Updates an existing machine learning transform. Call this operation to tune the algorithm parameters to achieve better results.
glue_update_ml_transform(TransformId, Name, Description, Parameters,
Role, GlueVersion, MaxCapacity, WorkerType, NumberOfWorkers, Timeout,
MaxRetries)[required] A unique identifier that was generated when the transform was created.
The unique name that you gave the transform when you created it.
A description of the transform. The default is an empty string.
The configuration parameters that are specific to the transform type (algorithm) used. Conditionally dependent on the transform type.
The name or Amazon Resource Name (ARN) of the IAM role with the required permissions.
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.
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.
The number of workers of a defined workerType that are allocated when
this task runs.
The timeout for a 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$update_ml_transform(
TransformId = "string",
Name = "string",
Description = "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
)
After calling this operation, you can call the
StartMLEvaluationTaskRun operation to assess how well your new
parameters achieved your goals (such as improving the quality of your
machine learning transform, or making it more cost-effective).