Creates an AWS Glue machine learning transform. This operation creates the transform and all the necessary parameters to train it.
glue_create_ml_transform(Name, Description, InputRecordTables,
Parameters, Role, GlueVersion, MaxCapacity, WorkerType, NumberOfWorkers,
Timeout, MaxRetries)[required] The unique name that you give the transform when you create it.
A description of the machine learning transform that is being defined. The default is an empty string.
[required] A list of AWS Glue table definitions used by the transform.
[required] The algorithmic parameters that are specific to the transform type used. Conditionally dependent on the transform type.
[required] 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.
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.
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 or WorkerType is set, then
MaxCapacity cannot be set.
If MaxCapacity is set then neither NumberOfWorkers or
WorkerType can be set.
If WorkerType is set, then NumberOfWorkers is required (and vice
versa).
MaxCapacity and NumberOfWorkers 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.
When the WorkerType field is set to a value other than Standard, the
MaxCapacity field is set automatically and becomes read-only.
The type of predefined worker that is allocated when this task 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 or WorkerType is set, then
MaxCapacity cannot be set.
If MaxCapacity is set then neither NumberOfWorkers or
WorkerType can be set.
If WorkerType is set, then NumberOfWorkers is required (and vice
versa).
MaxCapacity and NumberOfWorkers must both be at least 1.
The number of workers of a defined workerType that are allocated when
this task runs.
If WorkerType is set, then NumberOfWorkers is required (and vice
versa).
The timeout of the task run for this transform in minutes. This is the
maximum time that a task run for this transform can consume resources
before it is terminated and enters TIMEOUT status. The default is
2,880 minutes (48 hours).
The maximum number of times to retry a task for this transform after a task run fails.
svc$create_ml_transform(
Name = "string",
Description = "string",
InputRecordTables = list(
list(
DatabaseName = "string",
TableName = "string",
CatalogId = "string",
ConnectionName = "string"
)
),
Parameters = list(
TransformType = "FIND_MATCHES",
FindMatchesParameters = list(
PrimaryKeyColumnName = "string",
PrecisionRecallTradeoff = 123.0,
AccuracyCostTradeoff = 123.0,
EnforceProvidedLabels = TRUE|FALSE
)
),
Role = "string",
GlueVersion = "string",
MaxCapacity = 123.0,
WorkerType = "Standard"|"G.1X"|"G.2X",
NumberOfWorkers = 123,
Timeout = 123,
MaxRetries = 123
)
Call this operation as the first step in the process of using a machine
learning transform (such as the FindMatches transform) for
deduplicating data. You can provide an optional Description, in
addition to the parameters that you want to use for your algorithm.
You must also specify certain parameters for the tasks that AWS Glue
runs on your behalf as part of learning from your data and creating a
high-quality machine learning transform. These parameters include
Role, and optionally, AllocatedCapacity, Timeout, and
MaxRetries. For more information, see
Jobs.