CfnDatasetProps
- class aws_cdk.aws_forecast.CfnDatasetProps(*, dataset_name, dataset_type, domain, schema, data_frequency=None, encryption_config=None, tags=None)
Bases:
object
Properties for defining a
CfnDataset
.- Parameters:
dataset_name (
str
) – The name of the dataset.dataset_type (
str
) – The dataset type.domain (
str
) – The domain associated with the dataset.schema (
Any
) – The schema for the dataset. The schema attributes and their order must match the fields in your data. The datasetDomain
andDatasetType
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 .data_frequency (
Optional
[str
]) – 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”.encryption_config (
Optional
[Any
]) – A Key Management Service (KMS) key and the Identity and Access Management (IAM) role that Amazon Forecast can assume to access the key.tags (
Optional
[Sequence
[Union
[TagsItemsProperty
,Dict
[str
,Any
]]]]) – An array of key-value pairs to apply to this resource. For more information, see Tag .
- Link:
http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-resource-forecast-dataset.html
- ExampleMetadata:
fixture=_generated
Example:
# The code below shows an example of how to instantiate this type. # The values are placeholders you should change. import aws_cdk.aws_forecast as forecast # encryption_config: Any # schema: Any cfn_dataset_props = forecast.CfnDatasetProps( dataset_name="datasetName", dataset_type="datasetType", domain="domain", schema=schema, # the properties below are optional data_frequency="dataFrequency", encryption_config=encryption_config, tags=[forecast.CfnDataset.TagsItemsProperty( key="key", value="value" )] )
Attributes
- data_frequency
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”.
- dataset_name
The name of the dataset.
- dataset_type
The dataset type.
- domain
The domain associated with the dataset.
- encryption_config
A Key Management Service (KMS) key and the Identity and Access Management (IAM) role that Amazon Forecast can assume to access the key.
- schema
The schema for the dataset.
The schema attributes and their order must match the fields in your data. The dataset
Domain
andDatasetType
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 .