CfnMLTransformProps
- class aws_cdk.aws_glue.CfnMLTransformProps(*, input_record_tables, role, transform_parameters, description=None, glue_version=None, max_capacity=None, max_retries=None, name=None, number_of_workers=None, tags=None, timeout=None, transform_encryption=None, worker_type=None)
Bases:
objectProperties for defining a
CfnMLTransform.- Parameters:
input_record_tables (
Union[IResolvable,InputRecordTablesProperty,Dict[str,Any]]) – A list of AWS Glue table definitions used by the transform.role (
str) – The name or Amazon Resource Name (ARN) of the IAM role with the required permissions. The required permissions include both AWS Glue service role permissions to AWS Glue resources, and Amazon S3 permissions required by the transform. - This role needs AWS Glue service role permissions to allow access to resources in AWS Glue . See Attach a Policy to IAM Users That Access AWS Glue . - This role needs permission to your Amazon Simple Storage Service (Amazon S3) sources, targets, temporary directory, scripts, and any libraries used by the task run for this transform.transform_parameters (
Union[IResolvable,TransformParametersProperty,Dict[str,Any]]) – The algorithm-specific parameters that are associated with the machine learning transform.description (
Optional[str]) – A user-defined, long-form description text for the machine learning transform.glue_version (
Optional[str]) – This value determines which version of AWS Glue this machine learning transform is compatible with. Glue 1.0 is recommended for most customers. If the value is not set, the Glue compatibility defaults to Glue 0.9. For more information, see AWS Glue Versions in the developer guide.max_capacity (
Union[int,float,None]) – The number of AWS Glue data processing units (DPUs) that are allocated to task runs for this transform. You can allocate from 2 to 100 DPUs; the default is 10. A DPU is a relative measure of processing power that consists of 4 vCPUs of compute capacity and 16 GB of memory. For more information, see the AWS Glue pricing page .MaxCapacityis a mutually exclusive option withNumberOfWorkersandWorkerType. - If eitherNumberOfWorkersorWorkerTypeis set, thenMaxCapacitycannot be set. - IfMaxCapacityis set then neitherNumberOfWorkersorWorkerTypecan be set. - IfWorkerTypeis set, thenNumberOfWorkersis required (and vice versa). -MaxCapacityandNumberOfWorkersmust both be at least 1. When theWorkerTypefield is set to a value other thanStandard, theMaxCapacityfield is set automatically and becomes read-only.max_retries (
Union[int,float,None]) – The maximum number of times to retry after anMLTaskRunof the machine learning transform fails.name (
Optional[str]) – A user-defined name for the machine learning transform. Names are required to be unique.Nameis optional:. - If you supplyName, the stack cannot be repeatedly created. - IfNameis not provided, a randomly generated name will be used instead.number_of_workers (
Union[int,float,None]) – The number of workers of a definedworkerTypethat are allocated when a task of the transform runs. IfWorkerTypeis set, thenNumberOfWorkersis required (and vice versa).tags (
Optional[Any]) – The tags to use with this machine learning transform. You may use tags to limit access to the machine learning transform. For more information about tags in AWS Glue , see AWS Tags in AWS Glue in the developer guide.timeout (
Union[int,float,None]) – The timeout in minutes of the machine learning transform.transform_encryption (
Union[IResolvable,TransformEncryptionProperty,Dict[str,Any],None]) – The encryption-at-rest settings of the transform that apply to accessing user data. Machine learning transforms can access user data encrypted in Amazon S3 using KMS. Additionally, imported labels and trained transforms can now be encrypted using a customer provided KMS key.worker_type (
Optional[str]) – The type of predefined worker that is allocated when a task of this transform runs. Accepts a value of Standard, G.1X, or G.2X. - For theStandardworker type, each worker provides 4 vCPU, 16 GB of memory and a 50GB disk, and 2 executors per worker. - For theG.1Xworker type, each worker provides 4 vCPU, 16 GB of memory and a 64GB disk, and 1 executor per worker. - For theG.2Xworker type, each worker provides 8 vCPU, 32 GB of memory and a 128GB disk, and 1 executor per worker.MaxCapacityis a mutually exclusive option withNumberOfWorkersandWorkerType. - If eitherNumberOfWorkersorWorkerTypeis set, thenMaxCapacitycannot be set. - IfMaxCapacityis set then neitherNumberOfWorkersorWorkerTypecan be set. - IfWorkerTypeis set, thenNumberOfWorkersis required (and vice versa). -MaxCapacityandNumberOfWorkersmust both be at least 1.
- Link:
http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-resource-glue-mltransform.html
- ExampleMetadata:
fixture=_generated
Example:
# The code below shows an example of how to instantiate this type. # The values are placeholders you should change. import aws_cdk.aws_glue as glue # tags: Any cfn_mLTransform_props = glue.CfnMLTransformProps( input_record_tables=glue.CfnMLTransform.InputRecordTablesProperty( glue_tables=[glue.CfnMLTransform.GlueTablesProperty( database_name="databaseName", table_name="tableName", # the properties below are optional catalog_id="catalogId", connection_name="connectionName" )] ), role="role", transform_parameters=glue.CfnMLTransform.TransformParametersProperty( transform_type="transformType", # the properties below are optional find_matches_parameters=glue.CfnMLTransform.FindMatchesParametersProperty( primary_key_column_name="primaryKeyColumnName", # the properties below are optional accuracy_cost_tradeoff=123, enforce_provided_labels=False, precision_recall_tradeoff=123 ) ), # the properties below are optional description="description", glue_version="glueVersion", max_capacity=123, max_retries=123, name="name", number_of_workers=123, tags=tags, timeout=123, transform_encryption=glue.CfnMLTransform.TransformEncryptionProperty( ml_user_data_encryption=glue.CfnMLTransform.MLUserDataEncryptionProperty( ml_user_data_encryption_mode="mlUserDataEncryptionMode", # the properties below are optional kms_key_id="kmsKeyId" ), task_run_security_configuration_name="taskRunSecurityConfigurationName" ), worker_type="workerType" )
Attributes
- description
A user-defined, long-form description text for the machine learning transform.
- glue_version
This value determines which version of AWS Glue this machine learning transform is compatible with.
Glue 1.0 is recommended for most customers. If the value is not set, the Glue compatibility defaults to Glue 0.9. For more information, see AWS Glue Versions in the developer guide.
- input_record_tables
A list of AWS Glue table definitions used by the transform.
- max_capacity
The number of AWS Glue data processing units (DPUs) that are allocated to task runs for this transform.
You can allocate from 2 to 100 DPUs; the default is 10. A DPU is a relative measure of processing power that consists of 4 vCPUs of compute capacity and 16 GB of memory. For more information, see the AWS Glue pricing page .
MaxCapacityis a mutually exclusive option withNumberOfWorkersandWorkerType.If either
NumberOfWorkersorWorkerTypeis set, thenMaxCapacitycannot be set.If
MaxCapacityis set then neitherNumberOfWorkersorWorkerTypecan be set.If
WorkerTypeis set, thenNumberOfWorkersis required (and vice versa).MaxCapacityandNumberOfWorkersmust both be at least 1.
When the
WorkerTypefield is set to a value other thanStandard, theMaxCapacityfield is set automatically and becomes read-only.
- max_retries
The maximum number of times to retry after an
MLTaskRunof the machine learning transform fails.
- name
.
If you supply
Name, the stack cannot be repeatedly created.If
Nameis not provided, a randomly generated name will be used instead.
- Link:
- Type:
A user-defined name for the machine learning transform. Names are required to be unique.
Nameis optional
- number_of_workers
The number of workers of a defined
workerTypethat are allocated when a task of the transform runs.If
WorkerTypeis set, thenNumberOfWorkersis required (and vice versa).
- role
The name or Amazon Resource Name (ARN) of the IAM role with the required permissions.
The required permissions include both AWS Glue service role permissions to AWS Glue resources, and Amazon S3 permissions required by the transform.
This role needs AWS Glue service role permissions to allow access to resources in AWS Glue . See Attach a Policy to IAM Users That Access AWS Glue .
This role needs permission to your Amazon Simple Storage Service (Amazon S3) sources, targets, temporary directory, scripts, and any libraries used by the task run for this transform.
- tags
The tags to use with this machine learning transform.
You may use tags to limit access to the machine learning transform. For more information about tags in AWS Glue , see AWS Tags in AWS Glue in the developer guide.
- timeout
The timeout in minutes of the machine learning transform.
- transform_encryption
The encryption-at-rest settings of the transform that apply to accessing user data.
Machine learning transforms can access user data encrypted in Amazon S3 using KMS.
Additionally, imported labels and trained transforms can now be encrypted using a customer provided KMS key.
- transform_parameters
The algorithm-specific parameters that are associated with the machine learning transform.
- worker_type
The type of predefined worker that is allocated when a task of this transform runs.
Accepts a value of Standard, G.1X, or G.2X.
For the
Standardworker type, each worker provides 4 vCPU, 16 GB of memory and a 50GB disk, and 2 executors per worker.For the
G.1Xworker type, each worker provides 4 vCPU, 16 GB of memory and a 64GB disk, and 1 executor per worker.For the
G.2Xworker type, each worker provides 8 vCPU, 32 GB of memory and a 128GB disk, and 1 executor per worker.
MaxCapacityis a mutually exclusive option withNumberOfWorkersandWorkerType.If either
NumberOfWorkersorWorkerTypeis set, thenMaxCapacitycannot be set.If
MaxCapacityis set then neitherNumberOfWorkersorWorkerTypecan be set.If
WorkerTypeis set, thenNumberOfWorkersis required (and vice versa).MaxCapacityandNumberOfWorkersmust both be at least 1.