Defines the information necessary to create a training dataset¶

Description¶

Defines the information necessary to create a training dataset. In Clean Rooms ML, the TrainingDataset is metadata that points to a Glue table, which is read only during AudienceModel creation.

Usage¶

cleanroomsml_create_training_dataset(name, roleArn, trainingData, tags,
  description)

Arguments¶

• name

  [required] The name of the training dataset. This name must be unique in your account and region.

• roleArn

  [required] The ARN of the IAM role that Clean Rooms ML can assume to read the data referred to in the dataSource field of each dataset.

  Passing a role across AWS accounts is not allowed. If you pass a role that isn't in your account, you get an AccessDeniedException error.

• trainingData

  [required] An array of information that lists the Dataset objects, which specifies the dataset type and details on its location and schema. You must provide a role that has read access to these tables.

• tags

  The optional metadata that you apply to the resource 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 Clean Rooms ML 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.

• description

  The description of the training dataset.

Value¶

A list with the following syntax:

list(
  trainingDatasetArn = "string"
)

Request syntax¶

svc$create_training_dataset(
  name = "string",
  roleArn = "string",
  trainingData = list(
    list(
      type = "INTERACTIONS",
      inputConfig = list(
        schema = list(
          list(
            columnName = "string",
            columnTypes = list(
              "USER_ID"|"ITEM_ID"|"TIMESTAMP"|"CATEGORICAL_FEATURE"|"NUMERICAL_FEATURE"
            )
          )
        ),
        dataSource = list(
          glueDataSource = list(
            tableName = "string",
            databaseName = "string",
            catalogId = "string"
          )
        )
      )
    )
  ),
  tags = list(
    "string"
  ),
  description = "string"
)