Creates an Amazon Forecast dataset. The information about the dataset that you provide helps Forecast understand how to consume the data for model training. This includes the following:
See https://www.paws-r-sdk.com/docs/forecastservice_create_dataset/ for full documentation.
forecastservice_create_dataset(
DatasetName,
Domain,
DatasetType,
DataFrequency = NULL,
Schema,
EncryptionConfig = NULL,
Tags = NULL
)
[required] A name for the dataset.
[required] The domain associated with the dataset. When you add a dataset to a
dataset group, this value and the value specified for the Domain
parameter of the
create_dataset_group
operation
must match.
The Domain
and DatasetType
that you choose determine the fields that
must be present in the training data that you import to the dataset. For
example, if you choose the RETAIL
domain and TARGET_TIME_SERIES
as
the DatasetType
, Amazon Forecast requires item_id
, timestamp
, and
demand
fields to be present in your data. For more information, see
Importing datasets.
[required] The dataset type. Valid values depend on the chosen Domain
.
The frequency of data collection. This parameter is required for RELATED_TIME_SERIES datasets.
Valid intervals are an integer followed by Y (Year), M (Month), W (Week), D (Day), H (Hour), and min (Minute). For example, "1D" indicates every day and "15min" indicates every 15 minutes. You cannot specify a value that would overlap with the next larger frequency. That means, for example, you cannot specify a frequency of 60 minutes, because that is equivalent to 1 hour. The valid values for each frequency are the following:
Minute - 1-59
Hour - 1-23
Day - 1-6
Week - 1-4
Month - 1-11
Year - 1
Thus, if you want every other week forecasts, specify "2W". Or, if you want quarterly forecasts, you specify "3M".
[required] The schema for the dataset. The schema attributes and their order must
match the fields in your data. The dataset Domain
and DatasetType
that you choose determine the minimum required fields in your training
data. For information about the required fields for a specific dataset
domain and type, see Dataset Domains and Dataset Types.
An Key Management Service (KMS) key and the Identity and Access Management (IAM) role that Amazon Forecast can assume to access the key.
The optional metadata that you apply to the dataset 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 Amazon Web Services
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.