CfnDataSet
- class aws_cdk.aws_quicksight.CfnDataSet(scope, id, *, aws_account_id=None, column_groups=None, column_level_permission_rules=None, data_set_id=None, dataset_parameters=None, data_set_refresh_properties=None, data_set_usage_configuration=None, field_folders=None, folder_arns=None, import_mode=None, ingestion_wait_policy=None, logical_table_map=None, name=None, permissions=None, physical_table_map=None, row_level_permission_data_set=None, row_level_permission_tag_configuration=None, tags=None)
Bases:
CfnResource
Creates a dataset.
This operation doesn’t support datasets that include uploaded files as a source.
- See:
http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-resource-quicksight-dataset.html
- CloudformationResource:
AWS::QuickSight::DataSet
- 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 import aws_quicksight as quicksight # tag_rule_configurations: Any cfn_data_set = quicksight.CfnDataSet(self, "MyCfnDataSet", aws_account_id="awsAccountId", column_groups=[quicksight.CfnDataSet.ColumnGroupProperty( geo_spatial_column_group=quicksight.CfnDataSet.GeoSpatialColumnGroupProperty( columns=["columns"], name="name", # the properties below are optional country_code="countryCode" ) )], column_level_permission_rules=[quicksight.CfnDataSet.ColumnLevelPermissionRuleProperty( column_names=["columnNames"], principals=["principals"] )], data_set_id="dataSetId", dataset_parameters=[quicksight.CfnDataSet.DatasetParameterProperty( date_time_dataset_parameter=quicksight.CfnDataSet.DateTimeDatasetParameterProperty( id="id", name="name", value_type="valueType", # the properties below are optional default_values=quicksight.CfnDataSet.DateTimeDatasetParameterDefaultValuesProperty( static_values=["staticValues"] ), time_granularity="timeGranularity" ), decimal_dataset_parameter=quicksight.CfnDataSet.DecimalDatasetParameterProperty( id="id", name="name", value_type="valueType", # the properties below are optional default_values=quicksight.CfnDataSet.DecimalDatasetParameterDefaultValuesProperty( static_values=[123] ) ), integer_dataset_parameter=quicksight.CfnDataSet.IntegerDatasetParameterProperty( id="id", name="name", value_type="valueType", # the properties below are optional default_values=quicksight.CfnDataSet.IntegerDatasetParameterDefaultValuesProperty( static_values=[123] ) ), string_dataset_parameter=quicksight.CfnDataSet.StringDatasetParameterProperty( id="id", name="name", value_type="valueType", # the properties below are optional default_values=quicksight.CfnDataSet.StringDatasetParameterDefaultValuesProperty( static_values=["staticValues"] ) ) )], data_set_refresh_properties=quicksight.CfnDataSet.DataSetRefreshPropertiesProperty( refresh_configuration=quicksight.CfnDataSet.RefreshConfigurationProperty( incremental_refresh=quicksight.CfnDataSet.IncrementalRefreshProperty( lookback_window=quicksight.CfnDataSet.LookbackWindowProperty( column_name="columnName", size=123, size_unit="sizeUnit" ) ) ) ), data_set_usage_configuration=quicksight.CfnDataSet.DataSetUsageConfigurationProperty( disable_use_as_direct_query_source=False, disable_use_as_imported_source=False ), field_folders={ "field_folders_key": quicksight.CfnDataSet.FieldFolderProperty( columns=["columns"], description="description" ) }, folder_arns=["folderArns"], import_mode="importMode", ingestion_wait_policy=quicksight.CfnDataSet.IngestionWaitPolicyProperty( ingestion_wait_time_in_hours=123, wait_for_spice_ingestion=False ), logical_table_map={ "logical_table_map_key": quicksight.CfnDataSet.LogicalTableProperty( alias="alias", # the properties below are optional data_transforms=[quicksight.CfnDataSet.TransformOperationProperty( cast_column_type_operation=quicksight.CfnDataSet.CastColumnTypeOperationProperty( column_name="columnName", new_column_type="newColumnType", # the properties below are optional format="format", sub_type="subType" ), create_columns_operation=quicksight.CfnDataSet.CreateColumnsOperationProperty( columns=[quicksight.CfnDataSet.CalculatedColumnProperty( column_id="columnId", column_name="columnName", expression="expression" )] ), filter_operation=quicksight.CfnDataSet.FilterOperationProperty( condition_expression="conditionExpression" ), override_dataset_parameter_operation=quicksight.CfnDataSet.OverrideDatasetParameterOperationProperty( parameter_name="parameterName", # the properties below are optional new_default_values=quicksight.CfnDataSet.NewDefaultValuesProperty( date_time_static_values=["dateTimeStaticValues"], decimal_static_values=[123], integer_static_values=[123], string_static_values=["stringStaticValues"] ), new_parameter_name="newParameterName" ), project_operation=quicksight.CfnDataSet.ProjectOperationProperty( projected_columns=["projectedColumns"] ), rename_column_operation=quicksight.CfnDataSet.RenameColumnOperationProperty( column_name="columnName", new_column_name="newColumnName" ), tag_column_operation=quicksight.CfnDataSet.TagColumnOperationProperty( column_name="columnName", tags=[quicksight.CfnDataSet.ColumnTagProperty( column_description=quicksight.CfnDataSet.ColumnDescriptionProperty( text="text" ), column_geographic_role="columnGeographicRole" )] ), untag_column_operation=quicksight.CfnDataSet.UntagColumnOperationProperty( column_name="columnName", tag_names=["tagNames"] ) )], source=quicksight.CfnDataSet.LogicalTableSourceProperty( data_set_arn="dataSetArn", join_instruction=quicksight.CfnDataSet.JoinInstructionProperty( left_operand="leftOperand", on_clause="onClause", right_operand="rightOperand", type="type", # the properties below are optional left_join_key_properties=quicksight.CfnDataSet.JoinKeyPropertiesProperty( unique_key=False ), right_join_key_properties=quicksight.CfnDataSet.JoinKeyPropertiesProperty( unique_key=False ) ), physical_table_id="physicalTableId" ) ) }, name="name", permissions=[quicksight.CfnDataSet.ResourcePermissionProperty( actions=["actions"], principal="principal" )], physical_table_map={ "physical_table_map_key": quicksight.CfnDataSet.PhysicalTableProperty( custom_sql=quicksight.CfnDataSet.CustomSqlProperty( data_source_arn="dataSourceArn", name="name", sql_query="sqlQuery", # the properties below are optional columns=[quicksight.CfnDataSet.InputColumnProperty( name="name", type="type", # the properties below are optional sub_type="subType" )] ), relational_table=quicksight.CfnDataSet.RelationalTableProperty( data_source_arn="dataSourceArn", name="name", # the properties below are optional catalog="catalog", input_columns=[quicksight.CfnDataSet.InputColumnProperty( name="name", type="type", # the properties below are optional sub_type="subType" )], schema="schema" ), s3_source=quicksight.CfnDataSet.S3SourceProperty( data_source_arn="dataSourceArn", input_columns=[quicksight.CfnDataSet.InputColumnProperty( name="name", type="type", # the properties below are optional sub_type="subType" )], # the properties below are optional upload_settings=quicksight.CfnDataSet.UploadSettingsProperty( contains_header=False, delimiter="delimiter", format="format", start_from_row=123, text_qualifier="textQualifier" ) ) ) }, row_level_permission_data_set=quicksight.CfnDataSet.RowLevelPermissionDataSetProperty( arn="arn", permission_policy="permissionPolicy", # the properties below are optional format_version="formatVersion", namespace="namespace", status="status" ), row_level_permission_tag_configuration=quicksight.CfnDataSet.RowLevelPermissionTagConfigurationProperty( tag_rules=[quicksight.CfnDataSet.RowLevelPermissionTagRuleProperty( column_name="columnName", tag_key="tagKey", # the properties below are optional match_all_value="matchAllValue", tag_multi_value_delimiter="tagMultiValueDelimiter" )], # the properties below are optional status="status", tag_rule_configurations=tag_rule_configurations ), tags=[CfnTag( key="key", value="value" )] )
- Parameters:
scope (
Construct
) – Scope in which this resource is defined.id (
str
) – Construct identifier for this resource (unique in its scope).aws_account_id (
Optional
[str
]) – The AWS account ID.column_groups (
Union
[IResolvable
,Sequence
[Union
[IResolvable
,ColumnGroupProperty
,Dict
[str
,Any
]]],None
]) – Groupings of columns that work together in certain Amazon QuickSight features. Currently, only geospatial hierarchy is supported.column_level_permission_rules (
Union
[IResolvable
,Sequence
[Union
[IResolvable
,ColumnLevelPermissionRuleProperty
,Dict
[str
,Any
]]],None
]) – A set of one or more definitions of aColumnLevelPermissionRule
.data_set_id (
Optional
[str
]) – An ID for the dataset that you want to create. This ID is unique per AWS Region for each AWS account.dataset_parameters (
Union
[IResolvable
,Sequence
[Union
[IResolvable
,DatasetParameterProperty
,Dict
[str
,Any
]]],None
]) – The parameters that are declared in a dataset.data_set_refresh_properties (
Union
[IResolvable
,DataSetRefreshPropertiesProperty
,Dict
[str
,Any
],None
]) – The refresh properties of a dataset.data_set_usage_configuration (
Union
[IResolvable
,DataSetUsageConfigurationProperty
,Dict
[str
,Any
],None
]) – The usage configuration to apply to child datasets that reference this dataset as a source.field_folders (
Union
[IResolvable
,Mapping
[str
,Union
[IResolvable
,FieldFolderProperty
,Dict
[str
,Any
]]],None
]) – The folder that contains fields and nested subfolders for your dataset.folder_arns (
Optional
[Sequence
[str
]]) –import_mode (
Optional
[str
]) – Indicates whether you want to import the data into SPICE.ingestion_wait_policy (
Union
[IResolvable
,IngestionWaitPolicyProperty
,Dict
[str
,Any
],None
]) – The wait policy to use when creating or updating a Dataset. The default is to wait for SPICE ingestion to finish with timeout of 36 hours.logical_table_map (
Union
[IResolvable
,Mapping
[str
,Union
[IResolvable
,LogicalTableProperty
,Dict
[str
,Any
]]],None
]) – Configures the combination and transformation of the data from the physical tables.name (
Optional
[str
]) – The display name for the dataset.permissions (
Union
[IResolvable
,Sequence
[Union
[IResolvable
,ResourcePermissionProperty
,Dict
[str
,Any
]]],None
]) – A list of resource permissions on the dataset.physical_table_map (
Union
[IResolvable
,Mapping
[str
,Union
[IResolvable
,PhysicalTableProperty
,Dict
[str
,Any
]]],None
]) – Declares the physical tables that are available in the underlying data sources.row_level_permission_data_set (
Union
[IResolvable
,RowLevelPermissionDataSetProperty
,Dict
[str
,Any
],None
]) – The row-level security configuration for the data that you want to create.row_level_permission_tag_configuration (
Union
[IResolvable
,RowLevelPermissionTagConfigurationProperty
,Dict
[str
,Any
],None
]) – The element you can use to define tags for row-level security.tags (
Optional
[Sequence
[Union
[CfnTag
,Dict
[str
,Any
]]]]) – Contains a map of the key-value pairs for the resource tag or tags assigned to the dataset.
Methods
- add_deletion_override(path)
Syntactic sugar for
addOverride(path, undefined)
.- Parameters:
path (
str
) – The path of the value to delete.- Return type:
None
- add_dependency(target)
Indicates that this resource depends on another resource and cannot be provisioned unless the other resource has been successfully provisioned.
This can be used for resources across stacks (or nested stack) boundaries and the dependency will automatically be transferred to the relevant scope.
- Parameters:
target (
CfnResource
) –- Return type:
None
- add_depends_on(target)
(deprecated) Indicates that this resource depends on another resource and cannot be provisioned unless the other resource has been successfully provisioned.
- Parameters:
target (
CfnResource
) –- Deprecated:
use addDependency
- Stability:
deprecated
- Return type:
None
- add_metadata(key, value)
Add a value to the CloudFormation Resource Metadata.
- Parameters:
key (
str
) –value (
Any
) –
- See:
- Return type:
None
Note that this is a different set of metadata from CDK node metadata; this metadata ends up in the stack template under the resource, whereas CDK node metadata ends up in the Cloud Assembly.
- add_override(path, value)
Adds an override to the synthesized CloudFormation resource.
To add a property override, either use
addPropertyOverride
or prefixpath
with “Properties.” (i.e.Properties.TopicName
).If the override is nested, separate each nested level using a dot (.) in the path parameter. If there is an array as part of the nesting, specify the index in the path.
To include a literal
.
in the property name, prefix with a\
. In most programming languages you will need to write this as"\\."
because the\
itself will need to be escaped.For example:
cfn_resource.add_override("Properties.GlobalSecondaryIndexes.0.Projection.NonKeyAttributes", ["myattribute"]) cfn_resource.add_override("Properties.GlobalSecondaryIndexes.1.ProjectionType", "INCLUDE")
would add the overrides Example:
"Properties": { "GlobalSecondaryIndexes": [ { "Projection": { "NonKeyAttributes": [ "myattribute" ] ... } ... }, { "ProjectionType": "INCLUDE" ... }, ] ... }
The
value
argument toaddOverride
will not be processed or translated in any way. Pass raw JSON values in here with the correct capitalization for CloudFormation. If you pass CDK classes or structs, they will be rendered with lowercased key names, and CloudFormation will reject the template.- Parameters:
path (
str
) –The path of the property, you can use dot notation to override values in complex types. Any intermediate keys will be created as needed.
value (
Any
) –The value. Could be primitive or complex.
- Return type:
None
- add_property_deletion_override(property_path)
Adds an override that deletes the value of a property from the resource definition.
- Parameters:
property_path (
str
) – The path to the property.- Return type:
None
- add_property_override(property_path, value)
Adds an override to a resource property.
Syntactic sugar for
addOverride("Properties.<...>", value)
.- Parameters:
property_path (
str
) – The path of the property.value (
Any
) – The value.
- Return type:
None
- apply_removal_policy(policy=None, *, apply_to_update_replace_policy=None, default=None)
Sets the deletion policy of the resource based on the removal policy specified.
The Removal Policy controls what happens to this resource when it stops being managed by CloudFormation, either because you’ve removed it from the CDK application or because you’ve made a change that requires the resource to be replaced.
The resource can be deleted (
RemovalPolicy.DESTROY
), or left in your AWS account for data recovery and cleanup later (RemovalPolicy.RETAIN
). In some cases, a snapshot can be taken of the resource prior to deletion (RemovalPolicy.SNAPSHOT
). A list of resources that support this policy can be found in the following link:- Parameters:
policy (
Optional
[RemovalPolicy
]) –apply_to_update_replace_policy (
Optional
[bool
]) – Apply the same deletion policy to the resource’s “UpdateReplacePolicy”. Default: truedefault (
Optional
[RemovalPolicy
]) – The default policy to apply in case the removal policy is not defined. Default: - Default value is resource specific. To determine the default value for a resource, please consult that specific resource’s documentation.
- See:
- Return type:
None
- get_att(attribute_name, type_hint=None)
Returns a token for an runtime attribute of this resource.
Ideally, use generated attribute accessors (e.g.
resource.arn
), but this can be used for future compatibility in case there is no generated attribute.- Parameters:
attribute_name (
str
) – The name of the attribute.type_hint (
Optional
[ResolutionTypeHint
]) –
- Return type:
- get_metadata(key)
Retrieve a value value from the CloudFormation Resource Metadata.
- Parameters:
key (
str
) –- See:
- Return type:
Any
Note that this is a different set of metadata from CDK node metadata; this metadata ends up in the stack template under the resource, whereas CDK node metadata ends up in the Cloud Assembly.
- inspect(inspector)
Examines the CloudFormation resource and discloses attributes.
- Parameters:
inspector (
TreeInspector
) – tree inspector to collect and process attributes.- Return type:
None
- obtain_dependencies()
Retrieves an array of resources this resource depends on.
This assembles dependencies on resources across stacks (including nested stacks) automatically.
- Return type:
List
[Union
[Stack
,CfnResource
]]
- obtain_resource_dependencies()
Get a shallow copy of dependencies between this resource and other resources in the same stack.
- Return type:
List
[CfnResource
]
- override_logical_id(new_logical_id)
Overrides the auto-generated logical ID with a specific ID.
- Parameters:
new_logical_id (
str
) – The new logical ID to use for this stack element.- Return type:
None
- remove_dependency(target)
Indicates that this resource no longer depends on another resource.
This can be used for resources across stacks (including nested stacks) and the dependency will automatically be removed from the relevant scope.
- Parameters:
target (
CfnResource
) –- Return type:
None
- replace_dependency(target, new_target)
Replaces one dependency with another.
- Parameters:
target (
CfnResource
) – The dependency to replace.new_target (
CfnResource
) – The new dependency to add.
- Return type:
None
- to_string()
Returns a string representation of this construct.
- Return type:
str
- Returns:
a string representation of this resource
Attributes
- CFN_RESOURCE_TYPE_NAME = 'AWS::QuickSight::DataSet'
- attr_arn
The Amazon Resource Name (ARN) of the dataset.
- CloudformationAttribute:
Arn
- attr_consumed_spice_capacity_in_bytes
This is 0 if the dataset isn’t imported into SPICE.
- CloudformationAttribute:
ConsumedSpiceCapacityInBytes
- attr_created_time
The time this dataset version was created.
- CloudformationAttribute:
CreatedTime
- attr_last_updated_time
The time this dataset version was last updated.
- CloudformationAttribute:
LastUpdatedTime
- attr_output_columns
These columns are available in templates, analyses, and dashboards.
- CloudformationAttribute:
OutputColumns
- aws_account_id
The AWS account ID.
- cfn_options
Options for this resource, such as condition, update policy etc.
- cfn_resource_type
AWS resource type.
- column_groups
Groupings of columns that work together in certain Amazon QuickSight features.
- column_level_permission_rules
A set of one or more definitions of a
ColumnLevelPermissionRule
.
- creation_stack
return:
the stack trace of the point where this Resource was created from, sourced from the +metadata+ entry typed +aws:cdk:logicalId+, and with the bottom-most node +internal+ entries filtered.
- data_set_id
An ID for the dataset that you want to create.
- data_set_refresh_properties
The refresh properties of a dataset.
- data_set_usage_configuration
The usage configuration to apply to child datasets that reference this dataset as a source.
- dataset_parameters
The parameters that are declared in a dataset.
- field_folders
The folder that contains fields and nested subfolders for your dataset.
- folder_arns
- import_mode
Indicates whether you want to import the data into SPICE.
- ingestion_wait_policy
The wait policy to use when creating or updating a Dataset.
- logical_id
The logical ID for this CloudFormation stack element.
The logical ID of the element is calculated from the path of the resource node in the construct tree.
To override this value, use
overrideLogicalId(newLogicalId)
.- Returns:
the logical ID as a stringified token. This value will only get resolved during synthesis.
- logical_table_map
Configures the combination and transformation of the data from the physical tables.
- name
The display name for the dataset.
- node
The tree node.
- permissions
A list of resource permissions on the dataset.
- physical_table_map
Declares the physical tables that are available in the underlying data sources.
- ref
Return a string that will be resolved to a CloudFormation
{ Ref }
for this element.If, by any chance, the intrinsic reference of a resource is not a string, you could coerce it to an IResolvable through
Lazy.any({ produce: resource.ref })
.
- row_level_permission_data_set
The row-level security configuration for the data that you want to create.
- row_level_permission_tag_configuration
The element you can use to define tags for row-level security.
- stack
The stack in which this element is defined.
CfnElements must be defined within a stack scope (directly or indirectly).
- tags
Tag Manager which manages the tags for this resource.
- tags_raw
Contains a map of the key-value pairs for the resource tag or tags assigned to the dataset.
Static Methods
- classmethod is_cfn_element(x)
Returns
true
if a construct is a stack element (i.e. part of the synthesized cloudformation template).Uses duck-typing instead of
instanceof
to allow stack elements from different versions of this library to be included in the same stack.- Parameters:
x (
Any
) –- Return type:
bool
- Returns:
The construct as a stack element or undefined if it is not a stack element.
- classmethod is_cfn_resource(x)
Check whether the given object is a CfnResource.
- Parameters:
x (
Any
) –- Return type:
bool
- classmethod is_construct(x)
Checks if
x
is a construct.Use this method instead of
instanceof
to properly detectConstruct
instances, even when the construct library is symlinked.Explanation: in JavaScript, multiple copies of the
constructs
library on disk are seen as independent, completely different libraries. As a consequence, the classConstruct
in each copy of theconstructs
library is seen as a different class, and an instance of one class will not test asinstanceof
the other class.npm install
will not create installations like this, but users may manually symlink construct libraries together or use a monorepo tool: in those cases, multiple copies of theconstructs
library can be accidentally installed, andinstanceof
will behave unpredictably. It is safest to avoid usinginstanceof
, and using this type-testing method instead.- Parameters:
x (
Any
) – Any object.- Return type:
bool
- Returns:
true if
x
is an object created from a class which extendsConstruct
.
CalculatedColumnProperty
- class CfnDataSet.CalculatedColumnProperty(*, column_id, column_name, expression)
Bases:
object
A calculated column for a dataset.
- Parameters:
column_id (
str
) – A unique ID to identify a calculated column. During a dataset update, if the column ID of a calculated column matches that of an existing calculated column, Amazon QuickSight preserves the existing calculated column.column_name (
str
) – Column name.expression (
str
) – An expression that defines the calculated column.
- 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 import aws_quicksight as quicksight calculated_column_property = quicksight.CfnDataSet.CalculatedColumnProperty( column_id="columnId", column_name="columnName", expression="expression" )
Attributes
- column_id
A unique ID to identify a calculated column.
During a dataset update, if the column ID of a calculated column matches that of an existing calculated column, Amazon QuickSight preserves the existing calculated column.
- column_name
Column name.
- expression
An expression that defines the calculated column.
CastColumnTypeOperationProperty
- class CfnDataSet.CastColumnTypeOperationProperty(*, column_name, new_column_type, format=None, sub_type=None)
Bases:
object
A transform operation that casts a column to a different type.
- Parameters:
column_name (
str
) – Column name.new_column_type (
str
) – New column data type.format (
Optional
[str
]) – When casting a column from string to datetime type, you can supply a string in a format supported by Amazon QuickSight to denote the source data format.sub_type (
Optional
[str
]) – The sub data type of the new column. Sub types are only available for decimal columns that are part of a SPICE dataset.
- 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 import aws_quicksight as quicksight cast_column_type_operation_property = quicksight.CfnDataSet.CastColumnTypeOperationProperty( column_name="columnName", new_column_type="newColumnType", # the properties below are optional format="format", sub_type="subType" )
Attributes
- column_name
Column name.
- format
When casting a column from string to datetime type, you can supply a string in a format supported by Amazon QuickSight to denote the source data format.
- new_column_type
New column data type.
- sub_type
The sub data type of the new column.
Sub types are only available for decimal columns that are part of a SPICE dataset.
ColumnDescriptionProperty
- class CfnDataSet.ColumnDescriptionProperty(*, text=None)
Bases:
object
Metadata that contains a description for a column.
- Parameters:
text (
Optional
[str
]) – The text of a description for a column.- 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 import aws_quicksight as quicksight column_description_property = quicksight.CfnDataSet.ColumnDescriptionProperty( text="text" )
Attributes
- text
The text of a description for a column.
ColumnGroupProperty
- class CfnDataSet.ColumnGroupProperty(*, geo_spatial_column_group=None)
Bases:
object
Groupings of columns that work together in certain Amazon QuickSight features.
This is a variant type structure. For this structure to be valid, only one of the attributes can be non-null.
- Parameters:
geo_spatial_column_group (
Union
[IResolvable
,GeoSpatialColumnGroupProperty
,Dict
[str
,Any
],None
]) – Geospatial column group that denotes a hierarchy.- 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 import aws_quicksight as quicksight column_group_property = quicksight.CfnDataSet.ColumnGroupProperty( geo_spatial_column_group=quicksight.CfnDataSet.GeoSpatialColumnGroupProperty( columns=["columns"], name="name", # the properties below are optional country_code="countryCode" ) )
Attributes
- geo_spatial_column_group
Geospatial column group that denotes a hierarchy.
ColumnLevelPermissionRuleProperty
- class CfnDataSet.ColumnLevelPermissionRuleProperty(*, column_names=None, principals=None)
Bases:
object
A rule defined to grant access on one or more restricted columns.
Each dataset can have multiple rules. To create a restricted column, you add it to one or more rules. Each rule must contain at least one column and at least one user or group. To be able to see a restricted column, a user or group needs to be added to a rule for that column.
- Parameters:
column_names (
Optional
[Sequence
[str
]]) – An array of column names.principals (
Optional
[Sequence
[str
]]) – An array of Amazon Resource Names (ARNs) for Amazon QuickSight users or groups.
- 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 import aws_quicksight as quicksight column_level_permission_rule_property = quicksight.CfnDataSet.ColumnLevelPermissionRuleProperty( column_names=["columnNames"], principals=["principals"] )
Attributes
- column_names
An array of column names.
- principals
An array of Amazon Resource Names (ARNs) for Amazon QuickSight users or groups.
ColumnTagProperty
- class CfnDataSet.ColumnTagProperty(*, column_description=None, column_geographic_role=None)
Bases:
object
A tag for a column in a
[TagColumnOperation](https://docs.aws.amazon.com/quicksight/latest/APIReference/API_TagColumnOperation.html)
structure. This is a variant type structure. For this structure to be valid, only one of the attributes can be non-null.- Parameters:
column_description (
Union
[IResolvable
,ColumnDescriptionProperty
,Dict
[str
,Any
],None
]) – A description for a column.column_geographic_role (
Optional
[str
]) – A geospatial role for a column.
- 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 import aws_quicksight as quicksight column_tag_property = quicksight.CfnDataSet.ColumnTagProperty( column_description=quicksight.CfnDataSet.ColumnDescriptionProperty( text="text" ), column_geographic_role="columnGeographicRole" )
Attributes
- column_description
A description for a column.
- column_geographic_role
A geospatial role for a column.
CreateColumnsOperationProperty
- class CfnDataSet.CreateColumnsOperationProperty(*, columns)
Bases:
object
A transform operation that creates calculated columns.
Columns created in one such operation form a lexical closure.
- Parameters:
columns (
Union
[IResolvable
,Sequence
[Union
[IResolvable
,CalculatedColumnProperty
,Dict
[str
,Any
]]]]) – Calculated columns to create.- 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 import aws_quicksight as quicksight create_columns_operation_property = quicksight.CfnDataSet.CreateColumnsOperationProperty( columns=[quicksight.CfnDataSet.CalculatedColumnProperty( column_id="columnId", column_name="columnName", expression="expression" )] )
Attributes
CustomSqlProperty
- class CfnDataSet.CustomSqlProperty(*, data_source_arn, name, sql_query, columns=None)
Bases:
object
A physical table type built from the results of the custom SQL query.
- Parameters:
data_source_arn (
str
) – The Amazon Resource Name (ARN) of the data source.name (
str
) – A display name for the SQL query result.sql_query (
str
) – The SQL query.columns (
Union
[IResolvable
,Sequence
[Union
[IResolvable
,InputColumnProperty
,Dict
[str
,Any
]]],None
]) – The column schema from the SQL query result set.
- 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 import aws_quicksight as quicksight custom_sql_property = quicksight.CfnDataSet.CustomSqlProperty( data_source_arn="dataSourceArn", name="name", sql_query="sqlQuery", # the properties below are optional columns=[quicksight.CfnDataSet.InputColumnProperty( name="name", type="type", # the properties below are optional sub_type="subType" )] )
Attributes
- columns
The column schema from the SQL query result set.
- data_source_arn
The Amazon Resource Name (ARN) of the data source.
- name
A display name for the SQL query result.
DataSetRefreshPropertiesProperty
- class CfnDataSet.DataSetRefreshPropertiesProperty(*, refresh_configuration)
Bases:
object
The refresh properties of a dataset.
- Parameters:
refresh_configuration (
Union
[IResolvable
,RefreshConfigurationProperty
,Dict
[str
,Any
]]) – The refresh configuration for a dataset.- 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 import aws_quicksight as quicksight data_set_refresh_properties_property = quicksight.CfnDataSet.DataSetRefreshPropertiesProperty( refresh_configuration=quicksight.CfnDataSet.RefreshConfigurationProperty( incremental_refresh=quicksight.CfnDataSet.IncrementalRefreshProperty( lookback_window=quicksight.CfnDataSet.LookbackWindowProperty( column_name="columnName", size=123, size_unit="sizeUnit" ) ) ) )
Attributes
- refresh_configuration
The refresh configuration for a dataset.
DataSetUsageConfigurationProperty
- class CfnDataSet.DataSetUsageConfigurationProperty(*, disable_use_as_direct_query_source=None, disable_use_as_imported_source=None)
Bases:
object
The usage configuration to apply to child datasets that reference this dataset as a source.
- Parameters:
disable_use_as_direct_query_source (
Union
[bool
,IResolvable
,None
]) – An option that controls whether a child dataset of a direct query can use this dataset as a source. Default: - falsedisable_use_as_imported_source (
Union
[bool
,IResolvable
,None
]) – An option that controls whether a child dataset that’s stored in QuickSight can use this dataset as a source. Default: - false
- 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 import aws_quicksight as quicksight data_set_usage_configuration_property = quicksight.CfnDataSet.DataSetUsageConfigurationProperty( disable_use_as_direct_query_source=False, disable_use_as_imported_source=False )
Attributes
- disable_use_as_direct_query_source
An option that controls whether a child dataset of a direct query can use this dataset as a source.
- disable_use_as_imported_source
An option that controls whether a child dataset that’s stored in QuickSight can use this dataset as a source.
DatasetParameterProperty
- class CfnDataSet.DatasetParameterProperty(*, date_time_dataset_parameter=None, decimal_dataset_parameter=None, integer_dataset_parameter=None, string_dataset_parameter=None)
Bases:
object
The parameter declarations of the dataset.
- Parameters:
date_time_dataset_parameter (
Union
[IResolvable
,DateTimeDatasetParameterProperty
,Dict
[str
,Any
],None
]) – A date time parameter that is created in the dataset.decimal_dataset_parameter (
Union
[IResolvable
,DecimalDatasetParameterProperty
,Dict
[str
,Any
],None
]) – A decimal parameter that is created in the dataset.integer_dataset_parameter (
Union
[IResolvable
,IntegerDatasetParameterProperty
,Dict
[str
,Any
],None
]) – An integer parameter that is created in the dataset.string_dataset_parameter (
Union
[IResolvable
,StringDatasetParameterProperty
,Dict
[str
,Any
],None
]) – A string parameter that is created in the dataset.
- 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 import aws_quicksight as quicksight dataset_parameter_property = quicksight.CfnDataSet.DatasetParameterProperty( date_time_dataset_parameter=quicksight.CfnDataSet.DateTimeDatasetParameterProperty( id="id", name="name", value_type="valueType", # the properties below are optional default_values=quicksight.CfnDataSet.DateTimeDatasetParameterDefaultValuesProperty( static_values=["staticValues"] ), time_granularity="timeGranularity" ), decimal_dataset_parameter=quicksight.CfnDataSet.DecimalDatasetParameterProperty( id="id", name="name", value_type="valueType", # the properties below are optional default_values=quicksight.CfnDataSet.DecimalDatasetParameterDefaultValuesProperty( static_values=[123] ) ), integer_dataset_parameter=quicksight.CfnDataSet.IntegerDatasetParameterProperty( id="id", name="name", value_type="valueType", # the properties below are optional default_values=quicksight.CfnDataSet.IntegerDatasetParameterDefaultValuesProperty( static_values=[123] ) ), string_dataset_parameter=quicksight.CfnDataSet.StringDatasetParameterProperty( id="id", name="name", value_type="valueType", # the properties below are optional default_values=quicksight.CfnDataSet.StringDatasetParameterDefaultValuesProperty( static_values=["staticValues"] ) ) )
Attributes
- date_time_dataset_parameter
A date time parameter that is created in the dataset.
- decimal_dataset_parameter
A decimal parameter that is created in the dataset.
- integer_dataset_parameter
An integer parameter that is created in the dataset.
- string_dataset_parameter
A string parameter that is created in the dataset.
DateTimeDatasetParameterDefaultValuesProperty
- class CfnDataSet.DateTimeDatasetParameterDefaultValuesProperty(*, static_values=None)
Bases:
object
- Parameters:
static_values (
Optional
[Sequence
[str
]]) – A list of static default values for a given date time parameter. The valid format for this property isyyyy-MM-dd’T’HH:mm:ss’Z’
.- 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 import aws_quicksight as quicksight date_time_dataset_parameter_default_values_property = quicksight.CfnDataSet.DateTimeDatasetParameterDefaultValuesProperty( static_values=["staticValues"] )
Attributes
- static_values
A list of static default values for a given date time parameter.
The valid format for this property is
yyyy-MM-dd’T’HH:mm:ss’Z’
.
DateTimeDatasetParameterProperty
- class CfnDataSet.DateTimeDatasetParameterProperty(*, id, name, value_type, default_values=None, time_granularity=None)
Bases:
object
A date time parameter that is created in the dataset.
- Parameters:
id (
str
) – An identifier for the parameter that is created in the dataset.name (
str
) – The name of the date time parameter that is created in the dataset.value_type (
str
) – The value type of the dataset parameter. Valid values aresingle value
ormulti value
.default_values (
Union
[IResolvable
,DateTimeDatasetParameterDefaultValuesProperty
,Dict
[str
,Any
],None
]) – A list of default values for a given date time parameter. This structure only accepts static values.time_granularity (
Optional
[str
]) – The time granularity of the date time parameter.
- 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 import aws_quicksight as quicksight date_time_dataset_parameter_property = quicksight.CfnDataSet.DateTimeDatasetParameterProperty( id="id", name="name", value_type="valueType", # the properties below are optional default_values=quicksight.CfnDataSet.DateTimeDatasetParameterDefaultValuesProperty( static_values=["staticValues"] ), time_granularity="timeGranularity" )
Attributes
- default_values
A list of default values for a given date time parameter.
This structure only accepts static values.
- id
An identifier for the parameter that is created in the dataset.
- name
The name of the date time parameter that is created in the dataset.
- time_granularity
The time granularity of the date time parameter.
- value_type
The value type of the dataset parameter.
Valid values are
single value
ormulti value
.
DecimalDatasetParameterDefaultValuesProperty
- class CfnDataSet.DecimalDatasetParameterDefaultValuesProperty(*, static_values=None)
Bases:
object
A list of default values for a given decimal parameter.
This structure only accepts static values.
- Parameters:
static_values (
Union
[IResolvable
,Sequence
[Union
[int
,float
]],None
]) – A list of static default values for a given decimal parameter.- 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 import aws_quicksight as quicksight decimal_dataset_parameter_default_values_property = quicksight.CfnDataSet.DecimalDatasetParameterDefaultValuesProperty( static_values=[123] )
Attributes
- static_values
A list of static default values for a given decimal parameter.
DecimalDatasetParameterProperty
- class CfnDataSet.DecimalDatasetParameterProperty(*, id, name, value_type, default_values=None)
Bases:
object
A decimal parameter that is created in the dataset.
- Parameters:
id (
str
) – An identifier for the decimal parameter created in the dataset.name (
str
) – The name of the decimal parameter that is created in the dataset.value_type (
str
) – The value type of the dataset parameter. Valid values aresingle value
ormulti value
.default_values (
Union
[IResolvable
,DecimalDatasetParameterDefaultValuesProperty
,Dict
[str
,Any
],None
]) – A list of default values for a given decimal parameter. This structure only accepts static values.
- 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 import aws_quicksight as quicksight decimal_dataset_parameter_property = quicksight.CfnDataSet.DecimalDatasetParameterProperty( id="id", name="name", value_type="valueType", # the properties below are optional default_values=quicksight.CfnDataSet.DecimalDatasetParameterDefaultValuesProperty( static_values=[123] ) )
Attributes
- default_values
A list of default values for a given decimal parameter.
This structure only accepts static values.
- id
An identifier for the decimal parameter created in the dataset.
- name
The name of the decimal parameter that is created in the dataset.
- value_type
The value type of the dataset parameter.
Valid values are
single value
ormulti value
.
FieldFolderProperty
- class CfnDataSet.FieldFolderProperty(*, columns=None, description=None)
Bases:
object
A FieldFolder element is a folder that contains fields and nested subfolders.
- Parameters:
columns (
Optional
[Sequence
[str
]]) – A folder has a list of columns. A column can only be in one folder.description (
Optional
[str
]) – The description for a field folder.
- 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 import aws_quicksight as quicksight field_folder_property = quicksight.CfnDataSet.FieldFolderProperty( columns=["columns"], description="description" )
Attributes
- columns
A folder has a list of columns.
A column can only be in one folder.
- description
The description for a field folder.
FilterOperationProperty
- class CfnDataSet.FilterOperationProperty(*, condition_expression)
Bases:
object
A transform operation that filters rows based on a condition.
- Parameters:
condition_expression (
str
) – An expression that must evaluate to a Boolean value. Rows for which the expression evaluates to true are kept in the dataset.- 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 import aws_quicksight as quicksight filter_operation_property = quicksight.CfnDataSet.FilterOperationProperty( condition_expression="conditionExpression" )
Attributes
- condition_expression
An expression that must evaluate to a Boolean value.
Rows for which the expression evaluates to true are kept in the dataset.
GeoSpatialColumnGroupProperty
- class CfnDataSet.GeoSpatialColumnGroupProperty(*, columns, name, country_code=None)
Bases:
object
Geospatial column group that denotes a hierarchy.
- Parameters:
columns (
Sequence
[str
]) – Columns in this hierarchy.name (
str
) – A display name for the hierarchy.country_code (
Optional
[str
]) – Country code.
- 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 import aws_quicksight as quicksight geo_spatial_column_group_property = quicksight.CfnDataSet.GeoSpatialColumnGroupProperty( columns=["columns"], name="name", # the properties below are optional country_code="countryCode" )
Attributes
- columns
Columns in this hierarchy.
- country_code
Country code.
- name
A display name for the hierarchy.
IncrementalRefreshProperty
- class CfnDataSet.IncrementalRefreshProperty(*, lookback_window)
Bases:
object
The incremental refresh configuration for a dataset.
- Parameters:
lookback_window (
Union
[IResolvable
,LookbackWindowProperty
,Dict
[str
,Any
]]) – The lookback window setup for an incremental refresh configuration.- 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 import aws_quicksight as quicksight incremental_refresh_property = quicksight.CfnDataSet.IncrementalRefreshProperty( lookback_window=quicksight.CfnDataSet.LookbackWindowProperty( column_name="columnName", size=123, size_unit="sizeUnit" ) )
Attributes
- lookback_window
The lookback window setup for an incremental refresh configuration.
IngestionWaitPolicyProperty
- class CfnDataSet.IngestionWaitPolicyProperty(*, ingestion_wait_time_in_hours=None, wait_for_spice_ingestion=None)
Bases:
object
The wait policy to use when creating or updating a Dataset.
The default is to wait for SPICE ingestion to finish with timeout of 36 hours.
- Parameters:
ingestion_wait_time_in_hours (
Union
[int
,float
,None
]) – The maximum time (in hours) to wait for Ingestion to complete. Default timeout is 36 hours. Applicable only whenDataSetImportMode
mode is set to SPICE andWaitForSpiceIngestion
is set to true. Default: - 36wait_for_spice_ingestion (
Union
[bool
,IResolvable
,None
]) – Wait for SPICE ingestion to finish to mark dataset creation or update as successful. Default (true). Applicable only whenDataSetImportMode
mode is set to SPICE. Default: - true
- 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 import aws_quicksight as quicksight ingestion_wait_policy_property = quicksight.CfnDataSet.IngestionWaitPolicyProperty( ingestion_wait_time_in_hours=123, wait_for_spice_ingestion=False )
Attributes
- ingestion_wait_time_in_hours
The maximum time (in hours) to wait for Ingestion to complete.
Default timeout is 36 hours. Applicable only when
DataSetImportMode
mode is set to SPICE andWaitForSpiceIngestion
is set to true.
- wait_for_spice_ingestion
Wait for SPICE ingestion to finish to mark dataset creation or update as successful.
Default (true). Applicable only when
DataSetImportMode
mode is set to SPICE.
InputColumnProperty
- class CfnDataSet.InputColumnProperty(*, name, type, sub_type=None)
Bases:
object
Metadata for a column that is used as the input of a transform operation.
- Parameters:
name (
str
) – The name of this column in the underlying data source.type (
str
) – The data type of the column.sub_type (
Optional
[str
]) – The sub data type of the column. Sub types are only available for decimal columns that are part of a SPICE dataset.
- 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 import aws_quicksight as quicksight input_column_property = quicksight.CfnDataSet.InputColumnProperty( name="name", type="type", # the properties below are optional sub_type="subType" )
Attributes
- name
The name of this column in the underlying data source.
- sub_type
The sub data type of the column.
Sub types are only available for decimal columns that are part of a SPICE dataset.
- type
The data type of the column.
IntegerDatasetParameterDefaultValuesProperty
- class CfnDataSet.IntegerDatasetParameterDefaultValuesProperty(*, static_values=None)
Bases:
object
A list of default values for a given integer parameter.
This structure only accepts static values.
- Parameters:
static_values (
Union
[IResolvable
,Sequence
[Union
[int
,float
]],None
]) – A list of static default values for a given integer parameter.- 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 import aws_quicksight as quicksight integer_dataset_parameter_default_values_property = quicksight.CfnDataSet.IntegerDatasetParameterDefaultValuesProperty( static_values=[123] )
Attributes
- static_values
A list of static default values for a given integer parameter.
IntegerDatasetParameterProperty
- class CfnDataSet.IntegerDatasetParameterProperty(*, id, name, value_type, default_values=None)
Bases:
object
An integer parameter that is created in the dataset.
- Parameters:
id (
str
) – An identifier for the integer parameter created in the dataset.name (
str
) – The name of the integer parameter that is created in the dataset.value_type (
str
) – The value type of the dataset parameter. Valid values aresingle value
ormulti value
.default_values (
Union
[IResolvable
,IntegerDatasetParameterDefaultValuesProperty
,Dict
[str
,Any
],None
]) – A list of default values for a given integer parameter. This structure only accepts static values.
- 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 import aws_quicksight as quicksight integer_dataset_parameter_property = quicksight.CfnDataSet.IntegerDatasetParameterProperty( id="id", name="name", value_type="valueType", # the properties below are optional default_values=quicksight.CfnDataSet.IntegerDatasetParameterDefaultValuesProperty( static_values=[123] ) )
Attributes
- default_values
A list of default values for a given integer parameter.
This structure only accepts static values.
- id
An identifier for the integer parameter created in the dataset.
- name
The name of the integer parameter that is created in the dataset.
- value_type
The value type of the dataset parameter.
Valid values are
single value
ormulti value
.
JoinInstructionProperty
- class CfnDataSet.JoinInstructionProperty(*, left_operand, on_clause, right_operand, type, left_join_key_properties=None, right_join_key_properties=None)
Bases:
object
The instructions associated with a join.
- Parameters:
left_operand (
str
) – The operand on the left side of a join.on_clause (
str
) – The join instructions provided in theON
clause of a join.right_operand (
str
) – The operand on the right side of a join.type (
str
) – The type of join that it is.left_join_key_properties (
Union
[IResolvable
,JoinKeyPropertiesProperty
,Dict
[str
,Any
],None
]) – Join key properties of the left operand.right_join_key_properties (
Union
[IResolvable
,JoinKeyPropertiesProperty
,Dict
[str
,Any
],None
]) – Join key properties of the right operand.
- 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 import aws_quicksight as quicksight join_instruction_property = quicksight.CfnDataSet.JoinInstructionProperty( left_operand="leftOperand", on_clause="onClause", right_operand="rightOperand", type="type", # the properties below are optional left_join_key_properties=quicksight.CfnDataSet.JoinKeyPropertiesProperty( unique_key=False ), right_join_key_properties=quicksight.CfnDataSet.JoinKeyPropertiesProperty( unique_key=False ) )
Attributes
- left_join_key_properties
Join key properties of the left operand.
- left_operand
The operand on the left side of a join.
- on_clause
The join instructions provided in the
ON
clause of a join.
- right_join_key_properties
Join key properties of the right operand.
- right_operand
The operand on the right side of a join.
JoinKeyPropertiesProperty
- class CfnDataSet.JoinKeyPropertiesProperty(*, unique_key=None)
Bases:
object
Properties associated with the columns participating in a join.
- Parameters:
unique_key (
Union
[bool
,IResolvable
,None
]) – A value that indicates that a row in a table is uniquely identified by the columns in a join key. This is used by Amazon QuickSight to optimize query performance.- 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 import aws_quicksight as quicksight join_key_properties_property = quicksight.CfnDataSet.JoinKeyPropertiesProperty( unique_key=False )
Attributes
- unique_key
A value that indicates that a row in a table is uniquely identified by the columns in a join key.
This is used by Amazon QuickSight to optimize query performance.
LogicalTableProperty
- class CfnDataSet.LogicalTableProperty(*, alias, data_transforms=None, source=None)
Bases:
object
A logical table is a unit that joins and that data transformations operate on.
A logical table has a source, which can be either a physical table or result of a join. When a logical table points to a physical table, the logical table acts as a mutable copy of that physical table through transform operations.
- Parameters:
alias (
str
) – A display name for the logical table.data_transforms (
Union
[IResolvable
,Sequence
[Union
[IResolvable
,TransformOperationProperty
,Dict
[str
,Any
]]],None
]) – Transform operations that act on this logical table. For this structure to be valid, only one of the attributes can be non-null.source (
Union
[IResolvable
,LogicalTableSourceProperty
,Dict
[str
,Any
],None
]) – Source of this logical 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 import aws_quicksight as quicksight logical_table_property = quicksight.CfnDataSet.LogicalTableProperty( alias="alias", # the properties below are optional data_transforms=[quicksight.CfnDataSet.TransformOperationProperty( cast_column_type_operation=quicksight.CfnDataSet.CastColumnTypeOperationProperty( column_name="columnName", new_column_type="newColumnType", # the properties below are optional format="format", sub_type="subType" ), create_columns_operation=quicksight.CfnDataSet.CreateColumnsOperationProperty( columns=[quicksight.CfnDataSet.CalculatedColumnProperty( column_id="columnId", column_name="columnName", expression="expression" )] ), filter_operation=quicksight.CfnDataSet.FilterOperationProperty( condition_expression="conditionExpression" ), override_dataset_parameter_operation=quicksight.CfnDataSet.OverrideDatasetParameterOperationProperty( parameter_name="parameterName", # the properties below are optional new_default_values=quicksight.CfnDataSet.NewDefaultValuesProperty( date_time_static_values=["dateTimeStaticValues"], decimal_static_values=[123], integer_static_values=[123], string_static_values=["stringStaticValues"] ), new_parameter_name="newParameterName" ), project_operation=quicksight.CfnDataSet.ProjectOperationProperty( projected_columns=["projectedColumns"] ), rename_column_operation=quicksight.CfnDataSet.RenameColumnOperationProperty( column_name="columnName", new_column_name="newColumnName" ), tag_column_operation=quicksight.CfnDataSet.TagColumnOperationProperty( column_name="columnName", tags=[quicksight.CfnDataSet.ColumnTagProperty( column_description=quicksight.CfnDataSet.ColumnDescriptionProperty( text="text" ), column_geographic_role="columnGeographicRole" )] ), untag_column_operation=quicksight.CfnDataSet.UntagColumnOperationProperty( column_name="columnName", tag_names=["tagNames"] ) )], source=quicksight.CfnDataSet.LogicalTableSourceProperty( data_set_arn="dataSetArn", join_instruction=quicksight.CfnDataSet.JoinInstructionProperty( left_operand="leftOperand", on_clause="onClause", right_operand="rightOperand", type="type", # the properties below are optional left_join_key_properties=quicksight.CfnDataSet.JoinKeyPropertiesProperty( unique_key=False ), right_join_key_properties=quicksight.CfnDataSet.JoinKeyPropertiesProperty( unique_key=False ) ), physical_table_id="physicalTableId" ) )
Attributes
- alias
A display name for the logical table.
- data_transforms
Transform operations that act on this logical table.
For this structure to be valid, only one of the attributes can be non-null.
- source
Source of this logical table.
LogicalTableSourceProperty
- class CfnDataSet.LogicalTableSourceProperty(*, data_set_arn=None, join_instruction=None, physical_table_id=None)
Bases:
object
Information about the source of a logical table.
This is a variant type structure. For this structure to be valid, only one of the attributes can be non-null.
- Parameters:
data_set_arn (
Optional
[str
]) – The Amazon Resource Number (ARN) of the parent dataset.join_instruction (
Union
[IResolvable
,JoinInstructionProperty
,Dict
[str
,Any
],None
]) – Specifies the result of a join of two logical tables.physical_table_id (
Optional
[str
]) – Physical table ID.
- 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 import aws_quicksight as quicksight logical_table_source_property = quicksight.CfnDataSet.LogicalTableSourceProperty( data_set_arn="dataSetArn", join_instruction=quicksight.CfnDataSet.JoinInstructionProperty( left_operand="leftOperand", on_clause="onClause", right_operand="rightOperand", type="type", # the properties below are optional left_join_key_properties=quicksight.CfnDataSet.JoinKeyPropertiesProperty( unique_key=False ), right_join_key_properties=quicksight.CfnDataSet.JoinKeyPropertiesProperty( unique_key=False ) ), physical_table_id="physicalTableId" )
Attributes
- data_set_arn
The Amazon Resource Number (ARN) of the parent dataset.
- join_instruction
Specifies the result of a join of two logical tables.
LookbackWindowProperty
- class CfnDataSet.LookbackWindowProperty(*, column_name, size, size_unit)
Bases:
object
The lookback window setup of an incremental refresh configuration.
- Parameters:
column_name (
str
) – The name of the lookback window column.size (
Union
[int
,float
]) – The lookback window column size. Default: - 0size_unit (
str
) – The size unit that is used for the lookback window column. Valid values for this structure areHOUR
,DAY
, andWEEK
.
- 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 import aws_quicksight as quicksight lookback_window_property = quicksight.CfnDataSet.LookbackWindowProperty( column_name="columnName", size=123, size_unit="sizeUnit" )
Attributes
- column_name
The name of the lookback window column.
- size
The lookback window column size.
- size_unit
The size unit that is used for the lookback window column.
Valid values for this structure are
HOUR
,DAY
, andWEEK
.
NewDefaultValuesProperty
- class CfnDataSet.NewDefaultValuesProperty(*, date_time_static_values=None, decimal_static_values=None, integer_static_values=None, string_static_values=None)
Bases:
object
The new default values for the parameter.
- Parameters:
date_time_static_values (
Optional
[Sequence
[str
]]) – A list of static default values for a given date time parameter. The valid format for this property isyyyy-MM-dd’T’HH:mm:ss’Z’
.decimal_static_values (
Union
[IResolvable
,Sequence
[Union
[int
,float
]],None
]) – A list of static default values for a given decimal parameter.integer_static_values (
Union
[IResolvable
,Sequence
[Union
[int
,float
]],None
]) – A list of static default values for a given integer parameter.string_static_values (
Optional
[Sequence
[str
]]) – A list of static default values for a given string parameter.
- 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 import aws_quicksight as quicksight new_default_values_property = quicksight.CfnDataSet.NewDefaultValuesProperty( date_time_static_values=["dateTimeStaticValues"], decimal_static_values=[123], integer_static_values=[123], string_static_values=["stringStaticValues"] )
Attributes
- date_time_static_values
A list of static default values for a given date time parameter.
The valid format for this property is
yyyy-MM-dd’T’HH:mm:ss’Z’
.
- decimal_static_values
A list of static default values for a given decimal parameter.
- integer_static_values
A list of static default values for a given integer parameter.
- string_static_values
A list of static default values for a given string parameter.
OutputColumnProperty
- class CfnDataSet.OutputColumnProperty(*, description=None, name=None, sub_type=None, type=None)
Bases:
object
Output column.
- Parameters:
description (
Optional
[str
]) – A description for a column.name (
Optional
[str
]) – The display name of the column..sub_type (
Optional
[str
]) – The sub data type of the column.type (
Optional
[str
]) – The data type of the column.
- 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 import aws_quicksight as quicksight output_column_property = quicksight.CfnDataSet.OutputColumnProperty( description="description", name="name", sub_type="subType", type="type" )
Attributes
- description
A description for a column.
- name
The display name of the column..
- sub_type
The sub data type of the column.
- type
The data type of the column.
OverrideDatasetParameterOperationProperty
- class CfnDataSet.OverrideDatasetParameterOperationProperty(*, parameter_name, new_default_values=None, new_parameter_name=None)
Bases:
object
A transform operation that overrides the dataset parameter values that are defined in another dataset.
- Parameters:
parameter_name (
str
) – The name of the parameter to be overridden with different values.new_default_values (
Union
[IResolvable
,NewDefaultValuesProperty
,Dict
[str
,Any
],None
]) – The new default values for the parameter.new_parameter_name (
Optional
[str
]) – The new name for the parameter.
- 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 import aws_quicksight as quicksight override_dataset_parameter_operation_property = quicksight.CfnDataSet.OverrideDatasetParameterOperationProperty( parameter_name="parameterName", # the properties below are optional new_default_values=quicksight.CfnDataSet.NewDefaultValuesProperty( date_time_static_values=["dateTimeStaticValues"], decimal_static_values=[123], integer_static_values=[123], string_static_values=["stringStaticValues"] ), new_parameter_name="newParameterName" )
Attributes
- new_default_values
The new default values for the parameter.
- new_parameter_name
The new name for the parameter.
- parameter_name
The name of the parameter to be overridden with different values.
PhysicalTableProperty
- class CfnDataSet.PhysicalTableProperty(*, custom_sql=None, relational_table=None, s3_source=None)
Bases:
object
A view of a data source that contains information about the shape of the data in the underlying source.
This is a variant type structure. For this structure to be valid, only one of the attributes can be non-null.
- Parameters:
custom_sql (
Union
[IResolvable
,CustomSqlProperty
,Dict
[str
,Any
],None
]) – A physical table type built from the results of the custom SQL query.relational_table (
Union
[IResolvable
,RelationalTableProperty
,Dict
[str
,Any
],None
]) – A physical table type for relational data sources.s3_source (
Union
[IResolvable
,S3SourceProperty
,Dict
[str
,Any
],None
]) – A physical table type for as S3 data source.
- 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 import aws_quicksight as quicksight physical_table_property = quicksight.CfnDataSet.PhysicalTableProperty( custom_sql=quicksight.CfnDataSet.CustomSqlProperty( data_source_arn="dataSourceArn", name="name", sql_query="sqlQuery", # the properties below are optional columns=[quicksight.CfnDataSet.InputColumnProperty( name="name", type="type", # the properties below are optional sub_type="subType" )] ), relational_table=quicksight.CfnDataSet.RelationalTableProperty( data_source_arn="dataSourceArn", name="name", # the properties below are optional catalog="catalog", input_columns=[quicksight.CfnDataSet.InputColumnProperty( name="name", type="type", # the properties below are optional sub_type="subType" )], schema="schema" ), s3_source=quicksight.CfnDataSet.S3SourceProperty( data_source_arn="dataSourceArn", input_columns=[quicksight.CfnDataSet.InputColumnProperty( name="name", type="type", # the properties below are optional sub_type="subType" )], # the properties below are optional upload_settings=quicksight.CfnDataSet.UploadSettingsProperty( contains_header=False, delimiter="delimiter", format="format", start_from_row=123, text_qualifier="textQualifier" ) ) )
Attributes
- custom_sql
A physical table type built from the results of the custom SQL query.
- relational_table
A physical table type for relational data sources.
- s3_source
A physical table type for as S3 data source.
ProjectOperationProperty
- class CfnDataSet.ProjectOperationProperty(*, projected_columns)
Bases:
object
A transform operation that projects columns.
Operations that come after a projection can only refer to projected columns.
- Parameters:
projected_columns (
Sequence
[str
]) – Projected columns.- 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 import aws_quicksight as quicksight project_operation_property = quicksight.CfnDataSet.ProjectOperationProperty( projected_columns=["projectedColumns"] )
Attributes
RefreshConfigurationProperty
- class CfnDataSet.RefreshConfigurationProperty(*, incremental_refresh)
Bases:
object
The refresh configuration of a dataset.
- Parameters:
incremental_refresh (
Union
[IResolvable
,IncrementalRefreshProperty
,Dict
[str
,Any
]]) – The incremental refresh for the dataset.- 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 import aws_quicksight as quicksight refresh_configuration_property = quicksight.CfnDataSet.RefreshConfigurationProperty( incremental_refresh=quicksight.CfnDataSet.IncrementalRefreshProperty( lookback_window=quicksight.CfnDataSet.LookbackWindowProperty( column_name="columnName", size=123, size_unit="sizeUnit" ) ) )
Attributes
- incremental_refresh
The incremental refresh for the dataset.
RelationalTableProperty
- class CfnDataSet.RelationalTableProperty(*, data_source_arn, name, catalog=None, input_columns=None, schema=None)
Bases:
object
A physical table type for relational data sources.
- Parameters:
data_source_arn (
str
) – The Amazon Resource Name (ARN) for the data source.name (
str
) – The name of the relational table.catalog (
Optional
[str
]) – The catalog associated with a table.input_columns (
Union
[IResolvable
,Sequence
[Union
[IResolvable
,InputColumnProperty
,Dict
[str
,Any
]]],None
]) – The column schema of the table.schema (
Optional
[str
]) – The schema name. This name applies to certain relational database engines.
- 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 import aws_quicksight as quicksight relational_table_property = quicksight.CfnDataSet.RelationalTableProperty( data_source_arn="dataSourceArn", name="name", # the properties below are optional catalog="catalog", input_columns=[quicksight.CfnDataSet.InputColumnProperty( name="name", type="type", # the properties below are optional sub_type="subType" )], schema="schema" )
Attributes
- catalog
The catalog associated with a table.
- data_source_arn
The Amazon Resource Name (ARN) for the data source.
- input_columns
The column schema of the table.
- name
The name of the relational table.
- schema
The schema name.
This name applies to certain relational database engines.
RenameColumnOperationProperty
- class CfnDataSet.RenameColumnOperationProperty(*, column_name, new_column_name)
Bases:
object
A transform operation that renames a column.
- Parameters:
column_name (
str
) – The name of the column to be renamed.new_column_name (
str
) – The new name for the column.
- 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 import aws_quicksight as quicksight rename_column_operation_property = quicksight.CfnDataSet.RenameColumnOperationProperty( column_name="columnName", new_column_name="newColumnName" )
Attributes
- column_name
The name of the column to be renamed.
- new_column_name
The new name for the column.
ResourcePermissionProperty
- class CfnDataSet.ResourcePermissionProperty(*, actions, principal)
Bases:
object
Permission for the resource.
- Parameters:
actions (
Sequence
[str
]) – The IAM action to grant or revoke permisions on.principal (
str
) – The Amazon Resource Name (ARN) of the principal. This can be one of the following:. - The ARN of an Amazon QuickSight user or group associated with a data source or dataset. (This is common.) - The ARN of an Amazon QuickSight user, group, or namespace associated with an analysis, dashboard, template, or theme. (This is common.) - The ARN of an AWS account root: This is an IAM ARN rather than a Amazon QuickSight ARN. Use this option only to share resources (templates) across AWS accounts . (This is less common.)
- 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 import aws_quicksight as quicksight resource_permission_property = quicksight.CfnDataSet.ResourcePermissionProperty( actions=["actions"], principal="principal" )
Attributes
- actions
The IAM action to grant or revoke permisions on.
- principal
.
The ARN of an Amazon QuickSight user or group associated with a data source or dataset. (This is common.)
The ARN of an Amazon QuickSight user, group, or namespace associated with an analysis, dashboard, template, or theme. (This is common.)
The ARN of an AWS account root: This is an IAM ARN rather than a Amazon QuickSight ARN. Use this option only to share resources (templates) across AWS accounts . (This is less common.)
- See:
- Type:
The Amazon Resource Name (ARN) of the principal. This can be one of the following
RowLevelPermissionDataSetProperty
- class CfnDataSet.RowLevelPermissionDataSetProperty(*, arn, permission_policy, format_version=None, namespace=None, status=None)
Bases:
object
Information about a dataset that contains permissions for row-level security (RLS).
The permissions dataset maps fields to users or groups. For more information, see Using Row-Level Security (RLS) to Restrict Access to a Dataset in the Amazon QuickSight User Guide .
The option to deny permissions by setting
PermissionPolicy
toDENY_ACCESS
is not supported for new RLS datasets.- Parameters:
arn (
str
) – The Amazon Resource Name (ARN) of the dataset that contains permissions for RLS.permission_policy (
str
) – The type of permissions to use when interpreting the permissions for RLS.DENY_ACCESS
is included for backward compatibility only.format_version (
Optional
[str
]) – The user or group rules associated with the dataset that contains permissions for RLS. By default,FormatVersion
isVERSION_1
. WhenFormatVersion
isVERSION_1
,UserName
andGroupName
are required. WhenFormatVersion
isVERSION_2
,UserARN
andGroupARN
are required, andNamespace
must not exist.namespace (
Optional
[str
]) – The namespace associated with the dataset that contains permissions for RLS.status (
Optional
[str
]) – The status of the row-level security permission dataset. If enabled, the status isENABLED
. If disabled, the status isDISABLED
.
- 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 import aws_quicksight as quicksight row_level_permission_data_set_property = quicksight.CfnDataSet.RowLevelPermissionDataSetProperty( arn="arn", permission_policy="permissionPolicy", # the properties below are optional format_version="formatVersion", namespace="namespace", status="status" )
Attributes
- arn
The Amazon Resource Name (ARN) of the dataset that contains permissions for RLS.
- format_version
The user or group rules associated with the dataset that contains permissions for RLS.
By default,
FormatVersion
isVERSION_1
. WhenFormatVersion
isVERSION_1
,UserName
andGroupName
are required. WhenFormatVersion
isVERSION_2
,UserARN
andGroupARN
are required, andNamespace
must not exist.
- namespace
The namespace associated with the dataset that contains permissions for RLS.
- permission_policy
The type of permissions to use when interpreting the permissions for RLS.
DENY_ACCESS
is included for backward compatibility only.
- status
The status of the row-level security permission dataset.
If enabled, the status is
ENABLED
. If disabled, the status isDISABLED
.
RowLevelPermissionTagConfigurationProperty
- class CfnDataSet.RowLevelPermissionTagConfigurationProperty(*, tag_rules, status=None, tag_rule_configurations=None)
Bases:
object
The element you can use to define tags for row-level security.
- Parameters:
tag_rules (
Union
[IResolvable
,Sequence
[Union
[IResolvable
,RowLevelPermissionTagRuleProperty
,Dict
[str
,Any
]]]]) – A set of rules associated with row-level security, such as the tag names and columns that they are assigned to.status (
Optional
[str
]) – The status of row-level security tags. If enabled, the status isENABLED
. If disabled, the status isDISABLED
.tag_rule_configurations (
Any
) – The configuration of tags on a dataset to set row-level security.
- 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 import aws_quicksight as quicksight # tag_rule_configurations: Any row_level_permission_tag_configuration_property = quicksight.CfnDataSet.RowLevelPermissionTagConfigurationProperty( tag_rules=[quicksight.CfnDataSet.RowLevelPermissionTagRuleProperty( column_name="columnName", tag_key="tagKey", # the properties below are optional match_all_value="matchAllValue", tag_multi_value_delimiter="tagMultiValueDelimiter" )], # the properties below are optional status="status", tag_rule_configurations=tag_rule_configurations )
Attributes
- status
The status of row-level security tags.
If enabled, the status is
ENABLED
. If disabled, the status isDISABLED
.
- tag_rule_configurations
The configuration of tags on a dataset to set row-level security.
- tag_rules
A set of rules associated with row-level security, such as the tag names and columns that they are assigned to.
RowLevelPermissionTagRuleProperty
- class CfnDataSet.RowLevelPermissionTagRuleProperty(*, column_name, tag_key, match_all_value=None, tag_multi_value_delimiter=None)
Bases:
object
A set of rules associated with a tag.
- Parameters:
column_name (
str
) – The column name that a tag key is assigned to.tag_key (
str
) – The unique key for a tag.match_all_value (
Optional
[str
]) – A string that you want to use to filter by all the values in a column in the dataset and don’t want to list the values one by one. For example, you can use an asterisk as your match all value.tag_multi_value_delimiter (
Optional
[str
]) – A string that you want to use to delimit the values when you pass the values at run time. For example, you can delimit the values with a comma.
- 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 import aws_quicksight as quicksight row_level_permission_tag_rule_property = quicksight.CfnDataSet.RowLevelPermissionTagRuleProperty( column_name="columnName", tag_key="tagKey", # the properties below are optional match_all_value="matchAllValue", tag_multi_value_delimiter="tagMultiValueDelimiter" )
Attributes
- column_name
The column name that a tag key is assigned to.
- match_all_value
A string that you want to use to filter by all the values in a column in the dataset and don’t want to list the values one by one.
For example, you can use an asterisk as your match all value.
- tag_key
The unique key for a tag.
- tag_multi_value_delimiter
A string that you want to use to delimit the values when you pass the values at run time.
For example, you can delimit the values with a comma.
S3SourceProperty
- class CfnDataSet.S3SourceProperty(*, data_source_arn, input_columns, upload_settings=None)
Bases:
object
A physical table type for an S3 data source.
- Parameters:
data_source_arn (
str
) – The Amazon Resource Name (ARN) for the data source.input_columns (
Union
[IResolvable
,Sequence
[Union
[IResolvable
,InputColumnProperty
,Dict
[str
,Any
]]]]) – A physical table type for an S3 data source. .. epigraph:: For files that aren’t JSON, onlySTRING
data types are supported in input columns.upload_settings (
Union
[IResolvable
,UploadSettingsProperty
,Dict
[str
,Any
],None
]) – Information about the format for the S3 source file or files.
- 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 import aws_quicksight as quicksight s3_source_property = quicksight.CfnDataSet.S3SourceProperty( data_source_arn="dataSourceArn", input_columns=[quicksight.CfnDataSet.InputColumnProperty( name="name", type="type", # the properties below are optional sub_type="subType" )], # the properties below are optional upload_settings=quicksight.CfnDataSet.UploadSettingsProperty( contains_header=False, delimiter="delimiter", format="format", start_from_row=123, text_qualifier="textQualifier" ) )
Attributes
- data_source_arn
The Amazon Resource Name (ARN) for the data source.
- input_columns
A physical table type for an S3 data source.
For files that aren’t JSON, only
STRING
data types are supported in input columns.
- upload_settings
Information about the format for the S3 source file or files.
StringDatasetParameterDefaultValuesProperty
- class CfnDataSet.StringDatasetParameterDefaultValuesProperty(*, static_values=None)
Bases:
object
A list of default values for a given string dataset parameter type.
This structure only accepts static values.
- Parameters:
static_values (
Optional
[Sequence
[str
]]) – A list of static default values for a given string parameter.- 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 import aws_quicksight as quicksight string_dataset_parameter_default_values_property = quicksight.CfnDataSet.StringDatasetParameterDefaultValuesProperty( static_values=["staticValues"] )
Attributes
- static_values
A list of static default values for a given string parameter.
StringDatasetParameterProperty
- class CfnDataSet.StringDatasetParameterProperty(*, id, name, value_type, default_values=None)
Bases:
object
A string parameter that is created in the dataset.
- Parameters:
id (
str
) – An identifier for the string parameter that is created in the dataset.name (
str
) – The name of the string parameter that is created in the dataset.value_type (
str
) – The value type of the dataset parameter. Valid values aresingle value
ormulti value
.default_values (
Union
[IResolvable
,StringDatasetParameterDefaultValuesProperty
,Dict
[str
,Any
],None
]) – A list of default values for a given string dataset parameter type. This structure only accepts static values.
- 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 import aws_quicksight as quicksight string_dataset_parameter_property = quicksight.CfnDataSet.StringDatasetParameterProperty( id="id", name="name", value_type="valueType", # the properties below are optional default_values=quicksight.CfnDataSet.StringDatasetParameterDefaultValuesProperty( static_values=["staticValues"] ) )
Attributes
- default_values
A list of default values for a given string dataset parameter type.
This structure only accepts static values.
- id
An identifier for the string parameter that is created in the dataset.
- name
The name of the string parameter that is created in the dataset.
- value_type
The value type of the dataset parameter.
Valid values are
single value
ormulti value
.
TagColumnOperationProperty
- class CfnDataSet.TagColumnOperationProperty(*, column_name, tags)
Bases:
object
A transform operation that tags a column with additional information.
- Parameters:
column_name (
str
) – The column that this operation acts on.tags (
Sequence
[Union
[ColumnTagProperty
,Dict
[str
,Any
]]]) – The dataset column tag, currently only used for geospatial type tagging. .. epigraph:: This is not tags for the AWS tagging feature.
- 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 import aws_quicksight as quicksight tag_column_operation_property = quicksight.CfnDataSet.TagColumnOperationProperty( column_name="columnName", tags=[quicksight.CfnDataSet.ColumnTagProperty( column_description=quicksight.CfnDataSet.ColumnDescriptionProperty( text="text" ), column_geographic_role="columnGeographicRole" )] )
Attributes
- column_name
The column that this operation acts on.
- tags
The dataset column tag, currently only used for geospatial type tagging.
This is not tags for the AWS tagging feature.
TransformOperationProperty
- class CfnDataSet.TransformOperationProperty(*, cast_column_type_operation=None, create_columns_operation=None, filter_operation=None, override_dataset_parameter_operation=None, project_operation=None, rename_column_operation=None, tag_column_operation=None, untag_column_operation=None)
Bases:
object
A data transformation on a logical table.
This is a variant type structure. For this structure to be valid, only one of the attributes can be non-null.
- Parameters:
cast_column_type_operation (
Union
[IResolvable
,CastColumnTypeOperationProperty
,Dict
[str
,Any
],None
]) – A transform operation that casts a column to a different type.create_columns_operation (
Union
[IResolvable
,CreateColumnsOperationProperty
,Dict
[str
,Any
],None
]) – An operation that creates calculated columns. Columns created in one such operation form a lexical closure.filter_operation (
Union
[IResolvable
,FilterOperationProperty
,Dict
[str
,Any
],None
]) – An operation that filters rows based on some condition.override_dataset_parameter_operation (
Union
[IResolvable
,OverrideDatasetParameterOperationProperty
,Dict
[str
,Any
],None
]) – A transform operation that overrides the dataset parameter values that are defined in another dataset.project_operation (
Union
[IResolvable
,ProjectOperationProperty
,Dict
[str
,Any
],None
]) – An operation that projects columns. Operations that come after a projection can only refer to projected columns.rename_column_operation (
Union
[IResolvable
,RenameColumnOperationProperty
,Dict
[str
,Any
],None
]) – An operation that renames a column.tag_column_operation (
Union
[IResolvable
,TagColumnOperationProperty
,Dict
[str
,Any
],None
]) – An operation that tags a column with additional information.untag_column_operation (
Union
[IResolvable
,UntagColumnOperationProperty
,Dict
[str
,Any
],None
]) –
- 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 import aws_quicksight as quicksight transform_operation_property = quicksight.CfnDataSet.TransformOperationProperty( cast_column_type_operation=quicksight.CfnDataSet.CastColumnTypeOperationProperty( column_name="columnName", new_column_type="newColumnType", # the properties below are optional format="format", sub_type="subType" ), create_columns_operation=quicksight.CfnDataSet.CreateColumnsOperationProperty( columns=[quicksight.CfnDataSet.CalculatedColumnProperty( column_id="columnId", column_name="columnName", expression="expression" )] ), filter_operation=quicksight.CfnDataSet.FilterOperationProperty( condition_expression="conditionExpression" ), override_dataset_parameter_operation=quicksight.CfnDataSet.OverrideDatasetParameterOperationProperty( parameter_name="parameterName", # the properties below are optional new_default_values=quicksight.CfnDataSet.NewDefaultValuesProperty( date_time_static_values=["dateTimeStaticValues"], decimal_static_values=[123], integer_static_values=[123], string_static_values=["stringStaticValues"] ), new_parameter_name="newParameterName" ), project_operation=quicksight.CfnDataSet.ProjectOperationProperty( projected_columns=["projectedColumns"] ), rename_column_operation=quicksight.CfnDataSet.RenameColumnOperationProperty( column_name="columnName", new_column_name="newColumnName" ), tag_column_operation=quicksight.CfnDataSet.TagColumnOperationProperty( column_name="columnName", tags=[quicksight.CfnDataSet.ColumnTagProperty( column_description=quicksight.CfnDataSet.ColumnDescriptionProperty( text="text" ), column_geographic_role="columnGeographicRole" )] ), untag_column_operation=quicksight.CfnDataSet.UntagColumnOperationProperty( column_name="columnName", tag_names=["tagNames"] ) )
Attributes
- cast_column_type_operation
A transform operation that casts a column to a different type.
- create_columns_operation
An operation that creates calculated columns.
Columns created in one such operation form a lexical closure.
- filter_operation
An operation that filters rows based on some condition.
- override_dataset_parameter_operation
A transform operation that overrides the dataset parameter values that are defined in another dataset.
- project_operation
An operation that projects columns.
Operations that come after a projection can only refer to projected columns.
- rename_column_operation
An operation that renames a column.
- tag_column_operation
An operation that tags a column with additional information.
UntagColumnOperationProperty
- class CfnDataSet.UntagColumnOperationProperty(*, column_name, tag_names)
Bases:
object
A transform operation that removes tags associated with a column.
- Parameters:
column_name (
str
) – The column that this operation acts on.tag_names (
Sequence
[str
]) – The column tags to remove from this column.
- 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 import aws_quicksight as quicksight untag_column_operation_property = quicksight.CfnDataSet.UntagColumnOperationProperty( column_name="columnName", tag_names=["tagNames"] )
Attributes
- column_name
The column that this operation acts on.
- tag_names
The column tags to remove from this column.
UploadSettingsProperty
- class CfnDataSet.UploadSettingsProperty(*, contains_header=None, delimiter=None, format=None, start_from_row=None, text_qualifier=None)
Bases:
object
Information about the format for a source file or files.
- Parameters:
contains_header (
Union
[bool
,IResolvable
,None
]) – Whether the file has a header row, or the files each have a header row.delimiter (
Optional
[str
]) – The delimiter between values in the file.format (
Optional
[str
]) – File format.start_from_row (
Union
[int
,float
,None
]) – A row number to start reading data from.text_qualifier (
Optional
[str
]) – Text qualifier.
- 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 import aws_quicksight as quicksight upload_settings_property = quicksight.CfnDataSet.UploadSettingsProperty( contains_header=False, delimiter="delimiter", format="format", start_from_row=123, text_qualifier="textQualifier" )
Attributes
- contains_header
Whether the file has a header row, or the files each have a header row.
- delimiter
The delimiter between values in the file.
- format
File format.
- start_from_row
A row number to start reading data from.