CfnConfiguredTablePropsMixin
- class aws_cdk.mixins_preview.aws_cleanrooms.mixins.CfnConfiguredTablePropsMixin(props, *, strategy=None)
Bases:
MixinCreates a new configured table resource.
- See:
- CloudformationResource:
AWS::CleanRooms::ConfiguredTable
- Mixin:
true
- ExampleMetadata:
fixture=_generated
Example:
# The code below shows an example of how to instantiate this type. # The values are placeholders you should change. from aws_cdk.mixins_preview import mixins from aws_cdk.mixins_preview.aws_cleanrooms import mixins as cleanrooms_mixins cfn_configured_table_props_mixin = cleanrooms_mixins.CfnConfiguredTablePropsMixin(cleanrooms_mixins.CfnConfiguredTableMixinProps( allowed_columns=["allowedColumns"], analysis_method="analysisMethod", analysis_rules=[cleanrooms_mixins.CfnConfiguredTablePropsMixin.AnalysisRuleProperty( policy=cleanrooms_mixins.CfnConfiguredTablePropsMixin.ConfiguredTableAnalysisRulePolicyProperty( v1=cleanrooms_mixins.CfnConfiguredTablePropsMixin.ConfiguredTableAnalysisRulePolicyV1Property( aggregation=cleanrooms_mixins.CfnConfiguredTablePropsMixin.AnalysisRuleAggregationProperty( additional_analyses="additionalAnalyses", aggregate_columns=[cleanrooms_mixins.CfnConfiguredTablePropsMixin.AggregateColumnProperty( column_names=["columnNames"], function="function" )], allowed_join_operators=["allowedJoinOperators"], dimension_columns=["dimensionColumns"], join_columns=["joinColumns"], join_required="joinRequired", output_constraints=[cleanrooms_mixins.CfnConfiguredTablePropsMixin.AggregationConstraintProperty( column_name="columnName", minimum=123, type="type" )], scalar_functions=["scalarFunctions"] ), custom=cleanrooms_mixins.CfnConfiguredTablePropsMixin.AnalysisRuleCustomProperty( additional_analyses="additionalAnalyses", allowed_analyses=["allowedAnalyses"], allowed_analysis_providers=["allowedAnalysisProviders"], differential_privacy=cleanrooms_mixins.CfnConfiguredTablePropsMixin.DifferentialPrivacyProperty( columns=[cleanrooms_mixins.CfnConfiguredTablePropsMixin.DifferentialPrivacyColumnProperty( name="name" )] ), disallowed_output_columns=["disallowedOutputColumns"] ), list=cleanrooms_mixins.CfnConfiguredTablePropsMixin.AnalysisRuleListProperty( additional_analyses="additionalAnalyses", allowed_join_operators=["allowedJoinOperators"], join_columns=["joinColumns"], list_columns=["listColumns"] ) ) ), type="type" )], description="description", name="name", selected_analysis_methods=["selectedAnalysisMethods"], table_reference=cleanrooms_mixins.CfnConfiguredTablePropsMixin.TableReferenceProperty( athena=cleanrooms_mixins.CfnConfiguredTablePropsMixin.AthenaTableReferenceProperty( database_name="databaseName", output_location="outputLocation", region="region", table_name="tableName", work_group="workGroup" ), glue=cleanrooms_mixins.CfnConfiguredTablePropsMixin.GlueTableReferenceProperty( database_name="databaseName", region="region", table_name="tableName" ), snowflake=cleanrooms_mixins.CfnConfiguredTablePropsMixin.SnowflakeTableReferenceProperty( account_identifier="accountIdentifier", database_name="databaseName", schema_name="schemaName", secret_arn="secretArn", table_name="tableName", table_schema=cleanrooms_mixins.CfnConfiguredTablePropsMixin.SnowflakeTableSchemaProperty( v1=[cleanrooms_mixins.CfnConfiguredTablePropsMixin.SnowflakeTableSchemaV1Property( column_name="columnName", column_type="columnType" )] ) ) ), tags=[CfnTag( key="key", value="value" )] ), strategy=mixins.PropertyMergeStrategy.OVERRIDE )
Create a mixin to apply properties to
AWS::CleanRooms::ConfiguredTable.- Parameters:
props (
Union[CfnConfiguredTableMixinProps,Dict[str,Any]]) – L1 properties to apply.strategy (
Optional[PropertyMergeStrategy]) – (experimental) Strategy for merging nested properties. Default: - PropertyMergeStrategy.MERGE
Methods
- apply_to(construct)
Apply the mixin properties to the construct.
- Parameters:
construct (
IConstruct)- Return type:
- supports(construct)
Check if this mixin supports the given construct.
- Parameters:
construct (
IConstruct)- Return type:
bool
Attributes
- CFN_PROPERTY_KEYS = ['allowedColumns', 'analysisMethod', 'analysisRules', 'description', 'name', 'selectedAnalysisMethods', 'tableReference', 'tags']
Static Methods
- classmethod is_mixin(x)
(experimental) Checks if
xis a Mixin.- Parameters:
x (
Any) – Any object.- Return type:
bool- Returns:
true if
xis an object created from a class which extendsMixin.- Stability:
experimental
AggregateColumnProperty
- class CfnConfiguredTablePropsMixin.AggregateColumnProperty(*, column_names=None, function=None)
Bases:
objectColumn in configured table that can be used in aggregate function in query.
- Parameters:
column_names (
Optional[Sequence[str]]) – Column names in configured table of aggregate columns.function (
Optional[str]) – Aggregation function that can be applied to aggregate column in query.
- See:
- ExampleMetadata:
fixture=_generated
Example:
# The code below shows an example of how to instantiate this type. # The values are placeholders you should change. from aws_cdk.mixins_preview.aws_cleanrooms import mixins as cleanrooms_mixins aggregate_column_property = cleanrooms_mixins.CfnConfiguredTablePropsMixin.AggregateColumnProperty( column_names=["columnNames"], function="function" )
Attributes
- column_names
Column names in configured table of aggregate columns.
- function
Aggregation function that can be applied to aggregate column in query.
AggregationConstraintProperty
- class CfnConfiguredTablePropsMixin.AggregationConstraintProperty(*, column_name=None, minimum=None, type=None)
Bases:
objectConstraint on query output removing output rows that do not meet a minimum number of distinct values of a specified column.
- Parameters:
column_name (
Optional[str]) – Column in aggregation constraint for which there must be a minimum number of distinct values in an output row for it to be in the query output.minimum (
Union[int,float,None]) – The minimum number of distinct values that an output row must be an aggregation of. Minimum threshold of distinct values for a specified column that must exist in an output row for it to be in the query output.type (
Optional[str]) – The type of aggregation the constraint allows. The only valid value is currentlyCOUNT_DISTINCT.
- See:
- ExampleMetadata:
fixture=_generated
Example:
# The code below shows an example of how to instantiate this type. # The values are placeholders you should change. from aws_cdk.mixins_preview.aws_cleanrooms import mixins as cleanrooms_mixins aggregation_constraint_property = cleanrooms_mixins.CfnConfiguredTablePropsMixin.AggregationConstraintProperty( column_name="columnName", minimum=123, type="type" )
Attributes
- column_name
Column in aggregation constraint for which there must be a minimum number of distinct values in an output row for it to be in the query output.
- minimum
The minimum number of distinct values that an output row must be an aggregation of.
Minimum threshold of distinct values for a specified column that must exist in an output row for it to be in the query output.
- type
The type of aggregation the constraint allows.
The only valid value is currently
COUNT_DISTINCT.
AnalysisRuleAggregationProperty
- class CfnConfiguredTablePropsMixin.AnalysisRuleAggregationProperty(*, additional_analyses=None, aggregate_columns=None, allowed_join_operators=None, dimension_columns=None, join_columns=None, join_required=None, output_constraints=None, scalar_functions=None)
Bases:
objectA type of analysis rule that enables query structure and specified queries that produce aggregate statistics.
- Parameters:
additional_analyses (
Optional[str]) – An indicator as to whether additional analyses (such as AWS Clean Rooms ML) can be applied to the output of the direct query. TheadditionalAnalysesparameter is currently supported for the list analysis rule (AnalysisRuleList) and the custom analysis rule (AnalysisRuleCustom).aggregate_columns (
Union[IResolvable,Sequence[Union[IResolvable,AggregateColumnProperty,Dict[str,Any]]],None]) – The columns that query runners are allowed to use in aggregation queries.allowed_join_operators (
Optional[Sequence[str]]) – Which logical operators (if any) are to be used in an INNER JOIN match condition. Default isAND.dimension_columns (
Optional[Sequence[str]]) – The columns that query runners are allowed to select, group by, or filter by.join_columns (
Optional[Sequence[str]]) – Columns in configured table that can be used in join statements and/or as aggregate columns. They can never be outputted directly.join_required (
Optional[str]) – Control that requires member who runs query to do a join with their configured table and/or other configured table in query.output_constraints (
Union[IResolvable,Sequence[Union[IResolvable,AggregationConstraintProperty,Dict[str,Any]]],None]) – Columns that must meet a specific threshold value (after an aggregation function is applied to it) for each output row to be returned.scalar_functions (
Optional[Sequence[str]]) – Set of scalar functions that are allowed to be used on dimension columns and the output of aggregation of metrics.
- See:
- ExampleMetadata:
fixture=_generated
Example:
# The code below shows an example of how to instantiate this type. # The values are placeholders you should change. from aws_cdk.mixins_preview.aws_cleanrooms import mixins as cleanrooms_mixins analysis_rule_aggregation_property = cleanrooms_mixins.CfnConfiguredTablePropsMixin.AnalysisRuleAggregationProperty( additional_analyses="additionalAnalyses", aggregate_columns=[cleanrooms_mixins.CfnConfiguredTablePropsMixin.AggregateColumnProperty( column_names=["columnNames"], function="function" )], allowed_join_operators=["allowedJoinOperators"], dimension_columns=["dimensionColumns"], join_columns=["joinColumns"], join_required="joinRequired", output_constraints=[cleanrooms_mixins.CfnConfiguredTablePropsMixin.AggregationConstraintProperty( column_name="columnName", minimum=123, type="type" )], scalar_functions=["scalarFunctions"] )
Attributes
- additional_analyses
An indicator as to whether additional analyses (such as AWS Clean Rooms ML) can be applied to the output of the direct query.
The
additionalAnalysesparameter is currently supported for the list analysis rule (AnalysisRuleList) and the custom analysis rule (AnalysisRuleCustom).
- aggregate_columns
The columns that query runners are allowed to use in aggregation queries.
- allowed_join_operators
Which logical operators (if any) are to be used in an INNER JOIN match condition.
Default is
AND.
- dimension_columns
The columns that query runners are allowed to select, group by, or filter by.
- join_columns
Columns in configured table that can be used in join statements and/or as aggregate columns.
They can never be outputted directly.
- join_required
Control that requires member who runs query to do a join with their configured table and/or other configured table in query.
- output_constraints
Columns that must meet a specific threshold value (after an aggregation function is applied to it) for each output row to be returned.
- scalar_functions
Set of scalar functions that are allowed to be used on dimension columns and the output of aggregation of metrics.
AnalysisRuleCustomProperty
- class CfnConfiguredTablePropsMixin.AnalysisRuleCustomProperty(*, additional_analyses=None, allowed_analyses=None, allowed_analysis_providers=None, differential_privacy=None, disallowed_output_columns=None)
Bases:
objectA type of analysis rule that enables the table owner to approve custom SQL queries on their configured tables.
It supports differential privacy.
- Parameters:
additional_analyses (
Optional[str]) – An indicator as to whether additional analyses (such as AWS Clean Rooms ML) can be applied to the output of the direct query.allowed_analyses (
Optional[Sequence[str]]) – The ARN of the analysis templates that are allowed by the custom analysis rule.allowed_analysis_providers (
Optional[Sequence[str]]) – The IDs of the AWS accounts that are allowed to query by the custom analysis rule. Required whenallowedAnalysesisANY_QUERY.differential_privacy (
Union[IResolvable,DifferentialPrivacyProperty,Dict[str,Any],None]) – The differential privacy configuration.disallowed_output_columns (
Optional[Sequence[str]]) – A list of columns that aren’t allowed to be shown in the query output.
- See:
- ExampleMetadata:
fixture=_generated
Example:
# The code below shows an example of how to instantiate this type. # The values are placeholders you should change. from aws_cdk.mixins_preview.aws_cleanrooms import mixins as cleanrooms_mixins analysis_rule_custom_property = cleanrooms_mixins.CfnConfiguredTablePropsMixin.AnalysisRuleCustomProperty( additional_analyses="additionalAnalyses", allowed_analyses=["allowedAnalyses"], allowed_analysis_providers=["allowedAnalysisProviders"], differential_privacy=cleanrooms_mixins.CfnConfiguredTablePropsMixin.DifferentialPrivacyProperty( columns=[cleanrooms_mixins.CfnConfiguredTablePropsMixin.DifferentialPrivacyColumnProperty( name="name" )] ), disallowed_output_columns=["disallowedOutputColumns"] )
Attributes
- additional_analyses
An indicator as to whether additional analyses (such as AWS Clean Rooms ML) can be applied to the output of the direct query.
- allowed_analyses
The ARN of the analysis templates that are allowed by the custom analysis rule.
- allowed_analysis_providers
The IDs of the AWS accounts that are allowed to query by the custom analysis rule.
Required when
allowedAnalysesisANY_QUERY.
- differential_privacy
The differential privacy configuration.
- disallowed_output_columns
A list of columns that aren’t allowed to be shown in the query output.
AnalysisRuleListProperty
- class CfnConfiguredTablePropsMixin.AnalysisRuleListProperty(*, additional_analyses=None, allowed_join_operators=None, join_columns=None, list_columns=None)
Bases:
objectA type of analysis rule that enables row-level analysis.
- Parameters:
additional_analyses (
Optional[str]) – An indicator as to whether additional analyses (such as AWS Clean Rooms ML) can be applied to the output of the direct query.allowed_join_operators (
Optional[Sequence[str]]) – The logical operators (if any) that are to be used in an INNER JOIN match condition. Default isAND.join_columns (
Optional[Sequence[str]]) – Columns that can be used to join a configured table with the table of the member who can query and other members’ configured tables.list_columns (
Optional[Sequence[str]]) – Columns that can be listed in the output.
- See:
- ExampleMetadata:
fixture=_generated
Example:
# The code below shows an example of how to instantiate this type. # The values are placeholders you should change. from aws_cdk.mixins_preview.aws_cleanrooms import mixins as cleanrooms_mixins analysis_rule_list_property = cleanrooms_mixins.CfnConfiguredTablePropsMixin.AnalysisRuleListProperty( additional_analyses="additionalAnalyses", allowed_join_operators=["allowedJoinOperators"], join_columns=["joinColumns"], list_columns=["listColumns"] )
Attributes
- additional_analyses
An indicator as to whether additional analyses (such as AWS Clean Rooms ML) can be applied to the output of the direct query.
- allowed_join_operators
The logical operators (if any) that are to be used in an INNER JOIN match condition.
Default is
AND.
- join_columns
Columns that can be used to join a configured table with the table of the member who can query and other members’ configured tables.
- list_columns
Columns that can be listed in the output.
AnalysisRuleProperty
- class CfnConfiguredTablePropsMixin.AnalysisRuleProperty(*, policy=None, type=None)
Bases:
objectA specification about how data from the configured table can be used in a query.
- Parameters:
policy (
Union[IResolvable,ConfiguredTableAnalysisRulePolicyProperty,Dict[str,Any],None]) – A policy that describes the associated data usage limitations.type (
Optional[str]) – The type of analysis rule.
- See:
- ExampleMetadata:
fixture=_generated
Example:
# The code below shows an example of how to instantiate this type. # The values are placeholders you should change. from aws_cdk.mixins_preview.aws_cleanrooms import mixins as cleanrooms_mixins analysis_rule_property = cleanrooms_mixins.CfnConfiguredTablePropsMixin.AnalysisRuleProperty( policy=cleanrooms_mixins.CfnConfiguredTablePropsMixin.ConfiguredTableAnalysisRulePolicyProperty( v1=cleanrooms_mixins.CfnConfiguredTablePropsMixin.ConfiguredTableAnalysisRulePolicyV1Property( aggregation=cleanrooms_mixins.CfnConfiguredTablePropsMixin.AnalysisRuleAggregationProperty( additional_analyses="additionalAnalyses", aggregate_columns=[cleanrooms_mixins.CfnConfiguredTablePropsMixin.AggregateColumnProperty( column_names=["columnNames"], function="function" )], allowed_join_operators=["allowedJoinOperators"], dimension_columns=["dimensionColumns"], join_columns=["joinColumns"], join_required="joinRequired", output_constraints=[cleanrooms_mixins.CfnConfiguredTablePropsMixin.AggregationConstraintProperty( column_name="columnName", minimum=123, type="type" )], scalar_functions=["scalarFunctions"] ), custom=cleanrooms_mixins.CfnConfiguredTablePropsMixin.AnalysisRuleCustomProperty( additional_analyses="additionalAnalyses", allowed_analyses=["allowedAnalyses"], allowed_analysis_providers=["allowedAnalysisProviders"], differential_privacy=cleanrooms_mixins.CfnConfiguredTablePropsMixin.DifferentialPrivacyProperty( columns=[cleanrooms_mixins.CfnConfiguredTablePropsMixin.DifferentialPrivacyColumnProperty( name="name" )] ), disallowed_output_columns=["disallowedOutputColumns"] ), list=cleanrooms_mixins.CfnConfiguredTablePropsMixin.AnalysisRuleListProperty( additional_analyses="additionalAnalyses", allowed_join_operators=["allowedJoinOperators"], join_columns=["joinColumns"], list_columns=["listColumns"] ) ) ), type="type" )
Attributes
- policy
A policy that describes the associated data usage limitations.
AthenaTableReferenceProperty
- class CfnConfiguredTablePropsMixin.AthenaTableReferenceProperty(*, database_name=None, output_location=None, region=None, table_name=None, work_group=None)
Bases:
objectA reference to a table within Athena.
- Parameters:
database_name (
Optional[str]) – The database name.output_location (
Optional[str]) – The output location for the Athena table.region (
Optional[str]) – The AWS Region where the Athena table is located. This parameter is required to uniquely identify and access tables across different Regions.table_name (
Optional[str]) – The table reference.work_group (
Optional[str]) – The workgroup of the Athena table reference.
- See:
- ExampleMetadata:
fixture=_generated
Example:
# The code below shows an example of how to instantiate this type. # The values are placeholders you should change. from aws_cdk.mixins_preview.aws_cleanrooms import mixins as cleanrooms_mixins athena_table_reference_property = cleanrooms_mixins.CfnConfiguredTablePropsMixin.AthenaTableReferenceProperty( database_name="databaseName", output_location="outputLocation", region="region", table_name="tableName", work_group="workGroup" )
Attributes
- database_name
The database name.
- output_location
The output location for the Athena table.
- region
The AWS Region where the Athena table is located.
This parameter is required to uniquely identify and access tables across different Regions.
- table_name
The table reference.
- work_group
The workgroup of the Athena table reference.
ConfiguredTableAnalysisRulePolicyProperty
- class CfnConfiguredTablePropsMixin.ConfiguredTableAnalysisRulePolicyProperty(*, v1=None)
Bases:
objectControls on the query specifications that can be run on a configured table.
- Parameters:
v1 (
Union[IResolvable,ConfiguredTableAnalysisRulePolicyV1Property,Dict[str,Any],None]) – Controls on the query specifications that can be run on a configured table.- See:
- ExampleMetadata:
fixture=_generated
Example:
# The code below shows an example of how to instantiate this type. # The values are placeholders you should change. from aws_cdk.mixins_preview.aws_cleanrooms import mixins as cleanrooms_mixins configured_table_analysis_rule_policy_property = cleanrooms_mixins.CfnConfiguredTablePropsMixin.ConfiguredTableAnalysisRulePolicyProperty( v1=cleanrooms_mixins.CfnConfiguredTablePropsMixin.ConfiguredTableAnalysisRulePolicyV1Property( aggregation=cleanrooms_mixins.CfnConfiguredTablePropsMixin.AnalysisRuleAggregationProperty( additional_analyses="additionalAnalyses", aggregate_columns=[cleanrooms_mixins.CfnConfiguredTablePropsMixin.AggregateColumnProperty( column_names=["columnNames"], function="function" )], allowed_join_operators=["allowedJoinOperators"], dimension_columns=["dimensionColumns"], join_columns=["joinColumns"], join_required="joinRequired", output_constraints=[cleanrooms_mixins.CfnConfiguredTablePropsMixin.AggregationConstraintProperty( column_name="columnName", minimum=123, type="type" )], scalar_functions=["scalarFunctions"] ), custom=cleanrooms_mixins.CfnConfiguredTablePropsMixin.AnalysisRuleCustomProperty( additional_analyses="additionalAnalyses", allowed_analyses=["allowedAnalyses"], allowed_analysis_providers=["allowedAnalysisProviders"], differential_privacy=cleanrooms_mixins.CfnConfiguredTablePropsMixin.DifferentialPrivacyProperty( columns=[cleanrooms_mixins.CfnConfiguredTablePropsMixin.DifferentialPrivacyColumnProperty( name="name" )] ), disallowed_output_columns=["disallowedOutputColumns"] ), list=cleanrooms_mixins.CfnConfiguredTablePropsMixin.AnalysisRuleListProperty( additional_analyses="additionalAnalyses", allowed_join_operators=["allowedJoinOperators"], join_columns=["joinColumns"], list_columns=["listColumns"] ) ) )
Attributes
- v1
Controls on the query specifications that can be run on a configured table.
ConfiguredTableAnalysisRulePolicyV1Property
- class CfnConfiguredTablePropsMixin.ConfiguredTableAnalysisRulePolicyV1Property(*, aggregation=None, custom=None, list=None)
Bases:
objectControls on the query specifications that can be run on a configured table.
- Parameters:
aggregation (
Union[IResolvable,AnalysisRuleAggregationProperty,Dict[str,Any],None]) – Analysis rule type that enables only aggregation queries on a configured table.custom (
Union[IResolvable,AnalysisRuleCustomProperty,Dict[str,Any],None]) – Analysis rule type that enables custom SQL queries on a configured table.list (
Union[IResolvable,AnalysisRuleListProperty,Dict[str,Any],None]) – Analysis rule type that enables only list queries on a configured table.
- See:
- ExampleMetadata:
fixture=_generated
Example:
# The code below shows an example of how to instantiate this type. # The values are placeholders you should change. from aws_cdk.mixins_preview.aws_cleanrooms import mixins as cleanrooms_mixins configured_table_analysis_rule_policy_v1_property = cleanrooms_mixins.CfnConfiguredTablePropsMixin.ConfiguredTableAnalysisRulePolicyV1Property( aggregation=cleanrooms_mixins.CfnConfiguredTablePropsMixin.AnalysisRuleAggregationProperty( additional_analyses="additionalAnalyses", aggregate_columns=[cleanrooms_mixins.CfnConfiguredTablePropsMixin.AggregateColumnProperty( column_names=["columnNames"], function="function" )], allowed_join_operators=["allowedJoinOperators"], dimension_columns=["dimensionColumns"], join_columns=["joinColumns"], join_required="joinRequired", output_constraints=[cleanrooms_mixins.CfnConfiguredTablePropsMixin.AggregationConstraintProperty( column_name="columnName", minimum=123, type="type" )], scalar_functions=["scalarFunctions"] ), custom=cleanrooms_mixins.CfnConfiguredTablePropsMixin.AnalysisRuleCustomProperty( additional_analyses="additionalAnalyses", allowed_analyses=["allowedAnalyses"], allowed_analysis_providers=["allowedAnalysisProviders"], differential_privacy=cleanrooms_mixins.CfnConfiguredTablePropsMixin.DifferentialPrivacyProperty( columns=[cleanrooms_mixins.CfnConfiguredTablePropsMixin.DifferentialPrivacyColumnProperty( name="name" )] ), disallowed_output_columns=["disallowedOutputColumns"] ), list=cleanrooms_mixins.CfnConfiguredTablePropsMixin.AnalysisRuleListProperty( additional_analyses="additionalAnalyses", allowed_join_operators=["allowedJoinOperators"], join_columns=["joinColumns"], list_columns=["listColumns"] ) )
Attributes
- aggregation
Analysis rule type that enables only aggregation queries on a configured table.
- custom
Analysis rule type that enables custom SQL queries on a configured table.
- list
Analysis rule type that enables only list queries on a configured table.
DifferentialPrivacyColumnProperty
- class CfnConfiguredTablePropsMixin.DifferentialPrivacyColumnProperty(*, name=None)
Bases:
objectSpecifies the name of the column that contains the unique identifier of your users, whose privacy you want to protect.
- Parameters:
name (
Optional[str]) – The name of the column, such as user_id, that contains the unique identifier of your users, whose privacy you want to protect. If you want to turn on differential privacy for two or more tables in a collaboration, you must configure the same column as the user identifier column in both analysis rules.- See:
- ExampleMetadata:
fixture=_generated
Example:
# The code below shows an example of how to instantiate this type. # The values are placeholders you should change. from aws_cdk.mixins_preview.aws_cleanrooms import mixins as cleanrooms_mixins differential_privacy_column_property = cleanrooms_mixins.CfnConfiguredTablePropsMixin.DifferentialPrivacyColumnProperty( name="name" )
Attributes
- name
The name of the column, such as user_id, that contains the unique identifier of your users, whose privacy you want to protect.
If you want to turn on differential privacy for two or more tables in a collaboration, you must configure the same column as the user identifier column in both analysis rules.
DifferentialPrivacyProperty
- class CfnConfiguredTablePropsMixin.DifferentialPrivacyProperty(*, columns=None)
Bases:
objectThe analysis method allowed for the configured tables.
DIRECT_QUERYallows SQL queries to be run directly on this table.DIRECT_JOBallows PySpark jobs to be run directly on this table.MULTIPLEallows both SQL queries and PySpark jobs to be run directly on this table.- Parameters:
columns (
Union[IResolvable,Sequence[Union[IResolvable,DifferentialPrivacyColumnProperty,Dict[str,Any]]],None]) – The name of the column, such as user_id, that contains the unique identifier of your users, whose privacy you want to protect. If you want to turn on differential privacy for two or more tables in a collaboration, you must configure the same column as the user identifier column in both analysis rules.- See:
- ExampleMetadata:
fixture=_generated
Example:
# The code below shows an example of how to instantiate this type. # The values are placeholders you should change. from aws_cdk.mixins_preview.aws_cleanrooms import mixins as cleanrooms_mixins differential_privacy_property = cleanrooms_mixins.CfnConfiguredTablePropsMixin.DifferentialPrivacyProperty( columns=[cleanrooms_mixins.CfnConfiguredTablePropsMixin.DifferentialPrivacyColumnProperty( name="name" )] )
Attributes
- columns
The name of the column, such as user_id, that contains the unique identifier of your users, whose privacy you want to protect.
If you want to turn on differential privacy for two or more tables in a collaboration, you must configure the same column as the user identifier column in both analysis rules.
GlueTableReferenceProperty
- class CfnConfiguredTablePropsMixin.GlueTableReferenceProperty(*, database_name=None, region=None, table_name=None)
Bases:
objectA reference to a table within an AWS Glue data catalog.
- Parameters:
database_name (
Optional[str]) – The name of the database the AWS Glue table belongs to.region (
Optional[str]) – The AWS Region where the AWS Glue table is located. This parameter is required to uniquely identify and access tables across different Regions.table_name (
Optional[str]) – The name of the AWS Glue table.
- See:
- ExampleMetadata:
fixture=_generated
Example:
# The code below shows an example of how to instantiate this type. # The values are placeholders you should change. from aws_cdk.mixins_preview.aws_cleanrooms import mixins as cleanrooms_mixins glue_table_reference_property = cleanrooms_mixins.CfnConfiguredTablePropsMixin.GlueTableReferenceProperty( database_name="databaseName", region="region", table_name="tableName" )
Attributes
- database_name
The name of the database the AWS Glue table belongs to.
- region
The AWS Region where the AWS Glue table is located.
This parameter is required to uniquely identify and access tables across different Regions.
- table_name
The name of the AWS Glue table.
SnowflakeTableReferenceProperty
- class CfnConfiguredTablePropsMixin.SnowflakeTableReferenceProperty(*, account_identifier=None, database_name=None, schema_name=None, secret_arn=None, table_name=None, table_schema=None)
Bases:
objectA reference to a table within Snowflake.
- Parameters:
account_identifier (
Optional[str]) – The account identifier for the Snowflake table reference.database_name (
Optional[str]) – The name of the database the Snowflake table belongs to.schema_name (
Optional[str]) – The schema name of the Snowflake table reference.secret_arn (
Optional[str]) – The secret ARN of the Snowflake table reference.table_name (
Optional[str]) – The name of the Snowflake table.table_schema (
Union[IResolvable,SnowflakeTableSchemaProperty,Dict[str,Any],None]) – The schema of the Snowflake table.
- See:
- ExampleMetadata:
fixture=_generated
Example:
# The code below shows an example of how to instantiate this type. # The values are placeholders you should change. from aws_cdk.mixins_preview.aws_cleanrooms import mixins as cleanrooms_mixins snowflake_table_reference_property = cleanrooms_mixins.CfnConfiguredTablePropsMixin.SnowflakeTableReferenceProperty( account_identifier="accountIdentifier", database_name="databaseName", schema_name="schemaName", secret_arn="secretArn", table_name="tableName", table_schema=cleanrooms_mixins.CfnConfiguredTablePropsMixin.SnowflakeTableSchemaProperty( v1=[cleanrooms_mixins.CfnConfiguredTablePropsMixin.SnowflakeTableSchemaV1Property( column_name="columnName", column_type="columnType" )] ) )
Attributes
- account_identifier
The account identifier for the Snowflake table reference.
- database_name
The name of the database the Snowflake table belongs to.
- schema_name
The schema name of the Snowflake table reference.
- secret_arn
The secret ARN of the Snowflake table reference.
- table_name
The name of the Snowflake table.
- table_schema
The schema of the Snowflake table.
SnowflakeTableSchemaProperty
- class CfnConfiguredTablePropsMixin.SnowflakeTableSchemaProperty(*, v1=None)
Bases:
objectThe schema of a Snowflake table.
- Parameters:
v1 (
Union[IResolvable,Sequence[Union[IResolvable,SnowflakeTableSchemaV1Property,Dict[str,Any]]],None]) – The schema of a Snowflake table.- See:
- ExampleMetadata:
fixture=_generated
Example:
# The code below shows an example of how to instantiate this type. # The values are placeholders you should change. from aws_cdk.mixins_preview.aws_cleanrooms import mixins as cleanrooms_mixins snowflake_table_schema_property = cleanrooms_mixins.CfnConfiguredTablePropsMixin.SnowflakeTableSchemaProperty( v1=[cleanrooms_mixins.CfnConfiguredTablePropsMixin.SnowflakeTableSchemaV1Property( column_name="columnName", column_type="columnType" )] )
Attributes
SnowflakeTableSchemaV1Property
- class CfnConfiguredTablePropsMixin.SnowflakeTableSchemaV1Property(*, column_name=None, column_type=None)
Bases:
objectThe Snowflake table schema.
- Parameters:
column_name (
Optional[str]) – The column name.column_type (
Optional[str]) – The column’s data type. Supported data types:ARRAY,BIGINT,BOOLEAN,CHAR,DATE,DECIMAL,DOUBLE,DOUBLE PRECISION,FLOAT,FLOAT4,INT,INTEGER,MAP,NUMERIC,NUMBER,REAL,SMALLINT,STRING,TIMESTAMP,TIMESTAMP_LTZ,TIMESTAMP_NTZ,DATETIME,TINYINT,VARCHAR,TEXT,CHARACTER.
- See:
- ExampleMetadata:
fixture=_generated
Example:
# The code below shows an example of how to instantiate this type. # The values are placeholders you should change. from aws_cdk.mixins_preview.aws_cleanrooms import mixins as cleanrooms_mixins snowflake_table_schema_v1_property = cleanrooms_mixins.CfnConfiguredTablePropsMixin.SnowflakeTableSchemaV1Property( column_name="columnName", column_type="columnType" )
Attributes
- column_name
The column name.
- column_type
The column’s data type.
Supported data types:
ARRAY,BIGINT,BOOLEAN,CHAR,DATE,DECIMAL,DOUBLE,DOUBLE PRECISION,FLOAT,FLOAT4,INT,INTEGER,MAP,NUMERIC,NUMBER,REAL,SMALLINT,STRING,TIMESTAMP,TIMESTAMP_LTZ,TIMESTAMP_NTZ,DATETIME,TINYINT,VARCHAR,TEXT,CHARACTER.
TableReferenceProperty
- class CfnConfiguredTablePropsMixin.TableReferenceProperty(*, athena=None, glue=None, snowflake=None)
Bases:
objectA pointer to the dataset that underlies this table.
- Parameters:
athena (
Union[IResolvable,AthenaTableReferenceProperty,Dict[str,Any],None]) – If present, a reference to the Athena table referred to by this table reference.glue (
Union[IResolvable,GlueTableReferenceProperty,Dict[str,Any],None]) – If present, a reference to the AWS Glue table referred to by this table reference.snowflake (
Union[IResolvable,SnowflakeTableReferenceProperty,Dict[str,Any],None]) – If present, a reference to the Snowflake table referred to by this table reference.
- See:
- ExampleMetadata:
fixture=_generated
Example:
# The code below shows an example of how to instantiate this type. # The values are placeholders you should change. from aws_cdk.mixins_preview.aws_cleanrooms import mixins as cleanrooms_mixins table_reference_property = cleanrooms_mixins.CfnConfiguredTablePropsMixin.TableReferenceProperty( athena=cleanrooms_mixins.CfnConfiguredTablePropsMixin.AthenaTableReferenceProperty( database_name="databaseName", output_location="outputLocation", region="region", table_name="tableName", work_group="workGroup" ), glue=cleanrooms_mixins.CfnConfiguredTablePropsMixin.GlueTableReferenceProperty( database_name="databaseName", region="region", table_name="tableName" ), snowflake=cleanrooms_mixins.CfnConfiguredTablePropsMixin.SnowflakeTableReferenceProperty( account_identifier="accountIdentifier", database_name="databaseName", schema_name="schemaName", secret_arn="secretArn", table_name="tableName", table_schema=cleanrooms_mixins.CfnConfiguredTablePropsMixin.SnowflakeTableSchemaProperty( v1=[cleanrooms_mixins.CfnConfiguredTablePropsMixin.SnowflakeTableSchemaV1Property( column_name="columnName", column_type="columnType" )] ) ) )
Attributes
- athena
If present, a reference to the Athena table referred to by this table reference.
- glue
If present, a reference to the AWS Glue table referred to by this table reference.
- snowflake
If present, a reference to the Snowflake table referred to by this table reference.