2020-11-20 10:54:41 +01:00
|
|
|
use std::borrow::Cow;
|
|
|
|
use std::collections::{HashMap, HashSet};
|
|
|
|
use std::fmt;
|
|
|
|
|
2020-11-27 13:40:21 +01:00
|
|
|
use anyhow::{bail, Context};
|
2020-11-20 10:54:41 +01:00
|
|
|
use fst::{IntoStreamer, Streamer};
|
|
|
|
use levenshtein_automata::DFA;
|
|
|
|
use levenshtein_automata::LevenshteinAutomatonBuilder as LevBuilder;
|
|
|
|
use log::debug;
|
|
|
|
use once_cell::sync::Lazy;
|
|
|
|
use roaring::bitmap::RoaringBitmap;
|
|
|
|
|
2020-11-27 13:40:21 +01:00
|
|
|
use crate::facet::FacetType;
|
|
|
|
use crate::heed_codec::facet::{FacetLevelValueF64Codec, FacetLevelValueI64Codec};
|
2020-11-20 10:54:41 +01:00
|
|
|
use crate::mdfs::Mdfs;
|
|
|
|
use crate::query_tokens::{QueryTokens, QueryToken};
|
2020-11-27 13:40:21 +01:00
|
|
|
use crate::{Index, FieldId, DocumentId, Criterion};
|
2020-11-20 10:54:41 +01:00
|
|
|
|
2020-11-27 16:10:40 +01:00
|
|
|
pub use self::facet::{FacetCondition, FacetNumberOperator, FacetStringOperator};
|
2020-11-20 10:54:41 +01:00
|
|
|
|
|
|
|
// Building these factories is not free.
|
|
|
|
static LEVDIST0: Lazy<LevBuilder> = Lazy::new(|| LevBuilder::new(0, true));
|
|
|
|
static LEVDIST1: Lazy<LevBuilder> = Lazy::new(|| LevBuilder::new(1, true));
|
|
|
|
static LEVDIST2: Lazy<LevBuilder> = Lazy::new(|| LevBuilder::new(2, true));
|
|
|
|
|
|
|
|
mod facet;
|
|
|
|
|
|
|
|
pub struct Search<'a> {
|
|
|
|
query: Option<String>,
|
|
|
|
facet_condition: Option<FacetCondition>,
|
|
|
|
offset: usize,
|
|
|
|
limit: usize,
|
|
|
|
rtxn: &'a heed::RoTxn<'a>,
|
|
|
|
index: &'a Index,
|
|
|
|
}
|
|
|
|
|
|
|
|
impl<'a> Search<'a> {
|
|
|
|
pub fn new(rtxn: &'a heed::RoTxn, index: &'a Index) -> Search<'a> {
|
|
|
|
Search { query: None, facet_condition: None, offset: 0, limit: 20, rtxn, index }
|
|
|
|
}
|
|
|
|
|
|
|
|
pub fn query(&mut self, query: impl Into<String>) -> &mut Search<'a> {
|
|
|
|
self.query = Some(query.into());
|
|
|
|
self
|
|
|
|
}
|
|
|
|
|
|
|
|
pub fn offset(&mut self, offset: usize) -> &mut Search<'a> {
|
|
|
|
self.offset = offset;
|
|
|
|
self
|
|
|
|
}
|
|
|
|
|
|
|
|
pub fn limit(&mut self, limit: usize) -> &mut Search<'a> {
|
|
|
|
self.limit = limit;
|
|
|
|
self
|
|
|
|
}
|
|
|
|
|
|
|
|
pub fn facet_condition(&mut self, condition: FacetCondition) -> &mut Search<'a> {
|
|
|
|
self.facet_condition = Some(condition);
|
|
|
|
self
|
|
|
|
}
|
|
|
|
|
|
|
|
/// Extracts the query words from the query string and returns the DFAs accordingly.
|
|
|
|
/// TODO introduce settings for the number of typos regarding the words lengths.
|
|
|
|
fn generate_query_dfas(query: &str) -> Vec<(String, bool, DFA)> {
|
|
|
|
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();
|
|
|
|
|
|
|
|
words.into_iter().enumerate().map(|(i, word)| {
|
|
|
|
let (word, quoted) = match word {
|
|
|
|
QueryToken::Free(word) => (word.to_lowercase(), word.len() <= 3),
|
|
|
|
QueryToken::Quoted(word) => (word.to_lowercase(), 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)
|
|
|
|
})
|
|
|
|
.collect()
|
|
|
|
}
|
|
|
|
|
|
|
|
/// Fetch the words from the given FST related to the given DFAs along with
|
|
|
|
/// the associated documents ids.
|
|
|
|
fn fetch_words_docids(
|
|
|
|
&self,
|
|
|
|
fst: &fst::Set<Cow<[u8]>>,
|
|
|
|
dfas: Vec<(String, bool, DFA)>,
|
|
|
|
) -> anyhow::Result<Vec<(HashMap<String, (u8, RoaringBitmap)>, RoaringBitmap)>>
|
|
|
|
{
|
|
|
|
// A Vec storing all the derived words from the original query words, associated
|
|
|
|
// with the distance from the original word and the docids where the words appears.
|
|
|
|
let mut derived_words = Vec::<(HashMap::<String, (u8, RoaringBitmap)>, RoaringBitmap)>::with_capacity(dfas.len());
|
|
|
|
|
|
|
|
for (_word, _is_prefix, dfa) in dfas {
|
|
|
|
|
|
|
|
let mut acc_derived_words = HashMap::new();
|
|
|
|
let mut unions_docids = RoaringBitmap::new();
|
|
|
|
let mut stream = fst.search_with_state(&dfa).into_stream();
|
|
|
|
while let Some((word, state)) = stream.next() {
|
|
|
|
|
|
|
|
let word = std::str::from_utf8(word)?;
|
|
|
|
let docids = self.index.word_docids.get(self.rtxn, word)?.unwrap();
|
|
|
|
let distance = dfa.distance(state);
|
|
|
|
unions_docids.union_with(&docids);
|
|
|
|
acc_derived_words.insert(word.to_string(), (distance.to_u8(), docids));
|
|
|
|
}
|
|
|
|
derived_words.push((acc_derived_words, unions_docids));
|
|
|
|
}
|
|
|
|
|
|
|
|
Ok(derived_words)
|
|
|
|
}
|
|
|
|
|
|
|
|
/// Returns the set of docids that contains all of the query words.
|
|
|
|
fn compute_candidates(
|
|
|
|
derived_words: &[(HashMap<String, (u8, RoaringBitmap)>, RoaringBitmap)],
|
|
|
|
) -> RoaringBitmap
|
|
|
|
{
|
|
|
|
// We sort the derived words by inverse popularity, this way intersections are faster.
|
|
|
|
let mut derived_words: Vec<_> = derived_words.iter().collect();
|
|
|
|
derived_words.sort_unstable_by_key(|(_, docids)| docids.len());
|
|
|
|
|
|
|
|
// we do a union between all the docids of each of the derived words,
|
|
|
|
// we got N unions (the number of original query words), we then intersect them.
|
|
|
|
let mut candidates = RoaringBitmap::new();
|
|
|
|
|
|
|
|
for (i, (_, union_docids)) in derived_words.iter().enumerate() {
|
|
|
|
if i == 0 {
|
|
|
|
candidates = union_docids.clone();
|
|
|
|
} else {
|
|
|
|
candidates.intersect_with(&union_docids);
|
|
|
|
}
|
|
|
|
}
|
|
|
|
|
|
|
|
candidates
|
|
|
|
}
|
|
|
|
|
2020-11-27 13:40:21 +01:00
|
|
|
fn facet_ordered(
|
|
|
|
&self,
|
|
|
|
field_id: FieldId,
|
|
|
|
facet_type: FacetType,
|
|
|
|
order: Order,
|
|
|
|
documents_ids: RoaringBitmap,
|
|
|
|
limit: usize,
|
|
|
|
) -> anyhow::Result<Vec<DocumentId>>
|
|
|
|
{
|
2020-11-27 16:10:40 +01:00
|
|
|
let mut limit_tmp = limit;
|
2020-11-27 13:40:21 +01:00
|
|
|
let mut output = Vec::new();
|
|
|
|
match facet_type {
|
|
|
|
FacetType::Float => {
|
|
|
|
facet_number_recurse::<f64, FacetLevelValueF64Codec, _>(
|
|
|
|
self.rtxn,
|
|
|
|
self.index,
|
|
|
|
field_id,
|
|
|
|
order,
|
|
|
|
documents_ids,
|
|
|
|
|_val, docids| {
|
2020-11-27 16:10:40 +01:00
|
|
|
limit_tmp = limit_tmp.saturating_sub(docids.len() as usize);
|
|
|
|
debug!("Facet ordered iteration find {:?}", docids);
|
2020-11-27 13:40:21 +01:00
|
|
|
output.push(docids);
|
2020-11-27 16:10:40 +01:00
|
|
|
limit_tmp != 0 // Returns `true` if we must continue iterating
|
2020-11-27 13:40:21 +01:00
|
|
|
}
|
|
|
|
)?;
|
|
|
|
},
|
|
|
|
FacetType::Integer => {
|
|
|
|
facet_number_recurse::<i64, FacetLevelValueI64Codec, _>(
|
|
|
|
self.rtxn,
|
|
|
|
self.index,
|
|
|
|
field_id,
|
|
|
|
order,
|
|
|
|
documents_ids,
|
|
|
|
|_val, docids| {
|
2020-11-27 16:10:40 +01:00
|
|
|
limit_tmp = limit_tmp.saturating_sub(docids.len() as usize);
|
|
|
|
debug!("Facet ordered iteration find {:?}", docids);
|
2020-11-27 13:40:21 +01:00
|
|
|
output.push(docids);
|
2020-11-27 16:10:40 +01:00
|
|
|
limit_tmp != 0 // Returns `true` if we must continue iterating
|
2020-11-27 13:40:21 +01:00
|
|
|
}
|
|
|
|
)?;
|
|
|
|
},
|
|
|
|
FacetType::String => bail!("criteria facet type must be a number"),
|
|
|
|
}
|
|
|
|
Ok(output.into_iter().flatten().take(limit).collect())
|
|
|
|
}
|
|
|
|
|
2020-11-20 10:54:41 +01:00
|
|
|
pub fn execute(&self) -> anyhow::Result<SearchResult> {
|
|
|
|
let limit = self.limit;
|
|
|
|
let fst = self.index.words_fst(self.rtxn)?;
|
|
|
|
|
|
|
|
// Construct the DFAs related to the query words.
|
|
|
|
let derived_words = match self.query.as_deref().map(Self::generate_query_dfas) {
|
|
|
|
Some(dfas) if !dfas.is_empty() => Some(self.fetch_words_docids(&fst, dfas)?),
|
|
|
|
_otherwise => None,
|
|
|
|
};
|
|
|
|
|
|
|
|
// We create the original candidates with the facet conditions results.
|
2020-11-20 12:59:29 +01:00
|
|
|
let facet_candidates = match &self.facet_condition {
|
2020-11-21 13:09:49 +01:00
|
|
|
Some(condition) => Some(condition.evaluate(self.rtxn, self.index)?),
|
2020-11-20 10:54:41 +01:00
|
|
|
None => None,
|
|
|
|
};
|
|
|
|
|
2020-11-27 13:40:21 +01:00
|
|
|
let order_by_facet = {
|
|
|
|
let criteria = self.index.criteria(self.rtxn)?;
|
|
|
|
let result = criteria.into_iter().flat_map(|criterion| {
|
|
|
|
match criterion {
|
|
|
|
Criterion::Asc(fid) => Some((fid, Order::Asc)),
|
|
|
|
Criterion::Desc(fid) => Some((fid, Order::Desc)),
|
|
|
|
_ => None
|
|
|
|
}
|
|
|
|
}).next();
|
|
|
|
match result {
|
|
|
|
Some((fid, order)) => {
|
|
|
|
let faceted_fields = self.index.faceted_fields(self.rtxn)?;
|
|
|
|
let ftype = *faceted_fields.get(&fid).context("unknown field id")?;
|
|
|
|
Some((fid, ftype, order))
|
|
|
|
},
|
|
|
|
None => None,
|
|
|
|
}
|
|
|
|
};
|
|
|
|
|
2020-11-20 10:54:41 +01:00
|
|
|
debug!("facet candidates: {:?}", facet_candidates);
|
|
|
|
|
|
|
|
let (candidates, derived_words) = match (facet_candidates, derived_words) {
|
|
|
|
(Some(mut facet_candidates), Some(derived_words)) => {
|
|
|
|
let words_candidates = Self::compute_candidates(&derived_words);
|
|
|
|
facet_candidates.intersect_with(&words_candidates);
|
|
|
|
(facet_candidates, derived_words)
|
|
|
|
},
|
|
|
|
(None, Some(derived_words)) => {
|
|
|
|
(Self::compute_candidates(&derived_words), derived_words)
|
|
|
|
},
|
|
|
|
(Some(facet_candidates), None) => {
|
|
|
|
// If the query is not set or results in no DFAs but
|
|
|
|
// there is some facet conditions we return a placeholder.
|
2020-11-27 13:40:21 +01:00
|
|
|
let documents_ids = match order_by_facet {
|
|
|
|
Some((fid, ftype, order)) => self.facet_ordered(fid, ftype, order, facet_candidates, limit)?,
|
|
|
|
None => facet_candidates.iter().take(limit).collect(),
|
|
|
|
};
|
2020-11-20 10:54:41 +01:00
|
|
|
return Ok(SearchResult { documents_ids, ..Default::default() })
|
|
|
|
},
|
|
|
|
(None, None) => {
|
|
|
|
// If the query is not set or results in no DFAs we return a placeholder.
|
2020-11-27 13:40:21 +01:00
|
|
|
let documents_ids = self.index.documents_ids(self.rtxn)?;
|
|
|
|
let documents_ids = match order_by_facet {
|
|
|
|
Some((fid, ftype, order)) => self.facet_ordered(fid, ftype, order, documents_ids, limit)?,
|
|
|
|
None => documents_ids.iter().take(limit).collect(),
|
|
|
|
};
|
2020-11-20 10:54:41 +01:00
|
|
|
return Ok(SearchResult { documents_ids, ..Default::default() })
|
|
|
|
},
|
|
|
|
};
|
|
|
|
|
|
|
|
debug!("candidates: {:?}", candidates);
|
|
|
|
|
|
|
|
// The mana depth first search is a revised DFS that explore
|
|
|
|
// solutions in the order of their proximities.
|
|
|
|
let mut mdfs = Mdfs::new(self.index, self.rtxn, &derived_words, candidates);
|
|
|
|
let mut documents = Vec::new();
|
|
|
|
|
|
|
|
// We execute the Mdfs iterator until we find enough documents.
|
|
|
|
while documents.iter().map(RoaringBitmap::len).sum::<u64>() < limit as u64 {
|
|
|
|
match mdfs.next().transpose()? {
|
|
|
|
Some((proximity, answer)) => {
|
|
|
|
debug!("answer with a proximity of {}: {:?}", proximity, answer);
|
|
|
|
documents.push(answer);
|
|
|
|
},
|
|
|
|
None => break,
|
|
|
|
}
|
|
|
|
}
|
|
|
|
|
|
|
|
let found_words = derived_words.into_iter().flat_map(|(w, _)| w).map(|(w, _)| w).collect();
|
2020-11-27 14:52:53 +01:00
|
|
|
let documents_ids = match order_by_facet {
|
|
|
|
Some((fid, ftype, order)) => {
|
|
|
|
let mut ordered_documents = Vec::new();
|
|
|
|
for documents_ids in documents {
|
|
|
|
let docids = self.facet_ordered(fid, ftype, order, documents_ids, limit)?;
|
|
|
|
ordered_documents.push(docids);
|
|
|
|
if ordered_documents.iter().map(Vec::len).sum::<usize>() >= limit { break }
|
|
|
|
}
|
|
|
|
ordered_documents.into_iter().flatten().take(limit).collect()
|
|
|
|
},
|
|
|
|
None => documents.into_iter().flatten().take(limit).collect(),
|
|
|
|
};
|
|
|
|
|
2020-11-20 10:54:41 +01:00
|
|
|
Ok(SearchResult { found_words, documents_ids })
|
|
|
|
}
|
|
|
|
}
|
|
|
|
|
|
|
|
impl fmt::Debug for Search<'_> {
|
|
|
|
fn fmt(&self, f: &mut fmt::Formatter) -> fmt::Result {
|
2020-11-22 15:40:11 +01:00
|
|
|
let Search { query, facet_condition, offset, limit, rtxn: _, index: _ } = self;
|
2020-11-20 10:54:41 +01:00
|
|
|
f.debug_struct("Search")
|
2020-11-22 15:40:11 +01:00
|
|
|
.field("query", query)
|
|
|
|
.field("facet_condition", facet_condition)
|
|
|
|
.field("offset", offset)
|
|
|
|
.field("limit", limit)
|
2020-11-20 10:54:41 +01:00
|
|
|
.finish()
|
|
|
|
}
|
|
|
|
}
|
|
|
|
|
|
|
|
#[derive(Default)]
|
|
|
|
pub struct SearchResult {
|
|
|
|
pub found_words: HashSet<String>,
|
|
|
|
// TODO those documents ids should be associated with their criteria scores.
|
|
|
|
pub documents_ids: Vec<DocumentId>,
|
|
|
|
}
|