Introduce plane_sweep function in proximity criterion

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many 2021-03-03 15:41:09 +01:00 committed by Kerollmops
parent 636a9df177
commit ae47bb3594
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2 changed files with 188 additions and 2 deletions

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@ -5,7 +5,7 @@ use anyhow::bail;
use roaring::RoaringBitmap; use roaring::RoaringBitmap;
use crate::search::word_derivations; use crate::search::word_derivations;
use crate::Index; use crate::{DocumentId, Index};
use super::query_tree::{Operation, Query, QueryKind}; use super::query_tree::{Operation, Query, QueryKind};
use self::typo::Typo; use self::typo::Typo;
@ -66,6 +66,7 @@ pub trait Context {
fn word_prefix_pair_proximity_docids(&self, left: &str, right: &str, proximity: u8) -> heed::Result<Option<RoaringBitmap>>; fn word_prefix_pair_proximity_docids(&self, left: &str, right: &str, proximity: u8) -> heed::Result<Option<RoaringBitmap>>;
fn words_fst<'t>(&self) -> &'t fst::Set<Cow<[u8]>>; fn words_fst<'t>(&self) -> &'t fst::Set<Cow<[u8]>>;
fn in_prefix_cache(&self, word: &str) -> bool; fn in_prefix_cache(&self, word: &str) -> bool;
fn docid_word_positions(&self, docid: DocumentId, word: &str) -> heed::Result<Option<RoaringBitmap>>;
} }
pub struct CriteriaBuilder<'t> { pub struct CriteriaBuilder<'t> {
rtxn: &'t heed::RoTxn<'t>, rtxn: &'t heed::RoTxn<'t>,
@ -104,6 +105,11 @@ impl<'a> Context for CriteriaBuilder<'a> {
fn in_prefix_cache(&self, word: &str) -> bool { fn in_prefix_cache(&self, word: &str) -> bool {
self.words_prefixes_fst.contains(word) self.words_prefixes_fst.contains(word)
} }
fn docid_word_positions(&self, docid: DocumentId, word: &str) -> heed::Result<Option<RoaringBitmap>> {
let key = (docid, word);
self.index.docid_word_positions.get(self.rtxn, &key)
}
} }
impl<'t> CriteriaBuilder<'t> { impl<'t> CriteriaBuilder<'t> {
@ -368,6 +374,10 @@ pub mod test {
fn in_prefix_cache(&self, word: &str) -> bool { fn in_prefix_cache(&self, word: &str) -> bool {
self.word_prefix_docids.contains_key(&word.to_string()) self.word_prefix_docids.contains_key(&word.to_string())
} }
fn docid_word_positions(&self, _docid: DocumentId, _word: &str) -> heed::Result<Option<RoaringBitmap>> {
todo!()
}
} }
impl<'a> Default for TestContext<'a> { impl<'a> Default for TestContext<'a> {

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@ -1,9 +1,10 @@
use std::collections::HashMap; use std::collections::{BTreeMap, HashMap};
use std::mem::take; use std::mem::take;
use roaring::RoaringBitmap; use roaring::RoaringBitmap;
use log::debug; use log::debug;
use crate::{DocumentId, Position, search::{query_tree::QueryKind, word_derivations}};
use crate::search::query_tree::{maximum_proximity, Operation, Query}; use crate::search::query_tree::{maximum_proximity, Operation, Query};
use super::{Candidates, Criterion, CriterionResult, Context, query_docids, query_pair_proximity_docids}; use super::{Candidates, Criterion, CriterionResult, Context, query_docids, query_pair_proximity_docids};
@ -289,3 +290,178 @@ fn resolve_candidates<'t>(
} }
Ok(candidates) Ok(candidates)
} }
fn resolve_plane_sweep_candidates<'t>(
ctx: &'t dyn Context,
query_tree: &Operation,
allowed_candidates: &RoaringBitmap,
) -> anyhow::Result<BTreeMap<u8, RoaringBitmap>>
{
/// FIXME may be buggy with query like "new new york"
fn plane_sweep<'t>(
ctx: &'t dyn Context,
operations: &[Operation],
docid: DocumentId,
consecutive: bool,
) -> anyhow::Result<Vec<(Position, u8, Position)>> {
fn compute_groups_proximity(groups: &Vec<(usize, (Position, u8, Position))>, consecutive: bool) -> Option<(Position, u8, Position)> {
// take the inner proximity of the first group as initial
let mut proximity = groups.first()?.1.1;
let left_most_pos = groups.first()?.1.0;
let right_most_pos = groups.last()?.1.2;
for pair in groups.windows(2) {
if let [(i1, (_, _, rpos1)), (i2, (lpos2, prox2, _))] = pair {
// if a pair overlap, meaning that they share at least a word, we return None
if rpos1 >= lpos2 { return None }
// if groups are in the good order (query order) we remove 1 to the proximity
// the proximity is clamped to 7
let pair_proximity = if i1 < i2 {
(*lpos2 - *rpos1 - 1).min(7)
} else {
(*lpos2 - *rpos1).min(7)
};
proximity += pair_proximity as u8 + prox2;
}
}
// if groups should be consecutives, we will only accept groups with a proximity of 0
if !consecutive || proximity == 0 {
Some((left_most_pos, proximity, right_most_pos))
} else { None }
}
let groups_len = operations.len();
let mut groups_positions = Vec::with_capacity(groups_len);
for operation in operations {
let positions = resolve_operation(ctx, operation, docid)?;
groups_positions.push(positions.into_iter());
}
// Pop top elements of each list.
let mut current = Vec::with_capacity(groups_len);
for (i, positions) in groups_positions.iter_mut().enumerate() {
match positions.next() {
Some(p) => current.push((i, p)),
// if a group return None, it means that the document does not contain all the words,
// we return an empty result.
None => return Ok(Vec::new()),
}
}
// Sort k elements by their positions.
current.sort_unstable_by_key(|(_, p)| *p);
// Find leftmost and rightmost group and their positions.
let mut leftmost = *current.first().unwrap();
let mut rightmost = *current.last().unwrap();
let mut output = Vec::new();
loop {
// Find the position p of the next elements of a list of the leftmost group.
// If the list is empty, break the loop.
let p = groups_positions[leftmost.0].next().map(|p| (leftmost.0, p));
// let q be the position q of second group of the interval.
let q = current[1];
let mut leftmost_index = 0;
// If p > r, then the interval [l, r] is minimal and
// we insert it into the heap according to its size.
if p.map_or(true, |p| p.1 > rightmost.1) {
leftmost_index = current[0].0;
if let Some(group) = compute_groups_proximity(&current, consecutive) {
output.push(group);
}
}
// TODO not sure about breaking here or when the p list is found empty.
let p = match p {
Some(p) => p,
None => break,
};
// Remove the leftmost group P in the interval,
// and pop the same group from a list.
current[leftmost_index] = p;
if p.1 > rightmost.1 {
// if [l, r] is minimal, let r = p and l = q.
rightmost = p;
leftmost = q;
} else {
// Ohterwise, let l = min{p,q}.
leftmost = if p.1 < q.1 { p } else { q };
}
// Then update the interval and order of groups_positions in the interval.
current.sort_unstable_by_key(|(_, p)| *p);
}
// Sort the list according to the size and the positions.
output.sort_unstable();
Ok(output)
}
fn resolve_operation<'t>(
ctx: &'t dyn Context,
query_tree: &Operation,
docid: DocumentId,
) -> anyhow::Result<Vec<(Position, u8, Position)>> {
use Operation::{And, Consecutive, Or};
match query_tree {
And(ops) => plane_sweep(ctx, ops, docid, false),
Consecutive(ops) => plane_sweep(ctx, ops, docid, true),
Or(_, ops) => {
let mut result = Vec::new();
for op in ops {
result.extend(resolve_operation(ctx, op, docid)?)
}
result.sort_unstable();
Ok(result)
},
Operation::Query(Query {prefix, kind}) => {
let fst = ctx.words_fst();
let words = match kind {
QueryKind::Exact { word, .. } => {
if *prefix {
word_derivations(word, true, 0, fst)?
} else {
vec![(word.to_string(), 0)]
}
},
QueryKind::Tolerant { typo, word } => {
word_derivations(word, *prefix, *typo, fst)?
}
};
let mut result = Vec::new();
for (word, _) in words {
if let Some(positions) = ctx.docid_word_positions(docid, &word)? {
let iter = positions.iter().map(|p| (p, 0, p));
result.extend(iter);
}
}
result.sort_unstable();
Ok(result)
}
}
}
let mut candidates = BTreeMap::new();
for docid in allowed_candidates {
let positions = resolve_operation(ctx, query_tree, docid)?;
let best_proximity = positions.into_iter().min_by_key(|(_, proximity, _)| *proximity);
let best_proximity = best_proximity.map(|(_, proximity, _)| proximity).unwrap_or(7);
candidates.entry(best_proximity).or_insert_with(RoaringBitmap::new).insert(docid);
}
Ok(candidates)
}