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توضیحات

The CDK Construct Library for AWS::Neptune

ویژگی	مقدار
سیستم عامل	-
نام فایل	aws-cdk.aws-neptune-alpha-2.9.0a0
نام	aws-cdk.aws-neptune-alpha
نسخه کتابخانه	2.9.0a0
نگهدارنده	[]
ایمیل نگهدارنده	[]
نویسنده	Amazon Web Services
ایمیل نویسنده	-
آدرس صفحه اصلی	https://github.com/aws/aws-cdk
آدرس اینترنتی	https://pypi.org/project/aws-cdk.aws-neptune-alpha/
مجوز	Apache-2.0

# Amazon Neptune Construct Library --- ![cdk-constructs: Experimental](https://img.shields.io/badge/cdk--constructs-experimental-important.svg?style=for-the-badge) > The APIs of higher level constructs in this module are experimental and under active development. > They are subject to non-backward compatible changes or removal in any future version. These are > not subject to the [Semantic Versioning](https://semver.org/) model and breaking changes will be > announced in the release notes. This means that while you may use them, you may need to update > your source code when upgrading to a newer version of this package. ---  Amazon Neptune is a fast, reliable, fully managed graph database service that makes it easy to build and run applications that work with highly connected datasets. The core of Neptune is a purpose-built, high-performance graph database engine. This engine is optimized for storing billions of relationships and querying the graph with milliseconds latency. Neptune supports the popular graph query languages Apache TinkerPop Gremlin and W3C’s SPARQL, enabling you to build queries that efficiently navigate highly connected datasets. The `@aws-cdk/aws-neptune` package contains primitives for setting up Neptune database clusters and instances. ```python import aws_cdk.aws_neptune_alpha as neptune ``` ## Starting a Neptune Database To set up a Neptune database, define a `DatabaseCluster`. You must always launch a database in a VPC. ```python cluster = neptune.DatabaseCluster(self, "Database", vpc=vpc, instance_type=neptune.InstanceType.R5_LARGE ) ``` By default only writer instance is provisioned with this construct. ## Connecting To control who can access the cluster, use the `.connections` attribute. Neptune databases have a default port, so you don't need to specify the port: ```python cluster.connections.allow_default_port_from_any_ipv4("Open to the world") ``` The endpoints to access your database cluster will be available as the `.clusterEndpoint` and `.clusterReadEndpoint` attributes: ```python write_address = cluster.cluster_endpoint.socket_address ``` ## IAM Authentication You can also authenticate to a database cluster using AWS Identity and Access Management (IAM) database authentication; See [https://docs.aws.amazon.com/neptune/latest/userguide/iam-auth.html](https://docs.aws.amazon.com/neptune/latest/userguide/iam-auth.html) for more information and a list of supported versions and limitations. The following example shows enabling IAM authentication for a database cluster and granting connection access to an IAM role. ```python cluster = neptune.DatabaseCluster(self, "Cluster", vpc=vpc, instance_type=neptune.InstanceType.R5_LARGE, iam_authentication=True ) role = iam.Role(self, "DBRole", assumed_by=iam.AccountPrincipal(self.account)) # Use one of the following statements to grant the role the necessary permissions cluster.grant_connect(role) # Grant the role neptune-db:* access to the DB cluster.grant(role, "neptune-db:ReadDataViaQuery", "neptune-db:WriteDataViaQuery") ``` ## Customizing parameters Neptune allows configuring database behavior by supplying custom parameter groups. For more details, refer to the following link: [https://docs.aws.amazon.com/neptune/latest/userguide/parameters.html](https://docs.aws.amazon.com/neptune/latest/userguide/parameters.html) ```python cluster_params = neptune.ClusterParameterGroup(self, "ClusterParams", description="Cluster parameter group", parameters={ "neptune_enable_audit_log": "1" } ) db_params = neptune.ParameterGroup(self, "DbParams", description="Db parameter group", parameters={ "neptune_query_timeout": "120000" } ) cluster = neptune.DatabaseCluster(self, "Database", vpc=vpc, instance_type=neptune.InstanceType.R5_LARGE, cluster_parameter_group=cluster_params, parameter_group=db_params ) ``` Note: if you want to use Neptune engine `1.2.0.0` or later, you need to specify the corresponding `engineVersion` prop to `neptune.DatabaseCluster` and `family` prop of `ParameterGroupFamily.NEPTUNE_1_2` to `neptune.ClusterParameterGroup` and `neptune.ParameterGroup`. ## Adding replicas `DatabaseCluster` allows launching replicas along with the writer instance. This can be specified using the `instanceCount` attribute. ```python cluster = neptune.DatabaseCluster(self, "Database", vpc=vpc, instance_type=neptune.InstanceType.R5_LARGE, instances=2 ) ``` Additionally, it is also possible to add replicas using `DatabaseInstance` for an existing cluster. ```python replica1 = neptune.DatabaseInstance(self, "Instance", cluster=cluster, instance_type=neptune.InstanceType.R5_LARGE ) ``` ## Automatic minor version upgrades By setting `autoMinorVersionUpgrade` to true, Neptune will automatically update the engine of the entire cluster to the latest minor version after a stabilization window of 2 to 3 weeks. ```python neptune.DatabaseCluster(self, "Cluster", vpc=vpc, instance_type=neptune.InstanceType.R5_LARGE, auto_minor_version_upgrade=True ) ``` ## Logging Neptune supports various methods for monitoring performance and usage. One of those methods is logging 1. Neptune provides logs e.g. audit logs which can be viewed or downloaded via the AWS Console. Audit logs can be enabled using the `neptune_enable_audit_log` parameter in `ClusterParameterGroup` or `ParameterGroup` 2. Neptune provides the ability to export those logs to CloudWatch Logs ```python # Cluster parameter group with the neptune_enable_audit_log param set to 1 cluster_parameter_group = neptune.ClusterParameterGroup(self, "ClusterParams", description="Cluster parameter group", parameters={ "neptune_enable_audit_log": "1" } ) cluster = neptune.DatabaseCluster(self, "Database", vpc=vpc, instance_type=neptune.InstanceType.R5_LARGE, # Audit logs are enabled via the clusterParameterGroup cluster_parameter_group=cluster_parameter_group, # Optionally configuring audit logs to be exported to CloudWatch Logs cloudwatch_logs_exports=[neptune.LogType.AUDIT], # Optionally set a retention period on exported CloudWatch Logs cloudwatch_logs_retention=logs.RetentionDays.ONE_MONTH ) ``` For more information on monitoring, refer to https://docs.aws.amazon.com/neptune/latest/userguide/monitoring.html. For more information on audit logs, refer to https://docs.aws.amazon.com/neptune/latest/userguide/auditing.html. For more information on exporting logs to CloudWatch Logs, refer to https://docs.aws.amazon.com/neptune/latest/userguide/cloudwatch-logs.html. ## Metrics Both `DatabaseCluster` and `DatabaseInstance` provide a `metric()` method to help with cluster-level and instance-level monitoring. ```python # cluster: neptune.DatabaseCluster # instance: neptune.DatabaseInstance cluster.metric("SparqlRequestsPerSec") # cluster-level SparqlErrors metric instance.metric("SparqlRequestsPerSec") ``` For more details on the available metrics, refer to https://docs.aws.amazon.com/neptune/latest/userguide/cw-metrics.html

نیازمندی

مقدار	نام
==2.78.0	aws-cdk-lib
<11.0.0,>=10.0.0	constructs
<2.0.0,>=1.78.1	jsii
>=0.0.3	publication
~=2.13.3	typeguard

زبان مورد نیاز

مقدار	نام
~=3.7	Python

نحوه نصب

نصب پکیج whl aws-cdk.aws-neptune-alpha-2.9.0a0:

pip install aws-cdk.aws-neptune-alpha-2.9.0a0.whl

نصب پکیج tar.gz aws-cdk.aws-neptune-alpha-2.9.0a0:

pip install aws-cdk.aws-neptune-alpha-2.9.0a0.tar.gz