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https://github.com/quickwit-oss/tantivy.git
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* fix cardinality aggregation performance fix cardinality performance by fetching multiple terms at once. This avoids decompressing the same block and keeps the buffer state between terms. add cardinality aggregation benchmark bump rust version to 1.66 Performance comparison to before (AllQuery) ``` full cardinality_agg Memory: 3.5 MB (-0.00%) Avg: 21.2256ms (-97.78%) Median: 21.0042ms (-97.82%) [20.4717ms .. 23.6206ms] terms_few_with_cardinality_agg Memory: 10.6 MB Avg: 81.9293ms (-97.37%) Median: 81.5526ms (-97.38%) [79.7564ms .. 88.0374ms] dense cardinality_agg Memory: 3.6 MB (-0.00%) Avg: 25.9372ms (-97.24%) Median: 25.7744ms (-97.25%) [24.7241ms .. 27.8793ms] terms_few_with_cardinality_agg Memory: 10.6 MB Avg: 93.9897ms (-96.91%) Median: 92.7821ms (-96.94%) [90.3312ms .. 117.4076ms] sparse cardinality_agg Memory: 895.4 KB (-0.00%) Avg: 22.5113ms (-95.01%) Median: 22.5629ms (-94.99%) [22.1628ms .. 22.9436ms] terms_few_with_cardinality_agg Memory: 680.2 KB Avg: 26.4250ms (-94.85%) Median: 26.4135ms (-94.86%) [26.3210ms .. 26.6774ms] ``` * clippy * assert for sorted ordinals
456 lines
18 KiB
Rust
456 lines
18 KiB
Rust
use super::boolean_weight::BooleanWeight;
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use crate::query::{EnableScoring, Occur, Query, SumWithCoordsCombiner, TermQuery, Weight};
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use crate::schema::{IndexRecordOption, Term};
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/// The boolean query returns a set of documents
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/// that matches the Boolean combination of constituent subqueries.
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///
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/// The documents matched by the boolean query are
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/// those which
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/// * match all of the sub queries associated with the
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/// `Must` occurrence
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/// * match none of the sub queries associated with the
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/// `MustNot` occurrence.
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/// * match at least one of the sub queries associated
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/// with the `Must` or `Should` occurrence.
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///
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///
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/// You can combine other query types and their `Occur`ances into one `BooleanQuery`
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///
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/// ```rust
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/// use tantivy::collector::Count;
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/// use tantivy::doc;
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/// use tantivy::query::{BooleanQuery, Occur, PhraseQuery, Query, TermQuery};
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/// use tantivy::schema::{IndexRecordOption, Schema, TEXT};
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/// use tantivy::Term;
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/// use tantivy::Index;
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/// use tantivy::IndexWriter;
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///
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/// fn main() -> tantivy::Result<()> {
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/// let mut schema_builder = Schema::builder();
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/// let title = schema_builder.add_text_field("title", TEXT);
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/// let body = schema_builder.add_text_field("body", TEXT);
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/// let schema = schema_builder.build();
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/// let index = Index::create_in_ram(schema);
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/// {
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/// let mut index_writer: IndexWriter = index.writer(15_000_000)?;
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/// index_writer.add_document(doc!(
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/// title => "The Name of the Wind",
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/// ))?;
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/// index_writer.add_document(doc!(
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/// title => "The Diary of Muadib",
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/// ))?;
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/// index_writer.add_document(doc!(
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/// title => "A Dairy Cow",
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/// body => "hidden",
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/// ))?;
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/// index_writer.add_document(doc!(
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/// title => "A Dairy Cow",
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/// body => "found",
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/// ))?;
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/// index_writer.add_document(doc!(
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/// title => "The Diary of a Young Girl",
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/// ))?;
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/// index_writer.commit()?;
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/// }
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///
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/// let reader = index.reader()?;
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/// let searcher = reader.searcher();
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///
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/// // Make TermQuery's for "girl" and "diary" in the title
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/// let girl_term_query: Box<dyn Query> = Box::new(TermQuery::new(
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/// Term::from_field_text(title, "girl"),
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/// IndexRecordOption::Basic,
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/// ));
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/// let diary_term_query: Box<dyn Query> = Box::new(TermQuery::new(
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/// Term::from_field_text(title, "diary"),
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/// IndexRecordOption::Basic,
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/// ));
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/// let cow_term_query: Box<dyn Query> = Box::new(TermQuery::new(
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/// Term::from_field_text(title, "cow"),
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/// IndexRecordOption::Basic
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/// ));
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/// // A TermQuery with "found" in the body
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/// let body_term_query: Box<dyn Query> = Box::new(TermQuery::new(
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/// Term::from_field_text(body, "found"),
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/// IndexRecordOption::Basic,
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/// ));
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/// // TermQuery "diary" must and "girl" must not be present
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/// let queries_with_occurs1 = vec![
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/// (Occur::Must, diary_term_query.box_clone()),
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/// (Occur::MustNot, girl_term_query.box_clone()),
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/// ];
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/// // Make a BooleanQuery equivalent to
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/// // title:+diary title:-girl
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/// let diary_must_and_girl_mustnot = BooleanQuery::new(queries_with_occurs1);
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/// let count1 = searcher.search(&diary_must_and_girl_mustnot, &Count)?;
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/// assert_eq!(count1, 1);
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///
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/// // "title:diary OR title:cow"
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/// let title_diary_or_cow = BooleanQuery::new(vec![
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/// (Occur::Should, diary_term_query.box_clone()),
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/// (Occur::Should, cow_term_query.box_clone()),
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/// ]);
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/// let count2 = searcher.search(&title_diary_or_cow, &Count)?;
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/// assert_eq!(count2, 4);
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///
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/// // Make a `PhraseQuery` from a vector of `Term`s
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/// let phrase_query: Box<dyn Query> = Box::new(PhraseQuery::new(vec![
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/// Term::from_field_text(title, "dairy"),
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/// Term::from_field_text(title, "cow"),
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/// ]));
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/// // You can combine subqueries of different types into 1 BooleanQuery:
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/// // `TermQuery` and `PhraseQuery`
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/// // "title:diary OR "dairy cow"
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/// let term_of_phrase_query = BooleanQuery::new(vec![
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/// (Occur::Should, diary_term_query.box_clone()),
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/// (Occur::Should, phrase_query.box_clone()),
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/// ]);
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/// let count3 = searcher.search(&term_of_phrase_query, &Count)?;
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/// assert_eq!(count3, 4);
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///
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/// // You can nest one BooleanQuery inside another
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/// // body:found AND ("title:diary OR "dairy cow")
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/// let nested_query = BooleanQuery::new(vec![
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/// (Occur::Must, body_term_query),
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/// (Occur::Must, Box::new(term_of_phrase_query))
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/// ]);
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/// let count4 = searcher.search(&nested_query, &Count)?;
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/// assert_eq!(count4, 1);
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///
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/// // You may call `with_minimum_required_clauses` to
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/// // specify the number of should clauses the returned documents must match.
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/// let minimum_required_query = BooleanQuery::with_minimum_required_clauses(vec![
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/// (Occur::Should, cow_term_query.box_clone()),
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/// (Occur::Should, girl_term_query.box_clone()),
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/// (Occur::Should, diary_term_query.box_clone()),
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/// ], 2);
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/// // Return documents contains "Diary Cow", "Diary Girl" or "Cow Girl"
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/// // Notice: "Diary" isn't "Dairy". ;-)
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/// let count5 = searcher.search(&minimum_required_query, &Count)?;
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/// assert_eq!(count5, 1);
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/// Ok(())
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/// }
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/// ```
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#[derive(Debug)]
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pub struct BooleanQuery {
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subqueries: Vec<(Occur, Box<dyn Query>)>,
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minimum_number_should_match: usize,
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}
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impl Clone for BooleanQuery {
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fn clone(&self) -> Self {
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let subqueries = self
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.subqueries
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.iter()
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.map(|(occur, subquery)| (*occur, subquery.box_clone()))
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.collect::<Vec<_>>();
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Self {
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subqueries,
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minimum_number_should_match: self.minimum_number_should_match,
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}
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}
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}
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impl From<Vec<(Occur, Box<dyn Query>)>> for BooleanQuery {
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fn from(subqueries: Vec<(Occur, Box<dyn Query>)>) -> BooleanQuery {
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BooleanQuery::new(subqueries)
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}
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}
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impl Query for BooleanQuery {
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fn weight(&self, enable_scoring: EnableScoring<'_>) -> crate::Result<Box<dyn Weight>> {
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let sub_weights = self
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.subqueries
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.iter()
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.map(|(occur, subquery)| Ok((*occur, subquery.weight(enable_scoring)?)))
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.collect::<crate::Result<_>>()?;
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Ok(Box::new(BooleanWeight::with_minimum_number_should_match(
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sub_weights,
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self.minimum_number_should_match,
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enable_scoring.is_scoring_enabled(),
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Box::new(SumWithCoordsCombiner::default),
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)))
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}
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fn query_terms<'a>(&'a self, visitor: &mut dyn FnMut(&'a Term, bool)) {
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for (_occur, subquery) in &self.subqueries {
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subquery.query_terms(visitor);
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}
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}
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}
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impl BooleanQuery {
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/// Creates a new boolean query.
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pub fn new(subqueries: Vec<(Occur, Box<dyn Query>)>) -> BooleanQuery {
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// If the bool query includes at least one should clause
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// and no Must or MustNot clauses, the default value is 1. Otherwise, the default value is
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// 0. Keep pace with Elasticsearch.
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let mut minimum_required = 0;
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for (occur, _) in &subqueries {
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match occur {
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Occur::Should => minimum_required = 1,
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Occur::Must | Occur::MustNot => {
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minimum_required = 0;
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break;
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}
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}
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}
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Self::with_minimum_required_clauses(subqueries, minimum_required)
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}
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/// Create a new boolean query with minimum number of required should clauses specified.
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pub fn with_minimum_required_clauses(
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subqueries: Vec<(Occur, Box<dyn Query>)>,
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minimum_number_should_match: usize,
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) -> BooleanQuery {
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BooleanQuery {
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subqueries,
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minimum_number_should_match,
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}
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}
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/// Getter for `minimum_number_should_match`
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pub fn get_minimum_number_should_match(&self) -> usize {
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self.minimum_number_should_match
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}
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/// Setter for `minimum_number_should_match`
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pub fn set_minimum_number_should_match(&mut self, minimum_number_should_match: usize) {
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self.minimum_number_should_match = minimum_number_should_match;
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}
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/// Returns the intersection of the queries.
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pub fn intersection(queries: Vec<Box<dyn Query>>) -> BooleanQuery {
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let subqueries = queries.into_iter().map(|s| (Occur::Must, s)).collect();
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BooleanQuery::new(subqueries)
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}
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/// Returns the union of the queries.
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pub fn union(queries: Vec<Box<dyn Query>>) -> BooleanQuery {
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let subqueries = queries.into_iter().map(|s| (Occur::Should, s)).collect();
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BooleanQuery::new(subqueries)
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}
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/// Returns the union of the queries with minimum required clause.
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pub fn union_with_minimum_required_clauses(
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queries: Vec<Box<dyn Query>>,
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minimum_required_clauses: usize,
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) -> BooleanQuery {
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let subqueries = queries
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.into_iter()
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.map(|sub_query| (Occur::Should, sub_query))
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.collect();
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BooleanQuery::with_minimum_required_clauses(subqueries, minimum_required_clauses)
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}
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/// Helper method to create a boolean query matching a given list of terms.
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/// The resulting query is a disjunction of the terms.
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pub fn new_multiterms_query(terms: Vec<Term>) -> BooleanQuery {
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let occur_term_queries: Vec<(Occur, Box<dyn Query>)> = terms
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.into_iter()
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.map(|term| {
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let term_query: Box<dyn Query> =
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Box::new(TermQuery::new(term, IndexRecordOption::WithFreqs));
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(Occur::Should, term_query)
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})
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.collect();
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BooleanQuery::new(occur_term_queries)
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}
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/// Deconstructed view of the clauses making up this query.
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pub fn clauses(&self) -> &[(Occur, Box<dyn Query>)] {
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&self.subqueries[..]
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}
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}
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#[cfg(test)]
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mod tests {
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use std::collections::HashSet;
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use super::BooleanQuery;
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use crate::collector::{Count, DocSetCollector};
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use crate::query::{Query, QueryClone, QueryParser, TermQuery};
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use crate::schema::{Field, IndexRecordOption, Schema, TEXT};
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use crate::{DocAddress, DocId, Index, Term};
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fn create_test_index() -> crate::Result<Index> {
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let mut schema_builder = Schema::builder();
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let text = schema_builder.add_text_field("text", TEXT);
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let schema = schema_builder.build();
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let index = Index::create_in_ram(schema);
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let mut writer = index.writer_for_tests()?;
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writer.add_document(doc!(text=>"b c"))?;
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writer.add_document(doc!(text=>"a c"))?;
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writer.add_document(doc!(text=>"a b"))?;
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writer.add_document(doc!(text=>"a d"))?;
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writer.commit()?;
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Ok(index)
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}
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#[test]
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fn test_minimum_required() -> crate::Result<()> {
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fn create_test_index_with<T: IntoIterator<Item = &'static str>>(
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docs: T,
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) -> crate::Result<Index> {
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let mut schema_builder = Schema::builder();
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let text = schema_builder.add_text_field("text", TEXT);
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let schema = schema_builder.build();
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let index = Index::create_in_ram(schema);
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let mut writer = index.writer_for_tests()?;
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for doc in docs {
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writer.add_document(doc!(text => doc))?;
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}
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writer.commit()?;
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Ok(index)
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}
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fn create_boolean_query_with_mr<T: IntoIterator<Item = &'static str>>(
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queries: T,
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field: Field,
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mr: usize,
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) -> BooleanQuery {
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let terms = queries
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.into_iter()
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.map(|t| Term::from_field_text(field, t))
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.map(|t| TermQuery::new(t, IndexRecordOption::Basic))
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.map(|q| -> Box<dyn Query> { Box::new(q) })
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.collect();
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BooleanQuery::union_with_minimum_required_clauses(terms, mr)
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}
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fn check_doc_id<T: IntoIterator<Item = DocId>>(
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expected: T,
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actually: HashSet<DocAddress>,
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seg: u32,
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) {
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assert_eq!(
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actually,
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expected
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.into_iter()
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.map(|id| DocAddress::new(seg, id))
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.collect()
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);
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}
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let index = create_test_index_with(["a b c", "a c e", "d f g", "z z z", "c i b"])?;
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let searcher = index.reader()?.searcher();
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let text = index.schema().get_field("text").unwrap();
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// Documents contains 'a c' 'a z' 'a i' 'c z' 'c i' or 'z i' shall be return.
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let q1 = create_boolean_query_with_mr(["a", "c", "z", "i"], text, 2);
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let docs = searcher.search(&q1, &DocSetCollector)?;
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check_doc_id([0, 1, 4], docs, 0);
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// Documents contains 'a b c', 'a b e', 'a c e' or 'b c e' shall be return.
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let q2 = create_boolean_query_with_mr(["a", "b", "c", "e"], text, 3);
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let docs = searcher.search(&q2, &DocSetCollector)?;
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check_doc_id([0, 1], docs, 0);
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// Nothing queried since minimum_required is too large.
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let q3 = create_boolean_query_with_mr(["a", "b"], text, 3);
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let docs = searcher.search(&q3, &DocSetCollector)?;
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assert!(docs.is_empty());
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// When mr is set to zero or one, there are no difference with `Boolean::Union`.
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let q4 = create_boolean_query_with_mr(["a", "z"], text, 1);
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let docs = searcher.search(&q4, &DocSetCollector)?;
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check_doc_id([0, 1, 3], docs, 0);
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let q5 = create_boolean_query_with_mr(["a", "b"], text, 0);
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let docs = searcher.search(&q5, &DocSetCollector)?;
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check_doc_id([0, 1, 4], docs, 0);
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Ok(())
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}
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#[test]
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fn test_union() -> crate::Result<()> {
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let index = create_test_index()?;
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let searcher = index.reader()?.searcher();
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let text = index.schema().get_field("text").unwrap();
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let term_a = TermQuery::new(Term::from_field_text(text, "a"), IndexRecordOption::Basic);
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let term_d = TermQuery::new(Term::from_field_text(text, "d"), IndexRecordOption::Basic);
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let union_ad = BooleanQuery::union(vec![term_a.box_clone(), term_d.box_clone()]);
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let docs = searcher.search(&union_ad, &DocSetCollector)?;
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assert_eq!(
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docs,
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vec![
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DocAddress::new(0u32, 1u32),
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DocAddress::new(0u32, 2u32),
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DocAddress::new(0u32, 3u32)
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]
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.into_iter()
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.collect()
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);
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Ok(())
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}
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#[test]
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fn test_intersection() -> crate::Result<()> {
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let index = create_test_index()?;
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let searcher = index.reader()?.searcher();
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let text = index.schema().get_field("text").unwrap();
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let term_a = TermQuery::new(Term::from_field_text(text, "a"), IndexRecordOption::Basic);
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let term_b = TermQuery::new(Term::from_field_text(text, "b"), IndexRecordOption::Basic);
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let term_c = TermQuery::new(Term::from_field_text(text, "c"), IndexRecordOption::Basic);
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let intersection_ab =
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BooleanQuery::intersection(vec![term_a.box_clone(), term_b.box_clone()]);
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let intersection_ac =
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BooleanQuery::intersection(vec![term_a.box_clone(), term_c.box_clone()]);
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let intersection_bc =
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BooleanQuery::intersection(vec![term_b.box_clone(), term_c.box_clone()]);
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{
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let docs = searcher.search(&intersection_ab, &DocSetCollector)?;
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assert_eq!(
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docs,
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vec![DocAddress::new(0u32, 2u32)].into_iter().collect()
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);
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}
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{
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let docs = searcher.search(&intersection_ac, &DocSetCollector)?;
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assert_eq!(
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docs,
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vec![DocAddress::new(0u32, 1u32)].into_iter().collect()
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);
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}
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{
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let docs = searcher.search(&intersection_bc, &DocSetCollector)?;
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assert_eq!(
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docs,
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vec![DocAddress::new(0u32, 0u32)].into_iter().collect()
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);
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}
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Ok(())
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}
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#[test]
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pub fn test_json_array_pitfall_bag_of_terms() -> crate::Result<()> {
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let mut schema_builder = Schema::builder();
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let json_field = schema_builder.add_json_field("json", TEXT);
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let schema = schema_builder.build();
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let index = Index::create_in_ram(schema);
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{
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let mut index_writer = index.writer_for_tests()?;
|
|
index_writer.add_document(doc!(json_field=>json!({
|
|
"cart": [
|
|
{"product_type": "sneakers", "attributes": {"color": "white"}},
|
|
{"product_type": "t-shirt", "attributes": {"color": "red"}},
|
|
{"product_type": "cd", "attributes": {"genre": "blues"}},
|
|
]
|
|
})))?;
|
|
index_writer.commit()?;
|
|
}
|
|
let searcher = index.reader()?.searcher();
|
|
let doc_matches = |query: &str| {
|
|
let query_parser = QueryParser::for_index(&index, vec![json_field]);
|
|
let query = query_parser.parse_query(query).unwrap();
|
|
searcher.search(&query, &Count).unwrap() == 1
|
|
};
|
|
// As expected
|
|
assert!(doc_matches(
|
|
r#"cart.product_type:sneakers AND cart.attributes.color:white"#
|
|
));
|
|
// Unexpected match, due to the fact that array do not act as nested docs.
|
|
assert!(doc_matches(
|
|
r#"cart.product_type:sneakers AND cart.attributes.color:red"#
|
|
));
|
|
// However, bviously this works...
|
|
assert!(!doc_matches(
|
|
r#"cart.product_type:sneakers AND cart.attributes.color:blues"#
|
|
));
|
|
Ok(())
|
|
}
|
|
}
|