Introduce a customized A* algorithm.

This custom algo lazily compute the intersections between words, to avoid too much set operations and database reads

Cargo.lock

@@ -292,12 +292,6 @@ version = "0.1.2"
 source = "registry+https://github.com/rust-lang/crates.io-index"
 checksum = "e88a8acf291dafb59c2d96e8f59828f3838bb1a70398823ade51a84de6a6deed"
 
-[[package]]
-name = "fixedbitset"
-version = "0.2.0"
-source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "37ab347416e802de484e4d03c7316c48f1ecb56574dfd4a46a80f173ce1de04d"
-
 [[package]]
 name = "flate2"
 version = "1.0.14"
@@ -642,9 +636,9 @@ dependencies = [
 
 [[package]]
 name = "indexmap"
-version = "1.3.2"
+version = "1.4.0"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "076f042c5b7b98f31d205f1249267e12a6518c1481e9dae9764af19b707d2292"
+checksum = "c398b2b113b55809ceb9ee3e753fcbac793f1956663f3c36549c1346015c2afe"
 dependencies = [
  "autocfg 1.0.0",
 ]
@@ -667,15 +661,6 @@ dependencies = [
  "libc",
 ]
 
-[[package]]
-name = "itertools"
-version = "0.8.2"
-source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "f56a2d0bc861f9165be4eb3442afd3c236d8a98afd426f65d92324ae1091a484"
-dependencies = [
- "either",
-]
-
 [[package]]
 name = "itertools"
 version = "0.9.0"
@@ -805,13 +790,13 @@ dependencies = [
  "fst",
  "fxhash",
  "heed",
- "itertools 0.9.0",
+ "indexmap",
+ "itertools",
  "jemallocator",
  "levenshtein_automata",
  "memmap",
  "once_cell",
  "oxidized-mtbl",
- "pathfinding",
  "rayon",
  "roaring",
  "serde",
@@ -988,15 +973,6 @@ dependencies = [
  "winapi 0.3.8",
 ]
 
-[[package]]
-name = "num-traits"
-version = "0.2.11"
-source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "c62be47e61d1842b9170f0fdeec8eba98e60e90e5446449a0545e5152acd7096"
-dependencies = [
- "autocfg 1.0.0",
-]
-
 [[package]]
 name = "num_cpus"
 version = "1.13.0"
@@ -1041,18 +1017,6 @@ dependencies = [
  "winapi 0.3.8",
 ]
 
-[[package]]
-name = "pathfinding"
-version = "2.0.4"
-source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "86f4d8cc85ca67860ef4324faf86973a39e4e1c78338987eda29a8e6b6ec0c0e"
-dependencies = [
- "fixedbitset",
- "indexmap",
- "itertools 0.8.2",
- "num-traits",
-]
-
 [[package]]
 name = "percent-encoding"
 version = "2.1.0"
@@ -1979,6 +1943,6 @@ checksum = "c442965efc45353be5a9b9969c9b0872fff6828c7e06d118dda2cb2d0bb11d5a"
 dependencies = [
  "cc",
  "glob",
- "itertools 0.9.0",
+ "itertools",
  "libc",
 ]

Cargo.toml

@@ -28,7 +28,7 @@ structopt = { version = "0.3.14", default-features = false }
 tempfile = "3.1.0"
 
 # best proximity
-pathfinding = "2.0.4"
+indexmap = "1.4.0"
 
 # to implement internally
 itertools = "0.9.0"

src/best_proximity.rs

@@ -1,7 +1,7 @@
 use std::cmp;
 use std::time::Instant;
 
-use pathfinding::directed::astar::astar_bag;
+use crate::iter_shortest_paths::astar_bag;
 
 const ONE_ATTRIBUTE: u32 = 1000;
 const MAX_DISTANCE: u32 = 8;
@@ -37,6 +37,8 @@ enum Node {
         position: u32,
         // The total accumulated proximity until this node, used for skipping nodes.
         acc_proximity: u32,
+        // The parent position from the above layer.
+        parent_position: u32,
     },
 }
 
@@ -44,35 +46,29 @@ impl Node {
     // TODO we must skip the successors that have already been seen
     // TODO we must skip the successors that doesn't return any documents
     //      this way we are able to skip entire paths
-    fn successors<F>(
+    fn successors(&self, positions: &[Vec<u32>], best_proximity: u32) -> Vec<(Node, u32)> {
-        &self,
-        positions: &[Vec<u32>],
-        best_proximity: u32,
-        mut contains_documents: F,
-    ) -> Vec<(Node, u32)>
-    where F: FnMut((usize, u32), (usize, u32)) -> bool,
-    {
         match self {
             Node::Uninit => {
                 positions[0].iter().map(|p| {
-                    (Node::Init { layer: 0, position: *p, acc_proximity: 0 }, 0)
+                    (Node::Init { layer: 0, position: *p, acc_proximity: 0, parent_position: 0 }, 0)
                 }).collect()
             },
             // We reached the highest layer
             n @ Node::Init { .. } if n.is_complete(positions) => vec![],
-            Node::Init { layer, position, acc_proximity } => {
+            Node::Init { layer, position, acc_proximity, .. } => {
                 positions[layer + 1].iter().filter_map(|p| {
                     let proximity = positions_proximity(*position, *p);
-                    let node = Node::Init { layer: layer + 1, position: *p, acc_proximity: acc_proximity + proximity };
+                    let node = Node::Init {
-                    if (contains_documents)((*layer, *position), (layer + 1, *p)) {
+                        layer: layer + 1,
-                        // We do not produce the nodes we have already seen in previous iterations loops.
+                        position: *p,
-                        if node.is_complete(positions) && acc_proximity + proximity < best_proximity {
+                        acc_proximity: acc_proximity + proximity,
-                            None
+                        parent_position: *position,
-                        } else {
+                    };
-                            Some((node, proximity))
+                    // We do not produce the nodes we have already seen in previous iterations loops.
-                        }
+                    if node.is_complete(positions) && acc_proximity + proximity < best_proximity {
-                    } else {
                         None
+                    } else {
+                        Some((node, proximity))
                     }
                 }).collect()
             }
@@ -92,6 +88,35 @@ impl Node {
             Node::Init { position, .. } => Some(*position),
         }
     }
+
+    fn proximity(&self) -> u32 {
+        match self {
+            Node::Uninit => 0,
+            Node::Init { layer, position, acc_proximity, parent_position } => {
+                if layer.checked_sub(1).is_some() {
+                    acc_proximity + positions_proximity(*position, *parent_position)
+                } else {
+                    0
+                }
+            },
+        }
+    }
+
+    fn is_reachable<F>(&self, mut contains_documents: F) -> bool
+    where F: FnMut((usize, u32), (usize, u32)) -> bool,
+    {
+        match self {
+            Node::Uninit => true,
+            Node::Init { layer, position, parent_position, .. } => {
+                match layer.checked_sub(1) {
+                    Some(parent_layer) => {
+                        (contains_documents)((parent_layer, *parent_position), (*layer, *position))
+                    },
+                    None => true,
+                }
+            },
+        }
+    }
 }
 
 pub struct BestProximity<F> {
@@ -102,7 +127,7 @@ pub struct BestProximity<F> {
 
 impl<F> BestProximity<F> {
     pub fn new(positions: Vec<Vec<u32>>, contains_documents: F) -> BestProximity<F> {
-        let best_proximity = positions.len() as u32 - 1;
+        let best_proximity = (positions.len() as u32).saturating_sub(1);
         BestProximity { positions, best_proximity, contains_documents }
     }
 }
@@ -121,9 +146,12 @@ where F: FnMut((usize, u32), (usize, u32)) -> bool + Copy,
 
         let result = astar_bag(
             &Node::Uninit, // start
-            |n| n.successors(&self.positions, self.best_proximity, self.contains_documents),
+            |n| n.successors(&self.positions, self.best_proximity),
             |_| 0, // heuristic
-            |n| n.is_complete(&self.positions), // success
+            |n| { // success
+                let c = n.is_complete(&self.positions) && n.proximity() >= self.best_proximity;
+                if n.is_reachable(self.contains_documents) { Some(c) } else { None }
+            },
         );
 
         eprintln!("BestProximity::next() took {:.02?}", before.elapsed());

src/iter_shortest_paths.rs

@@ -0,0 +1,204 @@
+use std::cmp::Ordering;
+use std::collections::{BinaryHeap, HashSet};
+use std::hash::Hash;
+use std::usize;
+
+use indexmap::map::Entry::{Occupied, Vacant};
+use indexmap::IndexMap;
+
+pub fn astar_bag<N, FN, IN, FH, FS>(
+    start: &N,
+    mut successors: FN,
+    mut heuristic: FH,
+    mut success: FS,
+) -> Option<(AstarSolution<N>, u32)>
+where
+    N: Eq + Hash + Clone,
+    FN: FnMut(&N) -> IN,
+    IN: IntoIterator<Item = (N, u32)>,
+    FH: FnMut(&N) -> u32,
+    FS: FnMut(&N) -> Option<bool>,
+{
+    let mut to_see = BinaryHeap::new();
+    let mut min_cost = None;
+    let mut sinks = HashSet::new();
+    to_see.push(SmallestCostHolder {
+        estimated_cost: heuristic(start),
+        cost: 0,
+        index: 0,
+    });
+    let mut parents: IndexMap<N, (HashSet<usize>, u32)> = IndexMap::new();
+    parents.insert(start.clone(), (HashSet::new(), 0));
+    while let Some(SmallestCostHolder { cost, index, estimated_cost, .. }) = to_see.pop() {
+        if let Some(min_cost) = min_cost {
+            if estimated_cost > min_cost {
+                break;
+            }
+        }
+        let successors = {
+            let (node, &(_, c)) = parents.get_index(index).unwrap();
+            // We check that the node is even reachable and if so if it is an answer.
+            // If this node is unreachable we skip it.
+            match success(node) {
+                Some(success) => if success {
+                    min_cost = Some(cost);
+                    sinks.insert(index);
+                },
+                None => continue,
+            }
+
+            // We may have inserted a node several time into the binary heap if we found
+            // a better way to access it. Ensure that we are currently dealing with the
+            // best path and discard the others.
+            if cost > c {
+                continue;
+            }
+            successors(node)
+        };
+        for (successor, move_cost) in successors {
+            let new_cost = cost + move_cost;
+            let h; // heuristic(&successor)
+            let n; // index for successor
+            match parents.entry(successor) {
+                Vacant(e) => {
+                    h = heuristic(e.key());
+                    n = e.index();
+                    let mut p = HashSet::new();
+                    p.insert(index);
+                    e.insert((p, new_cost));
+                }
+                Occupied(mut e) => {
+                    if e.get().1 > new_cost {
+                        h = heuristic(e.key());
+                        n = e.index();
+                        let s = e.get_mut();
+                        s.0.clear();
+                        s.0.insert(index);
+                        s.1 = new_cost;
+                    } else {
+                        if e.get().1 == new_cost {
+                            // New parent with an identical cost, this is not
+                            // considered as an insertion.
+                            e.get_mut().0.insert(index);
+                        }
+                        continue;
+                    }
+                }
+            }
+
+            to_see.push(SmallestCostHolder {
+                estimated_cost: new_cost + h,
+                cost: new_cost,
+                index: n,
+            });
+        }
+    }
+
+    min_cost.map(|cost| {
+        let parents = parents
+            .into_iter()
+            .map(|(k, (ps, _))| (k, ps.into_iter().collect()))
+            .collect();
+        (
+            AstarSolution {
+                sinks: sinks.into_iter().collect(),
+                parents,
+                current: vec![],
+                terminated: false,
+            },
+            cost,
+        )
+    })
+}
+
+struct SmallestCostHolder<K> {
+    estimated_cost: K,
+    cost: K,
+    index: usize,
+}
+
+impl<K: PartialEq> PartialEq for SmallestCostHolder<K> {
+    fn eq(&self, other: &Self) -> bool {
+        self.estimated_cost.eq(&other.estimated_cost) && self.cost.eq(&other.cost)
+    }
+}
+
+impl<K: PartialEq> Eq for SmallestCostHolder<K> {}
+
+impl<K: Ord> PartialOrd for SmallestCostHolder<K> {
+    fn partial_cmp(&self, other: &Self) -> Option<Ordering> {
+        Some(self.cmp(other))
+    }
+}
+
+impl<K: Ord> Ord for SmallestCostHolder<K> {
+    fn cmp(&self, other: &Self) -> Ordering {
+        match other.estimated_cost.cmp(&self.estimated_cost) {
+            Ordering::Equal => self.cost.cmp(&other.cost),
+            s => s,
+        }
+    }
+}
+
+/// Iterator structure created by the `astar_bag` function.
+#[derive(Clone)]
+pub struct AstarSolution<N> {
+    sinks: Vec<usize>,
+    parents: Vec<(N, Vec<usize>)>,
+    current: Vec<Vec<usize>>,
+    terminated: bool,
+}
+
+impl<N: Clone + Eq + Hash> AstarSolution<N> {
+    fn complete(&mut self) {
+        loop {
+            let ps = match self.current.last() {
+                None => self.sinks.clone(),
+                Some(last) => {
+                    let &top = last.last().unwrap();
+                    self.parents(top).clone()
+                }
+            };
+            if ps.is_empty() {
+                break;
+            }
+            self.current.push(ps);
+        }
+    }
+
+    fn next_vec(&mut self) {
+        while self.current.last().map(Vec::len) == Some(1) {
+            self.current.pop();
+        }
+        self.current.last_mut().map(Vec::pop);
+    }
+
+    fn node(&self, i: usize) -> &N {
+        &self.parents[i].0
+    }
+
+    fn parents(&self, i: usize) -> &Vec<usize> {
+        &self.parents[i].1
+    }
+}
+
+impl<N: Clone + Eq + Hash> Iterator for AstarSolution<N> {
+    type Item = Vec<N>;
+
+    fn next(&mut self) -> Option<Self::Item> {
+        if self.terminated {
+            return None;
+        }
+        self.complete();
+        let path = self
+            .current
+            .iter()
+            .rev()
+            .map(|v| v.last().cloned().unwrap())
+            .map(|i| self.node(i).clone())
+            .collect::<Vec<_>>();
+        self.next_vec();
+        self.terminated = self.current.is_empty();
+        Some(path)
+    }
+}

src/lib.rs

@@ -1,4 +1,5 @@
 mod best_proximity;
+mod iter_shortest_paths;
 mod query_tokens;
 
 use std::borrow::Cow;