Files
tantivy/src/query/phrase_query/mod.rs
2019-07-22 13:43:00 +09:00

262 lines
10 KiB
Rust

mod phrase_query;
mod phrase_scorer;
mod phrase_weight;
pub use self::phrase_query::PhraseQuery;
pub use self::phrase_scorer::PhraseScorer;
pub use self::phrase_weight::PhraseWeight;
#[cfg(test)]
mod tests {
use super::*;
use crate::collector::tests::{TEST_COLLECTOR_WITHOUT_SCORE, TEST_COLLECTOR_WITH_SCORE};
use crate::core::Index;
use crate::error::TantivyError;
use crate::schema::{Schema, Term, TEXT};
use crate::tests::assert_nearly_equals;
use crate::DocId;
use crate::{DocAddress, DocSet};
fn create_index(texts: &[&'static str]) -> Index {
let mut schema_builder = Schema::builder();
let text_field = schema_builder.add_text_field("text", TEXT);
let schema = schema_builder.build();
let index = Index::create_in_ram(schema);
{
let mut index_writer = index.writer_with_num_threads(1, 3_000_000).unwrap();
for &text in texts {
let doc = doc!(text_field=>text);
index_writer.add_document(doc);
}
assert!(index_writer.commit().is_ok());
}
index
}
#[test]
pub fn test_phrase_query() {
let index = create_index(&[
"b b b d c g c",
"a b b d c g c",
"a b a b c",
"c a b a d ga a",
"a b c",
]);
let schema = index.schema();
let text_field = schema.get_field("text").unwrap();
let searcher = index.reader().unwrap().searcher();
let test_query = |texts: Vec<&str>| {
let terms: Vec<Term> = texts
.iter()
.map(|text| Term::from_field_text(text_field, text))
.collect();
let phrase_query = PhraseQuery::new(terms);
let test_fruits = searcher
.search(&phrase_query, &TEST_COLLECTOR_WITH_SCORE)
.expect("search should succeed");
test_fruits
.docs()
.iter()
.map(|docaddr| docaddr.1)
.collect::<Vec<_>>()
};
assert_eq!(test_query(vec!["a", "b", "c"]), vec![2, 4]);
assert_eq!(test_query(vec!["a", "b"]), vec![1, 2, 3, 4]);
assert_eq!(test_query(vec!["b", "b"]), vec![0, 1]);
assert!(test_query(vec!["g", "ewrwer"]).is_empty());
assert!(test_query(vec!["g", "a"]).is_empty());
}
#[test]
pub fn test_phrase_query_no_score() {
let index = create_index(&[
"b b b d c g c",
"a b b d c g c",
"a b a b c",
"c a b a d ga a",
"a b c",
]);
let schema = index.schema();
let text_field = schema.get_field("text").unwrap();
let searcher = index.reader().unwrap().searcher();
let test_query = |texts: Vec<&str>| {
let terms: Vec<Term> = texts
.iter()
.map(|text| Term::from_field_text(text_field, text))
.collect();
let phrase_query = PhraseQuery::new(terms);
let test_fruits = searcher
.search(&phrase_query, &TEST_COLLECTOR_WITHOUT_SCORE)
.expect("search should succeed");
test_fruits
.docs()
.iter()
.map(|docaddr| docaddr.1)
.collect::<Vec<_>>()
};
assert_eq!(test_query(vec!["a", "b", "c"]), vec![2, 4]);
assert_eq!(test_query(vec!["a", "b"]), vec![1, 2, 3, 4]);
assert_eq!(test_query(vec!["b", "b"]), vec![0, 1]);
assert!(test_query(vec!["g", "ewrwer"]).is_empty());
assert!(test_query(vec!["g", "a"]).is_empty());
}
#[test]
pub fn test_phrase_count() {
let index = create_index(&["a c", "a a b d a b c", " a b"]);
let schema = index.schema();
let text_field = schema.get_field("text").unwrap();
let searcher = index.reader().unwrap().searcher();
let phrase_query = PhraseQuery::new(vec![
Term::from_field_text(text_field, "a"),
Term::from_field_text(text_field, "b"),
]);
let phrase_weight = phrase_query.phrase_weight(&searcher, true).unwrap();
let mut phrase_scorer = phrase_weight
.phrase_scorer(searcher.segment_reader(0u32))
.unwrap()
.unwrap();
assert!(phrase_scorer.advance());
assert_eq!(phrase_scorer.doc(), 1);
assert_eq!(phrase_scorer.phrase_count(), 2);
assert!(phrase_scorer.advance());
assert_eq!(phrase_scorer.doc(), 2);
assert_eq!(phrase_scorer.phrase_count(), 1);
assert!(!phrase_scorer.advance());
}
#[test]
pub fn test_phrase_query_no_positions() {
let mut schema_builder = Schema::builder();
use crate::schema::IndexRecordOption;
use crate::schema::TextFieldIndexing;
use crate::schema::TextOptions;
let no_positions = TextOptions::default().set_indexing_options(
TextFieldIndexing::default()
.set_tokenizer("default")
.set_index_option(IndexRecordOption::WithFreqs),
);
let text_field = schema_builder.add_text_field("text", no_positions);
let schema = schema_builder.build();
let index = Index::create_in_ram(schema);
{
let mut index_writer = index.writer_with_num_threads(1, 3_000_000).unwrap();
index_writer.add_document(doc!(text_field=>"a b c"));
assert!(index_writer.commit().is_ok());
}
let searcher = index.reader().unwrap().searcher();
let phrase_query = PhraseQuery::new(vec![
Term::from_field_text(text_field, "a"),
Term::from_field_text(text_field, "b"),
]);
match searcher
.search(&phrase_query, &TEST_COLLECTOR_WITH_SCORE)
.map(|_| ())
.unwrap_err()
{
TantivyError::SchemaError(ref msg) => {
assert_eq!(
"Applied phrase query on field \"text\", which does not have positions indexed",
msg.as_str()
);
}
_ => {
panic!("Should have returned an error");
}
}
}
#[test]
pub fn test_phrase_score() {
let index = create_index(&["a b c", "a b c a b"]);
let schema = index.schema();
let text_field = schema.get_field("text").unwrap();
let searcher = index.reader().unwrap().searcher();
let test_query = |texts: Vec<&str>| {
let terms: Vec<Term> = texts
.iter()
.map(|text| Term::from_field_text(text_field, text))
.collect();
let phrase_query = PhraseQuery::new(terms);
searcher
.search(&phrase_query, &TEST_COLLECTOR_WITH_SCORE)
.expect("search should succeed")
.scores()
.to_vec()
};
let scores = test_query(vec!["a", "b"]);
assert_nearly_equals(scores[0], 0.40618482);
assert_nearly_equals(scores[1], 0.46844664);
}
#[test] // motivated by #234
pub fn test_phrase_query_docfreq_order() {
let mut schema_builder = Schema::builder();
let text_field = schema_builder.add_text_field("text", TEXT);
let schema = schema_builder.build();
let index = Index::create_in_ram(schema);
{
let mut index_writer = index.writer_with_num_threads(1, 3_000_000).unwrap();
index_writer.add_document(doc!(text_field=>"b"));
index_writer.add_document(doc!(text_field=>"a b"));
index_writer.add_document(doc!(text_field=>"b a"));
assert!(index_writer.commit().is_ok());
}
let searcher = index.reader().unwrap().searcher();
let test_query = |texts: Vec<&str>| {
let terms: Vec<Term> = texts
.iter()
.map(|text| Term::from_field_text(text_field, text))
.collect();
let phrase_query = PhraseQuery::new(terms);
searcher
.search(&phrase_query, &TEST_COLLECTOR_WITH_SCORE)
.expect("search should succeed")
.docs()
.to_vec()
};
assert_eq!(test_query(vec!["a", "b"]), vec![DocAddress(0, 1)]);
assert_eq!(test_query(vec!["b", "a"]), vec![DocAddress(0, 2)]);
}
#[test] // motivated by #234
pub fn test_phrase_query_non_trivial_offsets() {
let mut schema_builder = Schema::builder();
let text_field = schema_builder.add_text_field("text", TEXT);
let schema = schema_builder.build();
let index = Index::create_in_ram(schema);
{
let mut index_writer = index.writer_with_num_threads(1, 3_000_000).unwrap();
index_writer.add_document(doc!(text_field=>"a b c d e f g h"));
assert!(index_writer.commit().is_ok());
}
let searcher = index.reader().unwrap().searcher();
let test_query = |texts: Vec<(usize, &str)>| {
let terms: Vec<(usize, Term)> = texts
.iter()
.map(|(offset, text)| (*offset, Term::from_field_text(text_field, text)))
.collect();
let phrase_query = PhraseQuery::new_with_offset(terms);
searcher
.search(&phrase_query, &TEST_COLLECTOR_WITH_SCORE)
.expect("search should succeed")
.docs()
.iter()
.map(|doc_address| doc_address.1)
.collect::<Vec<DocId>>()
};
assert_eq!(test_query(vec![(0, "a"), (1, "b")]), vec![0]);
assert_eq!(test_query(vec![(1, "b"), (0, "a")]), vec![0]);
assert!(test_query(vec![(0, "a"), (2, "b")]).is_empty());
assert_eq!(test_query(vec![(0, "a"), (2, "c")]), vec![0]);
assert_eq!(test_query(vec![(0, "a"), (2, "c"), (3, "d")]), vec![0]);
assert_eq!(test_query(vec![(0, "a"), (2, "c"), (4, "e")]), vec![0]);
assert_eq!(test_query(vec![(4, "e"), (0, "a"), (2, "c")]), vec![0]);
assert!(test_query(vec![(0, "a"), (2, "d")]).is_empty());
assert_eq!(test_query(vec![(1, "a"), (3, "c")]), vec![0]);
}
}