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AWS for Query.Farm

aws.personalize.describe_solution_version

Example SQL Queries

SELECT * FROM
aws.personalize.describe_solution_version
WHERE
"solution_version_arn" = 'VALUE';

Description

Describes a specific version of a solution. For more information on solutions, see CreateSolution

Table Definition

Column NameColumn Data Type
solution_version_arn Required Input Column

The Amazon Resource Name (ARN) of the solution version.

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
solution_version

The solution version.

STRUCT(
    "name" VARCHAR,
    "solution_version_arn" VARCHAR,
    "solution_arn" VARCHAR,
    "perform_hpo" BOOLEAN,
    "perform_auto_ml" BOOLEAN,
    "recipe_arn" VARCHAR,
    "event_type" VARCHAR,
    "dataset_group_arn" VARCHAR,
    "solution_config" STRUCT(
        "event_value_threshold" VARCHAR,
        "hpo_config" STRUCT(
            "hpo_objective" STRUCT(
                "type" VARCHAR,
                "metric_name" VARCHAR,
                "metric_regex" VARCHAR
            ),
            "hpo_resource_config" STRUCT(
                "max_number_of_training_jobs" VARCHAR,
                "max_parallel_training_jobs" VARCHAR
            ),
            "algorithm_hyper_parameter_ranges" STRUCT(
                "integer_hyper_parameter_ranges" STRUCT(
                    "name" VARCHAR,
                    "min_value" BIGINT,
                    "max_value" BIGINT
                )[],
                "continuous_hyper_parameter_ranges" STRUCT(
                    "name" VARCHAR,
                    "min_value" DOUBLE,
                    "max_value" DOUBLE
                )[],
                "categorical_hyper_parameter_ranges" STRUCT(
                    "name" VARCHAR,
                    "values" VARCHAR[]
                )[]
            )
        ),
        "algorithm_hyper_parameters" MAP(VARCHAR, VARCHAR),
        "feature_transformation_parameters" MAP(VARCHAR, VARCHAR),
        "auto_ml_config" STRUCT(
            "metric_name" VARCHAR,
            "recipe_list" VARCHAR[]
        ),
        "optimization_objective" STRUCT(
            "item_attribute" VARCHAR,
            "objective_sensitivity" VARCHAR
        ),
        "training_data_config" STRUCT(
            "excluded_dataset_columns" MAP(VARCHAR, VARCHAR[])
        ),
        "auto_training_config" STRUCT(
            "scheduling_expression" VARCHAR
        )
    ),
    "training_hours" DOUBLE,
    "training_mode" VARCHAR,
    "tuned_hpo_params" STRUCT(
        "algorithm_hyper_parameters" MAP(VARCHAR, VARCHAR)
    ),
    "status" VARCHAR,
    "failure_reason" VARCHAR,
    "creation_date_time" TIMESTAMP_S,
    "last_updated_date_time" TIMESTAMP_S,
    "training_type" VARCHAR
)
Show child fields
solution_version.creation_date_time

The date and time (in Unix time) that this version of the solution was created.

solution_version.dataset_group_arn

The Amazon Resource Name (ARN) of the dataset group providing the training data.

solution_version.event_type

The event type (for example, 'click' or 'like') that is used for training the model.

solution_version.failure_reason

If training a solution version fails, the reason for the failure.

solution_version.last_updated_date_time

The date and time (in Unix time) that the solution was last updated.

solution_version.name

The name of the solution version.

solution_version.perform_auto_ml

When true, Amazon Personalize searches for the most optimal recipe according to the solution configuration. When false (the default), Amazon Personalize uses recipeArn.

solution_version.perform_hpo

Whether to perform hyperparameter optimization (HPO) on the chosen recipe. The default is false.

solution_version.recipe_arn

The ARN of the recipe used in the solution.

solution_version.solution_arn

The ARN of the solution.

solution_version.solution_config

Describes the configuration properties for the solution.

Show child fields
solution_version.solution_config.algorithm_hyper_parameters

Lists the algorithm hyperparameters and their values.

solution_version.solution_config.auto_ml_config

The AutoMLConfig object containing a list of recipes to search when AutoML is performed.

Show child fields
solution_version.solution_config.auto_ml_config.metric_name

The metric to optimize.

solution_version.solution_config.auto_ml_config.recipe_list[]
solution_version.solution_config.auto_training_config

Specifies the automatic training configuration to use.

Show child fields
solution_version.solution_config.auto_training_config.scheduling_expression

Specifies how often to automatically train new solution versions. Specify a rate expression in rate(value unit) format. For value, specify a number between 1 and 30. For unit, specify day or days. For example, to automatically create a new solution version every 5 days, specify rate(5 days). The default is every 7 days.

For more information about auto training, see Creating and configuring a solution.

solution_version.solution_config.event_value_threshold

Only events with a value greater than or equal to this threshold are used for training a model.

solution_version.solution_config.feature_transformation_parameters

Lists the feature transformation parameters.

solution_version.solution_config.hpo_config

Describes the properties for hyperparameter optimization (HPO).

Show child fields
solution_version.solution_config.hpo_config.algorithm_hyper_parameter_ranges

The hyperparameters and their allowable ranges.

Show child fields
solution_version.solution_config.hpo_config.algorithm_hyper_parameter_ranges.categorical_hyper_parameter_ranges[]
Show child fields
solution_version.solution_config.hpo_config.algorithm_hyper_parameter_ranges.categorical_hyper_parameter_ranges[].name

The name of the hyperparameter.

solution_version.solution_config.hpo_config.algorithm_hyper_parameter_ranges.categorical_hyper_parameter_ranges[].values[]
solution_version.solution_config.hpo_config.algorithm_hyper_parameter_ranges.continuous_hyper_parameter_ranges[]
Show child fields
solution_version.solution_config.hpo_config.algorithm_hyper_parameter_ranges.continuous_hyper_parameter_ranges[].max_value

The maximum allowable value for the hyperparameter.

solution_version.solution_config.hpo_config.algorithm_hyper_parameter_ranges.continuous_hyper_parameter_ranges[].min_value

The minimum allowable value for the hyperparameter.

solution_version.solution_config.hpo_config.algorithm_hyper_parameter_ranges.continuous_hyper_parameter_ranges[].name

The name of the hyperparameter.

solution_version.solution_config.hpo_config.algorithm_hyper_parameter_ranges.integer_hyper_parameter_ranges[]
Show child fields
solution_version.solution_config.hpo_config.algorithm_hyper_parameter_ranges.integer_hyper_parameter_ranges[].max_value

The maximum allowable value for the hyperparameter.

solution_version.solution_config.hpo_config.algorithm_hyper_parameter_ranges.integer_hyper_parameter_ranges[].min_value

The minimum allowable value for the hyperparameter.

solution_version.solution_config.hpo_config.algorithm_hyper_parameter_ranges.integer_hyper_parameter_ranges[].name

The name of the hyperparameter.

solution_version.solution_config.hpo_config.hpo_objective

The metric to optimize during HPO.

Amazon Personalize doesn't support configuring the hpoObjective at this time.

Show child fields
solution_version.solution_config.hpo_config.hpo_objective.metric_name

The name of the metric.

solution_version.solution_config.hpo_config.hpo_objective.metric_regex

A regular expression for finding the metric in the training job logs.

solution_version.solution_config.hpo_config.hpo_objective.type

The type of the metric. Valid values are Maximize and Minimize.

solution_version.solution_config.hpo_config.hpo_resource_config

Describes the resource configuration for HPO.

Show child fields
solution_version.solution_config.hpo_config.hpo_resource_config.max_number_of_training_jobs

The maximum number of training jobs when you create a solution version. The maximum value for maxNumberOfTrainingJobs is 40.

solution_version.solution_config.hpo_config.hpo_resource_config.max_parallel_training_jobs

The maximum number of parallel training jobs when you create a solution version. The maximum value for maxParallelTrainingJobs is 10.

solution_version.solution_config.optimization_objective

Describes the additional objective for the solution, such as maximizing streaming minutes or increasing revenue. For more information see Optimizing a solution.

Show child fields
solution_version.solution_config.optimization_objective.item_attribute

The numerical metadata column in an Items dataset related to the optimization objective. For example, VIDEO_LENGTH (to maximize streaming minutes), or PRICE (to maximize revenue).

solution_version.solution_config.optimization_objective.objective_sensitivity

Specifies how Amazon Personalize balances the importance of your optimization objective versus relevance.

solution_version.solution_config.training_data_config

Specifies the training data configuration to use when creating a custom solution version (trained model).

Show child fields
solution_version.solution_config.training_data_config.excluded_dataset_columns

Specifies the columns to exclude from training. Each key is a dataset type, and each value is a list of columns. Exclude columns to control what data Amazon Personalize uses to generate recommendations.

For example, you might have a column that you want to use only to filter recommendations. You can exclude this column from training and Amazon Personalize considers it only when filtering.

solution_version.solution_version_arn

The ARN of the solution version.

solution_version.status

The status of the solution version.

A solution version can be in one of the following states:

  • CREATE PENDING

  • CREATE IN_PROGRESS

  • ACTIVE

  • CREATE FAILED

  • CREATE STOPPING

  • CREATE STOPPED

solution_version.training_hours

The time used to train the model. You are billed for the time it takes to train a model. This field is visible only after Amazon Personalize successfully trains a model.

solution_version.training_mode

The scope of training to be performed when creating the solution version. A FULL training considers all of the data in your dataset group. An UPDATE processes only the data that has changed since the latest training. Only solution versions created with the User-Personalization recipe can use UPDATE.

solution_version.training_type

Whether the solution version was created automatically or manually.

solution_version.tuned_hpo_params

If hyperparameter optimization was performed, contains the hyperparameter values of the best performing model.

Show child fields
solution_version.tuned_hpo_params.algorithm_hyper_parameters

A list of the hyperparameter values of the best performing model.