Struct aws_sdk_machinelearning::operation::create_data_source_from_s3::CreateDataSourceFromS3Input

#[non_exhaustive]
pub struct CreateDataSourceFromS3Input {
    pub data_source_id: Option<String>,
    pub data_source_name: Option<String>,
    pub data_spec: Option<S3DataSpec>,
    pub compute_statistics: Option<bool>,
}

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.

data_source_id: Option<String>

A user-supplied identifier that uniquely identifies the DataSource.

data_source_name: Option<String>

A user-supplied name or description of the DataSource.

data_spec: Option<S3DataSpec>

The data specification of a DataSource:

• DataLocationS3 - The Amazon S3 location of the observation data.

• DataSchemaLocationS3 - The Amazon S3 location of the DataSchema.

• DataSchema - A JSON string representing the schema. This is not required if DataSchemaUri is specified.

• DataRearrangement - A JSON string that represents the splitting and rearrangement requirements for the Datasource.

  Sample - "{\"splitting\":{\"percentBegin\":10,\"percentEnd\":60}}"

compute_statistics: Option<bool>

The compute statistics for a DataSource. The statistics are generated from the observation data referenced by a DataSource. Amazon ML uses the statistics internally during MLModel training. This parameter must be set to true if the DataSource needs to be used for MLModel training.

Implementations

impl CreateDataSourceFromS3Input

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

A user-supplied identifier that uniquely identifies the DataSource.

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

A user-supplied name or description of the DataSource.

pub fn data_spec(&self) -> Option<&S3DataSpec>

The data specification of a DataSource:

• DataLocationS3 - The Amazon S3 location of the observation data.

• DataSchemaLocationS3 - The Amazon S3 location of the DataSchema.

• DataSchema - A JSON string representing the schema. This is not required if DataSchemaUri is specified.

• DataRearrangement - A JSON string that represents the splitting and rearrangement requirements for the Datasource.

  Sample - "{\"splitting\":{\"percentBegin\":10,\"percentEnd\":60}}"

pub fn compute_statistics(&self) -> Option<bool>

The compute statistics for a DataSource. The statistics are generated from the observation data referenced by a DataSource. Amazon ML uses the statistics internally during MLModel training. This parameter must be set to true if the DataSource needs to be used for MLModel training.

impl CreateDataSourceFromS3Input

pub fn builder() -> CreateDataSourceFromS3InputBuilder

Creates a new builder-style object to manufacture CreateDataSourceFromS3Input.

Trait Implementations

impl Clone for CreateDataSourceFromS3Input

fn clone(&self) -> CreateDataSourceFromS3Input

Returns a copy of the value.

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

Performs copy-assignment from source.

impl Debug for CreateDataSourceFromS3Input

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

Formats the value using the given formatter.

impl PartialEq for CreateDataSourceFromS3Input

fn eq(&self, other: &CreateDataSourceFromS3Input) -> 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 CreateDataSourceFromS3Input