aws.lookoutequipment.describe_model_version

Example SQL Queries

SELECT * FROM
aws.lookoutequipment.describe_model_version
WHERE
"model_name" = 'VALUE'
AND "model_version" = 'VALUE';

Description

Retrieves information about a specific machine learning model version.

• View All LookoutEquipment Tables
• Boto3 Reference

Table Definition

Column Name	Column Data Type
model_name Required Input Column The name of the machine learning model that this version belongs to.	VARCHAR
model_version Required Input Column The version of the machine learning model.	BIGINT
_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
auto_promotion_result Indicates whether the model version was promoted to be the active version after retraining or if there was an error with or cancellation of the retraining.	VARCHAR
auto_promotion_result_reason Indicates the reason for the AutoPromotionResult. For example, a model might not be promoted if its performance was worse than the active version, if there was an error during training, or if the retraining scheduler was using MANUAL promote mode. The model will be promoted in MANAGED promote mode if the performance is better than the previous model.	VARCHAR
created_at Indicates the time and date at which the machine learning model version was created.	TIMESTAMP_S
data_pre_processing_configuration The configuration is the TargetSamplingRate, which is the sampling rate of the data after post processing by Amazon Lookout for Equipment. For example, if you provide data that has been collected at a 1 second level and you want the system to resample the data at a 1 minute rate before training, the TargetSamplingRate is 1 minute. When providing a value for the TargetSamplingRate, you must attach the prefix "PT" to the rate you want. The value for a 1 second rate is therefore PT1S, the value for a 15 minute rate is PT15M, and the value for a 1 hour rate is PT1H	STRUCT( "target_sampling_rate" VARCHAR )
Show child fields data_pre_processing_configuration.target_sampling_rate The sampling rate of the data after post processing by Amazon Lookout for Equipment. For example, if you provide data that has been collected at a 1 second level and you want the system to resample the data at a 1 minute rate before training, the TargetSamplingRate is 1 minute. When providing a value for the TargetSamplingRate, you must attach the prefix "PT" to the rate you want. The value for a 1 second rate is therefore PT1S, the value for a 15 minute rate is PT15M, and the value for a 1 hour rate is PT1H
dataset_arn The Amazon Resource Name (ARN) of the dataset used to train the model version.	VARCHAR
dataset_name The name of the dataset used to train the model version.	VARCHAR
evaluation_data_end_time The date on which the data in the evaluation set began being gathered. If you imported the version, this is the date that the evaluation set data in the source version finished being gathered.	TIMESTAMP_S
evaluation_data_start_time The date on which the data in the evaluation set began being gathered. If you imported the version, this is the date that the evaluation set data in the source version began being gathered.	TIMESTAMP_S
failed_reason The failure message if the training of the model version failed.	VARCHAR
import_job_end_time The date and time when the import job completed. This field appears if the model version was imported.	TIMESTAMP_S
import_job_start_time The date and time when the import job began. This field appears if the model version was imported.	TIMESTAMP_S
imported_data_size_in_bytes The size in bytes of the imported data. This field appears if the model version was imported.	BIGINT
labels_input_configuration Contains the configuration information for the S3 location being used to hold label data.	STRUCT( "s3_input_configuration" STRUCT( "bucket" VARCHAR, "prefix" VARCHAR ), "label_group_name" VARCHAR )
Show child fields labels_input_configuration.label_group_name The name of the label group to be used for label data. labels_input_configuration.s3_input_configuration Contains location information for the S3 location being used for label data. Show child fields labels_input_configuration.s3_input_configuration.bucket The name of the S3 bucket holding the label data. labels_input_configuration.s3_input_configuration.prefix The prefix for the S3 bucket used for the label data.
last_updated_time Indicates the last time the machine learning model version was updated.	TIMESTAMP_S
model_arn The Amazon Resource Name (ARN) of the parent machine learning model that this version belong to.	VARCHAR
model_diagnostics_output_configuration The Amazon S3 location where Amazon Lookout for Equipment saves the pointwise model diagnostics for the model version.	STRUCT( "s3_output_configuration" STRUCT( "bucket" VARCHAR, "prefix" VARCHAR ), "kms_key_id" VARCHAR )
Show child fields model_diagnostics_output_configuration.kms_key_id The Amazon Web Services Key Management Service (KMS) key identifier to encrypt the pointwise model diagnostics files. model_diagnostics_output_configuration.s3_output_configuration The Amazon S3 location for the pointwise model diagnostics. Show child fields model_diagnostics_output_configuration.s3_output_configuration.bucket The name of the Amazon S3 bucket where the pointwise model diagnostics are located. You must be the owner of the Amazon S3 bucket. model_diagnostics_output_configuration.s3_output_configuration.prefix The Amazon S3 prefix for the location of the pointwise model diagnostics. The prefix specifies the folder and evaluation result file name. (bucket). When you call CreateModel or UpdateModel, specify the path within the bucket that you want Lookout for Equipment to save the model to. During training, Lookout for Equipment creates the model evaluation model as a compressed JSON file with the name model_diagnostics_results.json.gz. When you call DescribeModel or DescribeModelVersion, prefix contains the file path and filename of the model evaluation file.
model_diagnostics_results_object The Amazon S3 output prefix for where Lookout for Equipment saves the pointwise model diagnostics for the model version.	STRUCT( "bucket" VARCHAR, "key" VARCHAR )
Show child fields model_diagnostics_results_object.bucket The name of the specific S3 bucket. model_diagnostics_results_object.key The Amazon Web Services Key Management Service (KMS key) key being used to encrypt the S3 object. Without this key, data in the bucket is not accessible.
model_metrics Shows an aggregated summary, in JSON format, of the model's performance within the evaluation time range. These metrics are created when evaluating the model.	VARCHAR
model_quality Provides a quality assessment for a model that uses labels. If Lookout for Equipment determines that the model quality is poor based on training metrics, the value is POOR_QUALITY_DETECTED. Otherwise, the value is QUALITY_THRESHOLD_MET. If the model is unlabeled, the model quality can't be assessed and the value of ModelQuality is CANNOT_DETERMINE_QUALITY. In this situation, you can get a model quality assessment by adding labels to the input dataset and retraining the model. For information about using labels with your models, see Understanding labeling. For information about improving the quality of a model, see Best practices with Amazon Lookout for Equipment.	VARCHAR
model_version_arn The Amazon Resource Name (ARN) of the model version.	VARCHAR
off_condition Indicates that the asset associated with this sensor has been shut off. As long as this condition is met, Lookout for Equipment will not use data from this asset for training, evaluation, or inference.	VARCHAR
prior_model_metrics If the model version was retrained, this field shows a summary of the performance of the prior model on the new training range. You can use the information in this JSON-formatted object to compare the new model version and the prior model version.	VARCHAR
retraining_available_data_in_days Indicates the number of days of data used in the most recent scheduled retraining run.	BIGINT
role_arn The Amazon Resource Name (ARN) of the role that was used to train the model version.	VARCHAR
schema The schema of the data used to train the model version.	VARCHAR
server_side_kms_key_id The identifier of the KMS key key used to encrypt model version data by Amazon Lookout for Equipment.	VARCHAR
source_model_version_arn If model version was imported, then this field is the arn of the source model version.	VARCHAR
source_type Indicates whether this model version was created by training or by importing.	VARCHAR
status The current status of the model version.	VARCHAR
training_data_end_time The date on which the training data finished being gathered. If you imported the version, this is the date that the training data in the source version finished being gathered.	TIMESTAMP_S
training_data_start_time The date on which the training data began being gathered. If you imported the version, this is the date that the training data in the source version began being gathered.	TIMESTAMP_S
training_execution_end_time The time when the training of the version completed.	TIMESTAMP_S
training_execution_start_time The time when the training of the version began.	TIMESTAMP_S

Note

Tables may require input columns to have values specified before the table can return it’s rows. The values for input parameters are set in the where clause of the query typically using = or IN.