Struct rusoto_glue::CreateMLTransformRequest
source · [−]pub struct CreateMLTransformRequest {Show 13 fields
pub description: Option<String>,
pub glue_version: Option<String>,
pub input_record_tables: Vec<GlueTable>,
pub max_capacity: Option<f64>,
pub max_retries: Option<i64>,
pub name: String,
pub number_of_workers: Option<i64>,
pub parameters: TransformParameters,
pub role: String,
pub tags: Option<HashMap<String, String>>,
pub timeout: Option<i64>,
pub transform_encryption: Option<TransformEncryption>,
pub worker_type: Option<String>,
}
Fields
description: Option<String>
A description of the machine learning transform that is being defined. The default is an empty string.
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.
input_record_tables: Vec<GlueTable>
A list of Glue table definitions used by the transform.
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
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.
When the WorkerType
field is set to a value other than Standard
, the MaxCapacity
field is set automatically and becomes read-only.
max_retries: Option<i64>
The maximum number of times to retry a task for this transform after a task run fails.
name: String
The unique name that you give the transform when you create it.
number_of_workers: Option<i64>
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).
parameters: TransformParameters
The algorithmic parameters that are specific to the transform type used. Conditionally dependent on the transform type.
role: 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.
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.
timeout: Option<i64>
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).
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.
worker_type: Option<String>
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
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.
Trait Implementations
sourceimpl Clone for CreateMLTransformRequest
impl Clone for CreateMLTransformRequest
sourcefn clone(&self) -> CreateMLTransformRequest
fn clone(&self) -> CreateMLTransformRequest
Returns a copy of the value. Read more
1.0.0 · sourcefn clone_from(&mut self, source: &Self)
fn clone_from(&mut self, source: &Self)
Performs copy-assignment from source
. Read more
sourceimpl Debug for CreateMLTransformRequest
impl Debug for CreateMLTransformRequest
sourceimpl Default for CreateMLTransformRequest
impl Default for CreateMLTransformRequest
sourcefn default() -> CreateMLTransformRequest
fn default() -> CreateMLTransformRequest
Returns the “default value” for a type. Read more
sourceimpl PartialEq<CreateMLTransformRequest> for CreateMLTransformRequest
impl PartialEq<CreateMLTransformRequest> for CreateMLTransformRequest
sourcefn eq(&self, other: &CreateMLTransformRequest) -> bool
fn eq(&self, other: &CreateMLTransformRequest) -> bool
This method tests for self
and other
values to be equal, and is used
by ==
. Read more
sourcefn ne(&self, other: &CreateMLTransformRequest) -> bool
fn ne(&self, other: &CreateMLTransformRequest) -> bool
This method tests for !=
.
sourceimpl Serialize for CreateMLTransformRequest
impl Serialize for CreateMLTransformRequest
impl StructuralPartialEq for CreateMLTransformRequest
Auto Trait Implementations
impl RefUnwindSafe for CreateMLTransformRequest
impl Send for CreateMLTransformRequest
impl Sync for CreateMLTransformRequest
impl Unpin for CreateMLTransformRequest
impl UnwindSafe for CreateMLTransformRequest
Blanket Implementations
sourceimpl<T> BorrowMut<T> for T where
T: ?Sized,
impl<T> BorrowMut<T> for T where
T: ?Sized,
const: unstable · sourcefn borrow_mut(&mut self) -> &mut T
fn borrow_mut(&mut self) -> &mut T
Mutably borrows from an owned value. Read more
sourceimpl<T> Instrument for T
impl<T> Instrument for T
sourcefn instrument(self, span: Span) -> Instrumented<Self>
fn instrument(self, span: Span) -> Instrumented<Self>
sourcefn in_current_span(self) -> Instrumented<Self>
fn in_current_span(self) -> Instrumented<Self>
sourceimpl<T> ToOwned for T where
T: Clone,
impl<T> ToOwned for T where
T: Clone,
type Owned = T
type Owned = T
The resulting type after obtaining ownership.
sourcefn clone_into(&self, target: &mut T)
fn clone_into(&self, target: &mut T)
toowned_clone_into
)Uses borrowed data to replace owned data, usually by cloning. Read more
sourceimpl<T> WithSubscriber for T
impl<T> WithSubscriber for T
sourcefn with_subscriber<S>(self, subscriber: S) -> WithDispatch<Self> where
S: Into<Dispatch>,
fn with_subscriber<S>(self, subscriber: S) -> WithDispatch<Self> where
S: Into<Dispatch>,
Attaches the provided Subscriber
to this type, returning a
WithDispatch
wrapper. Read more
sourcefn with_current_subscriber(self) -> WithDispatch<Self>
fn with_current_subscriber(self) -> WithDispatch<Self>
Attaches the current default Subscriber
to this type, returning a
WithDispatch
wrapper. Read more