UpdateQuerySuggestionsConfigFluentBuilder

Struct UpdateQuerySuggestionsConfigFluentBuilder 

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

Fluent builder constructing a request to UpdateQuerySuggestionsConfig.

Updates the settings of query suggestions for an index.

Amazon Kendra supports partial updates, so you only need to provide the fields you want to update.

If an update is currently processing, you need to wait for the update to finish before making another update.

Updates to query suggestions settings might not take effect right away. The time for your updated settings to take effect depends on the updates made and the number of search queries in your index.

You can still enable/disable query suggestions at any time.

UpdateQuerySuggestionsConfig is currently not supported in the Amazon Web Services GovCloud (US-West) region.

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impl UpdateQuerySuggestionsConfigFluentBuilder

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pub fn as_input(&self) -> &UpdateQuerySuggestionsConfigInputBuilder

Access the UpdateQuerySuggestionsConfig as a reference.

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pub async fn send( self, ) -> Result<UpdateQuerySuggestionsConfigOutput, SdkError<UpdateQuerySuggestionsConfigError, 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<UpdateQuerySuggestionsConfigOutput, UpdateQuerySuggestionsConfigError, Self>

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

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

The identifier of the index with query suggestions you want to update.

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

The identifier of the index with query suggestions you want to update.

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

The identifier of the index with query suggestions you want to update.

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pub fn mode(self, input: Mode) -> Self

Set the mode to ENABLED or LEARN_ONLY.

By default, Amazon Kendra enables query suggestions. LEARN_ONLY mode allows you to turn off query suggestions. You can to update this at any time.

In LEARN_ONLY mode, Amazon Kendra continues to learn from new queries to keep suggestions up to date for when you are ready to switch to ENABLED mode again.

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pub fn set_mode(self, input: Option<Mode>) -> Self

Set the mode to ENABLED or LEARN_ONLY.

By default, Amazon Kendra enables query suggestions. LEARN_ONLY mode allows you to turn off query suggestions. You can to update this at any time.

In LEARN_ONLY mode, Amazon Kendra continues to learn from new queries to keep suggestions up to date for when you are ready to switch to ENABLED mode again.

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pub fn get_mode(&self) -> &Option<Mode>

Set the mode to ENABLED or LEARN_ONLY.

By default, Amazon Kendra enables query suggestions. LEARN_ONLY mode allows you to turn off query suggestions. You can to update this at any time.

In LEARN_ONLY mode, Amazon Kendra continues to learn from new queries to keep suggestions up to date for when you are ready to switch to ENABLED mode again.

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

How recent your queries are in your query log time window.

The time window is the number of days from current day to past days.

By default, Amazon Kendra sets this to 180.

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

How recent your queries are in your query log time window.

The time window is the number of days from current day to past days.

By default, Amazon Kendra sets this to 180.

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

How recent your queries are in your query log time window.

The time window is the number of days from current day to past days.

By default, Amazon Kendra sets this to 180.

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

TRUE to include queries without user information (i.e. all queries, irrespective of the user), otherwise FALSE to only include queries with user information.

If you pass user information to Amazon Kendra along with the queries, you can set this flag to FALSE and instruct Amazon Kendra to only consider queries with user information.

If you set to FALSE, Amazon Kendra only considers queries searched at least MinimumQueryCount times across MinimumNumberOfQueryingUsers unique users for suggestions.

If you set to TRUE, Amazon Kendra ignores all user information and learns from all queries.

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

TRUE to include queries without user information (i.e. all queries, irrespective of the user), otherwise FALSE to only include queries with user information.

If you pass user information to Amazon Kendra along with the queries, you can set this flag to FALSE and instruct Amazon Kendra to only consider queries with user information.

If you set to FALSE, Amazon Kendra only considers queries searched at least MinimumQueryCount times across MinimumNumberOfQueryingUsers unique users for suggestions.

If you set to TRUE, Amazon Kendra ignores all user information and learns from all queries.

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

TRUE to include queries without user information (i.e. all queries, irrespective of the user), otherwise FALSE to only include queries with user information.

If you pass user information to Amazon Kendra along with the queries, you can set this flag to FALSE and instruct Amazon Kendra to only consider queries with user information.

If you set to FALSE, Amazon Kendra only considers queries searched at least MinimumQueryCount times across MinimumNumberOfQueryingUsers unique users for suggestions.

If you set to TRUE, Amazon Kendra ignores all user information and learns from all queries.

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

The minimum number of unique users who must search a query in order for the query to be eligible to suggest to your users.

Increasing this number might decrease the number of suggestions. However, this ensures a query is searched by many users and is truly popular to suggest to users.

How you tune this setting depends on your specific needs.

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

The minimum number of unique users who must search a query in order for the query to be eligible to suggest to your users.

Increasing this number might decrease the number of suggestions. However, this ensures a query is searched by many users and is truly popular to suggest to users.

How you tune this setting depends on your specific needs.

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

The minimum number of unique users who must search a query in order for the query to be eligible to suggest to your users.

Increasing this number might decrease the number of suggestions. However, this ensures a query is searched by many users and is truly popular to suggest to users.

How you tune this setting depends on your specific needs.

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

The the minimum number of times a query must be searched in order to be eligible to suggest to your users.

Decreasing this number increases the number of suggestions. However, this affects the quality of suggestions as it sets a low bar for a query to be considered popular to suggest to users.

How you tune this setting depends on your specific needs.

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

The the minimum number of times a query must be searched in order to be eligible to suggest to your users.

Decreasing this number increases the number of suggestions. However, this affects the quality of suggestions as it sets a low bar for a query to be considered popular to suggest to users.

How you tune this setting depends on your specific needs.

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

The the minimum number of times a query must be searched in order to be eligible to suggest to your users.

Decreasing this number increases the number of suggestions. However, this affects the quality of suggestions as it sets a low bar for a query to be considered popular to suggest to users.

How you tune this setting depends on your specific needs.

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pub fn attribute_suggestions_config( self, input: AttributeSuggestionsUpdateConfig, ) -> Self

Configuration information for the document fields/attributes that you want to base query suggestions on.

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pub fn set_attribute_suggestions_config( self, input: Option<AttributeSuggestionsUpdateConfig>, ) -> Self

Configuration information for the document fields/attributes that you want to base query suggestions on.

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pub fn get_attribute_suggestions_config( &self, ) -> &Option<AttributeSuggestionsUpdateConfig>

Configuration information for the document fields/attributes that you want to base query suggestions on.

Trait Implementations§

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impl Clone for UpdateQuerySuggestionsConfigFluentBuilder

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fn clone(&self) -> UpdateQuerySuggestionsConfigFluentBuilder

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

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

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

Formats the value using the given formatter. Read more

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