aws_sdk_macie2::operation::create_classification_job::builders

Struct CreateClassificationJobFluentBuilder

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

Fluent builder constructing a request to CreateClassificationJob.

Creates and defines the settings for a classification job.

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impl CreateClassificationJobFluentBuilder

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pub fn as_input(&self) -> &CreateClassificationJobInputBuilder

Access the CreateClassificationJob as a reference.

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pub async fn send( self, ) -> Result<CreateClassificationJobOutput, SdkError<CreateClassificationJobError, 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<CreateClassificationJobOutput, CreateClassificationJobError, Self>

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

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

Appends an item to allowListIds.

To override the contents of this collection use set_allow_list_ids.

An array of unique identifiers, one for each allow list for the job to use when it analyzes data.

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

An array of unique identifiers, one for each allow list for the job to use when it analyzes data.

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pub fn get_allow_list_ids(&self) -> &Option<Vec<String>>

An array of unique identifiers, one for each allow list for the job to use when it analyzes data.

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

A unique, case-sensitive token that you provide to ensure the idempotency of the request.

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

A unique, case-sensitive token that you provide to ensure the idempotency of the request.

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

A unique, case-sensitive token that you provide to ensure the idempotency of the request.

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

Appends an item to customDataIdentifierIds.

To override the contents of this collection use set_custom_data_identifier_ids.

An array of unique identifiers, one for each custom data identifier for the job to use when it analyzes data. To use only managed data identifiers, don't specify a value for this property and specify a value other than NONE for the managedDataIdentifierSelector property.

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

An array of unique identifiers, one for each custom data identifier for the job to use when it analyzes data. To use only managed data identifiers, don't specify a value for this property and specify a value other than NONE for the managedDataIdentifierSelector property.

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pub fn get_custom_data_identifier_ids(&self) -> &Option<Vec<String>>

An array of unique identifiers, one for each custom data identifier for the job to use when it analyzes data. To use only managed data identifiers, don't specify a value for this property and specify a value other than NONE for the managedDataIdentifierSelector property.

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

A custom description of the job. The description can contain as many as 200 characters.

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

A custom description of the job. The description can contain as many as 200 characters.

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

A custom description of the job. The description can contain as many as 200 characters.

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pub fn initial_run(self, input: bool) -> Self

For a recurring job, specifies whether to analyze all existing, eligible objects immediately after the job is created (true). To analyze only those objects that are created or changed after you create the job and before the job's first scheduled run, set this value to false.

If you configure the job to run only once, don't specify a value for this property.

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pub fn set_initial_run(self, input: Option<bool>) -> Self

For a recurring job, specifies whether to analyze all existing, eligible objects immediately after the job is created (true). To analyze only those objects that are created or changed after you create the job and before the job's first scheduled run, set this value to false.

If you configure the job to run only once, don't specify a value for this property.

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pub fn get_initial_run(&self) -> &Option<bool>

For a recurring job, specifies whether to analyze all existing, eligible objects immediately after the job is created (true). To analyze only those objects that are created or changed after you create the job and before the job's first scheduled run, set this value to false.

If you configure the job to run only once, don't specify a value for this property.

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pub fn job_type(self, input: JobType) -> Self

The schedule for running the job. Valid values are:

  • ONE_TIME - Run the job only once. If you specify this value, don't specify a value for the scheduleFrequency property.

  • SCHEDULED - Run the job on a daily, weekly, or monthly basis. If you specify this value, use the scheduleFrequency property to specify the recurrence pattern for the job.

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pub fn set_job_type(self, input: Option<JobType>) -> Self

The schedule for running the job. Valid values are:

  • ONE_TIME - Run the job only once. If you specify this value, don't specify a value for the scheduleFrequency property.

  • SCHEDULED - Run the job on a daily, weekly, or monthly basis. If you specify this value, use the scheduleFrequency property to specify the recurrence pattern for the job.

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pub fn get_job_type(&self) -> &Option<JobType>

The schedule for running the job. Valid values are:

  • ONE_TIME - Run the job only once. If you specify this value, don't specify a value for the scheduleFrequency property.

  • SCHEDULED - Run the job on a daily, weekly, or monthly basis. If you specify this value, use the scheduleFrequency property to specify the recurrence pattern for the job.

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

Appends an item to managedDataIdentifierIds.

To override the contents of this collection use set_managed_data_identifier_ids.

An array of unique identifiers, one for each managed data identifier for the job to include (use) or exclude (not use) when it analyzes data. Inclusion or exclusion depends on the managed data identifier selection type that you specify for the job (managedDataIdentifierSelector).

To retrieve a list of valid values for this property, use the ListManagedDataIdentifiers operation.

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

An array of unique identifiers, one for each managed data identifier for the job to include (use) or exclude (not use) when it analyzes data. Inclusion or exclusion depends on the managed data identifier selection type that you specify for the job (managedDataIdentifierSelector).

To retrieve a list of valid values for this property, use the ListManagedDataIdentifiers operation.

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pub fn get_managed_data_identifier_ids(&self) -> &Option<Vec<String>>

An array of unique identifiers, one for each managed data identifier for the job to include (use) or exclude (not use) when it analyzes data. Inclusion or exclusion depends on the managed data identifier selection type that you specify for the job (managedDataIdentifierSelector).

To retrieve a list of valid values for this property, use the ListManagedDataIdentifiers operation.

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pub fn managed_data_identifier_selector( self, input: ManagedDataIdentifierSelector, ) -> Self

The selection type to apply when determining which managed data identifiers the job uses to analyze data. Valid values are:

  • ALL - Use all managed data identifiers. If you specify this value, don't specify any values for the managedDataIdentifierIds property.

  • EXCLUDE - Use all managed data identifiers except the ones specified by the managedDataIdentifierIds property.

  • INCLUDE - Use only the managed data identifiers specified by the managedDataIdentifierIds property.

  • NONE - Don't use any managed data identifiers. If you specify this value, specify at least one value for the customDataIdentifierIds property and don't specify any values for the managedDataIdentifierIds property.

  • RECOMMENDED (default) - Use the recommended set of managed data identifiers. If you specify this value, don't specify any values for the managedDataIdentifierIds property.

If you don't specify a value for this property, the job uses the recommended set of managed data identifiers.

If the job is a recurring job and you specify ALL or EXCLUDE, each job run automatically uses new managed data identifiers that are released. If you don't specify a value for this property or you specify RECOMMENDED for a recurring job, each job run automatically uses all the managed data identifiers that are in the recommended set when the run starts.

To learn about individual managed data identifiers or determine which ones are in the recommended set, see Using managed data identifiers or Recommended managed data identifiers in the Amazon Macie User Guide.

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pub fn set_managed_data_identifier_selector( self, input: Option<ManagedDataIdentifierSelector>, ) -> Self

The selection type to apply when determining which managed data identifiers the job uses to analyze data. Valid values are:

  • ALL - Use all managed data identifiers. If you specify this value, don't specify any values for the managedDataIdentifierIds property.

  • EXCLUDE - Use all managed data identifiers except the ones specified by the managedDataIdentifierIds property.

  • INCLUDE - Use only the managed data identifiers specified by the managedDataIdentifierIds property.

  • NONE - Don't use any managed data identifiers. If you specify this value, specify at least one value for the customDataIdentifierIds property and don't specify any values for the managedDataIdentifierIds property.

  • RECOMMENDED (default) - Use the recommended set of managed data identifiers. If you specify this value, don't specify any values for the managedDataIdentifierIds property.

If you don't specify a value for this property, the job uses the recommended set of managed data identifiers.

If the job is a recurring job and you specify ALL or EXCLUDE, each job run automatically uses new managed data identifiers that are released. If you don't specify a value for this property or you specify RECOMMENDED for a recurring job, each job run automatically uses all the managed data identifiers that are in the recommended set when the run starts.

To learn about individual managed data identifiers or determine which ones are in the recommended set, see Using managed data identifiers or Recommended managed data identifiers in the Amazon Macie User Guide.

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pub fn get_managed_data_identifier_selector( &self, ) -> &Option<ManagedDataIdentifierSelector>

The selection type to apply when determining which managed data identifiers the job uses to analyze data. Valid values are:

  • ALL - Use all managed data identifiers. If you specify this value, don't specify any values for the managedDataIdentifierIds property.

  • EXCLUDE - Use all managed data identifiers except the ones specified by the managedDataIdentifierIds property.

  • INCLUDE - Use only the managed data identifiers specified by the managedDataIdentifierIds property.

  • NONE - Don't use any managed data identifiers. If you specify this value, specify at least one value for the customDataIdentifierIds property and don't specify any values for the managedDataIdentifierIds property.

  • RECOMMENDED (default) - Use the recommended set of managed data identifiers. If you specify this value, don't specify any values for the managedDataIdentifierIds property.

If you don't specify a value for this property, the job uses the recommended set of managed data identifiers.

If the job is a recurring job and you specify ALL or EXCLUDE, each job run automatically uses new managed data identifiers that are released. If you don't specify a value for this property or you specify RECOMMENDED for a recurring job, each job run automatically uses all the managed data identifiers that are in the recommended set when the run starts.

To learn about individual managed data identifiers or determine which ones are in the recommended set, see Using managed data identifiers or Recommended managed data identifiers in the Amazon Macie User Guide.

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

A custom name for the job. The name can contain as many as 500 characters.

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

A custom name for the job. The name can contain as many as 500 characters.

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

A custom name for the job. The name can contain as many as 500 characters.

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pub fn s3_job_definition(self, input: S3JobDefinition) -> Self

The S3 buckets that contain the objects to analyze, and the scope of that analysis.

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pub fn set_s3_job_definition(self, input: Option<S3JobDefinition>) -> Self

The S3 buckets that contain the objects to analyze, and the scope of that analysis.

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pub fn get_s3_job_definition(&self) -> &Option<S3JobDefinition>

The S3 buckets that contain the objects to analyze, and the scope of that analysis.

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pub fn sampling_percentage(self, input: i32) -> Self

The sampling depth, as a percentage, for the job to apply when processing objects. This value determines the percentage of eligible objects that the job analyzes. If this value is less than 100, Amazon Macie selects the objects to analyze at random, up to the specified percentage, and analyzes all the data in those objects.

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pub fn set_sampling_percentage(self, input: Option<i32>) -> Self

The sampling depth, as a percentage, for the job to apply when processing objects. This value determines the percentage of eligible objects that the job analyzes. If this value is less than 100, Amazon Macie selects the objects to analyze at random, up to the specified percentage, and analyzes all the data in those objects.

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

The sampling depth, as a percentage, for the job to apply when processing objects. This value determines the percentage of eligible objects that the job analyzes. If this value is less than 100, Amazon Macie selects the objects to analyze at random, up to the specified percentage, and analyzes all the data in those objects.

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pub fn schedule_frequency(self, input: JobScheduleFrequency) -> Self

The recurrence pattern for running the job. To run the job only once, don't specify a value for this property and set the value for the jobType property to ONE_TIME.

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pub fn set_schedule_frequency(self, input: Option<JobScheduleFrequency>) -> Self

The recurrence pattern for running the job. To run the job only once, don't specify a value for this property and set the value for the jobType property to ONE_TIME.

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pub fn get_schedule_frequency(&self) -> &Option<JobScheduleFrequency>

The recurrence pattern for running the job. To run the job only once, don't specify a value for this property and set the value for the jobType property to ONE_TIME.

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pub fn tags(self, k: impl Into<String>, v: impl Into<String>) -> Self

Adds a key-value pair to tags.

To override the contents of this collection use set_tags.

A map of key-value pairs that specifies the tags to associate with the job.

A job can have a maximum of 50 tags. Each tag consists of a tag key and an associated tag value. The maximum length of a tag key is 128 characters. The maximum length of a tag value is 256 characters.

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

A map of key-value pairs that specifies the tags to associate with the job.

A job can have a maximum of 50 tags. Each tag consists of a tag key and an associated tag value. The maximum length of a tag key is 128 characters. The maximum length of a tag value is 256 characters.

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pub fn get_tags(&self) -> &Option<HashMap<String, String>>

A map of key-value pairs that specifies the tags to associate with the job.

A job can have a maximum of 50 tags. Each tag consists of a tag key and an associated tag value. The maximum length of a tag key is 128 characters. The maximum length of a tag value is 256 characters.

Trait Implementations§

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impl Clone for CreateClassificationJobFluentBuilder

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fn clone(&self) -> CreateClassificationJobFluentBuilder

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 CreateClassificationJobFluentBuilder

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

Formats the value using the given formatter. Read more

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👎Deprecated since 1.0.1: renamed to resetting() due to conflicts with Vec::clear(). The clear() method will be removed in a future release.

Returns self with the quirk() set to [Quirk :: Clear].

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println!("{}", value.clear());
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fn resetting(&self) -> Painted<&T>

Returns self with the quirk() set to [Quirk :: Resetting].

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println!("{}", value.resetting());
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fn bright(&self) -> Painted<&T>

Returns self with the quirk() set to [Quirk :: Bright].

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println!("{}", value.bright());
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fn on_bright(&self) -> Painted<&T>

Returns self with the quirk() set to [Quirk :: OnBright].

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println!("{}", value.on_bright());
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fn whenever(&self, value: Condition) -> Painted<&T>

Conditionally enable styling based on whether the Condition value applies. Replaces any previous condition.

See the crate level docs for more details.

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Enable styling painted only when both stdout and stderr are TTYs:

use yansi::{Paint, Condition};

painted.red().on_yellow().whenever(Condition::STDOUTERR_ARE_TTY);
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fn new(self) -> Painted<Self>
where Self: Sized,

Create a new Painted with a default Style. Read more
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fn paint<S>(&self, style: S) -> Painted<&Self>
where S: Into<Style>,

Apply a style wholesale to self. Any previous style is replaced. Read more
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impl<T> Same for T

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type Output = T

Should always be Self
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impl<T> ToOwned for T
where T: Clone,

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type Owned = T

The resulting type after obtaining ownership.
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fn to_owned(&self) -> T

Creates owned data from borrowed data, usually by cloning. Read more
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fn clone_into(&self, target: &mut T)

Uses borrowed data to replace owned data, usually by cloning. Read more
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impl<T, U> TryFrom<U> for T
where U: Into<T>,

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type Error = Infallible

The type returned in the event of a conversion error.
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fn try_from(value: U) -> Result<T, <T as TryFrom<U>>::Error>

Performs the conversion.
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impl<T, U> TryInto<U> for T
where U: TryFrom<T>,

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type Error = <U as TryFrom<T>>::Error

The type returned in the event of a conversion error.
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fn try_into(self) -> Result<U, <U as TryFrom<T>>::Error>

Performs the conversion.
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impl<T> WithSubscriber for T

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fn with_subscriber<S>(self, subscriber: S) -> WithDispatch<Self>
where S: Into<Dispatch>,

Attaches the provided Subscriber to this type, returning a WithDispatch wrapper. Read more
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fn with_current_subscriber(self) -> WithDispatch<Self>

Attaches the current default Subscriber to this type, returning a WithDispatch wrapper. Read more
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impl<T> ErasedDestructor for T
where T: 'static,