Struct FullTextIndex

pub struct FullTextIndex { /* private fields */ }

Full-text search index for a collection and field

This struct maintains an inverted index mapping terms to the documents that contain them, with term frequency information for relevance scoring.

Implementations

impl FullTextIndex

pub fn new(_collection: &str, field: &str) -> Self

Create a new full-text index for a collection field

Arguments

• collection - Name of the collection to index
• field - Name of the field within documents to index

Examples

let description_index = FullTextIndex::new("products", "description");

pub fn with_options( collection: &str, field: &str, enable_stop_words: bool, ) -> Self

Create a search index with specific options

Arguments

• collection - Name of the collection to index
• field - Name of the field within documents to index
• enable_stop_words - Whether to filter out common words (false = no filtering)

Examples

// Create an index that doesn't filter out common words
let index = FullTextIndex::with_options("products", "description", false);
 
// Create an index that does filter out common words
let index = FullTextIndex::with_options("articles", "content", true);

pub fn set_stop_words_filter(&mut self, enable: bool)

Set whether to filter out common stop words

Arguments

• enable - true to filter out common words, false to include all words

Examples

// Enable filtering of common words like "the", "and", etc.
index.set_stop_words_filter(true);
 
// Disable filtering to allow searching for all words
index.set_stop_words_filter(false);

pub fn index_document(&self, doc: &Document) -> Result<()>

Add or update a document in the index

Arguments

• doc - The document to index

Returns

A Result indicating success or an error

Examples

index.index_document(&document)?;

pub fn search(&self, query: &str) -> Vec<(String, f32)>

Search the index for documents matching a query

Arguments

• query - The search query text

Returns

A vector of document IDs and relevance scores

Examples

let matches = index.search("wireless headphones");

pub fn fuzzy_search( &self, query: &str, max_distance: usize, ) -> Vec<(String, f32)>

Search with fuzzy matching for typo tolerance

Arguments

• query - The search query text
• max_distance - Maximum edit distance for fuzzy matching

Returns

A vector of document IDs and relevance scores

Examples

// Allow up to 2 character differences
let matches = index.fuzzy_search("wireles headpones", 2);

pub fn remove_document(&self, doc_id: &str)

Remove a document from the index

Arguments

• doc_id - ID of the document to remove

Examples

index.remove_document("doc-123");

pub fn add_stopwords(&mut self, words: &[&str])

Add custom stopwords to the filter list

Arguments

• words - List of words to add to the stopword list

Examples

// Add domain-specific stopwords
index.add_stopwords(&["widget", "product", "item"]);

pub fn clear_stopwords(&mut self)

Remove all stopwords from the filter

Examples

// Allow searching for any word, including common ones
index.clear_stopwords();

pub fn get_stopwords(&self) -> Vec<String>

Get the current list of stopwords

Returns

A vector of stopwords currently in use

Examples

let current_stopwords = index.get_stopwords();
println!("Currently filtering: {:?}", current_stopwords);

pub fn get_fuzzy_matches( &self, query: &str, max_distance: u32, ) -> Vec<(String, f32)>

pub fn highlight_matches(&self, text: &str, query: &str) -> String