// Code generated by software.amazon.smithy.rust.codegen.smithy-rs. DO NOT EDIT.
pub use crate::operation::create_dataset_import_job::_create_dataset_import_job_output::CreateDatasetImportJobOutputBuilder;

pub use crate::operation::create_dataset_import_job::_create_dataset_import_job_input::CreateDatasetImportJobInputBuilder;

impl crate::operation::create_dataset_import_job::builders::CreateDatasetImportJobInputBuilder {
    /// 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_dataset_import_job::CreateDatasetImportJobOutput,
        ::aws_smithy_runtime_api::client::result::SdkError<
            crate::operation::create_dataset_import_job::CreateDatasetImportJobError,
            ::aws_smithy_runtime_api::client::orchestrator::HttpResponse,
        >,
    > {
        let mut fluent_builder = client.create_dataset_import_job();
        fluent_builder.inner = self;
        fluent_builder.send().await
    }
}
/// Fluent builder constructing a request to `CreateDatasetImportJob`.
///
/// <p>Creates a job that imports training data from your data source (an Amazon S3 bucket) to an Amazon Personalize dataset. To allow Amazon Personalize to import the training data, you must specify an IAM service role that has permission to read from the data source, as Amazon Personalize makes a copy of your data and processes it internally. For information on granting access to your Amazon S3 bucket, see <a href="https://docs.aws.amazon.com/personalize/latest/dg/granting-personalize-s3-access.html">Giving Amazon Personalize Access to Amazon S3 Resources</a>.</p>
/// <p>If you already created a recommender or deployed a custom solution version with a campaign, how new bulk records influence recommendations depends on the domain use case or recipe that you use. For more information, see <a href="https://docs.aws.amazon.com/personalize/latest/dg/how-new-data-influences-recommendations.html">How new data influences real-time recommendations</a>.</p><important>
/// <p>By default, a dataset import job replaces any existing data in the dataset that you imported in bulk. To add new records without replacing existing data, specify INCREMENTAL for the import mode in the CreateDatasetImportJob operation.</p>
/// </important>
/// <p><b>Status</b></p>
/// <p>A dataset import job can be in one of the following states:</p>
/// <ul>
/// <li>
/// <p>CREATE PENDING &gt; CREATE IN_PROGRESS &gt; ACTIVE -or- CREATE FAILED</p></li>
/// </ul>
/// <p>To get the status of the import job, call <a href="https://docs.aws.amazon.com/personalize/latest/dg/API_DescribeDatasetImportJob.html">DescribeDatasetImportJob</a>, providing the Amazon Resource Name (ARN) of the dataset import job. The dataset import is complete when the status shows as ACTIVE. If the status shows as CREATE FAILED, the response includes a <code>failureReason</code> key, which describes why the job failed.</p><note>
/// <p>Importing takes time. You must wait until the status shows as ACTIVE before training a model using the dataset.</p>
/// </note>
/// <p class="title"><b>Related APIs</b></p>
/// <ul>
/// <li>
/// <p><a href="https://docs.aws.amazon.com/personalize/latest/dg/API_ListDatasetImportJobs.html">ListDatasetImportJobs</a></p></li>
/// <li>
/// <p><a href="https://docs.aws.amazon.com/personalize/latest/dg/API_DescribeDatasetImportJob.html">DescribeDatasetImportJob</a></p></li>
/// </ul>
#[derive(::std::clone::Clone, ::std::fmt::Debug)]
pub struct CreateDatasetImportJobFluentBuilder {
    handle: ::std::sync::Arc<crate::client::Handle>,
    inner: crate::operation::create_dataset_import_job::builders::CreateDatasetImportJobInputBuilder,
    config_override: ::std::option::Option<crate::config::Builder>,
}
impl
    crate::client::customize::internal::CustomizableSend<
        crate::operation::create_dataset_import_job::CreateDatasetImportJobOutput,
        crate::operation::create_dataset_import_job::CreateDatasetImportJobError,
    > for CreateDatasetImportJobFluentBuilder
{
    fn send(
        self,
        config_override: crate::config::Builder,
    ) -> crate::client::customize::internal::BoxFuture<
        crate::client::customize::internal::SendResult<
            crate::operation::create_dataset_import_job::CreateDatasetImportJobOutput,
            crate::operation::create_dataset_import_job::CreateDatasetImportJobError,
        >,
    > {
        ::std::boxed::Box::pin(async move { self.config_override(config_override).send().await })
    }
}
impl CreateDatasetImportJobFluentBuilder {
    /// Creates a new `CreateDatasetImportJobFluentBuilder`.
    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 CreateDatasetImportJob as a reference.
    pub fn as_input(&self) -> &crate::operation::create_dataset_import_job::builders::CreateDatasetImportJobInputBuilder {
        &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_dataset_import_job::CreateDatasetImportJobOutput,
        ::aws_smithy_runtime_api::client::result::SdkError<
            crate::operation::create_dataset_import_job::CreateDatasetImportJobError,
            ::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_dataset_import_job::CreateDatasetImportJob::operation_runtime_plugins(
            self.handle.runtime_plugins.clone(),
            &self.handle.conf,
            self.config_override,
        );
        crate::operation::create_dataset_import_job::CreateDatasetImportJob::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_dataset_import_job::CreateDatasetImportJobOutput,
        crate::operation::create_dataset_import_job::CreateDatasetImportJobError,
        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>The name for the dataset import job.</p>
    pub fn job_name(mut self, input: impl ::std::convert::Into<::std::string::String>) -> Self {
        self.inner = self.inner.job_name(input.into());
        self
    }
    /// <p>The name for the dataset import job.</p>
    pub fn set_job_name(mut self, input: ::std::option::Option<::std::string::String>) -> Self {
        self.inner = self.inner.set_job_name(input);
        self
    }
    /// <p>The name for the dataset import job.</p>
    pub fn get_job_name(&self) -> &::std::option::Option<::std::string::String> {
        self.inner.get_job_name()
    }
    /// <p>The ARN of the dataset that receives the imported data.</p>
    pub fn dataset_arn(mut self, input: impl ::std::convert::Into<::std::string::String>) -> Self {
        self.inner = self.inner.dataset_arn(input.into());
        self
    }
    /// <p>The ARN of the dataset that receives the imported data.</p>
    pub fn set_dataset_arn(mut self, input: ::std::option::Option<::std::string::String>) -> Self {
        self.inner = self.inner.set_dataset_arn(input);
        self
    }
    /// <p>The ARN of the dataset that receives the imported data.</p>
    pub fn get_dataset_arn(&self) -> &::std::option::Option<::std::string::String> {
        self.inner.get_dataset_arn()
    }
    /// <p>The Amazon S3 bucket that contains the training data to import.</p>
    pub fn data_source(mut self, input: crate::types::DataSource) -> Self {
        self.inner = self.inner.data_source(input);
        self
    }
    /// <p>The Amazon S3 bucket that contains the training data to import.</p>
    pub fn set_data_source(mut self, input: ::std::option::Option<crate::types::DataSource>) -> Self {
        self.inner = self.inner.set_data_source(input);
        self
    }
    /// <p>The Amazon S3 bucket that contains the training data to import.</p>
    pub fn get_data_source(&self) -> &::std::option::Option<crate::types::DataSource> {
        self.inner.get_data_source()
    }
    /// <p>The ARN of the IAM role that has permissions to read from the Amazon S3 data source.</p>
    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>The ARN of the IAM role that has permissions to read from the Amazon S3 data source.</p>
    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>The ARN of the IAM role that has permissions to read from the Amazon S3 data source.</p>
    pub fn get_role_arn(&self) -> &::std::option::Option<::std::string::String> {
        self.inner.get_role_arn()
    }
    ///
    /// Appends an item to `tags`.
    ///
    /// To override the contents of this collection use [`set_tags`](Self::set_tags).
    ///
    /// <p>A list of <a href="https://docs.aws.amazon.com/personalize/latest/dg/tagging-resources.html">tags</a> to apply to the dataset import job.</p>
    pub fn tags(mut self, input: crate::types::Tag) -> Self {
        self.inner = self.inner.tags(input);
        self
    }
    /// <p>A list of <a href="https://docs.aws.amazon.com/personalize/latest/dg/tagging-resources.html">tags</a> to apply to the dataset import job.</p>
    pub fn set_tags(mut self, input: ::std::option::Option<::std::vec::Vec<crate::types::Tag>>) -> Self {
        self.inner = self.inner.set_tags(input);
        self
    }
    /// <p>A list of <a href="https://docs.aws.amazon.com/personalize/latest/dg/tagging-resources.html">tags</a> to apply to the dataset import job.</p>
    pub fn get_tags(&self) -> &::std::option::Option<::std::vec::Vec<crate::types::Tag>> {
        self.inner.get_tags()
    }
    /// <p>Specify how to add the new records to an existing dataset. The default import mode is <code>FULL</code>. If you haven't imported bulk records into the dataset previously, you can only specify <code>FULL</code>.</p>
    /// <ul>
    /// <li>
    /// <p>Specify <code>FULL</code> to overwrite all existing bulk data in your dataset. Data you imported individually is not replaced.</p></li>
    /// <li>
    /// <p>Specify <code>INCREMENTAL</code> to append the new records to the existing data in your dataset. Amazon Personalize replaces any record with the same ID with the new one.</p></li>
    /// </ul>
    pub fn import_mode(mut self, input: crate::types::ImportMode) -> Self {
        self.inner = self.inner.import_mode(input);
        self
    }
    /// <p>Specify how to add the new records to an existing dataset. The default import mode is <code>FULL</code>. If you haven't imported bulk records into the dataset previously, you can only specify <code>FULL</code>.</p>
    /// <ul>
    /// <li>
    /// <p>Specify <code>FULL</code> to overwrite all existing bulk data in your dataset. Data you imported individually is not replaced.</p></li>
    /// <li>
    /// <p>Specify <code>INCREMENTAL</code> to append the new records to the existing data in your dataset. Amazon Personalize replaces any record with the same ID with the new one.</p></li>
    /// </ul>
    pub fn set_import_mode(mut self, input: ::std::option::Option<crate::types::ImportMode>) -> Self {
        self.inner = self.inner.set_import_mode(input);
        self
    }
    /// <p>Specify how to add the new records to an existing dataset. The default import mode is <code>FULL</code>. If you haven't imported bulk records into the dataset previously, you can only specify <code>FULL</code>.</p>
    /// <ul>
    /// <li>
    /// <p>Specify <code>FULL</code> to overwrite all existing bulk data in your dataset. Data you imported individually is not replaced.</p></li>
    /// <li>
    /// <p>Specify <code>INCREMENTAL</code> to append the new records to the existing data in your dataset. Amazon Personalize replaces any record with the same ID with the new one.</p></li>
    /// </ul>
    pub fn get_import_mode(&self) -> &::std::option::Option<crate::types::ImportMode> {
        self.inner.get_import_mode()
    }
    /// <p>If you created a metric attribution, specify whether to publish metrics for this import job to Amazon S3</p>
    pub fn publish_attribution_metrics_to_s3(mut self, input: bool) -> Self {
        self.inner = self.inner.publish_attribution_metrics_to_s3(input);
        self
    }
    /// <p>If you created a metric attribution, specify whether to publish metrics for this import job to Amazon S3</p>
    pub fn set_publish_attribution_metrics_to_s3(mut self, input: ::std::option::Option<bool>) -> Self {
        self.inner = self.inner.set_publish_attribution_metrics_to_s3(input);
        self
    }
    /// <p>If you created a metric attribution, specify whether to publish metrics for this import job to Amazon S3</p>
    pub fn get_publish_attribution_metrics_to_s3(&self) -> &::std::option::Option<bool> {
        self.inner.get_publish_attribution_metrics_to_s3()
    }
}