SchemaSummary ¶

class SchemaSummary(TypedDict, closed=True):
    name: "capo_cleanrooms.types.table_alias.TableAlias"
    """<p>The name for the schema object.</p>"""
    type: "capo_cleanrooms.types.schema_type.SchemaType"
    """<p>The type of schema object.</p>"""
    creator_account_id: "capo_cleanrooms.types.account_id.AccountId"
    """<p>The unique account ID for the Amazon Web Services account that owns the schema.</p>"""
    create_time: "datetime.datetime"
    """<p>The time the schema object was created.</p>"""
    update_time: "datetime.datetime"
    """<p>The time the schema object was last updated.</p>"""
    collaboration_id: "capo_cleanrooms.types.uuid.UUID"
    """<p>The unique ID for the collaboration that the schema belongs to.</p>"""
    collaboration_arn: "capo_cleanrooms.types.collaboration_arn.CollaborationArn"
    """<p>The unique ARN for the collaboration that the schema belongs to.</p>"""
    analysis_rule_types: (
        "capo_cleanrooms.types.analysis_rule_type_list.AnalysisRuleTypeList"
    )
    """<p>The types of analysis rules that are associated with this schema object.</p>"""
    analysis_method: NotRequired["capo_cleanrooms.types.analysis_method.AnalysisMethod"]
    """<p>The analysis method for the associated schema.</p> <p> <code>DIRECT_QUERY</code> allows SQL queries to be run directly on this table.</p> <p> <code>DIRECT_JOB</code> allows PySpark jobs to be run directly on this table.</p> <p> <code>MULTIPLE</code> allows both SQL queries and PySpark jobs to be run directly on this table.</p>"""
    resource_arn: NotRequired[
        "capo_cleanrooms.types.schema_resource_arn.SchemaResourceArn"
    ]
    """<p>The Amazon Resource Name (ARN) of the schema summary resource.</p>"""
    selected_analysis_methods: NotRequired[
        "capo_cleanrooms.types.selected_analysis_methods.SelectedAnalysisMethods"
    ]
    """<p> The selected analysis methods for the schema.</p>"""