Struct aws_sdk_appsync::operation::update_resolver::UpdateResolverInput

#[non_exhaustive]
pub struct UpdateResolverInput {

    pub api_id: Option<String>,
    pub type_name: Option<String>,
    pub field_name: Option<String>,
    pub data_source_name: Option<String>,
    pub request_mapping_template: Option<String>,
    pub response_mapping_template: Option<String>,
    pub kind: Option<ResolverKind>,
    pub pipeline_config: Option<PipelineConfig>,
    pub sync_config: Option<SyncConfig>,
    pub caching_config: Option<CachingConfig>,
    pub max_batch_size: Option<i32>,
    pub runtime: Option<AppSyncRuntime>,
    pub code: Option<String>,
}

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.

api_id: Option<String>

The API ID.

type_name: Option<String>

The new type name.

field_name: Option<String>

The new field name.

data_source_name: Option<String>

The new data source name.

request_mapping_template: Option<String>

The new request mapping template.

A resolver uses a request mapping template to convert a GraphQL expression into a format that a data source can understand. Mapping templates are written in Apache Velocity Template Language (VTL).

VTL request mapping templates are optional when using an Lambda data source. For all other data sources, VTL request and response mapping templates are required.

response_mapping_template: Option<String>

The new response mapping template.

kind: Option<ResolverKind>

The resolver type.

• UNIT: A UNIT resolver type. A UNIT resolver is the default resolver type. You can use a UNIT resolver to run a GraphQL query against a single data source.

• PIPELINE: A PIPELINE resolver type. You can use a PIPELINE resolver to invoke a series of Function objects in a serial manner. You can use a pipeline resolver to run a GraphQL query against multiple data sources.

pipeline_config: Option<PipelineConfig>

The PipelineConfig.

sync_config: Option<SyncConfig>

The SyncConfig for a resolver attached to a versioned data source.

caching_config: Option<CachingConfig>

The caching configuration for the resolver.

max_batch_size: Option<i32>

The maximum batching size for a resolver.

runtime: Option<AppSyncRuntime>

Describes a runtime used by an Amazon Web Services AppSync pipeline resolver or Amazon Web Services AppSync function. Specifies the name and version of the runtime to use. Note that if a runtime is specified, code must also be specified.

code: Option<String>

The resolver code that contains the request and response functions. When code is used, the runtime is required. The runtime value must be APPSYNC_JS.

Implementations

impl UpdateResolverInput

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

The API ID.

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

The new type name.

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

The new field name.

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

The new data source name.

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

The new request mapping template.

A resolver uses a request mapping template to convert a GraphQL expression into a format that a data source can understand. Mapping templates are written in Apache Velocity Template Language (VTL).

VTL request mapping templates are optional when using an Lambda data source. For all other data sources, VTL request and response mapping templates are required.

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

The new response mapping template.

pub fn kind(&self) -> Option<&ResolverKind>

The resolver type.

• UNIT: A UNIT resolver type. A UNIT resolver is the default resolver type. You can use a UNIT resolver to run a GraphQL query against a single data source.

• PIPELINE: A PIPELINE resolver type. You can use a PIPELINE resolver to invoke a series of Function objects in a serial manner. You can use a pipeline resolver to run a GraphQL query against multiple data sources.

pub fn pipeline_config(&self) -> Option<&PipelineConfig>

The PipelineConfig.

pub fn sync_config(&self) -> Option<&SyncConfig>

The SyncConfig for a resolver attached to a versioned data source.

pub fn caching_config(&self) -> Option<&CachingConfig>

The caching configuration for the resolver.

pub fn max_batch_size(&self) -> Option<i32>

The maximum batching size for a resolver.

pub fn runtime(&self) -> Option<&AppSyncRuntime>

Describes a runtime used by an Amazon Web Services AppSync pipeline resolver or Amazon Web Services AppSync function. Specifies the name and version of the runtime to use. Note that if a runtime is specified, code must also be specified.

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

The resolver code that contains the request and response functions. When code is used, the runtime is required. The runtime value must be APPSYNC_JS.

impl UpdateResolverInput

pub fn builder() -> UpdateResolverInputBuilder

Creates a new builder-style object to manufacture UpdateResolverInput.

Trait Implementations

impl Clone for UpdateResolverInput

fn clone(&self) -> UpdateResolverInput

Returns a copy of the value.

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

Performs copy-assignment from source.

impl Debug for UpdateResolverInput

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

Formats the value using the given formatter.

impl PartialEq<UpdateResolverInput> for UpdateResolverInput

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

This method tests for self and other values to be equal, and is used by ==.

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

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

impl StructuralPartialEq for UpdateResolverInput