Create Training Dataset

cleanroomsml_create_training_dataset

R Documentation

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"
)