Struct aws_sdk_forecast::client::fluent_builders::CreateDatasetGroup

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

Fluent builder constructing a request to CreateDatasetGroup.

Creates a dataset group, which holds a collection of related datasets. You can add datasets to the dataset group when you create the dataset group, or later by using the UpdateDatasetGroup operation.

After creating a dataset group and adding datasets, you use the dataset group when you create a predictor. For more information, see howitworks-datasets-groups.

To get a list of all your datasets groups, use the ListDatasetGroups operation.

The Status of a dataset group must be ACTIVE before you can use the dataset group to create a predictor. To get the status, use the DescribeDatasetGroup operation.

Implementations

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

pub async fn send(
    self
) -> Result<CreateDatasetGroupOutput, SdkError<CreateDatasetGroupError>> where
    R::Policy: SmithyRetryPolicy<CreateDatasetGroupInputOperationOutputAlias, CreateDatasetGroupOutput, CreateDatasetGroupError, CreateDatasetGroupInputOperationRetryAlias>, 

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_group_name(self, input: impl Into<String>) -> Self

A name for the dataset group.

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

A name for the dataset group.

pub fn domain(self, input: Domain) -> Self

The domain associated with the dataset group. When you add a dataset to a dataset group, this value and the value specified for the Domain parameter of the CreateDataset operation must match.

The Domain and DatasetType that you choose determine the fields that must be present in training data that you import to a dataset. For example, if you choose the RETAIL domain and TARGET_TIME_SERIES as the DatasetType, Amazon Forecast requires that item_id, timestamp, and demand fields are present in your data. For more information, see howitworks-datasets-groups.

pub fn set_domain(self, input: Option<Domain>) -> Self

The domain associated with the dataset group. When you add a dataset to a dataset group, this value and the value specified for the Domain parameter of the CreateDataset operation must match.

The Domain and DatasetType that you choose determine the fields that must be present in training data that you import to a dataset. For example, if you choose the RETAIL domain and TARGET_TIME_SERIES as the DatasetType, Amazon Forecast requires that item_id, timestamp, and demand fields are present in your data. For more information, see howitworks-datasets-groups.

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

Appends an item to DatasetArns.

To override the contents of this collection use set_dataset_arns.

An array of Amazon Resource Names (ARNs) of the datasets that you want to include in the dataset group.

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

An array of Amazon Resource Names (ARNs) of the datasets that you want to include in the dataset group.

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 group 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 group 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 CreateDatasetGroup<C, M, R>

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

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

Formats the value using the given formatter.