use std::fmt; use downcast_rs::impl_downcast; use super::Weight; use crate::core::searcher::Searcher; use crate::query::Explanation; use crate::{DocAddress, Term}; /// The `Query` trait defines a set of documents and a scoring method /// for those documents. /// /// The `Query` trait is in charge of defining : /// /// - a set of documents /// - a way to score these documents /// /// When performing a [search](Searcher::search), these documents will then /// be pushed to a [`Collector`](crate::collector::Collector), /// which will in turn be in charge of deciding what to do with them. /// /// Concretely, this scored docset is represented by the /// [`Scorer`] trait. /// /// Because our index is actually split into segments, the /// query does not actually directly creates [`DocSet`](crate::DocSet) object. /// Instead, the query creates a [`Weight`] object for a given searcher. /// /// The weight object, in turn, makes it possible to create /// a scorer for a specific [`SegmentReader`]. /// /// So to sum it up : /// - a `Query` is a recipe to define a set of documents as well the way to score them. /// - a [`Weight`] is this recipe tied to a specific [`Searcher`]. It may for instance /// hold statistics about the different term of the query. It is created by the query. /// - a [`Scorer`] is a cursor over the set of matching documents, for a specific /// [`SegmentReader`]. It is created by the [`Weight`]. /// /// When implementing a new type of `Query`, it is normal to implement a /// dedicated `Query`, [`Weight`] and [`Scorer`]. /// /// [`Scorer`]: crate::query::Scorer /// [`SegmentReader`]: crate::SegmentReader pub trait Query: QueryClone + Send + Sync + downcast_rs::Downcast + fmt::Debug { /// Create the weight associated with a query. /// /// If scoring is not required, setting `scoring_enabled` to `false` /// can increase performances. /// /// See [`Weight`]. fn weight(&self, searcher: &Searcher, scoring_enabled: bool) -> crate::Result>; /// Returns an `Explanation` for the score of the document. fn explain(&self, searcher: &Searcher, doc_address: DocAddress) -> crate::Result { let reader = searcher.segment_reader(doc_address.segment_ord); let weight = self.weight(searcher, true)?; weight.explain(reader, doc_address.doc_id) } /// Returns the number of documents matching the query. fn count(&self, searcher: &Searcher) -> crate::Result { let weight = self.weight(searcher, false)?; let mut result = 0; for reader in searcher.segment_readers() { result += weight.count(reader)? as usize; } Ok(result) } /// Extract all of the terms associated with the query and pass them to the /// given closure. /// /// Each term is associated with a boolean indicating whether /// positions are required or not. /// /// Note that there can be multiple instances of any given term /// in a query and deduplication must be handled by the visitor. fn query_terms<'a>(&'a self, _visitor: &mut dyn FnMut(&'a Term, bool)) {} } /// Implements `box_clone`. pub trait QueryClone { /// Returns a boxed clone of `self`. fn box_clone(&self) -> Box; } impl QueryClone for T where T: 'static + Query + Clone { fn box_clone(&self) -> Box { Box::new(self.clone()) } } impl Query for Box { fn weight(&self, searcher: &Searcher, scoring_enabled: bool) -> crate::Result> { self.as_ref().weight(searcher, scoring_enabled) } fn count(&self, searcher: &Searcher) -> crate::Result { self.as_ref().count(searcher) } fn query_terms<'a>(&'a self, visitor: &mut dyn FnMut(&'a Term, bool)) { self.as_ref().query_terms(visitor); } } impl QueryClone for Box { fn box_clone(&self) -> Box { self.as_ref().box_clone() } } impl_downcast!(Query);