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AWS::Glue::MLTransform
The AWS::Glue::MLTransform is an AWS Glue resource type that manages machine learning transforms.
Syntax
To declare this entity in your AWS CloudFormation template, use the following syntax:
JSON
{ "Type" : "AWS::Glue::MLTransform", "Properties" : { "Description" :String, "GlueVersion" :String, "InputRecordTables" :InputRecordTables, "MaxCapacity" :Number, "MaxRetries" :Integer, "Name" :String, "NumberOfWorkers" :Integer, "Role" :String, "Tags" :[, "Timeout" :Tag, ... ]Integer, "TransformEncryption" :TransformEncryption, "TransformParameters" :TransformParameters, "WorkerType" :String} }
YAML
Type: AWS::Glue::MLTransform Properties: Description:StringGlueVersion:StringInputRecordTables:InputRecordTablesMaxCapacity:NumberMaxRetries:IntegerName:StringNumberOfWorkers:IntegerRole:StringTags:-Timeout:TagIntegerTransformEncryption:TransformEncryptionTransformParameters:TransformParametersWorkerType:String
Properties
Description-
A user-defined, long-form description text for the machine learning transform.
Required: No
Type: String
Pattern:
[\u0020-\uD7FF\uE000-\uFFFD\uD800\uDC00-\uDBFF\uDFFF\r\n\t]*Minimum:
0Maximum:
2048Update requires: No interruption
GlueVersion-
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.
Required: No
Type: String
Update requires: No interruption
InputRecordTables-
A list of AWS Glue table definitions used by the transform.
Required: Yes
Type: InputRecordTables
Minimum:
0Maximum:
10Update requires: Replacement
MaxCapacity-
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.Required: No
Type: Number
Update requires: No interruption
-
MaxRetries-
The maximum number of times to retry after an
MLTaskRunof the machine learning transform fails.Required: No
Type: Integer
Update requires: No interruption
Name-
A user-defined name for the machine learning transform. Names are required to be unique.
Nameis optional:-
If you supply
Name, the stack cannot be repeatedly created. -
If
Nameis not provided, a randomly generated name will be used instead.
Required: No
Type: String
Pattern:
[\u0020-\uD7FF\uE000-\uFFFD\uD800\uDC00-\uDBFF\uDFFF\t]*Minimum:
1Maximum:
255Update requires: No interruption
-
NumberOfWorkers-
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).Required: No
Type: Integer
Update requires: No interruption
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.
Required: Yes
Type: String
Update requires: No interruption
-
-
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.
Required: No
Type: Array of
TagUpdate requires: No interruption
Timeout-
The timeout in minutes of the machine learning transform.
Required: No
Type: Integer
Minimum:
1Update requires: No interruption
TransformEncryption-
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.
Required: No
Type: TransformEncryption
Update requires: No interruption
TransformParameters-
The algorithm-specific parameters that are associated with the machine learning transform.
Required: Yes
Type: TransformParameters
Update requires: No interruption
WorkerType-
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.
Required: No
Type: String
Allowed values:
Standard | G.1X | G.2X | G.025X | G.4X | G.8X | Z.2XUpdate requires: No interruption
-
Return values
Ref
When you pass the logical ID of this resource to the intrinsic Ref function, Ref returns the transform ID.
For more information about using the Ref function, see Ref.