Struct aws_sdk_comprehend::operation::start_topics_detection_job::StartTopicsDetectionJobInput

#[non_exhaustive]
pub struct StartTopicsDetectionJobInput {
    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 number_of_topics: Option<i32>,
    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>

Specifies the format and location of the input data for the job.

output_data_config: Option<OutputDataConfig>

Specifies where to send the output files. The output is a compressed archive with two files, topic-terms.csv that lists the terms associated with each topic, and doc-topics.csv that lists the documents associated with each topic

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.

number_of_topics: Option<i32>

The number of topics to detect.

client_request_token: Option<String>

A unique identifier for the request. If you do not set the client request token, Amazon Comprehend generates one.

volume_kms_key_id: Option<String>

ID for the Amazon Web Services Key Management Service (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 your topic detection job. For more information, see Amazon VPC.

tags: Option<Vec<Tag>>

Tags to associate with the topics 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 StartTopicsDetectionJobInput

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

Specifies the format and location of the input data for the job.

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

Specifies where to send the output files. The output is a compressed archive with two files, topic-terms.csv that lists the terms associated with each topic, and doc-topics.csv that lists the documents associated with each topic

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 number_of_topics(&self) -> Option<i32>

The number of topics to detect.

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

A unique identifier for the request. If you do not set the client request token, Amazon Comprehend generates one.

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

ID for the Amazon Web Services Key Management Service (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 your topic detection job. For more information, see Amazon VPC.

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

Tags to associate with the topics 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 StartTopicsDetectionJobInput

pub fn builder() -> StartTopicsDetectionJobInputBuilder

Creates a new builder-style object to manufacture StartTopicsDetectionJobInput.

Trait Implementations

impl Clone for StartTopicsDetectionJobInput

fn clone(&self) -> StartTopicsDetectionJobInput

Returns a copy of the value.

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

Performs copy-assignment from source.

impl Debug for StartTopicsDetectionJobInput

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

Formats the value using the given formatter.

impl PartialEq for StartTopicsDetectionJobInput

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