Struct aws_sdk_forecast::client::fluent_builders::CreateDatasetImportJob

pub struct CreateDatasetImportJob<C = DynConnector, M = DefaultMiddleware, R = Standard> { /* fields omitted */ }

Fluent builder constructing a request to CreateDatasetImportJob.

Imports your training data to an Amazon Forecast dataset. You provide the location of your training data in an Amazon Simple Storage Service (Amazon S3) bucket and the Amazon Resource Name (ARN) of the dataset that you want to import the data to.

You must specify a DataSource object that includes an AWS Identity and Access Management (IAM) role that Amazon Forecast can assume to access the data, as Amazon Forecast makes a copy of your data and processes it in an internal AWS system. For more information, see aws-forecast-iam-roles.

The training data must be in CSV format. The delimiter must be a comma (,).

You can specify the path to a specific CSV file, the S3 bucket, or to a folder in the S3 bucket. For the latter two cases, Amazon Forecast imports all files up to the limit of 10,000 files.

Because dataset imports are not aggregated, your most recent dataset import is the one that is used when training a predictor or generating a forecast. Make sure that your most recent dataset import contains all of the data you want to model off of, and not just the new data collected since the previous import.

To get a list of all your dataset import jobs, filtered by specified criteria, use the ListDatasetImportJobs operation.

Implementations

impl<C, M, R> CreateDatasetImportJob<C, M, R> where
    C: SmithyConnector,
    M: SmithyMiddleware<C>,
    R: NewRequestPolicy, 

pub async fn send(
    self
) -> Result<CreateDatasetImportJobOutput, SdkError<CreateDatasetImportJobError>> where
    R::Policy: SmithyRetryPolicy<CreateDatasetImportJobInputOperationOutputAlias, CreateDatasetImportJobOutput, CreateDatasetImportJobError, CreateDatasetImportJobInputOperationRetryAlias>, 

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.

pub fn dataset_import_job_name(self, input: impl Into<String>) -> Self

The name for the dataset import job. We recommend including the current timestamp in the name, for example, 20190721DatasetImport. This can help you avoid getting a ResourceAlreadyExistsException exception.

pub fn set_dataset_import_job_name(self, input: Option<String>) -> Self

The name for the dataset import job. We recommend including the current timestamp in the name, for example, 20190721DatasetImport. This can help you avoid getting a ResourceAlreadyExistsException exception.

pub fn dataset_arn(self, input: impl Into<String>) -> Self

The Amazon Resource Name (ARN) of the Amazon Forecast dataset that you want to import data to.

pub fn set_dataset_arn(self, input: Option<String>) -> Self

The Amazon Resource Name (ARN) of the Amazon Forecast dataset that you want to import data to.

pub fn data_source(self, input: DataSource) -> Self

The location of the training data to import and an AWS Identity and Access Management (IAM) role that Amazon Forecast can assume to access the data. The training data must be stored in an Amazon S3 bucket.

If encryption is used, DataSource must include an AWS Key Management Service (KMS) key and the IAM role must allow Amazon Forecast permission to access the key. The KMS key and IAM role must match those specified in the EncryptionConfig parameter of the CreateDataset operation.

pub fn set_data_source(self, input: Option<DataSource>) -> Self

The location of the training data to import and an AWS Identity and Access Management (IAM) role that Amazon Forecast can assume to access the data. The training data must be stored in an Amazon S3 bucket.

If encryption is used, DataSource must include an AWS Key Management Service (KMS) key and the IAM role must allow Amazon Forecast permission to access the key. The KMS key and IAM role must match those specified in the EncryptionConfig parameter of the CreateDataset operation.

pub fn timestamp_format(self, input: impl Into<String>) -> Self

The format of timestamps in the dataset. The format that you specify depends on the DataFrequency specified when the dataset was created. The following formats are supported

• "yyyy-MM-dd"

  For the following data frequencies: Y, M, W, and D

• "yyyy-MM-dd HH:mm:ss"

  For the following data frequencies: H, 30min, 15min, and 1min; and optionally, for: Y, M, W, and D

If the format isn't specified, Amazon Forecast expects the format to be "yyyy-MM-dd HH:mm:ss".

pub fn set_timestamp_format(self, input: Option<String>) -> Self

The format of timestamps in the dataset. The format that you specify depends on the DataFrequency specified when the dataset was created. The following formats are supported

• "yyyy-MM-dd"

  For the following data frequencies: Y, M, W, and D

• "yyyy-MM-dd HH:mm:ss"

  For the following data frequencies: H, 30min, 15min, and 1min; and optionally, for: Y, M, W, and D

If the format isn't specified, Amazon Forecast expects the format to be "yyyy-MM-dd HH:mm:ss".

pub fn time_zone(self, input: impl Into<String>) -> Self

A single time zone for every item in your dataset. This option is ideal for datasets with all timestamps within a single time zone, or if all timestamps are normalized to a single time zone.

Refer to the Joda-Time API for a complete list of valid time zone names.

pub fn set_time_zone(self, input: Option<String>) -> Self

A single time zone for every item in your dataset. This option is ideal for datasets with all timestamps within a single time zone, or if all timestamps are normalized to a single time zone.

Refer to the Joda-Time API for a complete list of valid time zone names.

pub fn use_geolocation_for_time_zone(self, input: bool) -> Self

Automatically derive time zone information from the geolocation attribute. This option is ideal for datasets that contain timestamps in multiple time zones and those timestamps are expressed in local time.

pub fn set_use_geolocation_for_time_zone(self, input: Option<bool>) -> Self

Automatically derive time zone information from the geolocation attribute. This option is ideal for datasets that contain timestamps in multiple time zones and those timestamps are expressed in local time.

pub fn geolocation_format(self, input: impl Into<String>) -> Self

The format of the geolocation attribute. The geolocation attribute can be formatted in one of two ways:

• LAT_LONG - the latitude and longitude in decimal format (Example: 47.61_-122.33).

• CC_POSTALCODE (US Only) - the country code (US), followed by the 5-digit ZIP code (Example: US_98121).

pub fn set_geolocation_format(self, input: Option<String>) -> Self

The format of the geolocation attribute. The geolocation attribute can be formatted in one of two ways:

• LAT_LONG - the latitude and longitude in decimal format (Example: 47.61_-122.33).

• CC_POSTALCODE (US Only) - the country code (US), followed by the 5-digit ZIP code (Example: US_98121).

pub fn tags(self, input: Tag) -> Self

Appends an item to Tags.

To override the contents of this collection use set_tags.

The optional metadata that you apply to the dataset import job to help you categorize and organize them. Each tag consists of a key and an optional value, both of which you define.

The following basic restrictions apply to tags:

• Maximum number of tags per resource - 50.

• For each resource, each tag key must be unique, and each tag key can have only one value.

• Maximum key length - 128 Unicode characters in UTF-8.

• Maximum value length - 256 Unicode characters in UTF-8.

• If your tagging schema is used across multiple services and resources, remember that other services may have restrictions on allowed characters. Generally allowed characters are: letters, numbers, and spaces representable in UTF-8, and the following characters: + - = . _ : / @.

• Tag keys and values are case sensitive.

• Do not use aws:, AWS:, or any upper or lowercase combination of such as a prefix for keys as it is reserved for AWS use. You cannot edit or delete tag keys with this prefix. Values can have this prefix. If a tag value has aws as its prefix but the key does not, then Forecast considers it to be a user tag and will count against the limit of 50 tags. Tags with only the key prefix of aws do not count against your tags per resource limit.

pub fn set_tags(self, input: Option<Vec<Tag>>) -> Self

The optional metadata that you apply to the dataset import job to help you categorize and organize them. Each tag consists of a key and an optional value, both of which you define.

The following basic restrictions apply to tags:

• Maximum number of tags per resource - 50.

• For each resource, each tag key must be unique, and each tag key can have only one value.

• Maximum key length - 128 Unicode characters in UTF-8.

• Maximum value length - 256 Unicode characters in UTF-8.

• If your tagging schema is used across multiple services and resources, remember that other services may have restrictions on allowed characters. Generally allowed characters are: letters, numbers, and spaces representable in UTF-8, and the following characters: + - = . _ : / @.

• Tag keys and values are case sensitive.

• Do not use aws:, AWS:, or any upper or lowercase combination of such as a prefix for keys as it is reserved for AWS use. You cannot edit or delete tag keys with this prefix. Values can have this prefix. If a tag value has aws as its prefix but the key does not, then Forecast considers it to be a user tag and will count against the limit of 50 tags. Tags with only the key prefix of aws do not count against your tags per resource limit.

Trait Implementations

impl<C: Clone, M: Clone, R: Clone> Clone for CreateDatasetImportJob<C, M, R>

fn clone(&self) -> CreateDatasetImportJob<C, M, R>

Returns a copy of the value.

fn clone_from(&mut self, source: &Self)

Performs copy-assignment from source.

impl<C: Debug, M: Debug, R: Debug> Debug for CreateDatasetImportJob<C, M, R>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.