Struct aws_sdk_glue::operation::create_ml_transform::CreateMlTransformInput

#[non_exhaustive]
pub struct CreateMlTransformInput {

    pub name: Option<String>,
    pub description: Option<String>,
    pub input_record_tables: Option<Vec<GlueTable>>,
    pub parameters: Option<TransformParameters>,
    pub role: Option<String>,
    pub glue_version: Option<String>,
    pub max_capacity: Option<f64>,
    pub worker_type: Option<WorkerType>,
    pub number_of_workers: Option<i32>,
    pub timeout: Option<i32>,
    pub max_retries: Option<i32>,
    pub tags: Option<HashMap<String, String>>,
    pub transform_encryption: Option<TransformEncryption>,
}

Fields (Non-exhaustive)

Non-exhaustive structs could have additional fields added in future. Therefore, non-exhaustive structs cannot be constructed in external crates using the traditional Struct { .. } syntax; cannot be matched against without a wildcard ..; and struct update syntax will not work.

name: Option<String>

The unique name that you give the transform when you create it.

description: Option<String>

A description of the machine learning transform that is being defined. The default is an empty string.

input_record_tables: Option<Vec<GlueTable>>

A list of Glue table definitions used by the transform.

parameters: Option<TransformParameters>

The algorithmic parameters that are specific to the transform type used. Conditionally dependent on the transform type.

role: Option<String>

The name or Amazon Resource Name (ARN) of the IAM role with the required permissions. The required permissions include both Glue service role permissions to Glue resources, and Amazon S3 permissions required by the transform.

• This role needs Glue service role permissions to allow access to resources in Glue. See Attach a Policy to IAM Users That Access 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.

glue_version: Option<String>

This value determines which version of 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 Glue Versions in the developer guide.

max_capacity: Option<f64>

The number of 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 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.

worker_type: Option<WorkerType>

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.

number_of_workers: Option<i32>

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).

timeout: Option<i32>

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).

max_retries: Option<i32>

The maximum number of times to retry a task for this transform after a task run fails.

tags: Option<HashMap<String, String>>

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 Glue, see Amazon Web Services Tags in Glue in the developer guide.

transform_encryption: Option<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.

Implementations

impl CreateMlTransformInput

pub fn name(&self) -> Option<&str>

The unique name that you give the transform when you create it.

pub fn description(&self) -> Option<&str>

A description of the machine learning transform that is being defined. The default is an empty string.

pub fn input_record_tables(&self) -> &[GlueTable]

A list of Glue table definitions used by the transform.

If no value was sent for this field, a default will be set. If you want to determine if no value was sent, use .input_record_tables.is_none().

pub fn parameters(&self) -> Option<&TransformParameters>

The algorithmic parameters that are specific to the transform type used. Conditionally dependent on the transform type.

pub fn role(&self) -> Option<&str>

The name or Amazon Resource Name (ARN) of the IAM role with the required permissions. The required permissions include both Glue service role permissions to Glue resources, and Amazon S3 permissions required by the transform.

• This role needs Glue service role permissions to allow access to resources in Glue. See Attach a Policy to IAM Users That Access 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.

pub fn glue_version(&self) -> Option<&str>

This value determines which version of 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 Glue Versions in the developer guide.

pub fn max_capacity(&self) -> Option<f64>

The number of 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 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.

pub fn worker_type(&self) -> Option<&WorkerType>

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.

pub fn number_of_workers(&self) -> Option<i32>

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).

pub fn timeout(&self) -> Option<i32>

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).

pub fn max_retries(&self) -> Option<i32>

The maximum number of times to retry a task for this transform after a task run fails.

pub fn tags(&self) -> Option<&HashMap<String, String>>

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 Glue, see Amazon Web Services Tags in Glue in the developer guide.

pub fn transform_encryption(&self) -> Option<&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.

impl CreateMlTransformInput

pub fn builder() -> CreateMlTransformInputBuilder

Creates a new builder-style object to manufacture CreateMlTransformInput.

Trait Implementations

impl Clone for CreateMlTransformInput

fn clone(&self) -> CreateMlTransformInput

Returns a copy of the value.

fn clone_from(&mut self, source: &Self)

Performs copy-assignment from source.

impl Debug for CreateMlTransformInput

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl PartialEq for CreateMlTransformInput

fn eq(&self, other: &CreateMlTransformInput) -> bool

This method tests for self and other values to be equal, and is used by ==.

fn ne(&self, other: &Rhs) -> bool

This method tests for !=. The default implementation is almost always sufficient, and should not be overridden without very good reason.

impl StructuralPartialEq for CreateMlTransformInput