create_dataset
(**kwargs)¶Creates an empty dataset and adds it to the specified dataset group. Use CreateDatasetImportJob to import your training data to a dataset.
There are three types of datasets:
Each dataset type has an associated schema with required field types. Only the 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:
To get the status of the dataset, call DescribeDataset.
Related APIs
See also: AWS API Documentation
Request Syntax
response = client.create_dataset(
name='string',
schemaArn='string',
datasetGroupArn='string',
datasetType='string',
tags=[
{
'tagKey': 'string',
'tagValue': 'string'
},
]
)
[REQUIRED]
The name for the dataset.
[REQUIRED]
The ARN of the schema to associate with the dataset. The schema defines the dataset fields.
[REQUIRED]
The Amazon Resource Name (ARN) of the dataset group to add the dataset to.
[REQUIRED]
The type of dataset.
One of the following (case insensitive) values:
A list of tags to apply to the dataset.
The optional metadata that you apply to resources to help you categorize and organize them. Each tag consists of a key and an optional value, both of which you define. For more information see Tagging Personalize resources.
One part of a key-value pair that makes up a tag. A key is a general label that acts like a category for more specific tag values.
The optional part of a key-value pair that makes up a tag. A value acts as a descriptor within a tag category (key).
dict
Response Syntax
{
'datasetArn': 'string'
}
Response Structure
(dict) --
datasetArn (string) --
The ARN of the dataset.
Exceptions
Personalize.Client.exceptions.InvalidInputException
Personalize.Client.exceptions.ResourceNotFoundException
Personalize.Client.exceptions.ResourceAlreadyExistsException
Personalize.Client.exceptions.LimitExceededException
Personalize.Client.exceptions.ResourceInUseException
Personalize.Client.exceptions.TooManyTagsException