// Code generated by software.amazon.smithy.rust.codegen.smithy-rs. DO NOT EDIT.
pub use crate::operation::create_data_source_from_redshift::_create_data_source_from_redshift_input::CreateDataSourceFromRedshiftInputBuilder;
pub use crate::operation::create_data_source_from_redshift::_create_data_source_from_redshift_output::CreateDataSourceFromRedshiftOutputBuilder;
impl crate::operation::create_data_source_from_redshift::builders::CreateDataSourceFromRedshiftInputBuilder {
/// 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_redshift::CreateDataSourceFromRedshiftOutput,
::aws_smithy_runtime_api::client::result::SdkError<
crate::operation::create_data_source_from_redshift::CreateDataSourceFromRedshiftError,
::aws_smithy_runtime_api::client::orchestrator::HttpResponse,
>,
> {
let mut fluent_builder = client.create_data_source_from_redshift();
fluent_builder.inner = self;
fluent_builder.send().await
}
}
/// Fluent builder constructing a request to `CreateDataSourceFromRedshift`.
///
/// <p>Creates a <code>DataSource</code> from a database hosted on an Amazon Redshift cluster. A <code>DataSource</code> references data that can be used to perform either <code>CreateMLModel</code>, <code>CreateEvaluation</code>, or <code>CreateBatchPrediction</code> operations.</p>
/// <p><code>CreateDataSourceFromRedshift</code> is an asynchronous operation. In response to <code>CreateDataSourceFromRedshift</code>, Amazon Machine Learning (Amazon ML) immediately returns and sets the <code>DataSource</code> status to <code>PENDING</code>. After the <code>DataSource</code> is created and ready for use, Amazon ML sets the <code>Status</code> parameter to <code>COMPLETED</code>. <code>DataSource</code> in <code>COMPLETED</code> or <code>PENDING</code> states 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 observations should be contained in the database hosted on an Amazon Redshift cluster and should be specified by a <code>SelectSqlQuery</code> query. Amazon ML executes an <code>Unload</code> command in Amazon Redshift to transfer the result set of the <code>SelectSqlQuery</code> query to <code>S3StagingLocation</code>.</p>
/// <p>After the <code>DataSource</code> has been created, it's ready for 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 requires 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>
/// <p>You can't change an existing datasource, but you can copy and modify the settings from an existing Amazon Redshift datasource to create a new datasource. To do so, call <code>GetDataSource</code> for an existing datasource and copy the values to a <code>CreateDataSource</code> call. Change the settings that you want to change and make sure that all required fields have the appropriate values.</p>
#[derive(::std::clone::Clone, ::std::fmt::Debug)]
pub struct CreateDataSourceFromRedshiftFluentBuilder {
handle: ::std::sync::Arc<crate::client::Handle>,
inner: crate::operation::create_data_source_from_redshift::builders::CreateDataSourceFromRedshiftInputBuilder,
config_override: ::std::option::Option<crate::config::Builder>,
}
impl
crate::client::customize::internal::CustomizableSend<
crate::operation::create_data_source_from_redshift::CreateDataSourceFromRedshiftOutput,
crate::operation::create_data_source_from_redshift::CreateDataSourceFromRedshiftError,
> for CreateDataSourceFromRedshiftFluentBuilder
{
fn send(
self,
config_override: crate::config::Builder,
) -> crate::client::customize::internal::BoxFuture<
crate::client::customize::internal::SendResult<
crate::operation::create_data_source_from_redshift::CreateDataSourceFromRedshiftOutput,
crate::operation::create_data_source_from_redshift::CreateDataSourceFromRedshiftError,
>,
> {
::std::boxed::Box::pin(async move { self.config_override(config_override).send().await })
}
}
impl CreateDataSourceFromRedshiftFluentBuilder {
/// Creates a new `CreateDataSourceFromRedshiftFluentBuilder`.
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 CreateDataSourceFromRedshift as a reference.
pub fn as_input(&self) -> &crate::operation::create_data_source_from_redshift::builders::CreateDataSourceFromRedshiftInputBuilder {
&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_redshift::CreateDataSourceFromRedshiftOutput,
::aws_smithy_runtime_api::client::result::SdkError<
crate::operation::create_data_source_from_redshift::CreateDataSourceFromRedshiftError,
::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_redshift::CreateDataSourceFromRedshift::operation_runtime_plugins(
self.handle.runtime_plugins.clone(),
&self.handle.conf,
self.config_override,
);
crate::operation::create_data_source_from_redshift::CreateDataSourceFromRedshift::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_redshift::CreateDataSourceFromRedshiftOutput,
crate::operation::create_data_source_from_redshift::CreateDataSourceFromRedshiftError,
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 ID 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 ID 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 ID 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 an Amazon Redshift <code>DataSource</code>:</p>
/// <ul>
/// <li>
/// <p>DatabaseInformation -</p>
/// <ul>
/// <li>
/// <p><code>DatabaseName</code> - The name of the Amazon Redshift database.</p></li>
/// <li>
/// <p><code> ClusterIdentifier</code> - The unique ID for the Amazon Redshift cluster.</p></li>
/// </ul></li>
/// <li>
/// <p>DatabaseCredentials - The AWS Identity and Access Management (IAM) credentials that are used to connect to the Amazon Redshift database.</p></li>
/// <li>
/// <p>SelectSqlQuery - The query that is used to retrieve the observation data for the <code>Datasource</code>.</p></li>
/// <li>
/// <p>S3StagingLocation - The Amazon Simple Storage Service (Amazon S3) location for staging Amazon Redshift data. The data retrieved from Amazon Redshift using the <code>SelectSqlQuery</code> query is stored in this location.</p></li>
/// <li>
/// <p>DataSchemaUri - 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::RedshiftDataSpec) -> Self {
self.inner = self.inner.data_spec(input);
self
}
/// <p>The data specification of an Amazon Redshift <code>DataSource</code>:</p>
/// <ul>
/// <li>
/// <p>DatabaseInformation -</p>
/// <ul>
/// <li>
/// <p><code>DatabaseName</code> - The name of the Amazon Redshift database.</p></li>
/// <li>
/// <p><code> ClusterIdentifier</code> - The unique ID for the Amazon Redshift cluster.</p></li>
/// </ul></li>
/// <li>
/// <p>DatabaseCredentials - The AWS Identity and Access Management (IAM) credentials that are used to connect to the Amazon Redshift database.</p></li>
/// <li>
/// <p>SelectSqlQuery - The query that is used to retrieve the observation data for the <code>Datasource</code>.</p></li>
/// <li>
/// <p>S3StagingLocation - The Amazon Simple Storage Service (Amazon S3) location for staging Amazon Redshift data. The data retrieved from Amazon Redshift using the <code>SelectSqlQuery</code> query is stored in this location.</p></li>
/// <li>
/// <p>DataSchemaUri - 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::RedshiftDataSpec>) -> Self {
self.inner = self.inner.set_data_spec(input);
self
}
/// <p>The data specification of an Amazon Redshift <code>DataSource</code>:</p>
/// <ul>
/// <li>
/// <p>DatabaseInformation -</p>
/// <ul>
/// <li>
/// <p><code>DatabaseName</code> - The name of the Amazon Redshift database.</p></li>
/// <li>
/// <p><code> ClusterIdentifier</code> - The unique ID for the Amazon Redshift cluster.</p></li>
/// </ul></li>
/// <li>
/// <p>DatabaseCredentials - The AWS Identity and Access Management (IAM) credentials that are used to connect to the Amazon Redshift database.</p></li>
/// <li>
/// <p>SelectSqlQuery - The query that is used to retrieve the observation data for the <code>Datasource</code>.</p></li>
/// <li>
/// <p>S3StagingLocation - The Amazon Simple Storage Service (Amazon S3) location for staging Amazon Redshift data. The data retrieved from Amazon Redshift using the <code>SelectSqlQuery</code> query is stored in this location.</p></li>
/// <li>
/// <p>DataSchemaUri - 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::RedshiftDataSpec> {
self.inner.get_data_spec()
}
/// <p>A fully specified role Amazon Resource Name (ARN). Amazon ML assumes the role on behalf of the user to create the following:</p>
/// <ul>
/// <li>
/// <p>A security group to allow Amazon ML to execute the <code>SelectSqlQuery</code> query on an Amazon Redshift cluster</p></li>
/// <li>
/// <p>An Amazon S3 bucket policy to grant Amazon ML read/write permissions on the <code>S3StagingLocation</code></p></li>
/// </ul>
pub fn role_arn(mut self, input: impl ::std::convert::Into<::std::string::String>) -> Self {
self.inner = self.inner.role_arn(input.into());
self
}
/// <p>A fully specified role Amazon Resource Name (ARN). Amazon ML assumes the role on behalf of the user to create the following:</p>
/// <ul>
/// <li>
/// <p>A security group to allow Amazon ML to execute the <code>SelectSqlQuery</code> query on an Amazon Redshift cluster</p></li>
/// <li>
/// <p>An Amazon S3 bucket policy to grant Amazon ML read/write permissions on the <code>S3StagingLocation</code></p></li>
/// </ul>
pub fn set_role_arn(mut self, input: ::std::option::Option<::std::string::String>) -> Self {
self.inner = self.inner.set_role_arn(input);
self
}
/// <p>A fully specified role Amazon Resource Name (ARN). Amazon ML assumes the role on behalf of the user to create the following:</p>
/// <ul>
/// <li>
/// <p>A security group to allow Amazon ML to execute the <code>SelectSqlQuery</code> query on an Amazon Redshift cluster</p></li>
/// <li>
/// <p>An Amazon S3 bucket policy to grant Amazon ML read/write permissions on the <code>S3StagingLocation</code></p></li>
/// </ul>
pub fn get_role_arn(&self) -> &::std::option::Option<::std::string::String> {
self.inner.get_role_arn()
}
/// <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>DataSource</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>DataSource</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>DataSource</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()
}
}