1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
use async_trait::async_trait;
use super::Scorer;
use crate::core::SegmentReader;
use crate::query::Explanation;
use crate::{DocId, DocSet, Score, TERMINATED};
/// Iterates through all of the documents and scores matched by the DocSet
/// `DocSet`.
pub(crate) fn for_each_scorer<TScorer: Scorer + ?Sized>(
scorer: &mut TScorer,
callback: &mut (dyn FnMut(DocId, Score) + Send),
) {
let mut doc = scorer.doc();
while doc != TERMINATED {
callback(doc, scorer.score());
doc = scorer.advance();
}
}
/// Iterates through all of the documents matched by the DocSet
/// `DocSet`.
pub(crate) fn for_each_docset<T: DocSet + ?Sized>(docset: &mut T, callback: &mut dyn FnMut(DocId)) {
let mut doc = docset.doc();
while doc != TERMINATED {
callback(doc);
doc = docset.advance();
}
}
/// Calls `callback` with all of the `(doc, score)` for which score
/// is exceeding a given threshold.
///
/// This method is useful for the [`TopDocs`](crate::collector::TopDocs) collector.
/// For all docsets, the blanket implementation has the benefit
/// of prefiltering (doc, score) pairs, avoiding the
/// virtual dispatch cost.
///
/// More importantly, it makes it possible for scorers to implement
/// important optimization (e.g. BlockWAND for union).
pub(crate) fn for_each_pruning_scorer<TScorer: Scorer + ?Sized>(
scorer: &mut TScorer,
mut threshold: Score,
callback: &mut dyn FnMut(DocId, Score) -> Score,
) {
let mut doc = scorer.doc();
while doc != TERMINATED {
let score = scorer.score();
if score > threshold {
threshold = callback(doc, score);
}
doc = scorer.advance();
}
}
/// A Weight is the specialization of a `Query`
/// for a given set of segments.
///
/// See [`Query`](crate::query::Query).
#[async_trait]
pub trait Weight: Send + Sync + 'static {
/// Returns the scorer for the given segment.
///
/// `boost` is a multiplier to apply to the score.
///
/// See [`Query`](crate::query::Query).
fn scorer(&self, reader: &SegmentReader, boost: Score) -> crate::Result<Box<dyn Scorer>>;
/// Returns the scorer for the given segment asynchronously.
///
/// See [`Self::scorer()`].
#[cfg(feature = "quickwit")]
async fn scorer_async(
&self,
reader: &SegmentReader,
boost: Score,
) -> crate::Result<Box<dyn Scorer>> {
self.scorer(reader, boost)
}
/// Returns an [`Explanation`] for the given document.
fn explain(&self, reader: &SegmentReader, doc: DocId) -> crate::Result<Explanation>;
/// Returns the number documents within the given [`SegmentReader`].
fn count(&self, reader: &SegmentReader) -> crate::Result<u32> {
let mut scorer = self.scorer(reader, 1.0)?;
if let Some(alive_bitset) = reader.alive_bitset() {
Ok(scorer.count(alive_bitset))
} else {
Ok(scorer.count_including_deleted())
}
}
/// Returns the number documents within the given [`SegmentReader`] asynchronously.
#[cfg(feature = "quickwit")]
async fn count_async(&self, reader: &SegmentReader) -> crate::Result<u32> {
self.count(reader)
}
/// Iterates through all of the document matched by the DocSet
/// `DocSet` and push the scored documents to the collector.
fn for_each(
&self,
reader: &SegmentReader,
callback: &mut (dyn FnMut(DocId, Score) + Send),
) -> crate::Result<()> {
let mut scorer = self.scorer(reader, 1.0)?;
for_each_scorer(scorer.as_mut(), callback);
Ok(())
}
/// Iterates through all of the document matched by the DocSet asynchronously
/// `DocSet` and push the scored documents to the collector.
#[cfg(feature = "quickwit")]
async fn for_each_async(
&self,
reader: &SegmentReader,
callback: &mut (dyn FnMut(DocId, Score) + Send),
) -> crate::Result<()> {
let mut scorer = self.scorer_async(reader, 1.0).await?;
for_each_scorer(scorer.as_mut(), callback);
Ok(())
}
/// Iterates through all of the document matched by the DocSet
/// `DocSet` and push the scored documents to the collector.
fn for_each_no_score(
&self,
reader: &SegmentReader,
callback: &mut dyn FnMut(DocId),
) -> crate::Result<()> {
let mut docset = self.scorer(reader, 1.0)?;
for_each_docset(docset.as_mut(), callback);
Ok(())
}
/// Iterates through all of the document matched by the DocSet asynchronously
/// `DocSet` and push the scored documents to the collector.
#[cfg(feature = "quickwit")]
async fn for_each_no_score_async(
&self,
reader: &SegmentReader,
callback: &mut (dyn FnMut(DocId) + Send),
) -> crate::Result<()> {
let mut docset = self.scorer_async(reader, 1.0).await?;
for_each_docset(docset.as_mut(), callback);
Ok(())
}
/// Calls `callback` with all of the `(doc, score)` for which score
/// is exceeding a given threshold.
///
/// This method is useful for the [`TopDocs`](crate::collector::TopDocs) collector.
/// For all docsets, the blanket implementation has the benefit
/// of prefiltering (doc, score) pairs, avoiding the
/// virtual dispatch cost.
///
/// More importantly, it makes it possible for scorers to implement
/// important optimization (e.g. BlockWAND for union).
fn for_each_pruning(
&self,
threshold: Score,
reader: &SegmentReader,
callback: &mut dyn FnMut(DocId, Score) -> Score,
) -> crate::Result<()> {
let mut scorer = self.scorer(reader, 1.0)?;
for_each_pruning_scorer(scorer.as_mut(), threshold, callback);
Ok(())
}
/// Calls `callback` with all of the `(doc, score)` for which score
/// is exceeding a given threshold.
///
/// See [`Self::for_each_pruning()`].
#[cfg(feature = "quickwit")]
async fn for_each_pruning_async(
&self,
threshold: Score,
reader: &SegmentReader,
callback: &mut (dyn FnMut(DocId, Score) -> Score + Send),
) -> crate::Result<()> {
let mut scorer = self.scorer_async(reader, 1.0).await?;
for_each_pruning_scorer(scorer.as_mut(), threshold, callback);
Ok(())
}
}