MeiliSearch/milli/src/search/new/ranking_rule_graph/mod.rs

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mod build;
mod cheapest_paths;
mod edge_docids_cache;
mod empty_paths_cache;
mod paths_map;
mod proximity;
mod typo;
use super::logger::SearchLogger;
use super::small_bitmap::SmallBitmap;
use super::{QueryGraph, QueryNode, SearchContext};
use crate::Result;
pub use edge_docids_cache::EdgeDocidsCache;
pub use empty_paths_cache::EmptyPathsCache;
pub use proximity::ProximityGraph;
use roaring::RoaringBitmap;
pub use typo::TypoGraph;
#[derive(Debug, Clone)]
pub enum EdgeDetails<E> {
Unconditional,
Data(E),
}
#[derive(Debug, Clone)]
pub struct Edge<E> {
pub from_node: u16,
pub to_node: u16,
pub cost: u8,
pub details: EdgeDetails<E>,
}
#[derive(Debug, Clone)]
pub struct EdgePointer<'graph, E> {
pub index: u16,
pub edge: &'graph Edge<E>,
}
// pub struct SubWordDerivations {
// words: FxHashSet<Interned<String>>,
// synonyms: FxHashSet<Interned<Phrase>>, // NO! they're phrases, not strings
// split_words: bool,
// use_prefix_db: bool,
// }
// pub struct EdgeWordDerivations {
// // TODO: not Option, instead: Any | All | Subset(SubWordDerivations)
// from_words: Option<SubWordDerivations>, // ???
// to_words: Option<SubWordDerivations>, // + use prefix db?
// }
// fn aggregate_edge_word_derivations(
// graph: (),
// edges: Vec<usize>,
// ) -> BTreeMap<usize, SubWordDerivations> {
// todo!()
// }
// fn reduce_word_term_to_sub_word_derivations(
// term: &mut WordDerivations,
// derivations: &SubWordDerivations,
// ) {
// let mut new_one_typo = vec![];
// for w in term.one_typo {
// if derivations.words.contains(w) {
// new_one_typo.push(w);
// }
// }
// if term.use_prefix_db && !derivations.use_prefix_db {
// term.use_prefix_db = false;
// }
// // etc.
// }
// fn word_derivations_used_by_edge<G: RankingRuleGraphTrait>(
// edge: G::EdgeDetails,
// ) -> SubWordDerivations {
// todo!()
// }
pub trait RankingRuleGraphTrait: Sized {
/// The details of an edge connecting two query nodes. These details
/// should be sufficient to compute the edge's cost and associated document ids
/// in [`compute_docids`](RankingRuleGraphTrait).
type EdgeDetails: Sized + Clone;
type BuildVisitedFromNode;
/// Return the label of the given edge details, to be used when visualising
/// the ranking rule graph using GraphViz.
fn graphviz_edge_details_label(edge: &Self::EdgeDetails) -> String;
/// Compute the document ids associated with the given edge.
fn compute_docids<'search>(
ctx: &mut SearchContext<'search>,
edge_details: &Self::EdgeDetails,
universe: &RoaringBitmap,
) -> Result<RoaringBitmap>;
/// Prepare to build the edges outgoing from `from_node`.
///
/// This call is followed by zero, one or more calls to [`build_visit_to_node`](RankingRuleGraphTrait::build_visit_to_node),
/// which builds the actual edges.
fn build_visit_from_node<'search>(
ctx: &mut SearchContext<'search>,
from_node: &QueryNode,
) -> Result<Option<Self::BuildVisitedFromNode>>;
/// Return the cost and details of the edges going from the previously visited node
/// (with [`build_visit_from_node`](RankingRuleGraphTrait::build_visit_from_node)) to `to_node`.
fn build_visit_to_node<'from_data, 'search: 'from_data>(
ctx: &mut SearchContext<'search>,
to_node: &QueryNode,
from_node_data: &'from_data Self::BuildVisitedFromNode,
) -> Result<Vec<(u8, EdgeDetails<Self::EdgeDetails>)>>;
fn log_state(
graph: &RankingRuleGraph<Self>,
paths: &[Vec<u16>],
empty_paths_cache: &EmptyPathsCache,
universe: &RoaringBitmap,
distances: &[Vec<u16>],
cost: u16,
logger: &mut dyn SearchLogger<QueryGraph>,
);
}
pub struct RankingRuleGraph<G: RankingRuleGraphTrait> {
pub query_graph: QueryGraph,
// pub edges: Vec<HashMap<usize, Vec<Edge<G::EdgeDetails>>>>,
pub all_edges: Vec<Option<Edge<G::EdgeDetails>>>,
pub node_edges: Vec<SmallBitmap>,
pub successors: Vec<SmallBitmap>,
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// TODO: to get the edges between two nodes:
// 1. get node_outgoing_edges[from]
// 2. get node_incoming_edges[to]
// 3. take intersection betweem the two
}
impl<G: RankingRuleGraphTrait> Clone for RankingRuleGraph<G> {
fn clone(&self) -> Self {
Self {
query_graph: self.query_graph.clone(),
all_edges: self.all_edges.clone(),
node_edges: self.node_edges.clone(),
successors: self.successors.clone(),
}
}
}
impl<G: RankingRuleGraphTrait> RankingRuleGraph<G> {
pub fn remove_edge(&mut self, edge_index: u16) {
let edge_opt = &mut self.all_edges[edge_index as usize];
let Some(edge) = &edge_opt else { return };
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let (from_node, _to_node) = (edge.from_node, edge.to_node);
*edge_opt = None;
let from_node_edges = &mut self.node_edges[from_node as usize];
from_node_edges.remove(edge_index);
let mut new_successors_from_node = SmallBitmap::new(self.all_edges.len() as u16);
let all_edges = &self.all_edges;
for from_node_edge in from_node_edges.iter() {
let Edge { to_node, .. } = &all_edges[from_node_edge as usize].as_ref().unwrap();
new_successors_from_node.insert(*to_node);
}
self.successors[from_node as usize] = new_successors_from_node;
}
}