Struct DatasetDefinition

#[non_exhaustive]
pub struct DatasetDefinition {
    pub athena_dataset_definition: Option<AthenaDatasetDefinition>,
    pub redshift_dataset_definition: Option<RedshiftDatasetDefinition>,
    pub local_path: Option<String>,
    pub data_distribution_type: Option<DataDistributionType>,
    pub input_mode: Option<InputMode>,
}

Configuration for Dataset Definition inputs. The Dataset Definition input must specify exactly one of either AthenaDatasetDefinition or RedshiftDatasetDefinition types.

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.

athena_dataset_definition: Option<AthenaDatasetDefinition>

Configuration for Athena Dataset Definition input.

redshift_dataset_definition: Option<RedshiftDatasetDefinition>

Configuration for Redshift Dataset Definition input.

local_path: Option<String>

The local path where you want Amazon SageMaker to download the Dataset Definition inputs to run a processing job. LocalPath is an absolute path to the input data. This is a required parameter when AppManaged is False (default).

data_distribution_type: Option<DataDistributionType>

Whether the generated dataset is FullyReplicated or ShardedByS3Key (default).

input_mode: Option<InputMode>

Whether to use File or Pipe input mode. In File (default) mode, Amazon SageMaker copies the data from the input source onto the local Amazon Elastic Block Store (Amazon EBS) volumes before starting your training algorithm. This is the most commonly used input mode. In Pipe mode, Amazon SageMaker streams input data from the source directly to your algorithm without using the EBS volume.

Implementations

impl DatasetDefinition

pub fn athena_dataset_definition(&self) -> Option<&AthenaDatasetDefinition>

Configuration for Athena Dataset Definition input.

pub fn redshift_dataset_definition(&self) -> Option<&RedshiftDatasetDefinition>

Configuration for Redshift Dataset Definition input.

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

The local path where you want Amazon SageMaker to download the Dataset Definition inputs to run a processing job. LocalPath is an absolute path to the input data. This is a required parameter when AppManaged is False (default).

pub fn data_distribution_type(&self) -> Option<&DataDistributionType>

Whether the generated dataset is FullyReplicated or ShardedByS3Key (default).

pub fn input_mode(&self) -> Option<&InputMode>

Whether to use File or Pipe input mode. In File (default) mode, Amazon SageMaker copies the data from the input source onto the local Amazon Elastic Block Store (Amazon EBS) volumes before starting your training algorithm. This is the most commonly used input mode. In Pipe mode, Amazon SageMaker streams input data from the source directly to your algorithm without using the EBS volume.

impl DatasetDefinition

pub fn builder() -> DatasetDefinitionBuilder

Creates a new builder-style object to manufacture DatasetDefinition.

Trait Implementations

impl Clone for DatasetDefinition

fn clone(&self) -> DatasetDefinition

Returns a copy of the value.

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

Performs copy-assignment from source.

impl Debug for DatasetDefinition

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

Formats the value using the given formatter.

impl PartialEq for DatasetDefinition

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

Tests for self and other values to be equal, and is used by ==.

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

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

impl StructuralPartialEq for DatasetDefinition