| Column Name | Column Data Type |
|---|
explainability_arn Required Input Column
The Amazon Resource Name (ARN) of the Explainability. | VARCHAR |
_aws_profile Input Column
The AWS profile defines the AWS identity used. It can be defined via credentials or by assuming a IAM role. | STRUCT(
"type" VARCHAR,
"name" VARCHAR,
"account_id" VARCHAR,
"via_profile_name" VARCHAR,
"assumed_role_arn" VARCHAR,
"organization" STRUCT(
"account_name" VARCHAR,
"id" VARCHAR,
"tags" STRUCT(
"key" VARCHAR,
"value" VARCHAR
)[],
"master_account" STRUCT(
"id" VARCHAR,
"email" VARCHAR
),
"parents" STRUCT(
"type" VARCHAR,
"id" VARCHAR,
"name" VARCHAR,
"tags" STRUCT(
"key" VARCHAR,
"value" VARCHAR
)[]
)[]
)
) |
Show child fields- _aws_profile.account_id
The AWS account id - _aws_profile.assumed_role_arn
The ARN of the assumed role - _aws_profile.name
The unique name of the profile. - _aws_profile.organization
Information about this profile's membership in the AWS organization. Show child fields- _aws_profile.organization.account_name
The name of account speciifed by the organization - _aws_profile.organization.id
The organization id - _aws_profile.organization.master_account
Show child fields- _aws_profile.organization.master_account.email
The organization master account email address - _aws_profile.organization.master_account.id
The organization master account id
- _aws_profile.organization.parents[]
Show child fields- _aws_profile.organization.parents[].id
The id of the parent - _aws_profile.organization.parents[].name
The name of the parent - _aws_profile.organization.parents[].tags[]
Show child fields- _aws_profile.organization.parents[].tags[].key
- _aws_profile.organization.parents[].tags[].value
- _aws_profile.organization.parents[].type
The type of parent can be an organization unit or a root
- _aws_profile.organization.tags[]
Show child fields- _aws_profile.organization.tags[].key
- _aws_profile.organization.tags[].value
- _aws_profile.type
The type of profile, either 'credentials' or 'assumed_role' - _aws_profile.via_profile_name
This IAM role for this profile is assumed by first utilizing another profile with this name to obtain credentials.
|
_aws_region Input Column
The AWS region to use. | VARCHAR |
creation_time
When the Explainability resource was created. | TIMESTAMP_S |
data_source
The source of your data, an Identity and Access Management (IAM) role that allows Amazon Forecast to access the data and, optionally, an Key Management Service (KMS) key. | STRUCT(
"s3_config" STRUCT(
"path" VARCHAR,
"role_arn" VARCHAR,
"kms_key_arn" VARCHAR
)
) |
Show child fields- data_source.s3_config
The path to the data stored in an Amazon Simple Storage Service (Amazon S3) bucket along with the credentials to access the data. Show child fields- data_source.s3_config.kms_key_arn
The Amazon Resource Name (ARN) of an Key Management Service (KMS) key. - data_source.s3_config.path
The path to an Amazon Simple Storage Service (Amazon S3) bucket or file(s) in an Amazon S3 bucket. - data_source.s3_config.role_arn
The ARN of the 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 Amazon Web Services accounts is not allowed. If you pass a role that isn't in your account, you get an InvalidInputException error.
|
enable_visualization
Whether the visualization was enabled for the Explainability resource. | BOOLEAN |
end_date_time
If TimePointGranularity is set to SPECIFIC, the last time point in the Explainability. | VARCHAR |
estimated_time_remaining_in_minutes
The estimated time remaining in minutes for the CreateExplainability job to complete. | BIGINT |
explainability_config
The configuration settings that define the granularity of time series and time points for the Explainability. | STRUCT(
"time_series_granularity" VARCHAR,
"time_point_granularity" VARCHAR
) |
Show child fields- explainability_config.time_point_granularity
To create an Explainability for all time points in your forecast horizon, use ALL. To create an Explainability for specific time points in your forecast horizon, use SPECIFIC. Specify time points with the StartDateTime and EndDateTime parameters within the CreateExplainability operation. - explainability_config.time_series_granularity
To create an Explainability for all time series in your datasets, use ALL. To create an Explainability for specific time series in your datasets, use SPECIFIC. Specify time series by uploading a CSV or Parquet file to an Amazon S3 bucket and set the location within the DataDestination data type.
|
explainability_name
The name of the Explainability. | VARCHAR |
last_modification_time
The last time the resource was modified. The timestamp depends on the status of the job: -
CREATE_PENDING - The CreationTime. -
CREATE_IN_PROGRESS - The current timestamp. -
CREATE_STOPPING - The current timestamp. -
CREATE_STOPPED - When the job stopped. -
ACTIVE or CREATE_FAILED - When the job finished or failed. | TIMESTAMP_S |
message
If an error occurred, a message about the error. | VARCHAR |
resource_arn
The Amazon Resource Name (ARN) of the Predictor or Forecast used to create the Explainability resource. | VARCHAR |
schema
Defines the fields of a dataset. | STRUCT(
"attributes" STRUCT(
"attribute_name" VARCHAR,
"attribute_type" VARCHAR
)[]
) |
Show child fields- schema.attributes[]
Show child fields- schema.attributes[].attribute_name
The name of the dataset field. - schema.attributes[].attribute_type
The data type of the field. For a related time series dataset, other than date, item_id, and forecast dimensions attributes, all attributes should be of numerical type (integer/float).
|
start_date_time
If TimePointGranularity is set to SPECIFIC, the first time point in the Explainability. | VARCHAR |
status
The status of the Explainability resource. States include: -
ACTIVE -
CREATE_PENDING, CREATE_IN_PROGRESS, CREATE_FAILED -
CREATE_STOPPING, CREATE_STOPPED -
DELETE_PENDING, DELETE_IN_PROGRESS, DELETE_FAILED | VARCHAR |