2020/07/08 - Amazon Forecast Service - 3 new 6 updated api methods
Changes With this release, Amazon Forecast now supports the ability to add a tag to any resource via the launch of three new APIs: TagResouce, UntagResource and ListTagsForResource. A tag is a simple label consisting of a customer-defined key and an optional value allowing for easier resource management.
Deletes the specified tags from a resource.
See also: AWS API Documentation
Request Syntax
client.untag_resource(
ResourceArn='string',
TagKeys=[
'string',
]
)
string
[REQUIRED]
The Amazon Resource Name (ARN) that identifies the resource for which to list the tags. Currently, the supported resources are Forecast dataset groups, datasets, dataset import jobs, predictors, forecasts, and forecast exports.
list
[REQUIRED]
The keys of the tags to be removed.
(string) --
dict
Response Syntax
{}
Response Structure
(dict) --
Associates the specified tags to a resource with the specified resourceArn . If existing tags on a resource are not specified in the request parameters, they are not changed. When a resource is deleted, the tags associated with that resource are also deleted.
See also: AWS API Documentation
Request Syntax
client.tag_resource(
ResourceArn='string',
Tags=[
{
'Key': 'string',
'Value': 'string'
},
]
)
string
[REQUIRED]
The Amazon Resource Name (ARN) that identifies the resource for which to list the tags. Currently, the supported resources are Forecast dataset groups, datasets, dataset import jobs, predictors, forecasts, and forecast export jobs.
list
[REQUIRED]
The tags to add to the resource. A tag is an array of key-value pairs.
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 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.
(dict) --
The optional metadata that you apply to a 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 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.
Key (string) -- [REQUIRED]
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.
Value (string) -- [REQUIRED]
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
{}
Response Structure
(dict) --
Lists the tags for an Amazon Forecast resource.
See also: AWS API Documentation
Request Syntax
client.list_tags_for_resource(
ResourceArn='string'
)
string
[REQUIRED]
The Amazon Resource Name (ARN) that identifies the resource for which to list the tags. Currently, the supported resources are Forecast dataset groups, datasets, dataset import jobs, predictors, forecasts, and forecast export jobs.
dict
Response Syntax
{
'Tags': [
{
'Key': 'string',
'Value': 'string'
},
]
}
Response Structure
(dict) --
Tags (list) --
The tags for the resource.
(dict) --
The optional metadata that you apply to a 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 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.
Key (string) --
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.
Value (string) --
The optional part of a key-value pair that makes up a tag. A value acts as a descriptor within a tag category (key).
{'Tags': [{'Key': 'string', 'Value': 'string'}]}
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:
*DataFrequency * - How frequently your historical time-series data is collected.
*Domain * and * DatasetType * - Each dataset has an associated dataset domain and a type within the domain. Amazon Forecast provides a list of predefined domains and types within each domain. For each unique dataset domain and type within the domain, Amazon Forecast requires your data to include a minimum set of predefined fields.
*Schema * - A schema specifies the fields in the dataset, including the field name and data type.
After creating a dataset, you import your training data into it and add the dataset to a dataset group. You use the dataset group to create a predictor. For more information, see howitworks-datasets-groups .
To get a list of all your datasets, use the ListDatasets operation.
For example Forecast datasets, see the Amazon Forecast Sample GitHub repository .
Note
The Status of a dataset must be ACTIVE before you can import training data. Use the DescribeDataset operation to get the status.
See also: AWS API Documentation
Request Syntax
client.create_dataset(
DatasetName='string',
Domain='RETAIL'|'CUSTOM'|'INVENTORY_PLANNING'|'EC2_CAPACITY'|'WORK_FORCE'|'WEB_TRAFFIC'|'METRICS',
DatasetType='TARGET_TIME_SERIES'|'RELATED_TIME_SERIES'|'ITEM_METADATA',
DataFrequency='string',
Schema={
'Attributes': [
{
'AttributeName': 'string',
'AttributeType': 'string'|'integer'|'float'|'timestamp'
},
]
},
EncryptionConfig={
'RoleArn': 'string',
'KMSKeyArn': 'string'
},
Tags=[
{
'Key': 'string',
'Value': 'string'
},
]
)
string
[REQUIRED]
A name for the dataset.
string
[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 CreateDatasetGroup 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 howitworks-datasets-groups .
string
[REQUIRED]
The dataset type. Valid values depend on the chosen Domain .
string
The frequency of data collection. This parameter is required for RELATED_TIME_SERIES datasets.
Valid intervals are Y (Year), M (Month), W (Week), D (Day), H (Hour), 30min (30 minutes), 15min (15 minutes), 10min (10 minutes), 5min (5 minutes), and 1min (1 minute). For example, "D" indicates every day and "15min" indicates every 15 minutes.
dict
[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 howitworks-domains-ds-types .
Attributes (list) --
An array of attributes specifying the name and type of each field in a dataset.
(dict) --
An attribute of a schema, which defines a dataset field. A schema attribute is required for every field in a dataset. The Schema object contains an array of SchemaAttribute objects.
AttributeName (string) --
The name of the dataset field.
AttributeType (string) --
The data type of the field.
dict
An AWS Key Management Service (KMS) key and the AWS Identity and Access Management (IAM) role that Amazon Forecast can assume to access the key.
RoleArn (string) -- [REQUIRED]
The ARN of the IAM role that Amazon Forecast can assume to access the AWS KMS key.
Passing a role across AWS accounts is not allowed. If you pass a role that isn't in your account, you get an InvalidInputException error.
KMSKeyArn (string) -- [REQUIRED]
The Amazon Resource Name (ARN) of the KMS key.
list
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 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 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.
(dict) --
The optional metadata that you apply to a 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 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.
Key (string) -- [REQUIRED]
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.
Value (string) -- [REQUIRED]
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 Amazon Resource Name (ARN) of the dataset.
{'Tags': [{'Key': 'string', 'Value': 'string'}]}
Creates a dataset group, which holds a collection of related datasets. You can add datasets to the dataset group when you create the dataset group, or later by using the UpdateDatasetGroup operation.
After creating a dataset group and adding datasets, you use the dataset group when you create a predictor. For more information, see howitworks-datasets-groups .
To get a list of all your datasets groups, use the ListDatasetGroups operation.
Note
The Status of a dataset group must be ACTIVE before you can create use the dataset group to create a predictor. To get the status, use the DescribeDatasetGroup operation.
See also: AWS API Documentation
Request Syntax
client.create_dataset_group(
DatasetGroupName='string',
Domain='RETAIL'|'CUSTOM'|'INVENTORY_PLANNING'|'EC2_CAPACITY'|'WORK_FORCE'|'WEB_TRAFFIC'|'METRICS',
DatasetArns=[
'string',
],
Tags=[
{
'Key': 'string',
'Value': 'string'
},
]
)
string
[REQUIRED]
A name for the dataset group.
string
[REQUIRED]
The domain associated with the dataset group. When you add a dataset to a dataset group, this value and the value specified for the Domain parameter of the CreateDataset operation must match.
The Domain and DatasetType that you choose determine the fields that must be present in training data that you import to a dataset. For example, if you choose the RETAIL domain and TARGET_TIME_SERIES as the DatasetType , Amazon Forecast requires that item_id , timestamp , and demand fields are present in your data. For more information, see howitworks-datasets-groups .
list
An array of Amazon Resource Names (ARNs) of the datasets that you want to include in the dataset group.
(string) --
list
The optional metadata that you apply to the dataset group 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 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.
(dict) --
The optional metadata that you apply to a 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 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.
Key (string) -- [REQUIRED]
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.
Value (string) -- [REQUIRED]
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
{
'DatasetGroupArn': 'string'
}
Response Structure
(dict) --
DatasetGroupArn (string) --
The Amazon Resource Name (ARN) of the dataset group.
{'Tags': [{'Key': 'string', 'Value': 'string'}]}
Imports your training data to an Amazon Forecast dataset. You provide the location of your training data in an Amazon Simple Storage Service (Amazon S3) bucket and the Amazon Resource Name (ARN) of the dataset that you want to import the data to.
You must specify a DataSource object that includes an AWS Identity and Access Management (IAM) role that Amazon Forecast can assume to access the data, as Amazon Forecast makes a copy of your data and processes it in an internal AWS system. For more information, see aws-forecast-iam-roles .
The training data must be in CSV format. The delimiter must be a comma (,).
You can specify the path to a specific CSV file, the S3 bucket, or to a folder in the S3 bucket. For the latter two cases, Amazon Forecast imports all files up to the limit of 10,000 files.
Because dataset imports are not aggregated, your most recent dataset import is the one that is used when training a predictor or generating a forecast. Make sure that your most recent dataset import contains all of the data you want to model off of, and not just the new data collected since the previous import.
To get a list of all your dataset import jobs, filtered by specified criteria, use the ListDatasetImportJobs operation.
See also: AWS API Documentation
Request Syntax
client.create_dataset_import_job(
DatasetImportJobName='string',
DatasetArn='string',
DataSource={
'S3Config': {
'Path': 'string',
'RoleArn': 'string',
'KMSKeyArn': 'string'
}
},
TimestampFormat='string',
Tags=[
{
'Key': 'string',
'Value': 'string'
},
]
)
string
[REQUIRED]
The name for the dataset import job. We recommend including the current timestamp in the name, for example, 20190721DatasetImport . This can help you avoid getting a ResourceAlreadyExistsException exception.
string
[REQUIRED]
The Amazon Resource Name (ARN) of the Amazon Forecast dataset that you want to import data to.
dict
[REQUIRED]
The location of the training data to import and an AWS Identity and Access Management (IAM) role that Amazon Forecast can assume to access the data. The training data must be stored in an Amazon S3 bucket.
If encryption is used, DataSource must include an AWS Key Management Service (KMS) key and the IAM role must allow Amazon Forecast permission to access the key. The KMS key and IAM role must match those specified in the EncryptionConfig parameter of the CreateDataset operation.
S3Config (dict) -- [REQUIRED]
The path to the training data stored in an Amazon Simple Storage Service (Amazon S3) bucket along with the credentials to access the data.
Path (string) -- [REQUIRED]
The path to an Amazon Simple Storage Service (Amazon S3) bucket or file(s) in an Amazon S3 bucket.
RoleArn (string) -- [REQUIRED]
The ARN of the AWS Identity and Access Management (IAM) role that Amazon Forecast can assume to access the Amazon S3 bucket or files. If you provide a value for the KMSKeyArn key, the role must allow access to the key.
Passing a role across AWS accounts is not allowed. If you pass a role that isn't in your account, you get an InvalidInputException error.
KMSKeyArn (string) --
The Amazon Resource Name (ARN) of an AWS Key Management Service (KMS) key.
string
The format of timestamps in the dataset. The format that you specify depends on the DataFrequency specified when the dataset was created. The following formats are supported
"yyyy-MM-dd" For the following data frequencies: Y, M, W, and D
"yyyy-MM-dd HH:mm:ss" For the following data frequencies: H, 30min, 15min, and 1min; and optionally, for: Y, M, W, and D
If the format isn't specified, Amazon Forecast expects the format to be "yyyy-MM-dd HH:mm:ss".
list
The optional metadata that you apply to the dataset import job 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 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.
(dict) --
The optional metadata that you apply to a 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 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.
Key (string) -- [REQUIRED]
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.
Value (string) -- [REQUIRED]
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
{
'DatasetImportJobArn': 'string'
}
Response Structure
(dict) --
DatasetImportJobArn (string) --
The Amazon Resource Name (ARN) of the dataset import job.
{'Tags': [{'Key': 'string', 'Value': 'string'}]}
Creates a forecast for each item in the TARGET_TIME_SERIES dataset that was used to train the predictor. This is known as inference. To retrieve the forecast for a single item at low latency, use the operation. To export the complete forecast into your Amazon Simple Storage Service (Amazon S3) bucket, use the CreateForecastExportJob operation.
The range of the forecast is determined by the ForecastHorizon value, which you specify in the CreatePredictor request. When you query a forecast, you can request a specific date range within the forecast.
To get a list of all your forecasts, use the ListForecasts operation.
Note
The forecasts generated by Amazon Forecast are in the same time zone as the dataset that was used to create the predictor.
For more information, see howitworks-forecast .
Note
The Status of the forecast must be ACTIVE before you can query or export the forecast. Use the DescribeForecast operation to get the status.
See also: AWS API Documentation
Request Syntax
client.create_forecast(
ForecastName='string',
PredictorArn='string',
ForecastTypes=[
'string',
],
Tags=[
{
'Key': 'string',
'Value': 'string'
},
]
)
string
[REQUIRED]
A name for the forecast.
string
[REQUIRED]
The Amazon Resource Name (ARN) of the predictor to use to generate the forecast.
list
The quantiles at which probabilistic forecasts are generated. You can currently specify up to 5 quantiles per forecast . Accepted values include 0.01 to 0.99 (increments of .01 only) and mean . The mean forecast is different from the median (0.50) when the distribution is not symmetric (for example, Beta and Negative Binomial). The default value is ["0.1", "0.5", "0.9"] .
(string) --
list
The optional metadata that you apply to the forecast 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 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.
(dict) --
The optional metadata that you apply to a 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 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.
Key (string) -- [REQUIRED]
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.
Value (string) -- [REQUIRED]
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
{
'ForecastArn': 'string'
}
Response Structure
(dict) --
ForecastArn (string) --
The Amazon Resource Name (ARN) of the forecast.
{'Tags': [{'Key': 'string', 'Value': 'string'}]}
Exports a forecast created by the CreateForecast operation to your Amazon Simple Storage Service (Amazon S3) bucket. The forecast file name will match the following conventions:
<ForecastExportJobName>_<ExportTimestamp>_<PartNumber>
where the <ExportTimestamp> component is in Java SimpleDateFormat (yyyy-MM-ddTHH-mm-ssZ).
You must specify a DataDestination object that includes an AWS Identity and Access Management (IAM) role that Amazon Forecast can assume to access the Amazon S3 bucket. For more information, see aws-forecast-iam-roles .
For more information, see howitworks-forecast .
To get a list of all your forecast export jobs, use the ListForecastExportJobs operation.
Note
The Status of the forecast export job must be ACTIVE before you can access the forecast in your Amazon S3 bucket. To get the status, use the DescribeForecastExportJob operation.
See also: AWS API Documentation
Request Syntax
client.create_forecast_export_job(
ForecastExportJobName='string',
ForecastArn='string',
Destination={
'S3Config': {
'Path': 'string',
'RoleArn': 'string',
'KMSKeyArn': 'string'
}
},
Tags=[
{
'Key': 'string',
'Value': 'string'
},
]
)
string
[REQUIRED]
The name for the forecast export job.
string
[REQUIRED]
The Amazon Resource Name (ARN) of the forecast that you want to export.
dict
[REQUIRED]
The location where you want to save the forecast and an AWS Identity and Access Management (IAM) role that Amazon Forecast can assume to access the location. The forecast must be exported to an Amazon S3 bucket.
If encryption is used, Destination must include an AWS Key Management Service (KMS) key. The IAM role must allow Amazon Forecast permission to access the key.
S3Config (dict) -- [REQUIRED]
The path to an Amazon Simple Storage Service (Amazon S3) bucket along with the credentials to access the bucket.
Path (string) -- [REQUIRED]
The path to an Amazon Simple Storage Service (Amazon S3) bucket or file(s) in an Amazon S3 bucket.
RoleArn (string) -- [REQUIRED]
The ARN of the AWS Identity and Access Management (IAM) role that Amazon Forecast can assume to access the Amazon S3 bucket or files. If you provide a value for the KMSKeyArn key, the role must allow access to the key.
Passing a role across AWS accounts is not allowed. If you pass a role that isn't in your account, you get an InvalidInputException error.
KMSKeyArn (string) --
The Amazon Resource Name (ARN) of an AWS Key Management Service (KMS) key.
list
The optional metadata that you apply to the forecast export job 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 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.
(dict) --
The optional metadata that you apply to a 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 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.
Key (string) -- [REQUIRED]
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.
Value (string) -- [REQUIRED]
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
{
'ForecastExportJobArn': 'string'
}
Response Structure
(dict) --
ForecastExportJobArn (string) --
The Amazon Resource Name (ARN) of the export job.
{'Tags': [{'Key': 'string', 'Value': 'string'}]}
Creates an Amazon Forecast predictor.
In the request, you provide a dataset group and either specify an algorithm or let Amazon Forecast choose the algorithm for you using AutoML. If you specify an algorithm, you also can override algorithm-specific hyperparameters.
Amazon Forecast uses the chosen algorithm to train a model using the latest version of the datasets in the specified dataset group. The result is called a predictor. You then generate a forecast using the CreateForecast operation.
After training a model, the CreatePredictor operation also evaluates it. To see the evaluation metrics, use the GetAccuracyMetrics operation. Always review the evaluation metrics before deciding to use the predictor to generate a forecast.
Optionally, you can specify a featurization configuration to fill and aggregate the data fields in the TARGET_TIME_SERIES dataset to improve model training. For more information, see FeaturizationConfig .
For RELATED_TIME_SERIES datasets, CreatePredictor verifies that the DataFrequency specified when the dataset was created matches the ForecastFrequency . TARGET_TIME_SERIES datasets don't have this restriction. Amazon Forecast also verifies the delimiter and timestamp format. For more information, see howitworks-datasets-groups .
AutoML
If you want Amazon Forecast to evaluate each algorithm and choose the one that minimizes the objective function , set PerformAutoML to true . The objective function is defined as the mean of the weighted p10, p50, and p90 quantile losses. For more information, see EvaluationResult .
When AutoML is enabled, the following properties are disallowed:
AlgorithmArn
HPOConfig
PerformHPO
TrainingParameters
To get a list of all of your predictors, use the ListPredictors operation.
Note
Before you can use the predictor to create a forecast, the Status of the predictor must be ACTIVE , signifying that training has completed. To get the status, use the DescribePredictor operation.
See also: AWS API Documentation
Request Syntax
client.create_predictor(
PredictorName='string',
AlgorithmArn='string',
ForecastHorizon=123,
PerformAutoML=True|False,
PerformHPO=True|False,
TrainingParameters={
'string': 'string'
},
EvaluationParameters={
'NumberOfBacktestWindows': 123,
'BackTestWindowOffset': 123
},
HPOConfig={
'ParameterRanges': {
'CategoricalParameterRanges': [
{
'Name': 'string',
'Values': [
'string',
]
},
],
'ContinuousParameterRanges': [
{
'Name': 'string',
'MaxValue': 123.0,
'MinValue': 123.0,
'ScalingType': 'Auto'|'Linear'|'Logarithmic'|'ReverseLogarithmic'
},
],
'IntegerParameterRanges': [
{
'Name': 'string',
'MaxValue': 123,
'MinValue': 123,
'ScalingType': 'Auto'|'Linear'|'Logarithmic'|'ReverseLogarithmic'
},
]
}
},
InputDataConfig={
'DatasetGroupArn': 'string',
'SupplementaryFeatures': [
{
'Name': 'string',
'Value': 'string'
},
]
},
FeaturizationConfig={
'ForecastFrequency': 'string',
'ForecastDimensions': [
'string',
],
'Featurizations': [
{
'AttributeName': 'string',
'FeaturizationPipeline': [
{
'FeaturizationMethodName': 'filling',
'FeaturizationMethodParameters': {
'string': 'string'
}
},
]
},
]
},
EncryptionConfig={
'RoleArn': 'string',
'KMSKeyArn': 'string'
},
Tags=[
{
'Key': 'string',
'Value': 'string'
},
]
)
string
[REQUIRED]
A name for the predictor.
string
The Amazon Resource Name (ARN) of the algorithm to use for model training. Required if PerformAutoML is not set to true .
Supported algorithms:
arn:aws:forecast:::algorithm/ARIMA
arn:aws:forecast:::algorithm/Deep_AR_Plus Supports hyperparameter optimization (HPO)
arn:aws:forecast:::algorithm/ETS
arn:aws:forecast:::algorithm/NPTS
arn:aws:forecast:::algorithm/Prophet
integer
[REQUIRED]
Specifies the number of time-steps that the model is trained to predict. The forecast horizon is also called the prediction length.
For example, if you configure a dataset for daily data collection (using the DataFrequency parameter of the CreateDataset operation) and set the forecast horizon to 10, the model returns predictions for 10 days.
The maximum forecast horizon is the lesser of 500 time-steps or 1/3 of the TARGET_TIME_SERIES dataset length.
boolean
Whether to perform AutoML. When Amazon Forecast performs AutoML, it evaluates the algorithms it provides and chooses the best algorithm and configuration for your training dataset.
The default value is false . In this case, you are required to specify an algorithm.
Set PerformAutoML to true to have Amazon Forecast perform AutoML. This is a good option if you aren't sure which algorithm is suitable for your training data. In this case, PerformHPO must be false.
boolean
Whether to perform hyperparameter optimization (HPO). HPO finds optimal hyperparameter values for your training data. The process of performing HPO is known as running a hyperparameter tuning job.
The default value is false . In this case, Amazon Forecast uses default hyperparameter values from the chosen algorithm.
To override the default values, set PerformHPO to true and, optionally, supply the HyperParameterTuningJobConfig object. The tuning job specifies a metric to optimize, which hyperparameters participate in tuning, and the valid range for each tunable hyperparameter. In this case, you are required to specify an algorithm and PerformAutoML must be false.
The following algorithm supports HPO:
DeepAR+
dict
The hyperparameters to override for model training. The hyperparameters that you can override are listed in the individual algorithms. For the list of supported algorithms, see aws-forecast-choosing-recipes .
(string) --
(string) --
dict
Used to override the default evaluation parameters of the specified algorithm. Amazon Forecast evaluates a predictor by splitting a dataset into training data and testing data. The evaluation parameters define how to perform the split and the number of iterations.
NumberOfBacktestWindows (integer) --
The number of times to split the input data. The default is 1. Valid values are 1 through 5.
BackTestWindowOffset (integer) --
The point from the end of the dataset where you want to split the data for model training and testing (evaluation). Specify the value as the number of data points. The default is the value of the forecast horizon. BackTestWindowOffset can be used to mimic a past virtual forecast start date. This value must be greater than or equal to the forecast horizon and less than half of the TARGET_TIME_SERIES dataset length.
ForecastHorizon <= BackTestWindowOffset < 1/2 * TARGET_TIME_SERIES dataset length
dict
Provides hyperparameter override values for the algorithm. If you don't provide this parameter, Amazon Forecast uses default values. The individual algorithms specify which hyperparameters support hyperparameter optimization (HPO). For more information, see aws-forecast-choosing-recipes .
If you included the HPOConfig object, you must set PerformHPO to true.
ParameterRanges (dict) --
Specifies the ranges of valid values for the hyperparameters.
CategoricalParameterRanges (list) --
Specifies the tunable range for each categorical hyperparameter.
(dict) --
Specifies a categorical hyperparameter and it's range of tunable values. This object is part of the ParameterRanges object.
Name (string) -- [REQUIRED]
The name of the categorical hyperparameter to tune.
Values (list) -- [REQUIRED]
A list of the tunable categories for the hyperparameter.
(string) --
ContinuousParameterRanges (list) --
Specifies the tunable range for each continuous hyperparameter.
(dict) --
Specifies a continuous hyperparameter and it's range of tunable values. This object is part of the ParameterRanges object.
Name (string) -- [REQUIRED]
The name of the hyperparameter to tune.
MaxValue (float) -- [REQUIRED]
The maximum tunable value of the hyperparameter.
MinValue (float) -- [REQUIRED]
The minimum tunable value of the hyperparameter.
ScalingType (string) --
The scale that hyperparameter tuning uses to search the hyperparameter range. Valid values:
Auto
Amazon Forecast hyperparameter tuning chooses the best scale for the hyperparameter.
Linear
Hyperparameter tuning searches the values in the hyperparameter range by using a linear scale.
Logarithmic
Hyperparameter tuning searches the values in the hyperparameter range by using a logarithmic scale.
Logarithmic scaling works only for ranges that have values greater than 0.
ReverseLogarithmic
hyperparameter tuning searches the values in the hyperparameter range by using a reverse logarithmic scale.
Reverse logarithmic scaling works only for ranges that are entirely within the range 0 <= x < 1.0.
For information about choosing a hyperparameter scale, see Hyperparameter Scaling . One of the following values:
IntegerParameterRanges (list) --
Specifies the tunable range for each integer hyperparameter.
(dict) --
Specifies an integer hyperparameter and it's range of tunable values. This object is part of the ParameterRanges object.
Name (string) -- [REQUIRED]
The name of the hyperparameter to tune.
MaxValue (integer) -- [REQUIRED]
The maximum tunable value of the hyperparameter.
MinValue (integer) -- [REQUIRED]
The minimum tunable value of the hyperparameter.
ScalingType (string) --
The scale that hyperparameter tuning uses to search the hyperparameter range. Valid values:
Auto
Amazon Forecast hyperparameter tuning chooses the best scale for the hyperparameter.
Linear
Hyperparameter tuning searches the values in the hyperparameter range by using a linear scale.
Logarithmic
Hyperparameter tuning searches the values in the hyperparameter range by using a logarithmic scale.
Logarithmic scaling works only for ranges that have values greater than 0.
ReverseLogarithmic
Not supported for IntegerParameterRange .
Reverse logarithmic scaling works only for ranges that are entirely within the range 0 <= x < 1.0.
For information about choosing a hyperparameter scale, see Hyperparameter Scaling . One of the following values:
dict
[REQUIRED]
Describes the dataset group that contains the data to use to train the predictor.
DatasetGroupArn (string) -- [REQUIRED]
The Amazon Resource Name (ARN) of the dataset group.
SupplementaryFeatures (list) --
An array of supplementary features. The only supported feature is a holiday calendar.
(dict) --
Describes a supplementary feature of a dataset group. This object is part of the InputDataConfig object.
The only supported feature is a holiday calendar. If you use the calendar, all data in the datasets should belong to the same country as the calendar. For the holiday calendar data, see the Jollyday web site.
India and Korea's holidays are not included in the Jollyday library, but both are supported by Amazon Forecast. Their holidays are:
"IN" - INDIA
JANUARY 26 - REPUBLIC DAY
AUGUST 15 - INDEPENDENCE DAY
OCTOBER 2 GANDHI'S BIRTHDAY
"KR" - KOREA
JANUARY 1 - NEW YEAR
MARCH 1 - INDEPENDENCE MOVEMENT DAY
MAY 5 - CHILDREN'S DAY
JUNE 6 - MEMORIAL DAY
AUGUST 15 - LIBERATION DAY
OCTOBER 3 - NATIONAL FOUNDATION DAY
OCTOBER 9 - HANGEUL DAY
DECEMBER 25 - CHRISTMAS DAY
Name (string) -- [REQUIRED]
The name of the feature. This must be "holiday".
Value (string) -- [REQUIRED]
One of the following 2 letter country codes:
"AR" - ARGENTINA
"AT" - AUSTRIA
"AU" - AUSTRALIA
"BE" - BELGIUM
"BR" - BRAZIL
"CA" - CANADA
"CN" - CHINA
"CZ" - CZECH REPUBLIC
"DK" - DENMARK
"EC" - ECUADOR
"FI" - FINLAND
"FR" - FRANCE
"DE" - GERMANY
"HU" - HUNGARY
"IE" - IRELAND
"IN" - INDIA
"IT" - ITALY
"JP" - JAPAN
"KR" - KOREA
"LU" - LUXEMBOURG
"MX" - MEXICO
"NL" - NETHERLANDS
"NO" - NORWAY
"PL" - POLAND
"PT" - PORTUGAL
"RU" - RUSSIA
"ZA" - SOUTH AFRICA
"ES" - SPAIN
"SE" - SWEDEN
"CH" - SWITZERLAND
"US" - UNITED STATES
"UK" - UNITED KINGDOM
dict
[REQUIRED]
The featurization configuration.
ForecastFrequency (string) -- [REQUIRED]
The frequency of predictions in a forecast.
Valid intervals are Y (Year), M (Month), W (Week), D (Day), H (Hour), 30min (30 minutes), 15min (15 minutes), 10min (10 minutes), 5min (5 minutes), and 1min (1 minute). For example, "Y" indicates every year and "5min" indicates every five minutes.
The frequency must be greater than or equal to the TARGET_TIME_SERIES dataset frequency.
When a RELATED_TIME_SERIES dataset is provided, the frequency must be equal to the RELATED_TIME_SERIES dataset frequency.
ForecastDimensions (list) --
An array of dimension (field) names that specify how to group the generated forecast.
For example, suppose that you are generating a forecast for item sales across all of your stores, and your dataset contains a store_id field. If you want the sales forecast for each item by store, you would specify store_id as the dimension.
All forecast dimensions specified in the TARGET_TIME_SERIES dataset don't need to be specified in the CreatePredictor request. All forecast dimensions specified in the RELATED_TIME_SERIES dataset must be specified in the CreatePredictor request.
(string) --
Featurizations (list) --
An array of featurization (transformation) information for the fields of a dataset.
(dict) --
Provides featurization (transformation) information for a dataset field. This object is part of the FeaturizationConfig object.
For example:
{
"AttributeName": "demand",
FeaturizationPipeline [ {
"FeaturizationMethodName": "filling",
"FeaturizationMethodParameters": {"aggregation": "avg", "backfill": "nan"}
} ]
}
AttributeName (string) -- [REQUIRED]
The name of the schema attribute that specifies the data field to be featurized. Amazon Forecast supports the target field of the TARGET_TIME_SERIES and the RELATED_TIME_SERIES datasets. For example, for the RETAIL domain, the target is demand , and for the CUSTOM domain, the target is target_value . For more information, see howitworks-missing-values .
FeaturizationPipeline (list) --
An array of one FeaturizationMethod object that specifies the feature transformation method.
(dict) --
Provides information about the method that featurizes (transforms) a dataset field. The method is part of the FeaturizationPipeline of the Featurization object.
The following is an example of how you specify a FeaturizationMethod object.
{
"FeaturizationMethodName": "filling",
"FeaturizationMethodParameters": {"aggregation": "sum", "middlefill": "zero", "backfill": "zero"}
}
FeaturizationMethodName (string) -- [REQUIRED]
The name of the method. The "filling" method is the only supported method.
FeaturizationMethodParameters (dict) --
The method parameters (key-value pairs), which are a map of override parameters. Specify these parameters to override the default values. Related Time Series attributes do not accept aggregation parameters.
The following list shows the parameters and their valid values for the "filling" featurization method for a Target Time Series dataset. Bold signifies the default value.
aggregation : sum , avg , first , min , max
frontfill : none
middlefill : zero , nan (not a number), value , median , mean , min , max
backfill : zero , nan , value , median , mean , min , max
The following list shows the parameters and their valid values for a Related Time Series featurization method (there are no defaults):
middlefill : zero , value , median , mean , min , max
backfill : zero , value , median , mean , min , max
futurefill : zero , value , median , mean , min , max
(string) --
(string) --
dict
An AWS Key Management Service (KMS) key and the AWS Identity and Access Management (IAM) role that Amazon Forecast can assume to access the key.
RoleArn (string) -- [REQUIRED]
The ARN of the IAM role that Amazon Forecast can assume to access the AWS KMS key.
Passing a role across AWS accounts is not allowed. If you pass a role that isn't in your account, you get an InvalidInputException error.
KMSKeyArn (string) -- [REQUIRED]
The Amazon Resource Name (ARN) of the KMS key.
list
The optional metadata that you apply to the predictor 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 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.
(dict) --
The optional metadata that you apply to a 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 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.
Key (string) -- [REQUIRED]
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.
Value (string) -- [REQUIRED]
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
{
'PredictorArn': 'string'
}
Response Structure
(dict) --
PredictorArn (string) --
The Amazon Resource Name (ARN) of the predictor.