Creates an empty dataset and adds it to the specified dataset group¶

Description¶

Creates an empty dataset and adds it to the specified dataset group. Use create_dataset_import_job to import your training data to a dataset.

There are 5 types of datasets:

• Item interactions
• Items
• Users
• Action interactions
• Actions

Each dataset type has an associated schema with required field types. Only the Item interactions dataset is required in order to train a model (also referred to as creating a solution).

A dataset can be in one of the following states:

• CREATE PENDING > CREATE IN_PROGRESS > ACTIVE -or- CREATE FAILED
• DELETE PENDING > DELETE IN_PROGRESS

To get the status of the dataset, call describe_dataset.

Related APIs

• create_dataset_group
• list_datasets
• describe_dataset
• delete_dataset

Usage¶

personalize_create_dataset(name, schemaArn, datasetGroupArn,
  datasetType, tags)

Arguments¶

• name

  [required] The name for the dataset.

• schemaArn

  [required] The ARN of the schema to associate with the dataset. The schema defines the dataset fields.

• datasetGroupArn

  [required] The Amazon Resource Name (ARN) of the dataset group to add the dataset to.

• datasetType

  [required] The type of dataset.

  One of the following (case insensitive) values:

  • Interactions
  • Items
  • Users
  • Actions
  • Action_Interactions

• tags

  A list of tags to apply to the dataset.

Value¶

A list with the following syntax:

list(
  datasetArn = "string"
)

Request syntax¶

svc$create_dataset(
  name = "string",
  schemaArn = "string",
  datasetGroupArn = "string",
  datasetType = "string",
  tags = list(
    list(
      tagKey = "string",
      tagValue = "string"
    )
  )
)