aws_sdk_comprehend::operation::start_entities_detection_job::builders

Struct StartEntitiesDetectionJobFluentBuilder

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pub struct StartEntitiesDetectionJobFluentBuilder { /* private fields */ }
Expand description

Fluent builder constructing a request to StartEntitiesDetectionJob.

Starts an asynchronous entity detection job for a collection of documents. Use the operation to track the status of a job.

This API can be used for either standard entity detection or custom entity recognition. In order to be used for custom entity recognition, the optional EntityRecognizerArn must be used in order to provide access to the recognizer being used to detect the custom entity.

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impl StartEntitiesDetectionJobFluentBuilder

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pub fn as_input(&self) -> &StartEntitiesDetectionJobInputBuilder

Access the StartEntitiesDetectionJob as a reference.

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pub async fn send( self, ) -> Result<StartEntitiesDetectionJobOutput, SdkError<StartEntitiesDetectionJobError, HttpResponse>>

Sends the request and returns the response.

If an error occurs, an SdkError will be returned with additional details that can be matched against.

By default, any retryable failures will be retried twice. Retry behavior is configurable with the RetryConfig, which can be set when configuring the client.

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pub fn customize( self, ) -> CustomizableOperation<StartEntitiesDetectionJobOutput, StartEntitiesDetectionJobError, Self>

Consumes this builder, creating a customizable operation that can be modified before being sent.

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pub fn input_data_config(self, input: InputDataConfig) -> Self

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

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pub fn set_input_data_config(self, input: Option<InputDataConfig>) -> Self

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

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

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

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pub fn output_data_config(self, input: OutputDataConfig) -> Self

Specifies where to send the output files.

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pub fn set_output_data_config(self, input: Option<OutputDataConfig>) -> Self

Specifies where to send the output files.

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

Specifies where to send the output files.

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pub fn data_access_role_arn(self, input: impl Into<String>) -> Self

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.

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pub fn set_data_access_role_arn(self, input: Option<String>) -> Self

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.

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pub fn get_data_access_role_arn(&self) -> &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.

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pub fn job_name(self, input: impl Into<String>) -> Self

The identifier of the job.

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pub fn set_job_name(self, input: Option<String>) -> Self

The identifier of the job.

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pub fn get_job_name(&self) -> &Option<String>

The identifier of the job.

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pub fn entity_recognizer_arn(self, input: impl Into<String>) -> Self

The Amazon Resource Name (ARN) that identifies the specific entity recognizer to be used by the StartEntitiesDetectionJob. This ARN is optional and is only used for a custom entity recognition job.

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pub fn set_entity_recognizer_arn(self, input: Option<String>) -> Self

The Amazon Resource Name (ARN) that identifies the specific entity recognizer to be used by the StartEntitiesDetectionJob. This ARN is optional and is only used for a custom entity recognition job.

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pub fn get_entity_recognizer_arn(&self) -> &Option<String>

The Amazon Resource Name (ARN) that identifies the specific entity recognizer to be used by the StartEntitiesDetectionJob. This ARN is optional and is only used for a custom entity recognition job.

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pub fn language_code(self, input: LanguageCode) -> Self

The language of the input documents. All documents must be in the same language. You can specify any of the languages supported by Amazon Comprehend. If custom entities recognition is used, this parameter is ignored and the language used for training the model is used instead.

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pub fn set_language_code(self, input: Option<LanguageCode>) -> Self

The language of the input documents. All documents must be in the same language. You can specify any of the languages supported by Amazon Comprehend. If custom entities recognition is used, this parameter is ignored and the language used for training the model is used instead.

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

The language of the input documents. All documents must be in the same language. You can specify any of the languages supported by Amazon Comprehend. If custom entities recognition is used, this parameter is ignored and the language used for training the model is used instead.

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pub fn client_request_token(self, input: impl Into<String>) -> Self

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

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pub fn set_client_request_token(self, input: Option<String>) -> Self

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

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pub fn get_client_request_token(&self) -> &Option<String>

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

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pub fn volume_kms_key_id(self, input: impl Into<String>) -> Self

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"

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pub fn set_volume_kms_key_id(self, input: Option<String>) -> Self

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"

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pub fn get_volume_kms_key_id(&self) -> &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"

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pub fn vpc_config(self, input: VpcConfig) -> Self

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

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pub fn set_vpc_config(self, input: Option<VpcConfig>) -> Self

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

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

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

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pub fn tags(self, input: Tag) -> Self

Appends an item to Tags.

To override the contents of this collection use set_tags.

Tags to associate with the entities 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.

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pub fn set_tags(self, input: Option<Vec<Tag>>) -> Self

Tags to associate with the entities 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.

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pub fn get_tags(&self) -> &Option<Vec<Tag>>

Tags to associate with the entities 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.

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pub fn flywheel_arn(self, input: impl Into<String>) -> Self

The Amazon Resource Number (ARN) of the flywheel associated with the model to use.

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pub fn set_flywheel_arn(self, input: Option<String>) -> Self

The Amazon Resource Number (ARN) of the flywheel associated with the model to use.

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pub fn get_flywheel_arn(&self) -> &Option<String>

The Amazon Resource Number (ARN) of the flywheel associated with the model to use.

Trait Implementations§

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impl Clone for StartEntitiesDetectionJobFluentBuilder

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fn clone(&self) -> StartEntitiesDetectionJobFluentBuilder

Returns a duplicate of the value. Read more
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const fn clone_from(&mut self, source: &Self)

Performs copy-assignment from source. Read more
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impl Debug for StartEntitiesDetectionJobFluentBuilder

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

Formats the value using the given formatter. Read more

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