pub struct CreateDataSourceFromS3FluentBuilder { /* private fields */ }Expand description
Fluent builder constructing a request to CreateDataSourceFromS3.
Creates a DataSource object. A DataSource references data that can be used to perform CreateMLModel, CreateEvaluation, or CreateBatchPrediction operations.
CreateDataSourceFromS3 is an asynchronous operation. In response to CreateDataSourceFromS3, Amazon Machine Learning (Amazon ML) immediately returns and sets the DataSource status to PENDING. After the DataSource has been created and is ready for use, Amazon ML sets the Status parameter to COMPLETED. DataSource in the COMPLETED or PENDING state can be used to perform only CreateMLModel, CreateEvaluation or CreateBatchPrediction operations.
If Amazon ML can't accept the input source, it sets the Status parameter to FAILED and includes an error message in the Message attribute of the GetDataSource operation response.
The observation data used in a DataSource should be ready to use; that is, it should have a consistent structure, and missing data values should be kept to a minimum. The observation data must reside in one or more .csv files in an Amazon Simple Storage Service (Amazon S3) location, along with a schema that describes the data items by name and type. The same schema must be used for all of the data files referenced by the DataSource.
After the DataSource has been created, it's ready to use in evaluations and batch predictions. If you plan to use the DataSource to train an MLModel, the DataSource also needs a recipe. A recipe describes how each input variable will be used in training an MLModel. Will the variable be included or excluded from training? Will the variable be manipulated; for example, will it be combined with another variable or will it be split apart into word combinations? The recipe provides answers to these questions.
Implementations§
Source§impl CreateDataSourceFromS3FluentBuilder
impl CreateDataSourceFromS3FluentBuilder
Sourcepub fn as_input(&self) -> &CreateDataSourceFromS3InputBuilder
pub fn as_input(&self) -> &CreateDataSourceFromS3InputBuilder
Access the CreateDataSourceFromS3 as a reference.
Sourcepub async fn send(
self,
) -> Result<CreateDataSourceFromS3Output, SdkError<CreateDataSourceFromS3Error, HttpResponse>>
pub async fn send( self, ) -> Result<CreateDataSourceFromS3Output, SdkError<CreateDataSourceFromS3Error, HttpResponse>>
Sends the request and returns the response.
If an error occurs, an SdkError will be returned with additional details that
can be matched against.
By default, any retryable failures will be retried twice. Retry behavior is configurable with the RetryConfig, which can be set when configuring the client.
Sourcepub fn customize(
self,
) -> CustomizableOperation<CreateDataSourceFromS3Output, CreateDataSourceFromS3Error, Self>
pub fn customize( self, ) -> CustomizableOperation<CreateDataSourceFromS3Output, CreateDataSourceFromS3Error, Self>
Consumes this builder, creating a customizable operation that can be modified before being sent.
Sourcepub fn data_source_id(self, input: impl Into<String>) -> Self
pub fn data_source_id(self, input: impl Into<String>) -> Self
A user-supplied identifier that uniquely identifies the DataSource.
Sourcepub fn set_data_source_id(self, input: Option<String>) -> Self
pub fn set_data_source_id(self, input: Option<String>) -> Self
A user-supplied identifier that uniquely identifies the DataSource.
Sourcepub fn get_data_source_id(&self) -> &Option<String>
pub fn get_data_source_id(&self) -> &Option<String>
A user-supplied identifier that uniquely identifies the DataSource.
Sourcepub fn data_source_name(self, input: impl Into<String>) -> Self
pub fn data_source_name(self, input: impl Into<String>) -> Self
A user-supplied name or description of the DataSource.
Sourcepub fn set_data_source_name(self, input: Option<String>) -> Self
pub fn set_data_source_name(self, input: Option<String>) -> Self
A user-supplied name or description of the DataSource.
Sourcepub fn get_data_source_name(&self) -> &Option<String>
pub fn get_data_source_name(&self) -> &Option<String>
A user-supplied name or description of the DataSource.
Sourcepub fn data_spec(self, input: S3DataSpec) -> Self
pub fn data_spec(self, input: S3DataSpec) -> Self
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
DataSchemaUriis specified. -
DataRearrangement - A JSON string that represents the splitting and rearrangement requirements for the
Datasource.Sample -
"{\"splitting\":{\"percentBegin\":10,\"percentEnd\":60}}"
Sourcepub fn set_data_spec(self, input: Option<S3DataSpec>) -> Self
pub fn set_data_spec(self, input: Option<S3DataSpec>) -> Self
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
DataSchemaUriis specified. -
DataRearrangement - A JSON string that represents the splitting and rearrangement requirements for the
Datasource.Sample -
"{\"splitting\":{\"percentBegin\":10,\"percentEnd\":60}}"
Sourcepub fn get_data_spec(&self) -> &Option<S3DataSpec>
pub fn get_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
DataSchemaUriis specified. -
DataRearrangement - A JSON string that represents the splitting and rearrangement requirements for the
Datasource.Sample -
"{\"splitting\":{\"percentBegin\":10,\"percentEnd\":60}}"
Sourcepub fn compute_statistics(self, input: bool) -> Self
pub fn compute_statistics(self, input: bool) -> Self
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.
Sourcepub fn set_compute_statistics(self, input: Option<bool>) -> Self
pub fn set_compute_statistics(self, input: Option<bool>) -> Self
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.
Sourcepub fn get_compute_statistics(&self) -> &Option<bool>
pub fn get_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.
Trait Implementations§
Source§impl Clone for CreateDataSourceFromS3FluentBuilder
impl Clone for CreateDataSourceFromS3FluentBuilder
Source§fn clone(&self) -> CreateDataSourceFromS3FluentBuilder
fn clone(&self) -> CreateDataSourceFromS3FluentBuilder
1.0.0 · Source§const fn clone_from(&mut self, source: &Self)
const fn clone_from(&mut self, source: &Self)
source. Read moreAuto Trait Implementations§
impl Freeze for CreateDataSourceFromS3FluentBuilder
impl !RefUnwindSafe for CreateDataSourceFromS3FluentBuilder
impl Send for CreateDataSourceFromS3FluentBuilder
impl Sync for CreateDataSourceFromS3FluentBuilder
impl Unpin for CreateDataSourceFromS3FluentBuilder
impl !UnwindSafe for CreateDataSourceFromS3FluentBuilder
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