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e1679f3fb9
* compact doc * add any value type * pass references when building CompactDoc * remove OwnedValue from API * clippy * clippy * fail on large documents * fmt * cleanup * cleanup * implement Value for different types fix serde_json date Value implementation * fmt * cleanup * fmt * cleanup * store positions instead of pos+len * remove nodes array * remove mediumvec * cleanup * infallible serialize into vec * remove positions indirection * remove 24MB limitation in document use u32 for Addr Remove the 3 byte addressing limitation and use VInt instead * cleanup * extend test * cleanup, add comments * rename, remove pub
105 lines
3.7 KiB
Rust
105 lines
3.7 KiB
Rust
// # Faceted Search With Tweak Score
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//
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// This example covers the faceted search functionalities of
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// tantivy.
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//
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// We will :
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// - define a text field "name" in our schema
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// - define a facet field "classification" in our schema
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use std::collections::HashSet;
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use tantivy::collector::TopDocs;
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use tantivy::query::BooleanQuery;
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use tantivy::schema::*;
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use tantivy::{doc, DocId, Index, IndexWriter, Score, SegmentReader};
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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", STORED);
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let ingredient = schema_builder.add_facet_field("ingredient", FacetOptions::default());
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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 index_writer: IndexWriter = index.writer(30_000_000)?;
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index_writer.add_document(doc!(
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title => "Fried egg",
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ingredient => Facet::from("/ingredient/egg"),
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ingredient => Facet::from("/ingredient/oil"),
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))?;
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index_writer.add_document(doc!(
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title => "Scrambled egg",
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ingredient => Facet::from("/ingredient/egg"),
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ingredient => Facet::from("/ingredient/butter"),
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ingredient => Facet::from("/ingredient/milk"),
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ingredient => Facet::from("/ingredient/salt"),
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))?;
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index_writer.add_document(doc!(
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title => "Egg rolls",
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ingredient => Facet::from("/ingredient/egg"),
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ingredient => Facet::from("/ingredient/garlic"),
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ingredient => Facet::from("/ingredient/salt"),
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ingredient => Facet::from("/ingredient/oil"),
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ingredient => Facet::from("/ingredient/tortilla-wrap"),
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ingredient => Facet::from("/ingredient/mushroom"),
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))?;
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index_writer.commit()?;
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let reader = index.reader()?;
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let searcher = reader.searcher();
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{
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let facets = [
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Facet::from("/ingredient/egg"),
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Facet::from("/ingredient/oil"),
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Facet::from("/ingredient/garlic"),
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Facet::from("/ingredient/mushroom"),
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];
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let query = BooleanQuery::new_multiterms_query(
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facets
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.iter()
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.map(|key| Term::from_facet(ingredient, key))
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.collect(),
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);
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let top_docs_by_custom_score =
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// Call TopDocs with a custom tweak score
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TopDocs::with_limit(2).tweak_score(move |segment_reader: &SegmentReader| {
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let ingredient_reader = segment_reader.facet_reader("ingredient").unwrap();
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let facet_dict = ingredient_reader.facet_dict();
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let query_ords: HashSet<u64> = facets
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.iter()
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.filter_map(|key| facet_dict.term_ord(key.encoded_str()).unwrap())
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.collect();
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move |doc: DocId, original_score: Score| {
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// Update the original score with a tweaked score
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let missing_ingredients = ingredient_reader
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.facet_ords(doc)
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.filter(|ord| !query_ords.contains(ord))
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.count();
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let tweak = 1.0 / 4_f32.powi(missing_ingredients as i32);
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original_score * tweak
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}
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});
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let top_docs = searcher.search(&query, &top_docs_by_custom_score)?;
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let titles: Vec<String> = top_docs
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.iter()
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.map(|(_, doc_id)| {
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searcher
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.doc::<TantivyDocument>(*doc_id)
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.unwrap()
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.get_first(title)
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.and_then(|v| v.as_str().map(|el| el.to_string()))
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.unwrap()
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})
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.collect();
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assert_eq!(titles, vec!["Fried egg", "Egg rolls"]);
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}
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Ok(())
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}
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