Struct aws_sdk_comprehend::operation::start_targeted_sentiment_detection_job::StartTargetedSentimentDetectionJobInput

#[non_exhaustive]
pub struct StartTargetedSentimentDetectionJobInput {
    pub input_data_config: Option<InputDataConfig>,
    pub output_data_config: Option<OutputDataConfig>,
    pub data_access_role_arn: Option<String>,
    pub job_name: Option<String>,
    pub language_code: Option<LanguageCode>,
    pub client_request_token: Option<String>,
    pub volume_kms_key_id: Option<String>,
    pub vpc_config: Option<VpcConfig>,
    pub tags: Option<Vec<Tag>>,
}

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.

input_data_config: Option<InputDataConfig>

The input properties for an inference job. The document reader config field applies only to non-text inputs for custom analysis.

output_data_config: Option<OutputDataConfig>

Specifies where to send the output files.

data_access_role_arn: Option<String>

The Amazon Resource Name (ARN) of the IAM role that grants Amazon Comprehend read access to your input data. For more information, see Role-based permissions.

job_name: Option<String>

The identifier of the job.

language_code: Option<LanguageCode>

The language of the input documents. Currently, English is the only supported language.

client_request_token: Option<String>

A unique identifier for the request. If you don't set the client request token, Amazon Comprehend generates one.

volume_kms_key_id: Option<String>

ID for the KMS key that Amazon Comprehend uses to encrypt data on the storage volume attached to the ML compute instance(s) that process the analysis job. The VolumeKmsKeyId can be either of the following formats:

• KMS Key ID: "1234abcd-12ab-34cd-56ef-1234567890ab"

• Amazon Resource Name (ARN) of a KMS Key: "arn:aws:kms:us-west-2:111122223333:key/1234abcd-12ab-34cd-56ef-1234567890ab"

vpc_config: Option<VpcConfig>

Configuration parameters for an optional private Virtual Private Cloud (VPC) containing the resources you are using for the job. For more information, see Amazon VPC.

tags: Option<Vec<Tag>>

Tags to associate with the targeted sentiment detection job. A tag is a key-value pair that adds metadata to a resource used by Amazon Comprehend. For example, a tag with "Sales" as the key might be added to a resource to indicate its use by the sales department.

Implementations

impl StartTargetedSentimentDetectionJobInput

pub fn input_data_config(&self) -> Option<&InputDataConfig>

The input properties for an inference job. The document reader config field applies only to non-text inputs for custom analysis.

pub fn output_data_config(&self) -> Option<&OutputDataConfig>

Specifies where to send the output files.

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

The Amazon Resource Name (ARN) of the IAM role that grants Amazon Comprehend read access to your input data. For more information, see Role-based permissions.

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

The identifier of the job.

pub fn language_code(&self) -> Option<&LanguageCode>

The language of the input documents. Currently, English is the only supported language.

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

A unique identifier for the request. If you don't set the client request token, Amazon Comprehend generates one.

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

ID for the KMS key that Amazon Comprehend uses to encrypt data on the storage volume attached to the ML compute instance(s) that process the analysis job. The VolumeKmsKeyId can be either of the following formats:

• KMS Key ID: "1234abcd-12ab-34cd-56ef-1234567890ab"

• Amazon Resource Name (ARN) of a KMS Key: "arn:aws:kms:us-west-2:111122223333:key/1234abcd-12ab-34cd-56ef-1234567890ab"

pub fn vpc_config(&self) -> Option<&VpcConfig>

Configuration parameters for an optional private Virtual Private Cloud (VPC) containing the resources you are using for the job. For more information, see Amazon VPC.

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

Tags to associate with the targeted sentiment detection job. A tag is a key-value pair that adds metadata to a resource used by Amazon Comprehend. For example, a tag with "Sales" as the key might be added to a resource to indicate its use by the sales department.

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().

impl StartTargetedSentimentDetectionJobInput

pub fn builder() -> StartTargetedSentimentDetectionJobInputBuilder

Creates a new builder-style object to manufacture StartTargetedSentimentDetectionJobInput.

Trait Implementations

impl Clone for StartTargetedSentimentDetectionJobInput

fn clone(&self) -> StartTargetedSentimentDetectionJobInput

Returns a copy of the value.

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

Performs copy-assignment from source.

impl Debug for StartTargetedSentimentDetectionJobInput

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

Formats the value using the given formatter.

impl PartialEq for StartTargetedSentimentDetectionJobInput

fn eq(&self, other: &StartTargetedSentimentDetectionJobInput) -> 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 StartTargetedSentimentDetectionJobInput