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AWS for Query.Farm

aws.personalize.describe_solution

Example SQL Queries

SELECT * FROM
aws.personalize.describe_solution
WHERE
"solution_arn" = 'VALUE';

Description

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

Table Definition

Column NameColumn Data Type
solution_arn Required Input Column

The Amazon Resource Name (ARN) of the solution to describe.

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

An object that describes the solution.

STRUCT(
    "name" VARCHAR,
    "solution_arn" VARCHAR,
    "perform_hpo" BOOLEAN,
    "perform_auto_ml" BOOLEAN,
    "perform_auto_training" BOOLEAN,
    "recipe_arn" VARCHAR,
    "dataset_group_arn" VARCHAR,
    "event_type" 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
        )
    ),
    "auto_ml_result" STRUCT(
        "best_recipe_arn" VARCHAR
    ),
    "status" VARCHAR,
    "creation_date_time" TIMESTAMP_S,
    "last_updated_date_time" TIMESTAMP_S,
    "latest_solution_version" STRUCT(
        "solution_version_arn" VARCHAR,
        "status" VARCHAR,
        "training_mode" VARCHAR,
        "training_type" VARCHAR,
        "creation_date_time" TIMESTAMP_S,
        "last_updated_date_time" TIMESTAMP_S,
        "failure_reason" VARCHAR
    )
)
Show child fields
solution.auto_ml_result

When performAutoML is true, specifies the best recipe found.

Show child fields
solution.auto_ml_result.best_recipe_arn

The Amazon Resource Name (ARN) of the best recipe.

solution.creation_date_time

The creation date and time (in Unix time) of the solution.

solution.dataset_group_arn

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

solution.event_type

The event type (for example, 'click' or 'like') that is used for training the model. If no eventType is provided, Amazon Personalize uses all interactions for training with equal weight regardless of type.

solution.last_updated_date_time

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

solution.latest_solution_version

Describes the latest version of the solution, including the status and the ARN.

Show child fields
solution.latest_solution_version.creation_date_time

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

solution.latest_solution_version.failure_reason

If a solution version fails, the reason behind the failure.

solution.latest_solution_version.last_updated_date_time

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

solution.latest_solution_version.solution_version_arn

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

solution.latest_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 -or- CREATE FAILED

solution.latest_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.latest_solution_version.training_type

Whether the solution version was created automatically or manually.

solution.name

The name of the solution.

solution.perform_auto_ml

We don't recommend enabling automated machine learning. Instead, match your use case to the available Amazon Personalize recipes. For more information, see Determining your use case.

When true, Amazon Personalize performs a search for the best USER_PERSONALIZATION recipe from the list specified in the solution configuration (recipeArn must not be specified). When false (the default), Amazon Personalize uses recipeArn for training.

solution.perform_auto_training

Specifies whether the solution automatically creates solution versions. The default is True and the solution automatically creates new solution versions every 7 days.

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

solution.perform_hpo

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

solution.recipe_arn

The ARN of the recipe used to create the solution. This is required when performAutoML is false.

solution.solution_arn

The ARN of the solution.

solution.solution_config

Describes the configuration properties for the solution.

Show child fields
solution.solution_config.algorithm_hyper_parameters

Lists the algorithm hyperparameters and their values.

solution.solution_config.auto_ml_config

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

Show child fields
solution.solution_config.auto_ml_config.metric_name

The metric to optimize.

solution.solution_config.auto_ml_config.recipe_list[]
solution.solution_config.auto_training_config

Specifies the automatic training configuration to use.

Show child fields
solution.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.solution_config.event_value_threshold

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

solution.solution_config.feature_transformation_parameters

Lists the feature transformation parameters.

solution.solution_config.hpo_config

Describes the properties for hyperparameter optimization (HPO).

Show child fields
solution.solution_config.hpo_config.algorithm_hyper_parameter_ranges

The hyperparameters and their allowable ranges.

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

The name of the hyperparameter.

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

The maximum allowable value for the hyperparameter.

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

The minimum allowable value for the hyperparameter.

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

The name of the hyperparameter.

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

The maximum allowable value for the hyperparameter.

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

The minimum allowable value for the hyperparameter.

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

The name of the hyperparameter.

solution.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.solution_config.hpo_config.hpo_objective.metric_name

The name of the metric.

solution.solution_config.hpo_config.hpo_objective.metric_regex

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

solution.solution_config.hpo_config.hpo_objective.type

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

solution.solution_config.hpo_config.hpo_resource_config

Describes the resource configuration for HPO.

Show child fields
solution.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.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.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.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.solution_config.optimization_objective.objective_sensitivity

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

solution.solution_config.training_data_config

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

Show child fields
solution.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.status

The status of the solution.

A solution can be in one of the following states:

  • CREATE PENDING > CREATE IN_PROGRESS > ACTIVE -or- CREATE FAILED

  • DELETE PENDING > DELETE IN_PROGRESS