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AWS for Query.Farm

aws.machinelearning.describe_evaluations

Example SQL Queries

SELECT * FROM
aws.machinelearning.describe_evaluations;

Description

Returns a list of DescribeEvaluations that match the search criteria in the request.

Table Definition

Column NameColumn Data Type
eq Input Column

The equal to operator. The Evaluation results will have FilterVariable values that exactly match the value specified with EQ.

VARCHAR
filter_variable Input Column

Use one of the following variable to filter a list of Evaluation objects:

  • CreatedAt - Sets the search criteria to the Evaluation creation date.

  • Status - Sets the search criteria to the Evaluation status.

  • Name - Sets the search criteria to the contents of Evaluation Name.

  • IAMUser - Sets the search criteria to the user account that invoked an Evaluation.

  • MLModelId - Sets the search criteria to the MLModel that was evaluated.

  • DataSourceId - Sets the search criteria to the DataSource used in Evaluation.

  • DataUri - Sets the search criteria to the data file(s) used in Evaluation. The URL can identify either a file or an Amazon Simple Storage Solution (Amazon S3) bucket or directory.

VARCHAR
ge Input Column

The greater than or equal to operator. The Evaluation results will have FilterVariable values that are greater than or equal to the value specified with GE. 

VARCHAR
gt Input Column

The greater than operator. The Evaluation results will have FilterVariable values that are greater than the value specified with GT.

VARCHAR
le Input Column

The less than or equal to operator. The Evaluation results will have FilterVariable values that are less than or equal to the value specified with LE.

VARCHAR
lt Input Column

The less than operator. The Evaluation results will have FilterVariable values that are less than the value specified with LT.

VARCHAR
ne Input Column

The not equal to operator. The Evaluation results will have FilterVariable values not equal to the value specified with NE.

VARCHAR
prefix Input Column

A string that is found at the beginning of a variable, such as Name or Id.

For example, an Evaluation could have the Name 2014-09-09-HolidayGiftMailer. To search for this Evaluation, select Name for the FilterVariable and any of the following strings for the Prefix:

  • 2014-09

  • 2014-09-09

  • 2014-09-09-Holiday

VARCHAR
sort_order Input Column

A two-value parameter that determines the sequence of the resulting list of Evaluation.

  • asc - Arranges the list in ascending order (A-Z, 0-9).

  • dsc - Arranges the list in descending order (Z-A, 9-0).

Results are sorted by FilterVariable.

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
compute_time

Long integer type that is a 64-bit signed number.

BIGINT
created_at

The time that the Evaluation was created. The time is expressed in epoch time.

TIMESTAMP_S
created_by_iam_user

The AWS user account that invoked the evaluation. The account type can be either an AWS root account or an AWS Identity and Access Management (IAM) user account.

VARCHAR
evaluation_data_source_id

The ID of the DataSource that is used to evaluate the MLModel.

VARCHAR
evaluation_id

The ID that is assigned to the Evaluation at creation.

VARCHAR
finished_at

A timestamp represented in epoch time.

TIMESTAMP_S
input_data_location_s3

The location and name of the data in Amazon Simple Storage Server (Amazon S3) that is used in the evaluation.

VARCHAR
last_updated_at

The time of the most recent edit to the Evaluation. The time is expressed in epoch time.

TIMESTAMP_S
message

A description of the most recent details about evaluating the MLModel.

VARCHAR
ml_model_id

The ID of the MLModel that is the focus of the evaluation.

VARCHAR
name

A user-supplied name or description of the Evaluation. 

VARCHAR
performance_metrics

Measurements of how well the MLModel performed, using observations referenced by the DataSource. One of the following metrics is returned, based on the type of the MLModel:

  • BinaryAUC: A binary MLModel uses the Area Under the Curve (AUC) technique to measure performance.

  • RegressionRMSE: A regression MLModel uses the Root Mean Square Error (RMSE) technique to measure performance. RMSE measures the difference between predicted and actual values for a single variable.

  • MulticlassAvgFScore: A multiclass MLModel uses the F1 score technique to measure performance.

For more information about performance metrics, please see the Amazon Machine Learning Developer Guide. 

STRUCT(
    "properties" MAP(VARCHAR, VARCHAR)
)
Show child fields
performance_metrics.properties
started_at

A timestamp represented in epoch time.

TIMESTAMP_S
status

The status of the evaluation. This element can have one of the following values:

  • PENDING - Amazon Machine Learning (Amazon ML) submitted a request to evaluate an MLModel.

  • INPROGRESS - The evaluation is underway.

  • FAILED - The request to evaluate an MLModel did not run to completion. It is not usable.

  • COMPLETED - The evaluation process completed successfully.

  • DELETED - The Evaluation is marked as deleted. It is not usable.

VARCHAR