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توضیحات

The CDK Construct Library for AWS::DynamoDB

ویژگی	مقدار
سیستم عامل	-
نام فایل	aws-cdk.aws-dynamodb-1.99.0
نام	aws-cdk.aws-dynamodb
نسخه کتابخانه	1.99.0
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-dynamodb/
مجوز	Apache-2.0

# Amazon DynamoDB Construct Library --- ![cfn-resources: Stable](https://img.shields.io/badge/cfn--resources-stable-success.svg?style=for-the-badge) ![cdk-constructs: Stable](https://img.shields.io/badge/cdk--constructs-stable-success.svg?style=for-the-badge) ---  Here is a minimal deployable DynamoDB table definition: ```python table = dynamodb.Table(self, "Table", partition_key=dynamodb.Attribute(name="id", type=dynamodb.AttributeType.STRING) ) ``` ## Importing existing tables To import an existing table into your CDK application, use the `Table.fromTableName`, `Table.fromTableArn` or `Table.fromTableAttributes` factory method. This method accepts table name or table ARN which describes the properties of an already existing table: ```python # user: iam.User table = dynamodb.Table.from_table_arn(self, "ImportedTable", "arn:aws:dynamodb:us-east-1:111111111:table/my-table") # now you can just call methods on the table table.grant_read_write_data(user) ``` If you intend to use the `tableStreamArn` (including indirectly, for example by creating an `@aws-cdk/aws-lambda-event-source.DynamoEventSource` on the imported table), you *must* use the `Table.fromTableAttributes` method and the `tableStreamArn` property *must* be populated. ## Keys When a table is defined, you must define it's schema using the `partitionKey` (required) and `sortKey` (optional) properties. ## Billing Mode DynamoDB supports two billing modes: * PROVISIONED - the default mode where the table and global secondary indexes have configured read and write capacity. * PAY_PER_REQUEST - on-demand pricing and scaling. You only pay for what you use and there is no read and write capacity for the table or its global secondary indexes. ```python table = dynamodb.Table(self, "Table", partition_key=dynamodb.Attribute(name="id", type=dynamodb.AttributeType.STRING), billing_mode=dynamodb.BillingMode.PAY_PER_REQUEST ) ``` Further reading: https://docs.aws.amazon.com/amazondynamodb/latest/developerguide/HowItWorks.ReadWriteCapacityMode. ## Table Class DynamoDB supports two table classes: * STANDARD - the default mode, and is recommended for the vast majority of workloads. * STANDARD_INFREQUENT_ACCESS - optimized for tables where storage is the dominant cost. ```python table = dynamodb.Table(self, "Table", partition_key=dynamodb.Attribute(name="id", type=dynamodb.AttributeType.STRING), table_class=dynamodb.TableClass.STANDARD_INFREQUENT_ACCESS ) ``` Further reading: https://docs.aws.amazon.com/amazondynamodb/latest/developerguide/HowItWorks.TableClasses.html ## Configure AutoScaling for your table You can have DynamoDB automatically raise and lower the read and write capacities of your table by setting up autoscaling. You can use this to either keep your tables at a desired utilization level, or by scaling up and down at pre-configured times of the day: Auto-scaling is only relevant for tables with the billing mode, PROVISIONED. ```python read_scaling = table.auto_scale_read_capacity(min_capacity=1, max_capacity=50) read_scaling.scale_on_utilization( target_utilization_percent=50 ) read_scaling.scale_on_schedule("ScaleUpInTheMorning", schedule=appscaling.Schedule.cron(hour="8", minute="0"), min_capacity=20 ) read_scaling.scale_on_schedule("ScaleDownAtNight", schedule=appscaling.Schedule.cron(hour="20", minute="0"), max_capacity=20 ) ``` Further reading: https://docs.aws.amazon.com/amazondynamodb/latest/developerguide/AutoScaling.html https://aws.amazon.com/blogs/database/how-to-use-aws-cloudformation-to-configure-auto-scaling-for-amazon-dynamodb-tables-and-indexes/ ## Amazon DynamoDB Global Tables You can create DynamoDB Global Tables by setting the `replicationRegions` property on a `Table`: ```python global_table = dynamodb.Table(self, "Table", partition_key=dynamodb.Attribute(name="id", type=dynamodb.AttributeType.STRING), replication_regions=["us-east-1", "us-east-2", "us-west-2"] ) ``` When doing so, a CloudFormation Custom Resource will be added to the stack in order to create the replica tables in the selected regions. The default billing mode for Global Tables is `PAY_PER_REQUEST`. If you want to use `PROVISIONED`, you have to make sure write auto-scaling is enabled for that Table: ```python global_table = dynamodb.Table(self, "Table", partition_key=dynamodb.Attribute(name="id", type=dynamodb.AttributeType.STRING), replication_regions=["us-east-1", "us-east-2", "us-west-2"], billing_mode=dynamodb.BillingMode.PROVISIONED ) global_table.auto_scale_write_capacity( min_capacity=1, max_capacity=10 ).scale_on_utilization(target_utilization_percent=75) ``` When adding a replica region for a large table, you might want to increase the timeout for the replication operation: ```python global_table = dynamodb.Table(self, "Table", partition_key=dynamodb.Attribute(name="id", type=dynamodb.AttributeType.STRING), replication_regions=["us-east-1", "us-east-2", "us-west-2"], replication_timeout=Duration.hours(2) ) ``` ## Encryption All user data stored in Amazon DynamoDB is fully encrypted at rest. When creating a new table, you can choose to encrypt using the following customer master keys (CMK) to encrypt your table: * AWS owned CMK - By default, all tables are encrypted under an AWS owned customer master key (CMK) in the DynamoDB service account (no additional charges apply). * AWS managed CMK - AWS KMS keys (one per region) are created in your account, managed, and used on your behalf by AWS DynamoDB (AWS KMS charges apply). * Customer managed CMK - You have full control over the KMS key used to encrypt the DynamoDB Table (AWS KMS charges apply). Creating a Table encrypted with a customer managed CMK: ```python table = dynamodb.Table(self, "MyTable", partition_key=dynamodb.Attribute(name="id", type=dynamodb.AttributeType.STRING), encryption=dynamodb.TableEncryption.CUSTOMER_MANAGED ) # You can access the CMK that was added to the stack on your behalf by the Table construct via: table_encryption_key = table.encryption_key ``` You can also supply your own key: ```python import aws_cdk.aws_kms as kms encryption_key = kms.Key(self, "Key", enable_key_rotation=True ) table = dynamodb.Table(self, "MyTable", partition_key=dynamodb.Attribute(name="id", type=dynamodb.AttributeType.STRING), encryption=dynamodb.TableEncryption.CUSTOMER_MANAGED, encryption_key=encryption_key ) ``` In order to use the AWS managed CMK instead, change the code to: ```python table = dynamodb.Table(self, "MyTable", partition_key=dynamodb.Attribute(name="id", type=dynamodb.AttributeType.STRING), encryption=dynamodb.TableEncryption.AWS_MANAGED ) ``` ## Get schema of table or secondary indexes To get the partition key and sort key of the table or indexes you have configured: ```python # table: dynamodb.Table schema = table.schema() partition_key = schema.partition_key sort_key = schema.sort_key ``` ## Kinesis Stream A Kinesis Data Stream can be configured on the DynamoDB table to capture item-level changes. ```python import aws_cdk.aws_kinesis as kinesis stream = kinesis.Stream(self, "Stream") table = dynamodb.Table(self, "Table", partition_key=dynamodb.Attribute(name="id", type=dynamodb.AttributeType.STRING), kinesis_stream=stream ) ```

نیازمندی

مقدار	نام
==1.200.0	aws-cdk.aws-applicationautoscaling
==1.200.0	aws-cdk.aws-cloudwatch
==1.200.0	aws-cdk.aws-iam
==1.200.0	aws-cdk.aws-kinesis
==1.200.0	aws-cdk.aws-kms
==1.200.0	aws-cdk.aws-lambda
==1.200.0	aws-cdk.core
==1.200.0	aws-cdk.custom-resources
<4.0.0,>=3.3.69	constructs
<2.0.0,>=1.74.0	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-dynamodb-1.99.0:

pip install aws-cdk.aws-dynamodb-1.99.0.whl

نصب پکیج tar.gz aws-cdk.aws-dynamodb-1.99.0:

pip install aws-cdk.aws-dynamodb-1.99.0.tar.gz