// Code generated by software.amazon.smithy.rust.codegen.smithy-rs. DO NOT EDIT.
pub use crate::operation::create_data_source_from_s3::_create_data_source_from_s3_input::CreateDataSourceFromS3InputBuilder;
pub use crate::operation::create_data_source_from_s3::_create_data_source_from_s3_output::CreateDataSourceFromS3OutputBuilder;
impl crate::operation::create_data_source_from_s3::builders::CreateDataSourceFromS3InputBuilder {
/// Sends a request with this input using the given client.
pub async fn send_with(
self,
client: &crate::Client,
) -> ::std::result::Result<
crate::operation::create_data_source_from_s3::CreateDataSourceFromS3Output,
::aws_smithy_runtime_api::client::result::SdkError<
crate::operation::create_data_source_from_s3::CreateDataSourceFromS3Error,
::aws_smithy_runtime_api::client::orchestrator::HttpResponse,
>,
> {
let mut fluent_builder = client.create_data_source_from_s3();
fluent_builder.inner = self;
fluent_builder.send().await
}
}
/// Fluent builder constructing a request to `CreateDataSourceFromS3`.
///
/// <p>Creates a <code>DataSource</code> object. A <code>DataSource</code> references data that can be used to perform <code>CreateMLModel</code>, <code>CreateEvaluation</code>, or <code>CreateBatchPrediction</code> operations.</p>
/// <p><code>CreateDataSourceFromS3</code> is an asynchronous operation. In response to <code>CreateDataSourceFromS3</code>, Amazon Machine Learning (Amazon ML) immediately returns and sets the <code>DataSource</code> status to <code>PENDING</code>. After the <code>DataSource</code> has been created and is ready for use, Amazon ML sets the <code>Status</code> parameter to <code>COMPLETED</code>. <code>DataSource</code> in the <code>COMPLETED</code> or <code>PENDING</code> state can be used to perform only <code>CreateMLModel</code>, <code>CreateEvaluation</code> or <code>CreateBatchPrediction</code> operations.</p>
/// <p>If Amazon ML can't accept the input source, it sets the <code>Status</code> parameter to <code>FAILED</code> and includes an error message in the <code>Message</code> attribute of the <code>GetDataSource</code> operation response.</p>
/// <p>The observation data used in a <code>DataSource</code> 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 <code>DataSource</code>.</p>
/// <p>After the <code>DataSource</code> has been created, it's ready to use in evaluations and batch predictions. If you plan to use the <code>DataSource</code> to train an <code>MLModel</code>, the <code>DataSource</code> also needs a recipe. A recipe describes how each input variable will be used in training an <code>MLModel</code>. 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.</p>
#[derive(::std::clone::Clone, ::std::fmt::Debug)]
pub struct CreateDataSourceFromS3FluentBuilder {
handle: ::std::sync::Arc<crate::client::Handle>,
inner: crate::operation::create_data_source_from_s3::builders::CreateDataSourceFromS3InputBuilder,
config_override: ::std::option::Option<crate::config::Builder>,
}
impl
crate::client::customize::internal::CustomizableSend<
crate::operation::create_data_source_from_s3::CreateDataSourceFromS3Output,
crate::operation::create_data_source_from_s3::CreateDataSourceFromS3Error,
> for CreateDataSourceFromS3FluentBuilder
{
fn send(
self,
config_override: crate::config::Builder,
) -> crate::client::customize::internal::BoxFuture<
crate::client::customize::internal::SendResult<
crate::operation::create_data_source_from_s3::CreateDataSourceFromS3Output,
crate::operation::create_data_source_from_s3::CreateDataSourceFromS3Error,
>,
> {
::std::boxed::Box::pin(async move { self.config_override(config_override).send().await })
}
}
impl CreateDataSourceFromS3FluentBuilder {
/// Creates a new `CreateDataSourceFromS3FluentBuilder`.
pub(crate) fn new(handle: ::std::sync::Arc<crate::client::Handle>) -> Self {
Self {
handle,
inner: ::std::default::Default::default(),
config_override: ::std::option::Option::None,
}
}
/// Access the CreateDataSourceFromS3 as a reference.
pub fn as_input(&self) -> &crate::operation::create_data_source_from_s3::builders::CreateDataSourceFromS3InputBuilder {
&self.inner
}
/// 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](aws_smithy_types::retry::RetryConfig), which can be
/// set when configuring the client.
pub async fn send(
self,
) -> ::std::result::Result<
crate::operation::create_data_source_from_s3::CreateDataSourceFromS3Output,
::aws_smithy_runtime_api::client::result::SdkError<
crate::operation::create_data_source_from_s3::CreateDataSourceFromS3Error,
::aws_smithy_runtime_api::client::orchestrator::HttpResponse,
>,
> {
let input = self
.inner
.build()
.map_err(::aws_smithy_runtime_api::client::result::SdkError::construction_failure)?;
let runtime_plugins = crate::operation::create_data_source_from_s3::CreateDataSourceFromS3::operation_runtime_plugins(
self.handle.runtime_plugins.clone(),
&self.handle.conf,
self.config_override,
);
crate::operation::create_data_source_from_s3::CreateDataSourceFromS3::orchestrate(&runtime_plugins, input).await
}
/// Consumes this builder, creating a customizable operation that can be modified before being sent.
pub fn customize(
self,
) -> crate::client::customize::CustomizableOperation<
crate::operation::create_data_source_from_s3::CreateDataSourceFromS3Output,
crate::operation::create_data_source_from_s3::CreateDataSourceFromS3Error,
Self,
> {
crate::client::customize::CustomizableOperation::new(self)
}
pub(crate) fn config_override(mut self, config_override: impl ::std::convert::Into<crate::config::Builder>) -> Self {
self.set_config_override(::std::option::Option::Some(config_override.into()));
self
}
pub(crate) fn set_config_override(&mut self, config_override: ::std::option::Option<crate::config::Builder>) -> &mut Self {
self.config_override = config_override;
self
}
/// <p>A user-supplied identifier that uniquely identifies the <code>DataSource</code>.</p>
pub fn data_source_id(mut self, input: impl ::std::convert::Into<::std::string::String>) -> Self {
self.inner = self.inner.data_source_id(input.into());
self
}
/// <p>A user-supplied identifier that uniquely identifies the <code>DataSource</code>.</p>
pub fn set_data_source_id(mut self, input: ::std::option::Option<::std::string::String>) -> Self {
self.inner = self.inner.set_data_source_id(input);
self
}
/// <p>A user-supplied identifier that uniquely identifies the <code>DataSource</code>.</p>
pub fn get_data_source_id(&self) -> &::std::option::Option<::std::string::String> {
self.inner.get_data_source_id()
}
/// <p>A user-supplied name or description of the <code>DataSource</code>.</p>
pub fn data_source_name(mut self, input: impl ::std::convert::Into<::std::string::String>) -> Self {
self.inner = self.inner.data_source_name(input.into());
self
}
/// <p>A user-supplied name or description of the <code>DataSource</code>.</p>
pub fn set_data_source_name(mut self, input: ::std::option::Option<::std::string::String>) -> Self {
self.inner = self.inner.set_data_source_name(input);
self
}
/// <p>A user-supplied name or description of the <code>DataSource</code>.</p>
pub fn get_data_source_name(&self) -> &::std::option::Option<::std::string::String> {
self.inner.get_data_source_name()
}
/// <p>The data specification of a <code>DataSource</code>:</p>
/// <ul>
/// <li>
/// <p>DataLocationS3 - The Amazon S3 location of the observation data.</p></li>
/// <li>
/// <p>DataSchemaLocationS3 - The Amazon S3 location of the <code>DataSchema</code>.</p></li>
/// <li>
/// <p>DataSchema - A JSON string representing the schema. This is not required if <code>DataSchemaUri</code> is specified.</p></li>
/// <li>
/// <p>DataRearrangement - A JSON string that represents the splitting and rearrangement requirements for the <code>Datasource</code>.</p>
/// <p>Sample - <code> "{\"splitting\":{\"percentBegin\":10,\"percentEnd\":60}}"</code></p></li>
/// </ul>
pub fn data_spec(mut self, input: crate::types::S3DataSpec) -> Self {
self.inner = self.inner.data_spec(input);
self
}
/// <p>The data specification of a <code>DataSource</code>:</p>
/// <ul>
/// <li>
/// <p>DataLocationS3 - The Amazon S3 location of the observation data.</p></li>
/// <li>
/// <p>DataSchemaLocationS3 - The Amazon S3 location of the <code>DataSchema</code>.</p></li>
/// <li>
/// <p>DataSchema - A JSON string representing the schema. This is not required if <code>DataSchemaUri</code> is specified.</p></li>
/// <li>
/// <p>DataRearrangement - A JSON string that represents the splitting and rearrangement requirements for the <code>Datasource</code>.</p>
/// <p>Sample - <code> "{\"splitting\":{\"percentBegin\":10,\"percentEnd\":60}}"</code></p></li>
/// </ul>
pub fn set_data_spec(mut self, input: ::std::option::Option<crate::types::S3DataSpec>) -> Self {
self.inner = self.inner.set_data_spec(input);
self
}
/// <p>The data specification of a <code>DataSource</code>:</p>
/// <ul>
/// <li>
/// <p>DataLocationS3 - The Amazon S3 location of the observation data.</p></li>
/// <li>
/// <p>DataSchemaLocationS3 - The Amazon S3 location of the <code>DataSchema</code>.</p></li>
/// <li>
/// <p>DataSchema - A JSON string representing the schema. This is not required if <code>DataSchemaUri</code> is specified.</p></li>
/// <li>
/// <p>DataRearrangement - A JSON string that represents the splitting and rearrangement requirements for the <code>Datasource</code>.</p>
/// <p>Sample - <code> "{\"splitting\":{\"percentBegin\":10,\"percentEnd\":60}}"</code></p></li>
/// </ul>
pub fn get_data_spec(&self) -> &::std::option::Option<crate::types::S3DataSpec> {
self.inner.get_data_spec()
}
/// <p>The compute statistics for a <code>DataSource</code>. The statistics are generated from the observation data referenced by a <code>DataSource</code>. Amazon ML uses the statistics internally during <code>MLModel</code> training. This parameter must be set to <code>true</code> if the <code></code>DataSource<code></code> needs to be used for <code>MLModel</code> training.</p>
pub fn compute_statistics(mut self, input: bool) -> Self {
self.inner = self.inner.compute_statistics(input);
self
}
/// <p>The compute statistics for a <code>DataSource</code>. The statistics are generated from the observation data referenced by a <code>DataSource</code>. Amazon ML uses the statistics internally during <code>MLModel</code> training. This parameter must be set to <code>true</code> if the <code></code>DataSource<code></code> needs to be used for <code>MLModel</code> training.</p>
pub fn set_compute_statistics(mut self, input: ::std::option::Option<bool>) -> Self {
self.inner = self.inner.set_compute_statistics(input);
self
}
/// <p>The compute statistics for a <code>DataSource</code>. The statistics are generated from the observation data referenced by a <code>DataSource</code>. Amazon ML uses the statistics internally during <code>MLModel</code> training. This parameter must be set to <code>true</code> if the <code></code>DataSource<code></code> needs to be used for <code>MLModel</code> training.</p>
pub fn get_compute_statistics(&self) -> &::std::option::Option<bool> {
self.inner.get_compute_statistics()
}
}