mirror of
https://github.com/meilisearch/MeiliSearch
synced 2024-11-11 15:38:55 +01:00
Clean up the fetch algorithm
This commit is contained in:
Clément Renault
parent
03eb7898e7
commit
7d9cf8d713
@ -29,8 +29,13 @@ impl AutomatonProducer {
|
||||
postings_list_store: store::PostingsLists,
|
||||
synonyms_store: store::Synonyms,
|
||||
) -> MResult<(AutomatonProducer, QueryEnhancer)> {
|
||||
let (automatons, query_enhancer) =
|
||||
generate_automatons(reader, query, main_store, postings_list_store, synonyms_store)?;
|
||||
let (automatons, query_enhancer) = generate_automatons(
|
||||
reader,
|
||||
query,
|
||||
main_store,
|
||||
postings_list_store,
|
||||
synonyms_store,
|
||||
)?;
|
||||
|
||||
Ok((AutomatonProducer { automatons }, query_enhancer))
|
||||
}
|
||||
@ -41,9 +46,25 @@ impl AutomatonProducer {
|
||||
}
|
||||
|
||||
#[derive(Debug)]
|
||||
pub enum AutomatonGroup {
|
||||
Normal(Vec<Automaton>),
|
||||
PhraseQuery(Vec<Automaton>),
|
||||
pub struct AutomatonGroup {
|
||||
pub is_phrase_query: bool,
|
||||
pub automatons: Vec<Automaton>,
|
||||
}
|
||||
|
||||
impl AutomatonGroup {
|
||||
fn normal(automatons: Vec<Automaton>) -> AutomatonGroup {
|
||||
AutomatonGroup {
|
||||
is_phrase_query: false,
|
||||
automatons,
|
||||
}
|
||||
}
|
||||
|
||||
fn phrase_query(automatons: Vec<Automaton>) -> AutomatonGroup {
|
||||
AutomatonGroup {
|
||||
is_phrase_query: true,
|
||||
automatons,
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
#[derive(Debug)]
|
||||
@ -143,8 +164,7 @@ fn generate_automatons(
|
||||
main_store: store::Main,
|
||||
postings_lists_store: store::PostingsLists,
|
||||
synonym_store: store::Synonyms,
|
||||
) -> MResult<(Vec<AutomatonGroup>, QueryEnhancer)>
|
||||
{
|
||||
) -> MResult<(Vec<AutomatonGroup>, QueryEnhancer)> {
|
||||
let has_end_whitespace = query.chars().last().map_or(false, char::is_whitespace);
|
||||
let query_words: Vec<_> = split_query_string(query).map(str::to_lowercase).collect();
|
||||
let synonyms = match main_store.synonyms_fst(reader)? {
|
||||
@ -173,7 +193,7 @@ fn generate_automatons(
|
||||
original_automatons.push(automaton);
|
||||
}
|
||||
|
||||
automatons.push(AutomatonGroup::Normal(original_automatons));
|
||||
automatons.push(AutomatonGroup::normal(original_automatons));
|
||||
|
||||
for n in 1..=NGRAMS {
|
||||
let mut ngrams = query_words.windows(n).enumerate().peekable();
|
||||
@ -225,14 +245,16 @@ fn generate_automatons(
|
||||
Automaton::non_exact(automaton_index, n, synonym)
|
||||
};
|
||||
automaton_index += 1;
|
||||
automatons.push(AutomatonGroup::Normal(vec![automaton]));
|
||||
automatons.push(AutomatonGroup::normal(vec![automaton]));
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
if n == 1 {
|
||||
if let Some((left, right)) = split_best_frequency(reader, &normalized, postings_lists_store)? {
|
||||
if let Some((left, right)) =
|
||||
split_best_frequency(reader, &normalized, postings_lists_store)?
|
||||
{
|
||||
let a = Automaton::exact(automaton_index, 1, left);
|
||||
enhancer_builder.declare(query_range.clone(), automaton_index, &[left]);
|
||||
automaton_index += 1;
|
||||
@ -241,7 +263,7 @@ fn generate_automatons(
|
||||
enhancer_builder.declare(query_range.clone(), automaton_index, &[left]);
|
||||
automaton_index += 1;
|
||||
|
||||
automatons.push(AutomatonGroup::PhraseQuery(vec![a, b]));
|
||||
automatons.push(AutomatonGroup::phrase_query(vec![a, b]));
|
||||
}
|
||||
} else {
|
||||
// automaton of concatenation of query words
|
||||
@ -253,7 +275,7 @@ fn generate_automatons(
|
||||
|
||||
let automaton = Automaton::exact(automaton_index, n, &normalized);
|
||||
automaton_index += 1;
|
||||
automatons.push(AutomatonGroup::Normal(vec![automaton]));
|
||||
automatons.push(AutomatonGroup::normal(vec![automaton]));
|
||||
}
|
||||
}
|
||||
}
|
||||
@ -261,10 +283,7 @@ fn generate_automatons(
|
||||
// order automatons, the most important first,
|
||||
// we keep the original automatons at the front.
|
||||
automatons[1..].sort_by_key(|group| {
|
||||
let a = match group {
|
||||
AutomatonGroup::Normal(group) => group.first().unwrap(),
|
||||
AutomatonGroup::PhraseQuery(group) => group.first().unwrap(),
|
||||
};
|
||||
let a = group.automatons.first().unwrap();
|
||||
(Reverse(a.is_exact), a.ngram)
|
||||
});
|
||||
|
||||
|
||||
@ -149,60 +149,20 @@ fn fetch_raw_documents(
|
||||
let mut highlights = Vec::new();
|
||||
|
||||
for group in automatons_groups {
|
||||
match group {
|
||||
AutomatonGroup::Normal(automatons) => {
|
||||
for automaton in automatons {
|
||||
let Automaton { index, is_exact, query_len, .. } = automaton;
|
||||
let dfa = automaton.dfa();
|
||||
|
||||
let words = match main_store.words_fst(reader)? {
|
||||
Some(words) => words,
|
||||
None => return Ok(Vec::new()),
|
||||
};
|
||||
|
||||
let mut stream = words.search(&dfa).into_stream();
|
||||
while let Some(input) = stream.next() {
|
||||
let distance = dfa.eval(input).to_u8();
|
||||
let is_exact = *is_exact && distance == 0 && input.len() == *query_len;
|
||||
|
||||
let doc_indexes = match postings_lists_store.postings_list(reader, input)? {
|
||||
Some(doc_indexes) => doc_indexes,
|
||||
None => continue,
|
||||
};
|
||||
|
||||
matches.reserve(doc_indexes.len());
|
||||
highlights.reserve(doc_indexes.len());
|
||||
|
||||
for di in doc_indexes.as_ref() {
|
||||
let attribute = searchables.map_or(Some(di.attribute), |r| r.get(di.attribute));
|
||||
if let Some(attribute) = attribute {
|
||||
let match_ = TmpMatch {
|
||||
query_index: *index as u32,
|
||||
distance,
|
||||
attribute,
|
||||
word_index: di.word_index,
|
||||
is_exact,
|
||||
};
|
||||
|
||||
let highlight = Highlight {
|
||||
attribute: di.attribute,
|
||||
char_index: di.char_index,
|
||||
char_length: di.char_length,
|
||||
};
|
||||
|
||||
matches.push((di.document_id, match_));
|
||||
highlights.push((di.document_id, highlight));
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
},
|
||||
AutomatonGroup::PhraseQuery(automatons) => {
|
||||
let mut tmp_matches = Vec::new();
|
||||
let AutomatonGroup {
|
||||
is_phrase_query,
|
||||
automatons,
|
||||
} = group;
|
||||
let phrase_query_len = automatons.len();
|
||||
|
||||
let mut tmp_matches = Vec::new();
|
||||
for (id, automaton) in automatons.into_iter().enumerate() {
|
||||
let Automaton { index, is_exact, query_len, .. } = automaton;
|
||||
let Automaton {
|
||||
index,
|
||||
is_exact,
|
||||
query_len,
|
||||
..
|
||||
} = automaton;
|
||||
let dfa = automaton.dfa();
|
||||
|
||||
let words = match main_store.words_fst(reader)? {
|
||||
@ -245,6 +205,7 @@ fn fetch_raw_documents(
|
||||
}
|
||||
}
|
||||
|
||||
if *is_phrase_query {
|
||||
tmp_matches.sort_unstable_by_key(|(id, _, m, _)| (*id, m.attribute, m.word_index));
|
||||
for group in tmp_matches.linear_group_by_key(|(id, _, m, _)| (*id, m.attribute)) {
|
||||
for window in group.windows(2) {
|
||||
@ -255,7 +216,6 @@ fn fetch_raw_documents(
|
||||
|
||||
// if matches must follow and actually follows themselves
|
||||
if ia + 1 == ib && ma.word_index + 1 == mb.word_index {
|
||||
|
||||
// TODO we must make it work for phrase query longer than 2
|
||||
// if the second match is the last phrase query word
|
||||
if ib + 1 == phrase_query_len {
|
||||
@ -270,6 +230,10 @@ fn fetch_raw_documents(
|
||||
}
|
||||
}
|
||||
}
|
||||
} else {
|
||||
for (id, _, match_, highlight) in tmp_matches {
|
||||
matches.push((id, match_));
|
||||
highlights.push((id, highlight));
|
||||
}
|
||||
}
|
||||
}
|
||||
@ -442,8 +406,13 @@ where
|
||||
let start_processing = Instant::now();
|
||||
let mut raw_documents_processed = Vec::with_capacity(range.len());
|
||||
|
||||
let (automaton_producer, query_enhancer) =
|
||||
AutomatonProducer::new(reader, query, main_store, postings_lists_store, synonyms_store)?;
|
||||
let (automaton_producer, query_enhancer) = AutomatonProducer::new(
|
||||
reader,
|
||||
query,
|
||||
main_store,
|
||||
postings_lists_store,
|
||||
synonyms_store,
|
||||
)?;
|
||||
|
||||
let automaton_producer = automaton_producer.into_iter();
|
||||
let mut automatons = Vec::new();
|
||||
@ -555,8 +524,13 @@ where
|
||||
let start_processing = Instant::now();
|
||||
let mut raw_documents_processed = Vec::new();
|
||||
|
||||
let (automaton_producer, query_enhancer) =
|
||||
AutomatonProducer::new(reader, query, main_store, postings_lists_store, synonyms_store)?;
|
||||
let (automaton_producer, query_enhancer) = AutomatonProducer::new(
|
||||
reader,
|
||||
query,
|
||||
main_store,
|
||||
postings_lists_store,
|
||||
synonyms_store,
|
||||
)?;
|
||||
|
||||
let automaton_producer = automaton_producer.into_iter();
|
||||
let mut automatons = Vec::new();
|
||||
@ -1778,7 +1752,6 @@ mod tests {
|
||||
let store = TempDatabase::from_iter(vec![
|
||||
("search", &[doc_index(0, 0)][..]),
|
||||
("engine", &[doc_index(0, 1)][..]),
|
||||
|
||||
("search", &[doc_index(1, 0)][..]),
|
||||
("slow", &[doc_index(1, 1)][..]),
|
||||
("engine", &[doc_index(1, 2)][..]),
|
||||
@ -1806,12 +1779,10 @@ mod tests {
|
||||
("search", &[doc_index(0, 0)][..]),
|
||||
("search", &[doc_index(0, 1)][..]),
|
||||
("engine", &[doc_index(0, 2)][..]),
|
||||
|
||||
("search", &[doc_index(1, 0)][..]),
|
||||
("slow", &[doc_index(1, 1)][..]),
|
||||
("search", &[doc_index(1, 2)][..]),
|
||||
("engine", &[doc_index(1, 3)][..]),
|
||||
|
||||
("search", &[doc_index(1, 0)][..]),
|
||||
("search", &[doc_index(1, 1)][..]),
|
||||
("slow", &[doc_index(1, 2)][..]),
|
||||
|
||||
Loading…
Reference in New Issue
Block a user