UpdateResolverRequest ¶

class UpdateResolverRequest(TypedDict, closed=True):
    api_id: "capo_appsync.types.string.String"
    """<p>The API ID.</p>"""
    type_name: "capo_appsync.types.resource_name.ResourceName"
    """<p>The new type name.</p>"""
    field_name: "capo_appsync.types.resource_name.ResourceName"
    """<p>The new field name.</p>"""
    data_source_name: NotRequired["capo_appsync.types.resource_name.ResourceName"]
    """<p>The new data source name.</p>"""
    request_mapping_template: NotRequired[
        "capo_appsync.types.mapping_template.MappingTemplate"
    ]
    """<p>The new request mapping template.</p> <p>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).</p> <p>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.</p>"""
    response_mapping_template: NotRequired[
        "capo_appsync.types.mapping_template.MappingTemplate"
    ]
    """<p>The new response mapping template.</p>"""
    kind: NotRequired["capo_appsync.types.resolver_kind.ResolverKind"]
    """<p>The resolver type.</p> <ul> <li> <p> <b>UNIT</b>: 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.</p> </li> <li> <p> <b>PIPELINE</b>: A PIPELINE resolver type. You can use a PIPELINE resolver to invoke a series of <code>Function</code> objects in a serial manner. You can use a pipeline resolver to run a GraphQL query against multiple data sources.</p> </li> </ul>"""
    pipeline_config: NotRequired["capo_appsync.types.pipeline_config.PipelineConfig"]
    """<p>The <code>PipelineConfig</code>.</p>"""
    sync_config: NotRequired["capo_appsync.types.sync_config.SyncConfig"]
    """<p>The <code>SyncConfig</code> for a resolver attached to a versioned data source.</p>"""
    caching_config: NotRequired["capo_appsync.types.caching_config.CachingConfig"]
    """<p>The caching configuration for the resolver.</p>"""
    max_batch_size: "capo_appsync.types.max_batch_size.MaxBatchSize"
    """<p>The maximum batching size for a resolver.</p>"""
    runtime: NotRequired["capo_appsync.types.app_sync_runtime.AppSyncRuntime"]
    code: NotRequired["capo_appsync.types.code.Code"]
    """<p>The <code>resolver</code> code that contains the request and response functions. When code is used, the <code>runtime</code> is required. The <code>runtime</code> value must be <code>APPSYNC_JS</code>.</p>"""
    metrics_config: NotRequired[
        "capo_appsync.types.resolver_level_metrics_config.ResolverLevelMetricsConfig"
    ]
    """<p>Enables or disables enhanced resolver metrics for specified resolvers. Note that <code>metricsConfig</code> won't be used unless the <code>resolverLevelMetricsBehavior</code> value is set to <code>PER_RESOLVER_METRICS</code>. If the <code>resolverLevelMetricsBehavior</code> is set to <code>FULL_REQUEST_RESOLVER_METRICS</code> instead, <code>metricsConfig</code> will be ignored. However, you can still set its value.</p> <p> <code>metricsConfig</code> can be <code>ENABLED</code> or <code>DISABLED</code>.</p>"""