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Use hashmap instead of Btree in wpp extractor
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parent
7ba49b849e
commit
f13e076b8a
@ -1,4 +1,4 @@
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use std::collections::{BTreeMap, VecDeque};
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use std::collections::{HashMap, VecDeque};
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use heed::RoTxn;
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use itertools::merge_join_by;
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@ -35,10 +35,8 @@ impl SearchableExtractor for WordPairProximityDocidsExtractor {
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cached_sorter: &mut CboCachedSorter<MergeDeladdCboRoaringBitmaps>,
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document_change: DocumentChange,
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) -> Result<()> {
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/// TODO: mutualize those buffers
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let mut key_buffer = Vec::new();
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let mut add_word_pair_proximity = BTreeMap::new();
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let mut del_word_pair_proximity = BTreeMap::new();
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let mut word_pair_proximity = HashMap::new();
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let mut word_positions: VecDeque<(String, u16)> =
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VecDeque::with_capacity(MAX_DISTANCE as usize);
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@ -51,7 +49,14 @@ impl SearchableExtractor for WordPairProximityDocidsExtractor {
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document_tokenizer,
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fields_ids_map,
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&mut word_positions,
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&mut del_word_pair_proximity,
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&mut |(w1, w2), prox| {
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word_pair_proximity
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.entry((w1, w2))
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.and_modify(|(del_p, _add_p)| {
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*del_p = std::cmp::min(*del_p, prox);
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})
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.or_insert((prox, 0));
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},
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)?;
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}
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DocumentChange::Update(inner) => {
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@ -61,7 +66,14 @@ impl SearchableExtractor for WordPairProximityDocidsExtractor {
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document_tokenizer,
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fields_ids_map,
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&mut word_positions,
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&mut del_word_pair_proximity,
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&mut |(w1, w2), prox| {
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word_pair_proximity
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.entry((w1, w2))
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.and_modify(|(del_p, _add_p)| {
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*del_p = std::cmp::min(*del_p, prox);
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})
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.or_insert((prox, 0));
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},
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)?;
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let document = inner.new();
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process_document_tokens(
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@ -69,7 +81,14 @@ impl SearchableExtractor for WordPairProximityDocidsExtractor {
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document_tokenizer,
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fields_ids_map,
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&mut word_positions,
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&mut add_word_pair_proximity,
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&mut |(w1, w2), prox| {
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word_pair_proximity
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.entry((w1, w2))
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.and_modify(|(_del_p, add_p)| {
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*add_p = std::cmp::min(*add_p, prox);
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})
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.or_insert((0, prox));
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},
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)?;
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}
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DocumentChange::Insertion(inner) => {
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@ -79,36 +98,24 @@ impl SearchableExtractor for WordPairProximityDocidsExtractor {
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document_tokenizer,
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fields_ids_map,
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&mut word_positions,
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&mut add_word_pair_proximity,
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&mut |(w1, w2), prox| {
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word_pair_proximity
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.entry((w1, w2))
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.and_modify(|(_del_p, add_p)| {
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*add_p = std::cmp::min(*add_p, prox);
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})
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.or_insert((0, prox));
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},
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)?;
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}
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}
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use itertools::EitherOrBoth::*;
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for eob in
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merge_join_by(del_word_pair_proximity.iter(), add_word_pair_proximity.iter(), |d, a| {
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d.cmp(a)
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})
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{
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match eob {
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Left(((w1, w2), prox)) => {
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let key = build_key(*prox, w1, w2, &mut key_buffer);
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for ((w1, w2), (del_p, add_p)) in word_pair_proximity.iter() {
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let key = build_key(*del_p, w1, w2, &mut key_buffer);
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cached_sorter.insert_del_u32(key, docid)?;
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}
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Right(((w1, w2), prox)) => {
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let key = build_key(*prox, w1, w2, &mut key_buffer);
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let key = build_key(*add_p, w1, w2, &mut key_buffer);
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cached_sorter.insert_add_u32(key, docid)?;
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}
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Both(((w1, w2), del_prox), (_, add_prox)) => {
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if del_prox != add_prox {
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let key = build_key(*del_prox, w1, w2, &mut key_buffer);
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cached_sorter.insert_del_u32(key, docid)?;
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let key = build_key(*add_prox, w1, w2, &mut key_buffer);
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cached_sorter.insert_add_u32(key, docid)?;
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}
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}
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}
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}
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Ok(())
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}
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@ -125,18 +132,19 @@ fn build_key<'a>(prox: u8, w1: &str, w2: &str, key_buffer: &'a mut Vec<u8>) -> &
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fn word_positions_into_word_pair_proximity(
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word_positions: &mut VecDeque<(String, u16)>,
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word_pair_proximity: &mut BTreeMap<(String, String), u8>,
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word_pair_proximity: &mut dyn FnMut((String, String), u8),
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) -> Result<()> {
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let (head_word, head_position) = word_positions.pop_front().unwrap();
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for (word, position) in word_positions.iter() {
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let prox = index_proximity(head_position as u32, *position as u32) as u8;
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if prox > 0 && prox < MAX_DISTANCE as u8 {
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word_pair_proximity
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.entry((head_word.clone(), word.clone()))
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.and_modify(|p| {
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*p = std::cmp::min(*p, prox);
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})
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.or_insert(prox);
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word_pair_proximity((head_word.clone(), word.clone()), prox);
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// word_pair_proximity
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// .entry((head_word.clone(), word.clone()))
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// .and_modify(|p| {
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// *p = std::cmp::min(*p, prox);
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// })
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// .or_insert(prox);
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}
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}
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Ok(())
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@ -147,7 +155,7 @@ fn process_document_tokens(
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document_tokenizer: &DocumentTokenizer,
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fields_ids_map: &mut GlobalFieldsIdsMap,
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word_positions: &mut VecDeque<(String, u16)>,
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word_pair_proximity: &mut BTreeMap<(String, String), u8>,
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word_pair_proximity: &mut dyn FnMut((String, String), u8),
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) -> Result<()> {
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let mut token_fn = |_fname: &str, _fid: FieldId, pos: u16, word: &str| {
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// drain the proximity window until the head word is considered close to the word we are inserting.
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