AWS::Glue::MLTransform
The AWS::Glue::MLTransform is an Amazon Glue resource type that manages machine learning transforms.
Syntax
To declare this entity in your Amazon 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:
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
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:
0
Maximum:
2048
Update requires: No interruption
GlueVersion
-
This value determines which version of Amazon 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 Amazon Glue Versions in the developer guide.
Required: No
Type: String
Update requires: No interruption
InputRecordTables
-
A list of Amazon Glue table definitions used by the transform.
Required: Yes
Type: InputRecordTables
Minimum:
0
Maximum:
10
Update requires: Replacement
MaxCapacity
-
The number of Amazon 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 Amazon Glue pricing page
. MaxCapacity
is a mutually exclusive option withNumberOfWorkers
andWorkerType
.-
If either
NumberOfWorkers
orWorkerType
is set, thenMaxCapacity
cannot be set. -
If
MaxCapacity
is set then neitherNumberOfWorkers
orWorkerType
can be set. -
If
WorkerType
is set, thenNumberOfWorkers
is required (and vice versa). -
MaxCapacity
andNumberOfWorkers
must both be at least 1.
When the
WorkerType
field is set to a value other thanStandard
, theMaxCapacity
field 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
MLTaskRun
of 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.
Name
is optional:-
If you supply
Name
, the stack cannot be repeatedly created. -
If
Name
is 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:
1
Maximum:
255
Update requires: No interruption
-
NumberOfWorkers
-
The number of workers of a defined
workerType
that are allocated when a task of the transform runs.If
WorkerType
is set, thenNumberOfWorkers
is 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 Amazon Glue service role permissions to Amazon Glue resources, and Amazon S3 permissions required by the transform.
-
This role needs Amazon Glue service role permissions to allow access to resources in Amazon Glue. See Attach a Policy to IAM Users That Access Amazon 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 Amazon Glue, see Amazon Tags in Amazon Glue in the developer guide.
Required: No
Type: Array of
Tag
Update requires: No interruption
Timeout
-
The timeout in minutes of the machine learning transform.
Required: No
Type: Integer
Minimum:
1
Update 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
Standard
worker type, each worker provides 4 vCPU, 16 GB of memory and a 50GB disk, and 2 executors per worker. -
For the
G.1X
worker type, each worker provides 4 vCPU, 16 GB of memory and a 64GB disk, and 1 executor per worker. -
For the
G.2X
worker type, each worker provides 8 vCPU, 32 GB of memory and a 128GB disk, and 1 executor per worker.
MaxCapacity
is a mutually exclusive option withNumberOfWorkers
andWorkerType
.-
If either
NumberOfWorkers
orWorkerType
is set, thenMaxCapacity
cannot be set. -
If
MaxCapacity
is set then neitherNumberOfWorkers
orWorkerType
can be set. -
If
WorkerType
is set, thenNumberOfWorkers
is required (and vice versa). -
MaxCapacity
andNumberOfWorkers
must both be at least 1.
Required: No
Type: String
Allowed values:
Standard | G.1X | G.2X | G.025X | G.4X | G.8X | Z.2X
Update 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
.