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//! # Collectors
//!
//! Collectors define the information you want to extract from the documents matching the queries.
//! In tantivy jargon, we call this information your search "fruit".
//!
//! Your fruit could for instance be :
//! - [the count of matching documents](crate::collector::Count)
//! - [the top 10 documents, by relevancy or by a fast field](crate::collector::TopDocs)
//! - [facet counts](FacetCollector)
//!
//! At some point in your code, you will trigger the actual search operation by calling
//! [`Searcher::search()`](crate::Searcher::search).
//! This call will look like this:
//!
//! ```verbatim
//! let fruit = searcher.search(&query, &collector)?;
//! ```
//!
//! Here the type of fruit is actually determined as an associated type of the collector
//! (`Collector::Fruit`).
//!
//!
//! # Combining several collectors
//!
//! A rich search experience often requires to run several collectors on your search query.
//! For instance,
//! - selecting the top-K products matching your query
//! - counting the matching documents
//! - computing several facets
//! - computing statistics about the matching product prices
//!
//! A simple and efficient way to do that is to pass your collectors as one tuple.
//! The resulting `Fruit` will then be a typed tuple with each collector's original fruits
//! in their respective position.
//!
//! ```rust
//! # use tantivy::schema::*;
//! # use tantivy::*;
//! # use tantivy::query::*;
//! use tantivy::collector::{Count, TopDocs};
//! #
//! # fn main() -> tantivy::Result<()> {
//! # let mut schema_builder = Schema::builder();
//! # let title = schema_builder.add_text_field("title", TEXT);
//! # let schema = schema_builder.build();
//! # let index = Index::create_in_ram(schema);
//! # let mut index_writer = index.writer(15_000_000)?;
//! # index_writer.add_document(doc!(
//! # title => "The Name of the Wind",
//! # ))?;
//! # index_writer.add_document(doc!(
//! # title => "The Diary of Muadib",
//! # ))?;
//! # index_writer.commit()?;
//! # let reader = index.reader()?;
//! # let searcher = reader.searcher();
//! # let query_parser = QueryParser::for_index(&index, vec![title]);
//! # let query = query_parser.parse_query("diary")?;
//! let (doc_count, top_docs): (usize, Vec<(Score, DocAddress)>) =
//! searcher.search(&query, &(Count, TopDocs::with_limit(2)))?;
//! # Ok(())
//! # }
//! ```
//!
//! The `Collector` trait is implemented for up to 4 collectors.
//! If you have more than 4 collectors, you can either group them into
//! tuples of tuples `(a,(b,(c,d)))`, or rely on [`MultiCollector`].
//!
//! # Combining several collectors dynamically
//!
//! Combining collectors into a tuple is a zero-cost abstraction: everything
//! happens as if you had manually implemented a single collector
//! combining all of our features.
//!
//! Unfortunately it requires you to know at compile time your collector types.
//! If on the other hand, the collectors depend on some query parameter,
//! you can rely on [`MultiCollector`]'s.
//!
//!
//! # Implementing your own collectors.
//!
//! See the `custom_collector` example.
use downcast_rs::impl_downcast;
use crate::{DocId, Score, SegmentOrdinal, SegmentReader};
mod count_collector;
pub use self::count_collector::Count;
mod histogram_collector;
pub use histogram_collector::HistogramCollector;
mod multi_collector;
pub use self::multi_collector::{FruitHandle, MultiCollector, MultiFruit};
mod top_collector;
mod top_score_collector;
pub use self::top_collector::ComparableDoc;
pub use self::top_score_collector::{TopDocs, TopNComputer};
mod custom_score_top_collector;
pub use self::custom_score_top_collector::{CustomScorer, CustomSegmentScorer};
mod tweak_score_top_collector;
pub use self::tweak_score_top_collector::{ScoreSegmentTweaker, ScoreTweaker};
mod facet_collector;
pub use self::facet_collector::{FacetCollector, FacetCounts};
use crate::query::Weight;
mod docset_collector;
pub use self::docset_collector::DocSetCollector;
mod filter_collector_wrapper;
pub use self::filter_collector_wrapper::{BytesFilterCollector, FilterCollector};
/// `Fruit` is the type for the result of our collection.
/// e.g. `usize` for the `Count` collector.
pub trait Fruit: Send + downcast_rs::Downcast {}
impl<T> Fruit for T where T: Send + downcast_rs::Downcast {}
/// Collectors are in charge of collecting and retaining relevant
/// information from the document found and scored by the query.
///
/// For instance,
///
/// - keeping track of the top 10 best documents
/// - computing a breakdown over a fast field
/// - computing the number of documents matching the query
///
/// Our search index is in fact a collection of segments, so
/// a `Collector` trait is actually more of a factory to instance
/// `SegmentCollector`s for each segments.
///
/// The collection logic itself is in the `SegmentCollector`.
///
/// Segments are not guaranteed to be visited in any specific order.
pub trait Collector: Sync + Send {
/// `Fruit` is the type for the result of our collection.
/// e.g. `usize` for the `Count` collector.
type Fruit: Fruit;
/// Type of the `SegmentCollector` associated with this collector.
type Child: SegmentCollector;
/// `set_segment` is called before beginning to enumerate
/// on this segment.
fn for_segment(
&self,
segment_local_id: SegmentOrdinal,
segment: &SegmentReader,
) -> crate::Result<Self::Child>;
/// Returns true iff the collector requires to compute scores for documents.
fn requires_scoring(&self) -> bool;
/// Combines the fruit associated with the collection of each segments
/// into one fruit.
fn merge_fruits(
&self,
segment_fruits: Vec<<Self::Child as SegmentCollector>::Fruit>,
) -> crate::Result<Self::Fruit>;
/// Created a segment collector and
fn collect_segment(
&self,
weight: &dyn Weight,
segment_ord: u32,
reader: &SegmentReader,
) -> crate::Result<<Self::Child as SegmentCollector>::Fruit> {
let mut segment_collector = self.for_segment(segment_ord, reader)?;
match (reader.alive_bitset(), self.requires_scoring()) {
(Some(alive_bitset), true) => {
weight.for_each(reader, &mut |doc, score| {
if alive_bitset.is_alive(doc) {
segment_collector.collect(doc, score);
}
})?;
}
(Some(alive_bitset), false) => {
weight.for_each_no_score(reader, &mut |docs| {
for doc in docs.iter().cloned() {
if alive_bitset.is_alive(doc) {
segment_collector.collect(doc, 0.0);
}
}
})?;
}
(None, true) => {
weight.for_each(reader, &mut |doc, score| {
segment_collector.collect(doc, score);
})?;
}
(None, false) => {
weight.for_each_no_score(reader, &mut |docs| {
segment_collector.collect_block(docs);
})?;
}
}
Ok(segment_collector.harvest())
}
}
impl<TSegmentCollector: SegmentCollector> SegmentCollector for Option<TSegmentCollector> {
type Fruit = Option<TSegmentCollector::Fruit>;
fn collect(&mut self, doc: DocId, score: Score) {
if let Some(segment_collector) = self {
segment_collector.collect(doc, score);
}
}
fn harvest(self) -> Self::Fruit {
self.map(|segment_collector| segment_collector.harvest())
}
}
impl<TCollector: Collector> Collector for Option<TCollector> {
type Fruit = Option<TCollector::Fruit>;
type Child = Option<<TCollector as Collector>::Child>;
fn for_segment(
&self,
segment_local_id: SegmentOrdinal,
segment: &SegmentReader,
) -> crate::Result<Self::Child> {
Ok(if let Some(inner) = self {
let inner_segment_collector = inner.for_segment(segment_local_id, segment)?;
Some(inner_segment_collector)
} else {
None
})
}
fn requires_scoring(&self) -> bool {
self.as_ref()
.map(|inner| inner.requires_scoring())
.unwrap_or(false)
}
fn merge_fruits(
&self,
segment_fruits: Vec<<Self::Child as SegmentCollector>::Fruit>,
) -> crate::Result<Self::Fruit> {
if let Some(inner) = self.as_ref() {
let inner_segment_fruits: Vec<_> = segment_fruits
.into_iter()
.flat_map(|fruit_opt| fruit_opt.into_iter())
.collect();
let fruit = inner.merge_fruits(inner_segment_fruits)?;
Ok(Some(fruit))
} else {
Ok(None)
}
}
}
/// The `SegmentCollector` is the trait in charge of defining the
/// collect operation at the scale of the segment.
///
/// `.collect(doc, score)` will be called for every documents
/// matching the query.
pub trait SegmentCollector: 'static {
/// `Fruit` is the type for the result of our collection.
/// e.g. `usize` for the `Count` collector.
type Fruit: Fruit;
/// The query pushes the scored document to the collector via this method.
fn collect(&mut self, doc: DocId, score: Score);
/// The query pushes the scored document to the collector via this method.
/// This method is used when the collector does not require scoring.
///
/// See [`COLLECT_BLOCK_BUFFER_LEN`](crate::COLLECT_BLOCK_BUFFER_LEN) for the
/// buffer size passed to the collector.
fn collect_block(&mut self, docs: &[DocId]) {
for doc in docs {
self.collect(*doc, 0.0);
}
}
/// Extract the fruit of the collection from the `SegmentCollector`.
fn harvest(self) -> Self::Fruit;
}
// -----------------------------------------------
// Tuple implementations.
impl<Left, Right> Collector for (Left, Right)
where
Left: Collector,
Right: Collector,
{
type Fruit = (Left::Fruit, Right::Fruit);
type Child = (Left::Child, Right::Child);
fn for_segment(
&self,
segment_local_id: u32,
segment: &SegmentReader,
) -> crate::Result<Self::Child> {
let left = self.0.for_segment(segment_local_id, segment)?;
let right = self.1.for_segment(segment_local_id, segment)?;
Ok((left, right))
}
fn requires_scoring(&self) -> bool {
self.0.requires_scoring() || self.1.requires_scoring()
}
fn merge_fruits(
&self,
segment_fruits: Vec<<Self::Child as SegmentCollector>::Fruit>,
) -> crate::Result<(Left::Fruit, Right::Fruit)> {
let mut left_fruits = vec![];
let mut right_fruits = vec![];
for (left_fruit, right_fruit) in segment_fruits {
left_fruits.push(left_fruit);
right_fruits.push(right_fruit);
}
Ok((
self.0.merge_fruits(left_fruits)?,
self.1.merge_fruits(right_fruits)?,
))
}
}
impl<Left, Right> SegmentCollector for (Left, Right)
where
Left: SegmentCollector,
Right: SegmentCollector,
{
type Fruit = (Left::Fruit, Right::Fruit);
fn collect(&mut self, doc: DocId, score: Score) {
self.0.collect(doc, score);
self.1.collect(doc, score);
}
fn harvest(self) -> <Self as SegmentCollector>::Fruit {
(self.0.harvest(), self.1.harvest())
}
}
// 3-Tuple
impl<One, Two, Three> Collector for (One, Two, Three)
where
One: Collector,
Two: Collector,
Three: Collector,
{
type Fruit = (One::Fruit, Two::Fruit, Three::Fruit);
type Child = (One::Child, Two::Child, Three::Child);
fn for_segment(
&self,
segment_local_id: u32,
segment: &SegmentReader,
) -> crate::Result<Self::Child> {
let one = self.0.for_segment(segment_local_id, segment)?;
let two = self.1.for_segment(segment_local_id, segment)?;
let three = self.2.for_segment(segment_local_id, segment)?;
Ok((one, two, three))
}
fn requires_scoring(&self) -> bool {
self.0.requires_scoring() || self.1.requires_scoring() || self.2.requires_scoring()
}
fn merge_fruits(
&self,
children: Vec<<Self::Child as SegmentCollector>::Fruit>,
) -> crate::Result<Self::Fruit> {
let mut one_fruits = vec![];
let mut two_fruits = vec![];
let mut three_fruits = vec![];
for (one_fruit, two_fruit, three_fruit) in children {
one_fruits.push(one_fruit);
two_fruits.push(two_fruit);
three_fruits.push(three_fruit);
}
Ok((
self.0.merge_fruits(one_fruits)?,
self.1.merge_fruits(two_fruits)?,
self.2.merge_fruits(three_fruits)?,
))
}
}
impl<One, Two, Three> SegmentCollector for (One, Two, Three)
where
One: SegmentCollector,
Two: SegmentCollector,
Three: SegmentCollector,
{
type Fruit = (One::Fruit, Two::Fruit, Three::Fruit);
fn collect(&mut self, doc: DocId, score: Score) {
self.0.collect(doc, score);
self.1.collect(doc, score);
self.2.collect(doc, score);
}
fn harvest(self) -> <Self as SegmentCollector>::Fruit {
(self.0.harvest(), self.1.harvest(), self.2.harvest())
}
}
// 4-Tuple
impl<One, Two, Three, Four> Collector for (One, Two, Three, Four)
where
One: Collector,
Two: Collector,
Three: Collector,
Four: Collector,
{
type Fruit = (One::Fruit, Two::Fruit, Three::Fruit, Four::Fruit);
type Child = (One::Child, Two::Child, Three::Child, Four::Child);
fn for_segment(
&self,
segment_local_id: u32,
segment: &SegmentReader,
) -> crate::Result<Self::Child> {
let one = self.0.for_segment(segment_local_id, segment)?;
let two = self.1.for_segment(segment_local_id, segment)?;
let three = self.2.for_segment(segment_local_id, segment)?;
let four = self.3.for_segment(segment_local_id, segment)?;
Ok((one, two, three, four))
}
fn requires_scoring(&self) -> bool {
self.0.requires_scoring()
|| self.1.requires_scoring()
|| self.2.requires_scoring()
|| self.3.requires_scoring()
}
fn merge_fruits(
&self,
children: Vec<<Self::Child as SegmentCollector>::Fruit>,
) -> crate::Result<Self::Fruit> {
let mut one_fruits = vec![];
let mut two_fruits = vec![];
let mut three_fruits = vec![];
let mut four_fruits = vec![];
for (one_fruit, two_fruit, three_fruit, four_fruit) in children {
one_fruits.push(one_fruit);
two_fruits.push(two_fruit);
three_fruits.push(three_fruit);
four_fruits.push(four_fruit);
}
Ok((
self.0.merge_fruits(one_fruits)?,
self.1.merge_fruits(two_fruits)?,
self.2.merge_fruits(three_fruits)?,
self.3.merge_fruits(four_fruits)?,
))
}
}
impl<One, Two, Three, Four> SegmentCollector for (One, Two, Three, Four)
where
One: SegmentCollector,
Two: SegmentCollector,
Three: SegmentCollector,
Four: SegmentCollector,
{
type Fruit = (One::Fruit, Two::Fruit, Three::Fruit, Four::Fruit);
fn collect(&mut self, doc: DocId, score: Score) {
self.0.collect(doc, score);
self.1.collect(doc, score);
self.2.collect(doc, score);
self.3.collect(doc, score);
}
fn harvest(self) -> <Self as SegmentCollector>::Fruit {
(
self.0.harvest(),
self.1.harvest(),
self.2.harvest(),
self.3.harvest(),
)
}
}
impl_downcast!(Fruit);
#[cfg(test)]
pub mod tests;