Struct CreateAnalysisTemplateInput 

#[non_exhaustive]
pub struct CreateAnalysisTemplateInput {
    pub description: Option<String>,
    pub membership_identifier: Option<String>,
    pub name: Option<String>,
    pub format: Option<AnalysisFormat>,
    pub source: Option<AnalysisSource>,
    pub tags: Option<HashMap<String, String>>,
    pub analysis_parameters: Option<Vec<AnalysisParameter>>,
    pub schema: Option<AnalysisSchema>,
    pub error_message_configuration: Option<ErrorMessageConfiguration>,
    pub synthetic_data_parameters: Option<SyntheticDataParameters>,
}

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.

description: Option<String>

The description of the analysis template.

membership_identifier: Option<String>

The identifier for a membership resource.

name: Option<String>

The name of the analysis template.

format: Option<AnalysisFormat>

The format of the analysis template.

source: Option<AnalysisSource>

The information in the analysis template.

tags: Option<HashMap<String, String>>

An optional label that you can assign to a resource when you create it. Each tag consists of a key and an optional value, both of which you define. When you use tagging, you can also use tag-based access control in IAM policies to control access to this resource.

analysis_parameters: Option<Vec<AnalysisParameter>>

The parameters of the analysis template.

schema: Option<AnalysisSchema>

A relation within an analysis.

error_message_configuration: Option<ErrorMessageConfiguration>

The configuration that specifies the level of detail in error messages returned by analyses using this template. When set to DETAILED, error messages include more information to help troubleshoot issues with PySpark jobs. Detailed error messages may expose underlying data, including sensitive information. Recommended for faster troubleshooting in development and testing environments.

synthetic_data_parameters: Option<SyntheticDataParameters>

The parameters for generating synthetic data when running the analysis template.

Implementations

impl CreateAnalysisTemplateInput

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

The description of the analysis template.

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

The identifier for a membership resource.

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

The name of the analysis template.

pub fn format(&self) -> Option<&AnalysisFormat>

The format of the analysis template.

pub fn source(&self) -> Option<&AnalysisSource>

The information in the analysis template.

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

An optional label that you can assign to a resource when you create it. Each tag consists of a key and an optional value, both of which you define. When you use tagging, you can also use tag-based access control in IAM policies to control access to this resource.

pub fn analysis_parameters(&self) -> &[AnalysisParameter]

The parameters of the analysis template.

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

pub fn schema(&self) -> Option<&AnalysisSchema>

A relation within an analysis.

pub fn error_message_configuration(&self) -> Option<&ErrorMessageConfiguration>

The configuration that specifies the level of detail in error messages returned by analyses using this template. When set to DETAILED, error messages include more information to help troubleshoot issues with PySpark jobs. Detailed error messages may expose underlying data, including sensitive information. Recommended for faster troubleshooting in development and testing environments.

pub fn synthetic_data_parameters(&self) -> Option<&SyntheticDataParameters>

The parameters for generating synthetic data when running the analysis template.

impl CreateAnalysisTemplateInput

pub fn builder() -> CreateAnalysisTemplateInputBuilder

Creates a new builder-style object to manufacture CreateAnalysisTemplateInput.

Trait Implementations

impl Clone for CreateAnalysisTemplateInput

fn clone(&self) -> CreateAnalysisTemplateInput

Returns a duplicate of the value.

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

Performs copy-assignment from source.

impl Debug for CreateAnalysisTemplateInput

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

Formats the value using the given formatter.

impl PartialEq for CreateAnalysisTemplateInput

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

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

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 CreateAnalysisTemplateInput