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https://github.com/meilisearch/meilisearch.git
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Make the MatchingWords return the number of matching bytes
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204
milli/src/search/matching_words.rs
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204
milli/src/search/matching_words.rs
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@ -0,0 +1,204 @@
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use std::collections::HashSet;
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use std::cmp::{min, Reverse};
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use std::collections::BTreeMap;
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use std::ops::{Index, IndexMut};
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use levenshtein_automata::{DFA, Distance};
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use crate::search::query_tree::{Operation, Query};
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use super::build_dfa;
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type IsPrefix = bool;
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/// The query tree builder is the interface to build a query tree.
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#[derive(Default)]
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pub struct MatchingWords {
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dfas: Vec<(DFA, String, u8, IsPrefix)>,
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}
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impl MatchingWords {
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/// Lists all words which can be considered as a match for the query tree.
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pub fn from_query_tree(tree: &Operation) -> Self {
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let mut dfas: Vec<_> = fetch_queries(tree)
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.into_iter()
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.map(|(w, t, p)| (build_dfa(w, t, p), w.to_string(), t, p))
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.collect();
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dfas.sort_unstable_by_key(|(_dfa, query_word, _typo, _is_prefix)| Reverse(query_word.len()));
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Self { dfas }
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}
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/// Returns the number of matching bytes if the word matches.
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pub fn matching_bytes(&self, word: &str) -> Option<usize> {
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self.dfas.iter().find_map(|(dfa, query_word, typo, is_prefix)| match dfa.eval(word) {
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Distance::Exact(t) if t <= *typo => {
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if *is_prefix {
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let (_dist, len) = prefix_damerau_levenshtein(query_word.as_bytes(), word.as_bytes());
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Some(len)
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} else {
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Some(word.len())
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}
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},
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_otherwise => None,
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})
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}
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}
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/// Lists all words which can be considered as a match for the query tree.
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fn fetch_queries(tree: &Operation) -> HashSet<(&str, u8, IsPrefix)> {
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fn resolve_ops<'a>(tree: &'a Operation, out: &mut HashSet<(&'a str, u8, IsPrefix)>) {
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match tree {
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Operation::Or(_, ops) | Operation::And(ops) | Operation::Consecutive(ops) => {
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ops.as_slice().iter().for_each(|op| resolve_ops(op, out));
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},
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Operation::Query(Query { prefix, kind }) => {
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let typo = if kind.is_exact() { 0 } else { kind.typo() };
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out.insert((kind.word(), typo, *prefix));
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},
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}
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}
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let mut queries = HashSet::new();
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resolve_ops(tree, &mut queries);
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queries
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}
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// A simple wrapper around vec so we can get contiguous but index it like it's 2D array.
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struct N2Array<T> {
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y_size: usize,
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buf: Vec<T>,
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}
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impl<T: Clone> N2Array<T> {
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fn new(x: usize, y: usize, value: T) -> N2Array<T> {
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N2Array {
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y_size: y,
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buf: vec![value; x * y],
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}
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}
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}
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impl<T> Index<(usize, usize)> for N2Array<T> {
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type Output = T;
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#[inline]
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fn index(&self, (x, y): (usize, usize)) -> &T {
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&self.buf[(x * self.y_size) + y]
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}
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}
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impl<T> IndexMut<(usize, usize)> for N2Array<T> {
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#[inline]
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fn index_mut(&mut self, (x, y): (usize, usize)) -> &mut T {
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&mut self.buf[(x * self.y_size) + y]
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}
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}
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fn prefix_damerau_levenshtein(source: &[u8], target: &[u8]) -> (u32, usize) {
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let (n, m) = (source.len(), target.len());
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if n == 0 {
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return (m as u32, 0);
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}
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if m == 0 {
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return (n as u32, 0);
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}
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if n == m && source == target {
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return (0, m);
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}
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let inf = n + m;
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let mut matrix = N2Array::new(n + 2, m + 2, 0);
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matrix[(0, 0)] = inf;
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for i in 0..n + 1 {
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matrix[(i + 1, 0)] = inf;
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matrix[(i + 1, 1)] = i;
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}
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for j in 0..m + 1 {
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matrix[(0, j + 1)] = inf;
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matrix[(1, j + 1)] = j;
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}
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let mut last_row = BTreeMap::new();
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for (row, char_s) in source.iter().enumerate() {
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let mut last_match_col = 0;
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let row = row + 1;
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for (col, char_t) in target.iter().enumerate() {
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let col = col + 1;
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let last_match_row = *last_row.get(&char_t).unwrap_or(&0);
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let cost = if char_s == char_t { 0 } else { 1 };
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let dist_add = matrix[(row, col + 1)] + 1;
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let dist_del = matrix[(row + 1, col)] + 1;
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let dist_sub = matrix[(row, col)] + cost;
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let dist_trans = matrix[(last_match_row, last_match_col)]
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+ (row - last_match_row - 1)
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+ 1
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+ (col - last_match_col - 1);
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let dist = min(min(dist_add, dist_del), min(dist_sub, dist_trans));
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matrix[(row + 1, col + 1)] = dist;
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if cost == 0 {
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last_match_col = col;
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}
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}
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last_row.insert(char_s, row);
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}
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let mut minimum = (u32::max_value(), 0);
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for x in 0..=m {
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let dist = matrix[(n + 1, x + 1)] as u32;
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if dist < minimum.0 {
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minimum = (dist, x)
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}
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}
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minimum
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}
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#[cfg(test)]
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mod tests {
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use super::*;
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use crate::MatchingWords;
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use crate::search::query_tree::{Operation, Query, QueryKind};
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#[test]
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fn matched_length() {
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let query = "Levenste";
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let text = "Levenshtein";
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let (dist, length) = prefix_damerau_levenshtein(query.as_bytes(), text.as_bytes());
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assert_eq!(dist, 1);
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assert_eq!(&text[..length], "Levenshte");
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}
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#[test]
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fn matching_words() {
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let query_tree = Operation::Or(false, vec![
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Operation::And(vec![
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Operation::Query(Query { prefix: true, kind: QueryKind::exact("split".to_string()) }),
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Operation::Query(Query { prefix: false, kind: QueryKind::exact("this".to_string()) }),
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Operation::Query(Query { prefix: true, kind: QueryKind::tolerant(1, "world".to_string()) }),
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]),
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]);
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let matching_words = MatchingWords::from_query_tree(&query_tree);
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assert_eq!(matching_words.matching_bytes("word"), Some(4));
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assert_eq!(matching_words.matching_bytes("nyc"), None);
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assert_eq!(matching_words.matching_bytes("world"), Some(5));
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assert_eq!(matching_words.matching_bytes("splitted"), Some(5));
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assert_eq!(matching_words.matching_bytes("thisnew"), None);
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assert_eq!(matching_words.matching_bytes("borld"), Some(5));
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assert_eq!(matching_words.matching_bytes("wordsplit"), Some(4));
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}
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}
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@ -17,7 +17,7 @@ use crate::search::criteria::r#final::{Final, FinalResult};
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use crate::{Index, DocumentId};
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pub use self::facet::{FacetCondition, FacetDistribution, FacetIter, Operator};
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pub use self::query_tree::MatchingWords;
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pub use self::matching_words::MatchingWords;
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use self::query_tree::QueryTreeBuilder;
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// Building these factories is not free.
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@ -29,6 +29,7 @@ mod criteria;
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mod distinct;
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mod facet;
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mod query_tree;
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mod matching_words;
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pub struct Search<'a> {
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query: Option<String>,
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@ -294,48 +294,6 @@ fn synonyms(ctx: &impl Context, word: &[&str]) -> heed::Result<Option<Vec<Operat
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}))
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}
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/// The query tree builder is the interface to build a query tree.
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#[derive(Default)]
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pub struct MatchingWords {
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dfas: Vec<(DFA, u8)>,
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}
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impl MatchingWords {
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/// List all words which can be considered as a match for the query tree.
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pub fn from_query_tree(tree: &Operation) -> Self {
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Self {
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dfas: fetch_queries(tree).into_iter().map(|(w, t, p)| (build_dfa(w, t, p), t)).collect()
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}
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}
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/// Return true if the word match.
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pub fn matches(&self, word: &str) -> bool {
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self.dfas.iter().any(|(dfa, typo)| match dfa.eval(word) {
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Distance::Exact(t) => t <= *typo,
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Distance::AtLeast(_) => false,
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})
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}
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}
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/// Lists all words which can be considered as a match for the query tree.
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fn fetch_queries(tree: &Operation) -> HashSet<(&str, u8, IsPrefix)> {
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fn resolve_ops<'a>(tree: &'a Operation, out: &mut HashSet<(&'a str, u8, IsPrefix)>) {
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match tree {
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Operation::Or(_, ops) | Operation::And(ops) | Operation::Consecutive(ops) => {
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ops.as_slice().iter().for_each(|op| resolve_ops(op, out));
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},
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Operation::Query(Query { prefix, kind }) => {
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let typo = if kind.is_exact() { 0 } else { kind.typo() };
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out.insert((kind.word(), typo, *prefix));
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},
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}
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}
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let mut queries = HashSet::new();
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resolve_ops(tree, &mut queries);
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queries
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}
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/// Main function that creates the final query tree from the primitive query.
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fn create_query_tree(
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ctx: &impl Context,
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@ -951,39 +909,6 @@ mod test {
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assert_eq!(expected, query_tree);
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}
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#[test]
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fn fetching_words() {
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let query = "wordsplit nyc world";
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let analyzer = Analyzer::new(AnalyzerConfig::<Vec<u8>>::default());
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let result = analyzer.analyze(query);
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let tokens = result.tokens();
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let context = TestContext::default();
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let (query_tree, _) = context.build(false, true, None, tokens).unwrap().unwrap();
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let expected = hashset!{
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("word", 0, false),
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("nyc", 0, false),
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("wordsplit", 2, false),
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("wordsplitnycworld", 2, true),
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("nature", 0, false),
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("new", 0, false),
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("city", 0, false),
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("world", 1, true),
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("york", 0, false),
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("split", 0, false),
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("nycworld", 1, true),
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("earth", 0, false),
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("wordsplitnyc", 2, false),
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};
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let mut keys = context.postings.keys().collect::<Vec<_>>();
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keys.sort_unstable();
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let words = fetch_queries(&query_tree);
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assert_eq!(expected, words);
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}
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#[test]
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fn words_limit() {
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let query = "\"hey my\" good friend";
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