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https://github.com/meilisearch/meilisearch.git
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Make the algo don't work with an astar
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parent
0a83a86e65
commit
302866ad73
@ -1,9 +1,8 @@
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use std::cmp;
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use std::time::Instant;
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use pathfinding::directed::dijkstra::dijkstra;
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use pathfinding::directed::astar::astar_bag;
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use smallvec::smallvec; // the macro
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use crate::SmallVec16;
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const ONE_ATTRIBUTE: u32 = 1000;
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@ -29,53 +28,47 @@ fn extract_position(position: u32) -> (u32, u32) {
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(position / ONE_ATTRIBUTE, position % ONE_ATTRIBUTE)
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}
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#[derive(Debug, Clone, PartialOrd, Ord, PartialEq, Eq, Hash)]
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#[derive(Debug, Default, Clone, PartialOrd, Ord, PartialEq, Eq, Hash)]
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struct Path(SmallVec16<u32>);
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impl Path {
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fn new(positions: &[Vec<u32>]) -> Option<Path> {
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let position = positions.first()?.first()?;
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Some(Path(smallvec![*position]))
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}
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// TODO we must skip the successors that have already been sent
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fn successors(&self, positions: &[Vec<u32>]) -> SmallVec16<(Path, u32)> {
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let mut successors = SmallVec16::new();
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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<(Path, u32)> {
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let next_positions = match positions.get(self.0.len()) {
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Some(positions) => positions,
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None => return vec![],
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};
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// If we can grow or shift the path
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if self.0.len() < positions.len() {
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for next_pos in &positions[self.0.len()] {
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let mut grown_path = self.0.clone();
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grown_path.push(*next_pos);
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let path = Path(grown_path);
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next_positions.iter()
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.filter_map(|p| {
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let mut path = self.clone();
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path.0.push(*p);
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let proximity = path.proximity();
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successors.push((path, proximity));
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}
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}
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// We retrieve the tail of the current path and try to find
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// the successor of this tail.
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let next_path_tail = self.0.last().unwrap() + 1;
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// To do so we add 1 to the tail and check that something exists.
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let path_tail_index = positions[self.0.len() - 1].binary_search(&next_path_tail).unwrap_or_else(|p| p);
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// If we found something it means that we can shift the path.
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if let Some(pos) = positions[self.0.len() - 1].get(path_tail_index) {
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let mut shifted_path = self.0.clone();
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*shifted_path.last_mut().unwrap() = *pos;
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let path = Path(shifted_path);
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let proximity = path.proximity();
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successors.push((path, proximity));
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}
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successors
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if path.is_complete(positions) && proximity < best_proximity {
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None
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} else {
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Some((path, proximity))
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}
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})
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.inspect(|p| eprintln!("{:?}", p))
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.collect()
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}
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fn proximity(&self) -> u32 {
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self.0.windows(2).map(|ps| positions_proximity(ps[0], ps[1])).sum::<u32>()
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}
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fn heuristic(&self, positions: &[Vec<u32>]) -> u32 {
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let remaining = (positions.len() - self.0.len()) as u32;
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self.proximity() + remaining * MAX_DISTANCE
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}
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fn is_complete(&self, positions: &[Vec<u32>]) -> bool {
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positions.len() == self.0.len()
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let res = positions.len() == self.0.len();
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eprintln!("is_complete: {:?} {}", self, res);
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res
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}
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}
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@ -88,65 +81,45 @@ impl BestProximity {
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pub fn new(positions: Vec<Vec<u32>>) -> BestProximity {
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BestProximity { positions, best_proximity: 0 }
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}
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fn is_path_successful(&self, path: &Path) -> bool {
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path.is_complete(&self.positions) && path.proximity() >= self.best_proximity
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}
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}
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impl Iterator for BestProximity {
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type Item = (u32, Vec<Vec<u32>>);
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fn next(&mut self) -> Option<Self::Item> {
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let mut output: Option<(u32, Vec<Vec<u32>>)> = None;
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let before = Instant::now();
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loop {
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let result = dijkstra(
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&Path::new(&self.positions)?,
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|p| p.successors(&self.positions),
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|p| {
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self.is_path_successful(p) &&
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output.as_ref().map_or(true, |(_, paths)| {
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!paths.iter().position(|q| q.as_slice() == p.0.as_slice()).is_some()
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})
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},
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);
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match result {
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Some((mut paths, _)) => {
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let positions = paths.pop().unwrap();
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let proximity = positions.proximity();
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// If the current output is
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match &mut output {
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Some((best_proximity, paths)) => {
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// If the shortest path we found is bigger than the one requested
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// it means that we found all the paths with the same proximity and can
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// return those to the user.
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if proximity > *best_proximity {
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break;
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}
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// We add the new path to the output list as this path is known
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// to be the requested distance.
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paths.push(positions.0.to_vec());
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},
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None => output = Some((positions.proximity(), vec![positions.0.to_vec()])),
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}
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},
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None => break,
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}
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if self.best_proximity == self.positions.len() as u32 * MAX_DISTANCE {
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return None;
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}
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// We start with nothing
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let start = Path::default();
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let result = astar_bag(
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&start,
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|p| p.successors(&self.positions, self.best_proximity),
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|p| p.heuristic(&self.positions),
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|p| p.is_complete(&self.positions), // success
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);
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eprintln!("BestProximity::next() took {:.02?}", before.elapsed());
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if let Some((proximity, _)) = output.as_ref() {
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self.best_proximity = proximity + 1;
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match result {
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Some((paths, proximity)) => {
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self.best_proximity = proximity + 1;
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// We retrieve the last path that we convert into a Vec
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let paths: Vec<_> = paths.map(|p| {
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p.last().unwrap().0.to_vec()
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}).collect();
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eprintln!("result: {} {:?}", proximity, paths);
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Some((proximity, paths))
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},
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None => {
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eprintln!("result: {:?}", None as Option<()>);
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self.best_proximity += 1;
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None
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},
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}
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output
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}
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}
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