Glue / Client / get_data_quality_result

get_data_quality_result#

Glue.Client.get_data_quality_result(**kwargs)#

Retrieves the result of a data quality rule evaluation.

See also: AWS API Documentation

Request Syntax

response = client.get_data_quality_result(
    ResultId='string'
)
Parameters:

ResultId (string) –

[REQUIRED]

A unique result ID for the data quality result.

Return type:

dict

Returns:

Response Syntax

{
    'ResultId': 'string',
    'Score': 123.0,
    'DataSource': {
        'GlueTable': {
            'DatabaseName': 'string',
            'TableName': 'string',
            'CatalogId': 'string',
            'ConnectionName': 'string',
            'AdditionalOptions': {
                'string': 'string'
            }
        }
    },
    'RulesetName': 'string',
    'EvaluationContext': 'string',
    'StartedOn': datetime(2015, 1, 1),
    'CompletedOn': datetime(2015, 1, 1),
    'JobName': 'string',
    'JobRunId': 'string',
    'RulesetEvaluationRunId': 'string',
    'RuleResults': [
        {
            'Name': 'string',
            'Description': 'string',
            'EvaluationMessage': 'string',
            'Result': 'PASS'|'FAIL'|'ERROR',
            'EvaluatedMetrics': {
                'string': 123.0
            }
        },
    ],
    'AnalyzerResults': [
        {
            'Name': 'string',
            'Description': 'string',
            'EvaluationMessage': 'string',
            'EvaluatedMetrics': {
                'string': 123.0
            }
        },
    ],
    'Observations': [
        {
            'Description': 'string',
            'MetricBasedObservation': {
                'MetricName': 'string',
                'MetricValues': {
                    'ActualValue': 123.0,
                    'ExpectedValue': 123.0,
                    'LowerLimit': 123.0,
                    'UpperLimit': 123.0
                },
                'NewRules': [
                    'string',
                ]
            }
        },
    ]
}

Response Structure

  • (dict) –

    • ResultId (string) –

      A unique result ID for the data quality result.

    • Score (float) –

      An aggregate data quality score. Represents the ratio of rules that passed to the total number of rules.

    • DataSource (dict) –

      The table associated with the data quality result, if any.

      • GlueTable (dict) –

        An Glue table.

        • DatabaseName (string) –

          A database name in the Glue Data Catalog.

        • TableName (string) –

          A table name in the Glue Data Catalog.

        • CatalogId (string) –

          A unique identifier for the Glue Data Catalog.

        • ConnectionName (string) –

          The name of the connection to the Glue Data Catalog.

        • AdditionalOptions (dict) –

          Additional options for the table. Currently there are two keys supported:

          • pushDownPredicate: to filter on partitions without having to list and read all the files in your dataset.

          • catalogPartitionPredicate: to use server-side partition pruning using partition indexes in the Glue Data Catalog.

          • (string) –

            • (string) –

    • RulesetName (string) –

      The name of the ruleset associated with the data quality result.

    • EvaluationContext (string) –

      In the context of a job in Glue Studio, each node in the canvas is typically assigned some sort of name and data quality nodes will have names. In the case of multiple nodes, the evaluationContext can differentiate the nodes.

    • StartedOn (datetime) –

      The date and time when the run for this data quality result started.

    • CompletedOn (datetime) –

      The date and time when the run for this data quality result was completed.

    • JobName (string) –

      The job name associated with the data quality result, if any.

    • JobRunId (string) –

      The job run ID associated with the data quality result, if any.

    • RulesetEvaluationRunId (string) –

      The unique run ID associated with the ruleset evaluation.

    • RuleResults (list) –

      A list of DataQualityRuleResult objects representing the results for each rule.

      • (dict) –

        Describes the result of the evaluation of a data quality rule.

        • Name (string) –

          The name of the data quality rule.

        • Description (string) –

          A description of the data quality rule.

        • EvaluationMessage (string) –

          An evaluation message.

        • Result (string) –

          A pass or fail status for the rule.

        • EvaluatedMetrics (dict) –

          A map of metrics associated with the evaluation of the rule.

          • (string) –

            • (float) –

    • AnalyzerResults (list) –

      A list of DataQualityAnalyzerResult objects representing the results for each analyzer.

      • (dict) –

        Describes the result of the evaluation of a data quality analyzer.

        • Name (string) –

          The name of the data quality analyzer.

        • Description (string) –

          A description of the data quality analyzer.

        • EvaluationMessage (string) –

          An evaluation message.

        • EvaluatedMetrics (dict) –

          A map of metrics associated with the evaluation of the analyzer.

          • (string) –

            • (float) –

    • Observations (list) –

      A list of DataQualityObservation objects representing the observations generated after evaluating the rules and analyzers.

      • (dict) –

        Describes the observation generated after evaluating the rules and analyzers.

        • Description (string) –

          A description of the data quality observation.

        • MetricBasedObservation (dict) –

          An object of type MetricBasedObservation representing the observation that is based on evaluated data quality metrics.

          • MetricName (string) –

            The name of the data quality metric used for generating the observation.

          • MetricValues (dict) –

            An object of type DataQualityMetricValues representing the analysis of the data quality metric value.

            • ActualValue (float) –

              The actual value of the data quality metric.

            • ExpectedValue (float) –

              The expected value of the data quality metric according to the analysis of historical data.

            • LowerLimit (float) –

              The lower limit of the data quality metric value according to the analysis of historical data.

            • UpperLimit (float) –

              The upper limit of the data quality metric value according to the analysis of historical data.

          • NewRules (list) –

            A list of new data quality rules generated as part of the observation based on the data quality metric value.

            • (string) –

Exceptions