + :param tags: Specifies metadata tags to add to the graph. + :param import_options: Contains options for controlling the import process. + :param wait_for_completion: Whether to wait for the graph to be created and data imported. (default: True) + :param waiter_delay: Time in seconds to wait between status checks. (default: 30) + :param waiter_max_attempts: Maximum number of attempts to check for job completion. (default: 60) + :param deferrable: If True, the operator will wait asynchronously for the graph to be created and data imported. + This implies waiting for completion. This mode requires aiobotocore module to be installed. + (default: False) + :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 graph id + """ + + aws_hook_class = NeptuneAnalyticsHook + template_fields: Sequence[str] = aws_template_fields( + "graph_name", "vector_search_config", "source", "role_arn", "kms_key" + ) + + template_fields_renderers = { + "vector_search_config": "json", + } + + operator_extra_links = ( + NeptuneImportTaskLink(), + NeptuneGraphLink(), + ) + + def __init__( + self, + graph_name: str, + vector_search_config: dict, + source: str, + role_arn: str, + blank_node_handling: str | None = None, + parquet_type: str | None = None, + format: str | None = None, + min_provisioned_memory: int | None = None, + max_provisioned_memory: int | None = None, + fail_on_error: bool | None = None, + public_connectivity: bool | None = None, + replica_count: int | None = None, + deletion_protection: bool | None = None, + kms_key_id: str | None = None, + tags: dict | None = None, + import_options: dict | None = None, + 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.graph_name = graph_name + self.vector_search_config = vector_search_config + self.source = source + self.role_arn = role_arn + self.blank_node_handling = blank_node_handling + self.parquet_type = parquet_type + self.format = format + self.min_provisioned_memory = min_provisioned_memory + self.max_provisioned_memory = max_provisioned_memory + self.fail_on_error = fail_on_error + self.public_connectivity = public_connectivity + self.replica_count = replica_count + self.deletion_protect = deletion_protection + self.kms_key = kms_key_id + self.tags = tags + self.import_options = import_options + self.wait_for_completion = wait_for_completion + self.deferrable = deferrable + self.waiter_delay = waiter_delay + self.waiter_max_attempts = waiter_max_attempts + + def execute(self, context: Context) -> dict: + self.log.info("Creating graph %s with import", self.graph_name) + + # Build the import options + import_options = { + "neptune-analytics:blank-node-handling": self.blank_node_handling, + "neptune-analytics:parquet-type": self.parquet_type, + } + + # Remove None values from import_options + import_options = {k: v for k, v in import_options.items() if v is not None} + + # Merge with user-provided import_options + if self.import_options: + import_options.update(self.import_options) + + create_params = { + "graphName": self.graph_name, + "vectorSearchConfiguration": self.vector_search_config, + "source": self.source, + "roleArn": self.role_arn, + **{ + k: v + for k, v in { + "format": self.format, + "minProvisionedMemory": self.min_provisioned_memory, + "maxProvisionedMemory": self.max_provisioned_memory, + "failOnError": self.fail_on_error, + "replicaCount": self.replica_count, + "publicConnectivity": self.public_connectivity, + "deletionProtection": self.deletion_protect, + "kmsKeyIdentifier": self.kms_key, + "tags": self.tags, + "importOptions": import_options if import_options else None, + }.items() + if v is not None + }, + } + + response = self.hook.conn.create_graph_using_import_task(**create_params) + + self.log.info("Graph %s import task in status %s", self.graph_name, response.get("status", "Unknown")) + self.graph_id = response.get("graphId", None) + import_task_id = response.get("taskId") + + graph_url = NeptuneGraphLink.format_str.format( + graph_id=self.graph_id, + aws_domain=NeptuneGraphLink.get_aws_domain(self.hook.conn_partition), + region_name=self.hook.conn_region_name, + ) + + NeptuneGraphLink.persist( + context=context, + operator=self, + region_name=self.hook.conn_region_name, + aws_partition=self.hook.conn_partition, + graph_id=self.graph_id, + ) + + import_task_url = NeptuneImportTaskLink.format_str.format( + import_task_id=import_task_id, + aws_domain=NeptuneImportTaskLink.get_aws_domain(self.hook.conn_partition), + region_name=self.hook.conn_region_name, + ) + + NeptuneImportTaskLink.persist( + context=context, + operator=self, + region_name=self.hook.conn_region_name, + aws_partition=self.hook.conn_partition, + import_task_id=import_task_id, + ) + + self.log.info("You can view this import task at : %s", import_task_url) + + self.log.info("You can view this Neptune Graph at : %s", graph_url) + + if self.deferrable: + self.log.info("Deferring until graph %s is available", self.graph_id) + self.defer( + trigger=NeptuneGraphAvailableTrigger( + aws_conn_id=self.aws_conn_id, + graph_id=self.graph_id, + waiter_delay=self.waiter_delay, + waiter_max_attempts=self.waiter_max_attempts, + ), + method_name="defer_wait_for_task", + kwargs={"import_task_id": import_task_id}, + ) + + if self.wait_for_completion: + self.log.info("Waiting until graph %s is available", self.graph_id) + self.hook.get_waiter("graph_available").wait( + graphIdentifier=self.graph_id, + WaiterConfig={"Delay": self.waiter_delay, "MaxAttempts": self.waiter_max_attempts}, + ) + # Once the graph is available, wait for the task to complete + + self.log.info("Waiting for import task %s", import_task_id) + self.hook.get_waiter("import_task_successful").wait( + taskIdentifier=import_task_id, + WaiterConfig={"Delay": self.waiter_delay, "MaxAttempts": self.waiter_max_attempts}, + ) + + return {"graph_id": self.graph_id} + + def defer_wait_for_task( + self, context: Context, event: dict[str, Any] | None = None, import_task_id: str | None = None + ) -> None: + """Defers for import task completion.""" + if import_task_id: + self.log.info("Deferring for import task %s completion", import_task_id) + self.defer( + trigger=NeptuneImportTaskCompleteTrigger( + import_task_id=import_task_id, + waiter_delay=self.waiter_delay, + waiter_max_attempts=self.waiter_max_attempts, + aws_conn_id=self.aws_conn_id, + ), + method_name="execute_complete", + ) + + def execute_complete(self, context: Context, event: dict[str, Any] | None = None) -> dict[str, Any]: + if event is None or event.get("status") != "success": + message = (event or {}).get( + "message", f"Neptune graph {self.graph_id} import did not complete successfully" + ) + raise NeptuneGraphCreationFailedError(message) + self.log.info("Import complete for graph %s", self.graph_id) + return {"graph_id": self.graph_id} + + +class NeptuneStartImportTaskOperator(AwsBaseOperator[NeptuneAnalyticsHook]): + """ + Starts a bulk data import task to load data into an empty Neptune graph. + + .. seealso:: + For more information on how to use this operator, take a look at the guide: + :ref:`howto/operator:NeptuneStartImportTaskOperator` + + :param graph_identifier: Graph Id of target Neptune Graph + :param role_arn: IAM role ARN granting access to source data + :param source: URL identifying the source data location. + :param blank_node_handling: Method to handle blank nodes in dataset. + :param fail_on_error: If set to true, the task halts when an import error is encountered. If set to false, the task skips the data that caused the error and continues if possible. + :param format: Specifies the format of the Amazon S3 data to be imported. + :param import_options: Options on how to perform an import + :param parquet_type: Parquet type of import task + :param wait_for_completion: Whether to wait for the endpoint to be available. (default: True) + :param deferrable: If True, the operator will wait asynchronously for the endpoint to become available. + 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 graph id + """ + + aws_hook_class = NeptuneAnalyticsHook + template_fields: Sequence[str] = aws_template_fields( + "graph_identifier", "role_arn", "source", "import_options" + ) + template_fields_renderers = { + "import_options": "json", + } + operator_extra_links = (NeptuneImportTaskLink(),) + + def __init__( + self, + graph_identifier: str, + role_arn: str, + source: str, + blank_node_handling: str | None = None, + fail_on_error: bool = True, + format: str | None = None, + import_options: dict | None = None, + parquet_type: str | None = "COLUMNAR", + 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.graph_identifier = graph_identifier + self.role_arn = role_arn + self.source = source + self.blank_node_handling = blank_node_handling + self.fail_on_error = fail_on_error + self.format = format + self.import_options = import_options + self.parquet_type = parquet_type + self.wait_for_completion = wait_for_completion + self.waiter_delay = waiter_delay + self.waiter_max_attempts = waiter_max_attempts + self.deferrable = deferrable + + def execute(self, context: Context) -> dict: + self.log.info("Starting data import to graph %s", self.graph_identifier) + + create_params = { + "graphIdentifier": self.graph_identifier, + "roleArn": self.role_arn, + "source": self.source, + **{ + k: v + for k, v in { + "blankNodeHandling": self.blank_node_handling, + "failOnError": self.fail_on_error, + "format": self.format, + "importOptions": self.import_options, + "parquetType": self.parquet_type, + }.items() + if v is not None + }, + } + + response = self.hook.conn.start_import_task(**create_params) + import_task_id = response.get("taskId") + self.log.info("Import task %s started for graph %s", import_task_id, self.graph_identifier) + + # Create the console link + import_task_url = NeptuneImportTaskLink.format_str.format( + import_task_id=import_task_id, + aws_domain=NeptuneImportTaskLink.get_aws_domain(self.hook.conn_partition), + region_name=self.hook.conn_region_name, + ) + + NeptuneImportTaskLink.persist( + context=context, + operator=self, + region_name=self.hook.conn_region_name, + aws_partition=self.hook.conn_partition, + import_task_id=import_task_id, + ) + self.log.info("You can view this import task at : %s", import_task_url) + + if self.deferrable: + self.log.info("Deferring until import task %s completes", import_task_id) + self.defer( + trigger=NeptuneImportTaskCompleteTrigger( + import_task_id=import_task_id, + waiter_delay=self.waiter_delay, + waiter_max_attempts=self.waiter_max_attempts, + aws_conn_id=self.aws_conn_id, + ), + method_name="execute_complete", + ) + + if self.wait_for_completion: + self.log.info("Waiting for import task %s to complete", import_task_id) + self.hook.get_waiter("import_task_successful").wait( + taskIdentifier=import_task_id, + WaiterConfig={"Delay": self.waiter_delay, "MaxAttempts": self.waiter_max_attempts}, + ) + + return {"import_task_id": import_task_id, "graph_id": self.graph_identifier} + + def execute_complete(self, context: Context, event: dict[str, Any] | None = None) -> dict[str, Any]: + task_id = "" + if event: + task_id = event.get("import_task_id", "") Review Comment: same issue. I think we need to check if the trigger event has returned success or error.\ NeptuneCreateGraphOperator.execute_complete (line 190) and NeptuneCancelImportTaskOperator.execute_complete (line 991) already do the check correctly -- This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. To unsubscribe, e-mail: [email protected] For queries about this service, please contact Infrastructure at: [email protected]
