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https://github.com/meilisearch/MeiliSearch
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Introduce the Search builder struct
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@ -1,8 +1,9 @@
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use std::cmp;
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use std::time::Instant;
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use log::debug;
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use crate::iter_shortest_paths::astar_bag;
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use log::debug;
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use roaring::RoaringBitmap;
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const ONE_ATTRIBUTE: u32 = 1000;
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const MAX_DISTANCE: u32 = 8;
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@ -47,21 +48,21 @@ impl Node {
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// TODO we must skip the successors that have already been seen
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// TODO we must skip the successors that doesn't return any documents
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// this way we are able to skip entire paths
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fn successors(&self, positions: &[Vec<u32>], best_proximity: u32) -> Vec<(Node, u32)> {
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fn successors(&self, positions: &[RoaringBitmap], best_proximity: u32) -> Vec<(Node, u32)> {
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match self {
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Node::Uninit => {
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positions[0].iter().map(|p| {
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(Node::Init { layer: 0, position: *p, acc_proximity: 0, parent_position: 0 }, 0)
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positions[0].iter().map(|position| {
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(Node::Init { layer: 0, position, acc_proximity: 0, parent_position: 0 }, 0)
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}).collect()
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},
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// We reached the highest layer
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n @ Node::Init { .. } if n.is_complete(positions) => vec![],
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Node::Init { layer, position, acc_proximity, .. } => {
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positions[layer + 1].iter().filter_map(|p| {
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let proximity = positions_proximity(*position, *p);
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let proximity = positions_proximity(*position, p);
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let node = Node::Init {
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layer: layer + 1,
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position: *p,
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position: p,
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acc_proximity: acc_proximity + proximity,
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parent_position: *position,
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};
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@ -76,7 +77,7 @@ impl Node {
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}
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}
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fn is_complete(&self, positions: &[Vec<u32>]) -> bool {
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fn is_complete(&self, positions: &[RoaringBitmap]) -> bool {
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match self {
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Node::Uninit => false,
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Node::Init { layer, .. } => *layer == positions.len() - 1,
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@ -121,19 +122,19 @@ impl Node {
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}
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pub struct BestProximity {
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positions: Vec<Vec<u32>>,
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positions: Vec<RoaringBitmap>,
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best_proximity: u32,
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}
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impl BestProximity {
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pub fn new(positions: Vec<Vec<u32>>) -> BestProximity {
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pub fn new(positions: Vec<RoaringBitmap>) -> BestProximity {
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let best_proximity = (positions.len() as u32).saturating_sub(1);
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BestProximity { positions, best_proximity }
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}
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}
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impl BestProximity {
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pub fn next<F>(&mut self, mut contains_documents: F) -> Option<(u32, Vec<Vec<u32>>)>
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pub fn next<F>(&mut self, mut contains_documents: F) -> Option<(u32, Vec<RoaringBitmap>)>
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where F: FnMut((usize, u32), (usize, u32)) -> bool,
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{
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let before = Instant::now();
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@ -176,6 +177,7 @@ impl BestProximity {
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#[cfg(test)]
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mod tests {
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use super::*;
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use std::iter::FromIterator;
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fn sort<T: Ord>(mut val: (u32, Vec<T>)) -> (u32, Vec<T>) {
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val.1.sort_unstable();
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@ -185,37 +187,37 @@ mod tests {
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#[test]
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fn same_attribute() {
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let positions = vec![
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vec![0, 2, 3, 4 ],
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vec![ 1, ],
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vec![ 3, 6],
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RoaringBitmap::from_iter(vec![0, 2, 3, 4 ]),
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RoaringBitmap::from_iter(vec![ 1, ]),
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RoaringBitmap::from_iter(vec![ 3, 6]),
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];
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let mut iter = BestProximity::new(positions);
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let f = |_, _| true;
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assert_eq!(iter.next(f), Some((1+2, vec![vec![0, 1, 3]]))); // 3
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assert_eq!(iter.next(f), Some((2+2, vec![vec![2, 1, 3]]))); // 4
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assert_eq!(iter.next(f), Some((3+2, vec![vec![3, 1, 3]]))); // 5
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assert_eq!(iter.next(f).map(sort), Some((1+5, vec![vec![0, 1, 6], vec![4, 1, 3]]))); // 6
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assert_eq!(iter.next(f), Some((2+5, vec![vec![2, 1, 6]]))); // 7
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assert_eq!(iter.next(f), Some((3+5, vec![vec![3, 1, 6]]))); // 8
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assert_eq!(iter.next(f), Some((4+5, vec![vec![4, 1, 6]]))); // 9
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assert_eq!(iter.next(f), Some((1+2, vec![RoaringBitmap::from_iter(vec![0, 1, 3])]))); // 3
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assert_eq!(iter.next(f), Some((2+2, vec![RoaringBitmap::from_iter(vec![2, 1, 3])]))); // 4
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assert_eq!(iter.next(f), Some((3+2, vec![RoaringBitmap::from_iter(vec![3, 1, 3])]))); // 5
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assert_eq!(iter.next(f), Some((1+5, vec![RoaringBitmap::from_iter(vec![0, 1, 6]), RoaringBitmap::from_iter(vec![4, 1, 3])]))); // 6
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assert_eq!(iter.next(f), Some((2+5, vec![RoaringBitmap::from_iter(vec![2, 1, 6])]))); // 7
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assert_eq!(iter.next(f), Some((3+5, vec![RoaringBitmap::from_iter(vec![3, 1, 6])]))); // 8
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assert_eq!(iter.next(f), Some((4+5, vec![RoaringBitmap::from_iter(vec![4, 1, 6])]))); // 9
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assert_eq!(iter.next(f), None);
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}
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#[test]
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fn different_attributes() {
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let positions = vec![
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vec![0, 2, 1000, 1001, 2000 ],
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vec![ 1, 1000, 2001 ],
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vec![ 3, 6, 2002, 3000],
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RoaringBitmap::from_iter(vec![0, 2, 1000, 1001, 2000 ]),
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RoaringBitmap::from_iter(vec![ 1, 1000, 2001 ]),
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RoaringBitmap::from_iter(vec![ 3, 6, 2002, 3000]),
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];
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let mut iter = BestProximity::new(positions);
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let f = |_, _| true;
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assert_eq!(iter.next(f), Some((1+1, vec![vec![2000, 2001, 2002]]))); // 2
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assert_eq!(iter.next(f), Some((1+2, vec![vec![0, 1, 3]]))); // 3
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assert_eq!(iter.next(f), Some((2+2, vec![vec![2, 1, 3]]))); // 4
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assert_eq!(iter.next(f), Some((1+5, vec![vec![0, 1, 6]]))); // 6
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assert_eq!(iter.next(f), Some((1+1, vec![RoaringBitmap::from_iter(vec![2000, 2001, 2002])]))); // 2
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assert_eq!(iter.next(f), Some((1+2, vec![RoaringBitmap::from_iter(vec![0, 1, 3])]))); // 3
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assert_eq!(iter.next(f), Some((2+2, vec![RoaringBitmap::from_iter(vec![2, 1, 3])]))); // 4
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assert_eq!(iter.next(f), Some((1+5, vec![RoaringBitmap::from_iter(vec![0, 1, 6])]))); // 6
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// We ignore others here...
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}
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@ -62,12 +62,13 @@ fn main() -> anyhow::Result<()> {
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let before = Instant::now();
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let query = result?;
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let (_, documents_ids) = index.search(&rtxn, &query)?;
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let result = index.search(&rtxn).query(query).execute().unwrap();
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let headers = match index.headers(&rtxn)? {
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Some(headers) => headers,
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None => return Ok(()),
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};
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let documents = index.documents(documents_ids.iter().cloned())?;
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let documents = index.documents(result.documents_ids.iter().cloned())?;
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let mut stdout = io::stdout();
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stdout.write_all(&headers)?;
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@ -76,7 +77,7 @@ fn main() -> anyhow::Result<()> {
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stdout.write_all(&content)?;
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}
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debug!("Took {:.02?} to find {} documents", before.elapsed(), documents_ids.len());
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debug!("Took {:.02?} to find {} documents", before.elapsed(), result.documents_ids.len());
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}
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Ok(())
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@ -13,7 +13,7 @@ use slice_group_by::StrGroupBy;
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use structopt::StructOpt;
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use warp::{Filter, http::Response};
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use milli::Index;
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use milli::{Index, SearchResult};
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#[cfg(target_os = "linux")]
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#[global_allocator]
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@ -183,7 +183,10 @@ async fn main() -> anyhow::Result<()> {
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let before_search = Instant::now();
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let rtxn = env_cloned.read_txn().unwrap();
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let (words, documents_ids) = index.search(&rtxn, &query.query).unwrap();
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let SearchResult { found_words, documents_ids } = index.search(&rtxn)
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.query(query.query)
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.execute()
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.unwrap();
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let mut body = Vec::new();
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if let Some(headers) = index.headers(&rtxn).unwrap() {
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@ -196,7 +199,7 @@ async fn main() -> anyhow::Result<()> {
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let content = if disable_highlighting {
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Cow::from(content)
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} else {
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Cow::from(highlight_string(content, &words))
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Cow::from(highlight_string(content, &found_words))
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};
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body.extend_from_slice(content.as_bytes());
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273
src/lib.rs
273
src/lib.rs
@ -3,38 +3,27 @@ mod criterion;
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mod heed_codec;
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mod iter_shortest_paths;
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mod query_tokens;
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mod search;
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mod transitive_arc;
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use std::collections::{HashSet, HashMap};
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use std::collections::HashMap;
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use std::fs::{File, OpenOptions};
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use std::hash::BuildHasherDefault;
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use std::path::{Path, PathBuf};
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use std::sync::Arc;
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use std::time::Instant;
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use anyhow::Context;
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use cow_utils::CowUtils;
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use fst::{IntoStreamer, Streamer};
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use fxhash::{FxHasher32, FxHasher64};
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use heed::types::*;
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use heed::{PolyDatabase, Database};
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use levenshtein_automata::LevenshteinAutomatonBuilder as LevBuilder;
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use log::debug;
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use memmap::Mmap;
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use once_cell::sync::Lazy;
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use oxidized_mtbl as omtbl;
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use roaring::RoaringBitmap;
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use self::best_proximity::BestProximity;
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pub use self::search::{Search, SearchResult};
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pub use self::criterion::{Criterion, default_criteria};
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use self::heed_codec::RoaringBitmapCodec;
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use self::query_tokens::{QueryTokens, QueryToken};
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use self::transitive_arc::TransitiveArc;
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// Building these factories is not free.
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static LEVDIST0: Lazy<LevBuilder> = Lazy::new(|| LevBuilder::new(0, true));
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static LEVDIST1: Lazy<LevBuilder> = Lazy::new(|| LevBuilder::new(1, true));
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static LEVDIST2: Lazy<LevBuilder> = Lazy::new(|| LevBuilder::new(2, true));
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pub type FastMap4<K, V> = HashMap<K, V, BuildHasherDefault<FxHasher32>>;
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pub type FastMap8<K, V> = HashMap<K, V, BuildHasherDefault<FxHasher64>>;
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pub type SmallString32 = smallstr::SmallString<[u8; 32]>;
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@ -138,257 +127,7 @@ impl Index {
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self.documents.metadata().count_entries as usize
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}
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pub fn search(&self, rtxn: &heed::RoTxn, query: &str) -> anyhow::Result<(HashSet<String>, Vec<DocumentId>)> {
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let fst = match self.fst(rtxn)? {
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Some(fst) => fst,
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None => return Ok(Default::default()),
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};
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let (lev0, lev1, lev2) = (&LEVDIST0, &LEVDIST1, &LEVDIST2);
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let words: Vec<_> = QueryTokens::new(query).collect();
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let ends_with_whitespace = query.chars().last().map_or(false, char::is_whitespace);
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let number_of_words = words.len();
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let dfas = words.into_iter().enumerate().map(|(i, word)| {
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let (word, quoted) = match word {
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QueryToken::Free(word) => (word.cow_to_lowercase(), word.len() <= 3),
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QueryToken::Quoted(word) => (word.cow_to_lowercase(), true),
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};
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let is_last = i + 1 == number_of_words;
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let is_prefix = is_last && !ends_with_whitespace && !quoted;
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let lev = match word.len() {
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0..=4 => if quoted { lev0 } else { lev0 },
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5..=8 => if quoted { lev0 } else { lev1 },
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_ => if quoted { lev0 } else { lev2 },
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};
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let dfa = if is_prefix {
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lev.build_prefix_dfa(&word)
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} else {
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lev.build_dfa(&word)
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};
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(word, is_prefix, dfa)
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});
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let mut words = Vec::new();
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let mut positions = Vec::new();
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let before = Instant::now();
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for (word, _is_prefix, dfa) in dfas {
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let before = Instant::now();
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let mut count = 0;
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let mut union_positions = RoaringBitmap::default();
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let mut derived_words = Vec::new();
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let mut stream = fst.search_with_state(&dfa).into_stream();
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while let Some((word, state)) = stream.next() {
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let word = std::str::from_utf8(word)?;
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let distance = dfa.distance(state);
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debug!("found {:?} at distance of {}", word, distance.to_u8());
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if let Some(positions) = self.word_positions.get(rtxn, word)? {
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union_positions.union_with(&positions);
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derived_words.push((word.as_bytes().to_vec(), distance.to_u8(), positions));
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count += 1;
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}
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}
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debug!("{} words for {:?} we have found positions {:?} in {:.02?}",
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count, word, union_positions, before.elapsed());
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words.push(derived_words);
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positions.push(union_positions.iter().collect());
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}
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// We compute the docids candidates for these words (and derived words).
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// We do a union between all the docids of each of the words and derived words,
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// we got N unions (where N is the number of query words), we then intersect them.
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// TODO we must store the words documents ids to avoid these unions.
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let mut candidates = RoaringBitmap::new();
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let number_of_attributes = self.number_of_attributes(rtxn)?.map_or(0, |n| n as u32);
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for (i, derived_words) in words.iter().enumerate() {
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let mut union_docids = RoaringBitmap::new();
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for (word, _distance, _positions) in derived_words {
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for attr in 0..number_of_attributes {
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let mut key = word.to_vec();
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key.extend_from_slice(&attr.to_be_bytes());
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if let Some(right) = self.word_attribute_docids.get(rtxn, &key)? {
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union_docids.union_with(&right);
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}
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}
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}
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if i == 0 {
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candidates = union_docids;
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} else {
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candidates.intersect_with(&union_docids);
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}
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}
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debug!("The candidates are {:?}", candidates);
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debug!("Retrieving words positions took {:.02?}", before.elapsed());
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// Returns the union of the same position for all the derived words.
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let unions_word_pos = |word: usize, pos: u32| {
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let mut union_docids = RoaringBitmap::new();
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for (word, _distance, attrs) in &words[word] {
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if attrs.contains(pos) {
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let mut key = word.clone();
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key.extend_from_slice(&pos.to_be_bytes());
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if let Some(right) = self.word_position_docids.get(rtxn, &key).unwrap() {
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union_docids.union_with(&right);
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}
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}
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}
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union_docids
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};
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// Returns the union of the same attribute for all the derived words.
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let unions_word_attr = |word: usize, attr: u32| {
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let mut union_docids = RoaringBitmap::new();
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for (word, _distance, _) in &words[word] {
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let mut key = word.clone();
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key.extend_from_slice(&attr.to_be_bytes());
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if let Some(right) = self.word_attribute_docids.get(rtxn, &key).unwrap() {
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union_docids.union_with(&right);
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}
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}
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union_docids
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};
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let mut union_cache = HashMap::new();
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let mut intersect_cache = HashMap::new();
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let mut attribute_union_cache = HashMap::new();
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let mut attribute_intersect_cache = HashMap::new();
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// Returns `true` if there is documents in common between the two words and positions given.
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let mut contains_documents = |(lword, lpos), (rword, rpos), union_cache: &mut HashMap<_, _>, candidates: &RoaringBitmap| {
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if lpos == rpos { return false }
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let (lattr, _) = best_proximity::extract_position(lpos);
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let (rattr, _) = best_proximity::extract_position(rpos);
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if lattr == rattr {
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// We retrieve or compute the intersection between the two given words and positions.
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*intersect_cache.entry(((lword, lpos), (rword, rpos))).or_insert_with(|| {
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// We retrieve or compute the unions for the two words and positions.
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union_cache.entry((lword, lpos)).or_insert_with(|| unions_word_pos(lword, lpos));
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union_cache.entry((rword, rpos)).or_insert_with(|| unions_word_pos(rword, rpos));
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// TODO is there a way to avoid this double gets?
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let lunion_docids = union_cache.get(&(lword, lpos)).unwrap();
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let runion_docids = union_cache.get(&(rword, rpos)).unwrap();
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// We first check that the docids of these unions are part of the candidates.
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if lunion_docids.is_disjoint(candidates) { return false }
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if runion_docids.is_disjoint(candidates) { return false }
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!lunion_docids.is_disjoint(&runion_docids)
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})
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} else {
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*attribute_intersect_cache.entry(((lword, lattr), (rword, rattr))).or_insert_with(|| {
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// We retrieve or compute the unions for the two words and positions.
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attribute_union_cache.entry((lword, lattr)).or_insert_with(|| unions_word_attr(lword, lattr));
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attribute_union_cache.entry((rword, rattr)).or_insert_with(|| unions_word_attr(rword, rattr));
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// TODO is there a way to avoid this double gets?
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let lunion_docids = attribute_union_cache.get(&(lword, lattr)).unwrap();
|
||||
let runion_docids = attribute_union_cache.get(&(rword, rattr)).unwrap();
|
||||
|
||||
// We first check that the docids of these unions are part of the candidates.
|
||||
if lunion_docids.is_disjoint(candidates) { return false }
|
||||
if runion_docids.is_disjoint(candidates) { return false }
|
||||
|
||||
!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, &candidates)) {
|
||||
positions.sort_unstable();
|
||||
|
||||
let same_prox_before = Instant::now();
|
||||
let mut same_proximity_union = RoaringBitmap::default();
|
||||
|
||||
for positions in positions {
|
||||
let before = Instant::now();
|
||||
|
||||
// Precompute the potentially missing unions
|
||||
positions.iter().enumerate().for_each(|(word, pos)| {
|
||||
union_cache.entry((word, *pos)).or_insert_with(|| unions_word_pos(word, *pos));
|
||||
});
|
||||
|
||||
// Retrieve the unions along with the popularity of it.
|
||||
let mut to_intersect: Vec<_> = positions.iter()
|
||||
.enumerate()
|
||||
.map(|(word, pos)| {
|
||||
let docids = union_cache.get(&(word, *pos)).unwrap();
|
||||
(docids.len(), docids)
|
||||
})
|
||||
.collect();
|
||||
|
||||
// Sort the unions by popuarity to help reduce
|
||||
// the number of documents as soon as possible.
|
||||
to_intersect.sort_unstable_by_key(|(l, _)| *l);
|
||||
let elapsed_retrieving = before.elapsed();
|
||||
|
||||
let before_intersect = Instant::now();
|
||||
let intersect_docids: Option<RoaringBitmap> = to_intersect.into_iter()
|
||||
.fold(None, |acc, (_, union_docids)| {
|
||||
match acc {
|
||||
Some(mut left) => {
|
||||
left.intersect_with(&union_docids);
|
||||
Some(left)
|
||||
},
|
||||
None => Some(union_docids.clone()),
|
||||
}
|
||||
});
|
||||
|
||||
debug!("retrieving words took {:.02?} and took {:.02?} to intersect",
|
||||
elapsed_retrieving, before_intersect.elapsed());
|
||||
|
||||
debug!("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::<u64>() + same_proximity_union.len() >= 20 {
|
||||
debug!("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 candidates list.
|
||||
candidates.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());
|
||||
|
||||
debug!("documents: {:?}", documents);
|
||||
debug!("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::<u64>() >= 20 {
|
||||
break;
|
||||
}
|
||||
}
|
||||
|
||||
debug!("{} final candidates", documents.iter().map(RoaringBitmap::len).sum::<u64>());
|
||||
let words = words.into_iter().flatten().map(|(w, _distance, _)| String::from_utf8(w).unwrap()).collect();
|
||||
let documents = documents.iter().flatten().take(20).collect();
|
||||
|
||||
Ok((words, documents))
|
||||
pub fn search<'a>(&'a self, rtxn: &'a heed::RoTxn) -> Search<'a> {
|
||||
Search::new(rtxn, self)
|
||||
}
|
||||
}
|
||||
|
361
src/search.rs
Normal file
361
src/search.rs
Normal file
@ -0,0 +1,361 @@
|
||||
use std::collections::{HashMap, HashSet};
|
||||
|
||||
use fst::{IntoStreamer, Streamer};
|
||||
use levenshtein_automata::DFA;
|
||||
use levenshtein_automata::LevenshteinAutomatonBuilder as LevBuilder;
|
||||
use once_cell::sync::Lazy;
|
||||
use roaring::RoaringBitmap;
|
||||
|
||||
use crate::query_tokens::{QueryTokens, QueryToken};
|
||||
use crate::{Index, DocumentId, Position, Attribute};
|
||||
use crate::best_proximity::{self, BestProximity};
|
||||
|
||||
// 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));
|
||||
|
||||
pub struct Search<'a> {
|
||||
query: Option<String>,
|
||||
offset: usize,
|
||||
limit: usize,
|
||||
rtxn: &'a heed::RoTxn,
|
||||
index: &'a Index,
|
||||
}
|
||||
|
||||
impl<'a> Search<'a> {
|
||||
pub fn new(rtxn: &'a heed::RoTxn, index: &'a Index) -> Search<'a> {
|
||||
Search {
|
||||
query: 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
|
||||
}
|
||||
|
||||
/// 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
|
||||
/// positions and the unions of those positions where the words found appears in the documents.
|
||||
fn fetch_words_positions(
|
||||
rtxn: &heed::RoTxn,
|
||||
index: &Index,
|
||||
fst: &fst::Set<&[u8]>,
|
||||
dfas: Vec<(String, bool, DFA)>,
|
||||
) -> anyhow::Result<(Vec<Vec<(String, u8, RoaringBitmap)>>, Vec<RoaringBitmap>)>
|
||||
{
|
||||
// A Vec storing all the derived words from the original query words, associated
|
||||
// with the distance from the original word and the positions it appears at.
|
||||
// The index the derived words appears in the Vec corresponds to the original query
|
||||
// word position.
|
||||
let mut derived_words = Vec::<Vec::<(String, u8, RoaringBitmap)>>::with_capacity(dfas.len());
|
||||
// A Vec storing the unions of all of each of the derived words positions. The index
|
||||
// the union appears in the Vec corresponds to the original query word position.
|
||||
let mut union_positions = Vec::<RoaringBitmap>::with_capacity(dfas.len());
|
||||
|
||||
for (_word, _is_prefix, dfa) in dfas {
|
||||
|
||||
let mut acc_derived_words = Vec::new();
|
||||
let mut acc_union_positions = 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 positions = index.word_positions.get(rtxn, word)?.unwrap();
|
||||
let distance = dfa.distance(state);
|
||||
acc_union_positions.union_with(&positions);
|
||||
acc_derived_words.push((word.to_string(), distance.to_u8(), positions));
|
||||
}
|
||||
derived_words.push(acc_derived_words);
|
||||
union_positions.push(acc_union_positions);
|
||||
}
|
||||
|
||||
Ok((derived_words, union_positions))
|
||||
}
|
||||
|
||||
/// Returns the set of docids that contains all of the query words.
|
||||
fn compute_candidates(
|
||||
rtxn: &heed::RoTxn,
|
||||
index: &Index,
|
||||
derived_words: &[Vec<(String, u8, RoaringBitmap)>],
|
||||
) -> anyhow::Result<RoaringBitmap>
|
||||
{
|
||||
// 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.
|
||||
// TODO we must store the words documents ids to avoid these unions.
|
||||
let mut candidates = RoaringBitmap::new();
|
||||
let number_of_attributes = index.number_of_attributes(rtxn)?.map_or(0, |n| n as u32);
|
||||
|
||||
for (i, derived_words) in derived_words.iter().enumerate() {
|
||||
|
||||
let mut union_docids = RoaringBitmap::new();
|
||||
for (word, _distance, _positions) in derived_words {
|
||||
for attr in 0..number_of_attributes {
|
||||
|
||||
let mut key = word.clone().into_bytes();
|
||||
key.extend_from_slice(&attr.to_be_bytes());
|
||||
if let Some(docids) = index.word_attribute_docids.get(rtxn, &key)? {
|
||||
union_docids.union_with(&docids);
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
if i == 0 {
|
||||
candidates = union_docids;
|
||||
} else {
|
||||
candidates.intersect_with(&union_docids);
|
||||
}
|
||||
}
|
||||
|
||||
Ok(candidates)
|
||||
}
|
||||
|
||||
/// Returns the union of the same position for all the given words.
|
||||
fn union_word_position(
|
||||
rtxn: &heed::RoTxn,
|
||||
index: &Index,
|
||||
words: &[(String, u8, RoaringBitmap)],
|
||||
position: Position,
|
||||
) -> anyhow::Result<RoaringBitmap>
|
||||
{
|
||||
let mut union_docids = RoaringBitmap::new();
|
||||
for (word, _distance, positions) in words {
|
||||
if positions.contains(position) {
|
||||
let mut key = word.clone().into_bytes();
|
||||
key.extend_from_slice(&position.to_be_bytes());
|
||||
if let Some(docids) = index.word_position_docids.get(rtxn, &key)? {
|
||||
union_docids.union_with(&docids);
|
||||
}
|
||||
}
|
||||
}
|
||||
Ok(union_docids)
|
||||
}
|
||||
|
||||
/// Returns the union of the same attribute for all the given words.
|
||||
fn union_word_attribute(
|
||||
rtxn: &heed::RoTxn,
|
||||
index: &Index,
|
||||
words: &[(String, u8, RoaringBitmap)],
|
||||
attribute: Attribute,
|
||||
) -> anyhow::Result<RoaringBitmap>
|
||||
{
|
||||
let mut union_docids = RoaringBitmap::new();
|
||||
for (word, _distance, _positions) in words {
|
||||
let mut key = word.clone().into_bytes();
|
||||
key.extend_from_slice(&attribute.to_be_bytes());
|
||||
if let Some(docids) = index.word_attribute_docids.get(rtxn, &key)? {
|
||||
union_docids.union_with(&docids);
|
||||
}
|
||||
}
|
||||
Ok(union_docids)
|
||||
}
|
||||
|
||||
pub fn execute(&self) -> anyhow::Result<SearchResult> {
|
||||
let rtxn = self.rtxn;
|
||||
let index = self.index;
|
||||
|
||||
let fst = match index.fst(rtxn)? {
|
||||
Some(fst) => fst,
|
||||
None => return Ok(Default::default()),
|
||||
};
|
||||
|
||||
// Construct the DFAs related to the query words.
|
||||
// TODO do a placeholder search when query string isn't present.
|
||||
let dfas = match &self.query {
|
||||
Some(q) => Self::generate_query_dfas(q),
|
||||
None => return Ok(Default::default()),
|
||||
};
|
||||
|
||||
let (derived_words, union_positions) = Self::fetch_words_positions(rtxn, index, &fst, dfas)?;
|
||||
let mut candidates = Self::compute_candidates(rtxn, index, &derived_words)?;
|
||||
|
||||
let mut union_cache = HashMap::new();
|
||||
let mut intersect_cache = HashMap::new();
|
||||
|
||||
let mut attribute_union_cache = HashMap::new();
|
||||
let mut attribute_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<_, _>, candidates: &RoaringBitmap| {
|
||||
if lpos == rpos { return false }
|
||||
|
||||
let (lattr, _) = best_proximity::extract_position(lpos);
|
||||
let (rattr, _) = best_proximity::extract_position(rpos);
|
||||
|
||||
if lattr == rattr {
|
||||
// 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(|| {
|
||||
let words: &Vec<_> = &derived_words[lword];
|
||||
Self::union_word_position(rtxn, index, words, lpos).unwrap()
|
||||
});
|
||||
union_cache.entry((rword, rpos)).or_insert_with(|| {
|
||||
let words: &Vec<_> = &derived_words[rword];
|
||||
Self::union_word_position(rtxn, index, words, rpos).unwrap()
|
||||
});
|
||||
|
||||
// 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();
|
||||
|
||||
// We first check that the docids of these unions are part of the candidates.
|
||||
if lunion_docids.is_disjoint(candidates) { return false }
|
||||
if runion_docids.is_disjoint(candidates) { return false }
|
||||
|
||||
!lunion_docids.is_disjoint(&runion_docids)
|
||||
})
|
||||
} else {
|
||||
*attribute_intersect_cache.entry(((lword, lattr), (rword, rattr))).or_insert_with(|| {
|
||||
// We retrieve or compute the unions for the two words and positions.
|
||||
attribute_union_cache.entry((lword, lattr)).or_insert_with(|| {
|
||||
let words: &Vec<_> = &derived_words[lword];
|
||||
Self::union_word_attribute(rtxn, index, words, lattr).unwrap()
|
||||
});
|
||||
attribute_union_cache.entry((rword, rattr)).or_insert_with(|| {
|
||||
let words: &Vec<_> = &derived_words[rword];
|
||||
Self::union_word_attribute(rtxn, index, words, rattr).unwrap()
|
||||
});
|
||||
|
||||
// TODO is there a way to avoid this double gets?
|
||||
let lunion_docids = attribute_union_cache.get(&(lword, lattr)).unwrap();
|
||||
let runion_docids = attribute_union_cache.get(&(rword, rattr)).unwrap();
|
||||
|
||||
// We first check that the docids of these unions are part of the candidates.
|
||||
if lunion_docids.is_disjoint(candidates) { return false }
|
||||
if runion_docids.is_disjoint(candidates) { return false }
|
||||
|
||||
!lunion_docids.is_disjoint(&runion_docids)
|
||||
})
|
||||
}
|
||||
};
|
||||
|
||||
let mut documents = Vec::new();
|
||||
let mut iter = BestProximity::new(union_positions);
|
||||
while let Some((_proximity, mut positions)) = iter.next(|l, r| contains_documents(l, r, &mut union_cache, &candidates)) {
|
||||
positions.sort_unstable_by(|a, b| a.iter().cmp(b.iter()));
|
||||
|
||||
let mut same_proximity_union = RoaringBitmap::default();
|
||||
for positions in positions {
|
||||
|
||||
// Precompute the potentially missing unions
|
||||
positions.iter().enumerate().for_each(|(word, pos)| {
|
||||
union_cache.entry((word, pos)).or_insert_with(|| {
|
||||
let words = &derived_words[word];
|
||||
Self::union_word_position(rtxn, index, words, pos).unwrap()
|
||||
});
|
||||
});
|
||||
|
||||
// Retrieve the unions along with the popularity of it.
|
||||
let mut to_intersect: Vec<_> = positions.iter()
|
||||
.enumerate()
|
||||
.map(|(word, pos)| {
|
||||
let docids = union_cache.get(&(word, pos)).unwrap();
|
||||
(docids.len(), docids)
|
||||
})
|
||||
.collect();
|
||||
|
||||
// Sort the unions by popularity to help reduce
|
||||
// the number of documents as soon as possible.
|
||||
to_intersect.sort_unstable_by_key(|(l, _)| *l);
|
||||
|
||||
let intersect_docids: Option<RoaringBitmap> = to_intersect.into_iter()
|
||||
.fold(None, |acc, (_, union_docids)| {
|
||||
match acc {
|
||||
Some(mut left) => {
|
||||
left.intersect_with(&union_docids);
|
||||
Some(left)
|
||||
},
|
||||
None => Some(union_docids.clone()),
|
||||
}
|
||||
});
|
||||
|
||||
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::<u64>() + same_proximity_union.len() >= 20 {
|
||||
break;
|
||||
}
|
||||
}
|
||||
|
||||
// We achieve to find valid documents ids so we remove them from the candidates list.
|
||||
candidates.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());
|
||||
|
||||
// We found enough documents we can stop here.
|
||||
if documents.iter().map(RoaringBitmap::len).sum::<u64>() >= 20 {
|
||||
break;
|
||||
}
|
||||
}
|
||||
|
||||
let found_words = derived_words.into_iter().flatten().map(|(w, _, _)| w).collect();
|
||||
let documents_ids = documents.iter().flatten().take(20).collect();
|
||||
|
||||
Ok(SearchResult { found_words, documents_ids })
|
||||
}
|
||||
}
|
||||
|
||||
#[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>,
|
||||
}
|
Loading…
Reference in New Issue
Block a user