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Class: Aws::Glue::Types::MLTransform
- Inherits:
-
Struct
- Object
- Struct
- Aws::Glue::Types::MLTransform
- Defined in:
- (unknown)
Overview
A structure for a machine learning transform.
Instance Attribute Summary collapse
-
#created_on ⇒ Time
A timestamp.
-
#description ⇒ String
A user-defined, long-form description text for the machine learning transform.
-
#evaluation_metrics ⇒ Types::EvaluationMetrics
An
EvaluationMetrics
object. -
#glue_version ⇒ String
This value determines which version of AWS Glue this machine learning transform is compatible with.
-
#input_record_tables ⇒ Array<Types::GlueTable>
A list of AWS Glue table definitions used by the transform.
-
#label_count ⇒ Integer
A count identifier for the labeling files generated by AWS Glue for this transform.
-
#last_modified_on ⇒ Time
A timestamp.
-
#max_capacity ⇒ Float
The number of AWS Glue data processing units (DPUs) that are allocated to task runs for this transform.
-
#max_retries ⇒ Integer
The maximum number of times to retry after an
MLTaskRun
of the machine learning transform fails. -
#name ⇒ String
A user-defined name for the machine learning transform.
-
#number_of_workers ⇒ Integer
The number of workers of a defined
workerType
that are allocated when a task of the transform runs. -
#parameters ⇒ Types::TransformParameters
A
TransformParameters
object. -
#role ⇒ String
The name or Amazon Resource Name (ARN) of the IAM role with the required permissions.
-
#schema ⇒ Array<Types::SchemaColumn>
A map of key-value pairs representing the columns and data types that this transform can run against.
-
#status ⇒ String
The current status of the machine learning transform.
-
#timeout ⇒ Integer
The timeout in minutes of the machine learning transform.
-
#transform_encryption ⇒ Types::TransformEncryption
The encryption-at-rest settings of the transform that apply to accessing user data.
-
#transform_id ⇒ String
The unique transform ID that is generated for the machine learning transform.
-
#worker_type ⇒ String
The type of predefined worker that is allocated when a task of this transform runs.
Instance Attribute Details
#created_on ⇒ Time
A timestamp. The time and date that this machine learning transform was created.
#description ⇒ String
A user-defined, long-form description text for the machine learning transform. Descriptions are not guaranteed to be unique and can be changed at any time.
#evaluation_metrics ⇒ Types::EvaluationMetrics
An EvaluationMetrics
object. Evaluation metrics provide an estimate of
the quality of your machine learning transform.
#glue_version ⇒ String
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 ⇒ Array<Types::GlueTable>
A list of AWS Glue table definitions used by the transform.
#label_count ⇒ Integer
A count identifier for the labeling files generated by AWS Glue for this transform. As you create a better transform, you can iteratively download, label, and upload the labeling file.
#last_modified_on ⇒ Time
A timestamp. The last point in time when this machine learning transform was modified.
#max_capacity ⇒ Float
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.
MaxCapacity
is a mutually exclusive option with NumberOfWorkers
and
WorkerType
.
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 than Standard
, the
MaxCapacity
field is set automatically and becomes read-only.
#max_retries ⇒ Integer
The maximum number of times to retry after an MLTaskRun
of the machine
learning transform fails.
#name ⇒ String
A user-defined name for the machine learning transform. Names are not guaranteed unique and can be changed at any time.
#number_of_workers ⇒ Integer
The number of workers of a defined workerType
that are allocated when
a task of the transform runs.
If WorkerType
is set, then NumberOfWorkers
is required (and vice
versa).
#parameters ⇒ Types::TransformParameters
A TransformParameters
object. You can use parameters to tune
(customize) the behavior of the machine learning transform by specifying
what data it learns from and your preference on various tradeoffs (such
as precious vs. recall, or accuracy vs. cost).
#role ⇒ String
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.
#schema ⇒ Array<Types::SchemaColumn>
A map of key-value pairs representing the columns and data types that this transform can run against. Has an upper bound of 100 columns.
#status ⇒ String
The current status of the machine learning transform.
Possible values:
- NOT_READY
- READY
- DELETING
#timeout ⇒ Integer
The timeout in minutes of the machine learning transform.
#transform_encryption ⇒ Types::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.
#transform_id ⇒ String
The unique transform ID that is generated for the machine learning transform. The ID is guaranteed to be unique and does not change.
#worker_type ⇒ String
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 with NumberOfWorkers
and
WorkerType
.
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.Possible values:
- Standard
- G.1X
- G.2X