mod best_proximity; mod heed_codec; mod iter_shortest_paths; mod query_tokens; use std::borrow::Cow; use std::collections::HashMap; use std::hash::BuildHasherDefault; use std::time::Instant; use cow_utils::CowUtils; use fst::{IntoStreamer, Streamer}; use fxhash::FxHasher32; use heed::types::*; use heed::{PolyDatabase, Database}; use levenshtein_automata::LevenshteinAutomatonBuilder as LevBuilder; use once_cell::sync::Lazy; use roaring::RoaringBitmap; use self::best_proximity::BestProximity; use self::heed_codec::RoaringBitmapCodec; use self::query_tokens::{QueryTokens, QueryToken}; // Building these factories is not free. static LEVDIST0: Lazy = Lazy::new(|| LevBuilder::new(0, true)); static LEVDIST1: Lazy = Lazy::new(|| LevBuilder::new(1, true)); static LEVDIST2: Lazy = Lazy::new(|| LevBuilder::new(2, true)); pub type FastMap4 = HashMap>; pub type SmallString32 = smallstr::SmallString<[u8; 32]>; pub type SmallVec32 = smallvec::SmallVec<[T; 32]>; pub type SmallVec16 = smallvec::SmallVec<[T; 16]>; pub type BEU32 = heed::zerocopy::U32; pub type DocumentId = u32; pub type AttributeId = u32; #[derive(Clone)] pub struct Index { /// Contains many different types (e.g. the documents CSV headers). pub main: PolyDatabase, /// A word and all the positions where it appears in the whole dataset. pub word_positions: Database, pub prefix_word_positions: Database, /// Maps a word at a position (u32) and all the documents ids where it appears. pub word_position_docids: Database, pub prefix_word_position_docids: Database, /// Maps a word and an attribute (u32) to all the documents ids that it appears in. pub word_attribute_docids: Database, /// Maps an internal document to the content of the document in CSV. pub documents: Database, ByteSlice>, } impl Index { pub fn new(env: &heed::Env) -> heed::Result { Ok(Index { main: env.create_poly_database(None)?, word_positions: env.create_database(Some("word-positions"))?, prefix_word_positions: env.create_database(Some("prefix-word-positions"))?, word_position_docids: env.create_database(Some("word-position-docids"))?, prefix_word_position_docids: env.create_database(Some("prefix-word-position-docids"))?, word_attribute_docids: env.create_database(Some("word-attribute-docids"))?, documents: env.create_database(Some("documents"))?, }) } pub fn headers<'t>(&self, rtxn: &'t heed::RoTxn) -> heed::Result> { self.main.get::<_, Str, ByteSlice>(rtxn, "headers") } pub fn fst<'t>(&self, rtxn: &'t heed::RoTxn) -> anyhow::Result>> { match self.main.get::<_, Str, ByteSlice>(rtxn, "words-fst")? { Some(bytes) => Ok(Some(fst::Set::new(bytes)?)), None => Ok(None), } } pub fn search(&self, rtxn: &heed::RoTxn, query: &str) -> anyhow::Result> { let fst = match self.fst(rtxn)? { Some(fst) => fst, None => return Ok(vec![]), }; let (lev0, lev1, lev2) = (&LEVDIST0, &LEVDIST1, &LEVDIST2); let words: Vec<_> = QueryTokens::new(query).collect(); let ends_with_whitespace = query.chars().last().map_or(false, char::is_whitespace); let number_of_words = words.len(); let dfas = words.into_iter().enumerate().map(|(i, word)| { let (word, quoted) = match word { QueryToken::Free(word) => (word.cow_to_lowercase(), false), QueryToken::Quoted(word) => (Cow::Borrowed(word), true), }; let is_last = i + 1 == number_of_words; let is_prefix = is_last && !ends_with_whitespace && !quoted; let lev = match word.len() { 0..=4 => if quoted { lev0 } else { lev0 }, 5..=8 => if quoted { lev0 } else { lev1 }, _ => if quoted { lev0 } else { lev2 }, }; let dfa = if is_prefix { lev.build_prefix_dfa(&word) } else { lev.build_dfa(&word) }; (word, is_prefix, dfa) }); let mut words = Vec::new(); let mut positions = Vec::new(); let before = Instant::now(); for (word, _is_prefix, dfa) in dfas { let before = Instant::now(); let mut count = 0; let mut union_positions = RoaringBitmap::default(); let mut derived_words = Vec::new(); // TODO re-enable the prefixes system let mut stream = fst.search(&dfa).into_stream(); while let Some(word) = stream.next() { let word = std::str::from_utf8(word)?; if let Some(right) = self.word_positions.get(rtxn, word)? { union_positions.union_with(&right); derived_words.push((word.as_bytes().to_vec(), right)); count += 1; } } eprintln!("{} words for {:?} we have found positions {:?} in {:.02?}", count, word, union_positions, before.elapsed()); words.push(derived_words); positions.push(union_positions.iter().collect()); } let mut words_attributes_docids = HashMap::new(); let number_attributes: u32 = 6; for i in 0..number_attributes { let mut intersect_docids: Option = None; for derived_words in &words { let mut union_docids = RoaringBitmap::new(); for (word, _) in derived_words { // generate the key with the attribute number. let mut key = word.to_vec(); key.extend_from_slice(&i.to_be_bytes()); if let Some(right) = self.word_attribute_docids.get(rtxn, &key)? { union_docids.union_with(&right); } } match &mut intersect_docids { Some(left) => left.intersect_with(&union_docids), None => intersect_docids = Some(union_docids), } } if let Some(docids) = intersect_docids { words_attributes_docids.insert(i, docids); } } eprintln!("The documents you must find for each attribute: {:?}", words_attributes_docids); eprintln!("Retrieving words positions took {:.02?}", before.elapsed()); // Returns the union of the same position for all the derived words. let unions_word_pos = |word: usize, pos: u32| { let mut union_docids = RoaringBitmap::new(); for (word, attrs) in &words[word] { if attrs.contains(pos) { let mut key = word.clone(); key.extend_from_slice(&pos.to_be_bytes()); if let Some(right) = self.word_position_docids.get(rtxn, &key).unwrap() { union_docids.union_with(&right); } } } union_docids }; let mut union_cache = HashMap::new(); let mut intersect_cache = HashMap::new(); // Returns `true` if there is documents in common between the two words and positions given. let mut contains_documents = |(lword, lpos), (rword, rpos), union_cache: &mut HashMap<_, _>| { let proximity = best_proximity::positions_proximity(lpos, rpos); if proximity == 0 { return false } // We retrieve or compute the intersection between the two given words and positions. *intersect_cache.entry(((lword, lpos), (rword, rpos))).or_insert_with(|| { // We retrieve or compute the unions for the two words and positions. union_cache.entry((lword, lpos)).or_insert_with(|| unions_word_pos(lword, lpos)); union_cache.entry((rword, rpos)).or_insert_with(|| unions_word_pos(rword, rpos)); // TODO is there a way to avoid this double gets? let lunion_docids = union_cache.get(&(lword, lpos)).unwrap(); let runion_docids = union_cache.get(&(rword, rpos)).unwrap(); !lunion_docids.is_disjoint(&runion_docids) }) }; let mut documents = Vec::new(); let mut iter = BestProximity::new(positions); while let Some((proximity, mut positions)) = iter.next(|l, r| contains_documents(l, r, &mut union_cache)) { positions.sort_unstable(); let same_prox_before = Instant::now(); let mut same_proximity_union = RoaringBitmap::default(); for positions in positions { let before = Instant::now(); let mut intersect_docids: Option = None; for (word, pos) in positions.iter().enumerate() { let before = Instant::now(); let union_docids = union_cache.entry((word, *pos)).or_insert_with(|| unions_word_pos(word, *pos)); let before_intersect = Instant::now(); match &mut intersect_docids { Some(left) => left.intersect_with(&union_docids), None => intersect_docids = Some(union_docids.clone()), } eprintln!("retrieving words took {:.02?} and took {:.02?} to intersect", before.elapsed(), before_intersect.elapsed()); } eprintln!("for proximity {:?} {:?} we took {:.02?} to find {} documents", proximity, positions, before.elapsed(), intersect_docids.as_ref().map_or(0, |rb| rb.len())); if let Some(intersect_docids) = intersect_docids { same_proximity_union.union_with(&intersect_docids); } // We found enough documents we can stop here if documents.iter().map(RoaringBitmap::len).sum::() + same_proximity_union.len() >= 20 { eprintln!("proximity {} took a total of {:.02?}", proximity, same_prox_before.elapsed()); break; } } // We achieve to find valid documents ids so we remove them from the candidate list. for (_, docids) in &mut words_attributes_docids { docids.difference_with(&same_proximity_union); } documents.push(same_proximity_union); // We remove the double occurences of documents. for i in 0..documents.len() { if let Some((docs, others)) = documents[..=i].split_last_mut() { others.iter().for_each(|other| docs.difference_with(other)); } } documents.retain(|rb| !rb.is_empty()); eprintln!("documents: {:?}", documents); eprintln!("proximity {} took a total of {:.02?}", proximity, same_prox_before.elapsed()); // We found enough documents we can stop here. if documents.iter().map(RoaringBitmap::len).sum::() >= 20 { break; } } eprintln!("{} candidates", documents.iter().map(RoaringBitmap::len).sum::()); Ok(documents.iter().flatten().take(20).collect()) } }