1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189

// 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_output::CreateDataSourceFromS3OutputBuilder;

pub use crate::operation::create_data_source_from_s3::_create_data_source_from_s3_input::CreateDataSourceFromS3InputBuilder;

impl 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 `CreateDataSourceFromS3`.
    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 Into<crate::config::Builder>) -> Self {
        self.set_config_override(Some(config_override.into()));
        self
    }

    pub(crate) fn set_config_override(&mut self, config_override: 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()
    }
}