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Class: Aws::ForecastService::Types::CreateDatasetImportJobRequest

Inherits:
Struct
  • Object
show all
Defined in:
(unknown)

Overview

Note:

When passing CreateDatasetImportJobRequest as input to an Aws::Client method, you can use a vanilla Hash:

{
  dataset_import_job_name: "Name", # required
  dataset_arn: "Arn", # required
  data_source: { # required
    s3_config: { # required
      path: "S3Path", # required
      role_arn: "Arn", # required
      kms_key_arn: "KMSKeyArn",
    },
  },
  timestamp_format: "TimestampFormat",
  tags: [
    {
      key: "TagKey", # required
      value: "TagValue", # required
    },
  ],
}

See Also:

Instance Attribute Summary collapse

Instance Attribute Details

#data_source ⇒ Types::DataSource

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.

Returns:

  • (Types::DataSource) —

    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.

#dataset_arn ⇒ String

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

Returns:

  • (String) —

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

#dataset_import_job_name ⇒ String

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.

Returns:

  • (String) —

    The name for the dataset import job.

#tags ⇒ Array<Types::Tag>

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.

Returns:

  • (Array<Types::Tag>) —

    The optional metadata that you apply to the dataset import job to help you categorize and organize them.

#timestamp_format ⇒ String

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\".

Returns:

  • (String) —

    The format of timestamps in the dataset.