Struct CreateDataSetInput

#[non_exhaustive]
pub struct CreateDataSetInput {

    pub aws_account_id: Option<String>,
    pub data_set_id: Option<String>,
    pub name: Option<String>,
    pub physical_table_map: Option<HashMap<String, PhysicalTable>>,
    pub logical_table_map: Option<HashMap<String, LogicalTable>>,
    pub import_mode: Option<DataSetImportMode>,
    pub column_groups: Option<Vec<ColumnGroup>>,
    pub field_folders: Option<HashMap<String, FieldFolder>>,
    pub permissions: Option<Vec<ResourcePermission>>,
    pub row_level_permission_data_set: Option<RowLevelPermissionDataSet>,
    pub row_level_permission_tag_configuration: Option<RowLevelPermissionTagConfiguration>,
    pub column_level_permission_rules: Option<Vec<ColumnLevelPermissionRule>>,
    pub tags: Option<Vec<Tag>>,
    pub data_set_usage_configuration: Option<DataSetUsageConfiguration>,
    pub dataset_parameters: Option<Vec<DatasetParameter>>,
    pub folder_arns: Option<Vec<String>>,
    pub performance_configuration: Option<PerformanceConfiguration>,
    pub use_as: Option<DataSetUseAs>,
}

Fields (Non-exhaustive)

Non-exhaustive structs could have additional fields added in future. Therefore, non-exhaustive structs cannot be constructed in external crates using the traditional Struct { .. } syntax; cannot be matched against without a wildcard ..; and struct update syntax will not work.

aws_account_id: Option<String>

The Amazon Web Services account ID.

data_set_id: Option<String>

An ID for the dataset that you want to create. This ID is unique per Amazon Web Services Region for each Amazon Web Services account.

name: Option<String>

The display name for the dataset.

physical_table_map: Option<HashMap<String, PhysicalTable>>

Declares the physical tables that are available in the underlying data sources.

logical_table_map: Option<HashMap<String, LogicalTable>>

Configures the combination and transformation of the data from the physical tables.

import_mode: Option<DataSetImportMode>

Indicates whether you want to import the data into SPICE.

column_groups: Option<Vec<ColumnGroup>>

Groupings of columns that work together in certain Amazon QuickSight features. Currently, only geospatial hierarchy is supported.

field_folders: Option<HashMap<String, FieldFolder>>

The folder that contains fields and nested subfolders for your dataset.

permissions: Option<Vec<ResourcePermission>>

A list of resource permissions on the dataset.

row_level_permission_data_set: Option<RowLevelPermissionDataSet>

The row-level security configuration for the data that you want to create.

row_level_permission_tag_configuration: Option<RowLevelPermissionTagConfiguration>

The configuration of tags on a dataset to set row-level security. Row-level security tags are currently supported for anonymous embedding only.

column_level_permission_rules: Option<Vec<ColumnLevelPermissionRule>>

A set of one or more definitions of a ColumnLevelPermissionRule .

tags: Option<Vec<Tag>>

Contains a map of the key-value pairs for the resource tag or tags assigned to the dataset.

data_set_usage_configuration: Option<DataSetUsageConfiguration>

The usage configuration to apply to child datasets that reference this dataset as a source.

dataset_parameters: Option<Vec<DatasetParameter>>

The parameter declarations of the dataset.

folder_arns: Option<Vec<String>>

When you create the dataset, Amazon QuickSight adds the dataset to these folders.

performance_configuration: Option<PerformanceConfiguration>

The configuration for the performance optimization of the dataset that contains a UniqueKey configuration.

use_as: Option<DataSetUseAs>

The usage of the dataset. RLS_RULES must be specified for RLS permission datasets.

Implementations

impl CreateDataSetInput

pub fn aws_account_id(&self) -> Option<&str>

The Amazon Web Services account ID.

pub fn data_set_id(&self) -> Option<&str>

An ID for the dataset that you want to create. This ID is unique per Amazon Web Services Region for each Amazon Web Services account.

pub fn name(&self) -> Option<&str>

The display name for the dataset.

pub fn physical_table_map(&self) -> Option<&HashMap<String, PhysicalTable>>

Declares the physical tables that are available in the underlying data sources.

pub fn logical_table_map(&self) -> Option<&HashMap<String, LogicalTable>>

Configures the combination and transformation of the data from the physical tables.

pub fn import_mode(&self) -> Option<&DataSetImportMode>

Indicates whether you want to import the data into SPICE.

pub fn column_groups(&self) -> &[ColumnGroup]

Groupings of columns that work together in certain Amazon QuickSight features. Currently, only geospatial hierarchy is supported.

If no value was sent for this field, a default will be set. If you want to determine if no value was sent, use .column_groups.is_none().

pub fn field_folders(&self) -> Option<&HashMap<String, FieldFolder>>

The folder that contains fields and nested subfolders for your dataset.

pub fn permissions(&self) -> &[ResourcePermission]

A list of resource permissions on the dataset.

If no value was sent for this field, a default will be set. If you want to determine if no value was sent, use .permissions.is_none().

pub fn row_level_permission_data_set( &self, ) -> Option<&RowLevelPermissionDataSet>

The row-level security configuration for the data that you want to create.

pub fn row_level_permission_tag_configuration( &self, ) -> Option<&RowLevelPermissionTagConfiguration>

The configuration of tags on a dataset to set row-level security. Row-level security tags are currently supported for anonymous embedding only.

pub fn column_level_permission_rules(&self) -> &[ColumnLevelPermissionRule]

A set of one or more definitions of a ColumnLevelPermissionRule .

If no value was sent for this field, a default will be set. If you want to determine if no value was sent, use .column_level_permission_rules.is_none().

pub fn tags(&self) -> &[Tag]

Contains a map of the key-value pairs for the resource tag or tags assigned to the dataset.

If no value was sent for this field, a default will be set. If you want to determine if no value was sent, use .tags.is_none().

pub fn data_set_usage_configuration(&self) -> Option<&DataSetUsageConfiguration>

The usage configuration to apply to child datasets that reference this dataset as a source.

pub fn dataset_parameters(&self) -> &[DatasetParameter]

The parameter declarations of the dataset.

If no value was sent for this field, a default will be set. If you want to determine if no value was sent, use .dataset_parameters.is_none().

pub fn folder_arns(&self) -> &[String]

When you create the dataset, Amazon QuickSight adds the dataset to these folders.

If no value was sent for this field, a default will be set. If you want to determine if no value was sent, use .folder_arns.is_none().

pub fn performance_configuration(&self) -> Option<&PerformanceConfiguration>

The configuration for the performance optimization of the dataset that contains a UniqueKey configuration.

pub fn use_as(&self) -> Option<&DataSetUseAs>

The usage of the dataset. RLS_RULES must be specified for RLS permission datasets.

impl CreateDataSetInput

pub fn builder() -> CreateDataSetInputBuilder

Creates a new builder-style object to manufacture CreateDataSetInput.

Trait Implementations

impl Clone for CreateDataSetInput

fn clone(&self) -> CreateDataSetInput

Returns a duplicate of the value.

const fn clone_from(&mut self, source: &Self)

Performs copy-assignment from source.

impl Debug for CreateDataSetInput

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl PartialEq for CreateDataSetInput

fn eq(&self, other: &CreateDataSetInput) -> bool

Tests for self and other values to be equal, and is used by ==.

const fn ne(&self, other: &Rhs) -> bool

Tests for !=. The default implementation is almost always sufficient, and should not be overridden without very good reason.

impl StructuralPartialEq for CreateDataSetInput