mirror of
https://github.com/meilisearch/meilisearch.git
synced 2024-11-29 08:35:15 +08:00
feat: Introduce a way to distinct documents
This commit is contained in:
parent
3acac1458f
commit
37c709c9a9
@ -117,14 +117,14 @@ impl CsvIndexer {
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}
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}
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fn insert_document_words<'a, I, A, B>(builder: &mut MetadataBuilder<A, B>, doc_index: u64, attr: u8, words: I)
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fn insert_document_words<'a, I, A, B>(builder: &mut MetadataBuilder<A, B>, doc_id: u64, attr: u8, words: I)
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where A: io::Write,
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B: io::Write,
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I: IntoIterator<Item=(usize, &'a str)>,
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{
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for (index, word) in words {
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let doc_index = DocIndex {
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document: doc_index,
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document_id: doc_id,
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attribute: attr,
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attribute_index: index as u32,
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};
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@ -122,14 +122,14 @@ impl JsonLinesIndexer {
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}
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}
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fn insert_document_words<'a, I, A, B>(builder: &mut MetadataBuilder<A, B>, doc_index: u64, attr: u8, words: I)
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fn insert_document_words<'a, I, A, B>(builder: &mut MetadataBuilder<A, B>, doc_id: u64, attr: u8, words: I)
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where A: io::Write,
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B: io::Write,
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I: IntoIterator<Item=(usize, &'a str)>,
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{
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for (index, word) in words {
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let doc_index = DocIndex {
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document: doc_index,
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document_id: doc_id,
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attribute: attr,
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attribute_index: index as u32,
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};
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@ -5,8 +5,8 @@ use std::path::PathBuf;
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use elapsed::measure_time;
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use rocksdb::{DB, DBOptions, IngestExternalFileOptions};
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use raptor::rank::{criterion, Config, RankedStream, Document};
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use raptor::{automaton, Metadata, CommonWords};
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use raptor::rank::{criterion, RankedStreamBuilder};
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#[derive(Debug, StructOpt)]
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pub struct CommandConsole {
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@ -62,6 +62,13 @@ impl ConsoleSearch {
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}
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}
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// "Sony" "PlayStation 4 500GB"
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fn starts_with_playstation(doc: &Document, database: &DB) -> Vec<u8> {
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let title_key = format!("{}-title", doc.id);
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let title = database.get(title_key.as_bytes()).unwrap().unwrap();
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title.get(0..4).map(|s| s.to_vec()).unwrap_or(Vec::new())
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}
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fn search(metadata: &Metadata, database: &DB, common_words: &CommonWords, query: &str) {
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let mut automatons = Vec::new();
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for query in query.split_whitespace().filter(|q| !common_words.contains(*q)) {
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@ -69,10 +76,15 @@ fn search(metadata: &Metadata, database: &DB, common_words: &CommonWords, query:
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automatons.push(lev);
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}
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let mut builder = RankedStreamBuilder::new(metadata, automatons);
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builder.criteria(criterion::default());
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let config = Config {
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metadata: metadata,
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automatons: automatons,
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criteria: criterion::default(),
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distinct: ((), 1),
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};
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let stream = RankedStream::new(config);
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let mut stream = builder.build();
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// let documents = stream.retrieve_distinct_documents(|doc| starts_with_playstation(doc, database), 0..20);
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let documents = stream.retrieve_documents(0..20);
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for document in documents {
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@ -7,11 +7,10 @@ use std::path::PathBuf;
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use std::error::Error;
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use std::sync::Arc;
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use raptor::rank::{criterion, RankedStreamBuilder};
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use raptor::rank::{criterion, Config, RankedStream};
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use raptor::{automaton, Metadata, CommonWords};
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use rocksdb::{DB, DBOptions, IngestExternalFileOptions};
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use warp::Filter;
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use structopt::StructOpt;
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#[derive(Debug, StructOpt)]
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@ -99,10 +98,14 @@ where M: AsRef<Metadata>,
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automatons.push(lev);
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}
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let mut builder = RankedStreamBuilder::new(metadata.as_ref(), automatons);
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builder.criteria(criterion::default());
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let config = Config {
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metadata: metadata.as_ref(),
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automatons: automatons,
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criteria: criterion::default(),
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distinct: ((), 1),
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};
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let stream = RankedStream::new(config);
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let mut stream = builder.build();
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let documents = stream.retrieve_documents(0..20);
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let mut body = Vec::new();
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@ -24,7 +24,7 @@ pub type DocumentId = u64;
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#[repr(C)]
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pub struct DocIndex {
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/// The document identifier where the word was found.
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pub document: DocumentId,
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pub document_id: DocumentId,
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/// The attribute identifier in the document
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/// where the word was found.
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@ -7,7 +7,6 @@ mod exact;
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use std::vec;
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use std::cmp::Ordering;
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use std::ops::Deref;
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use crate::rank::Document;
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pub use self::{
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@ -31,21 +30,21 @@ pub trait Criterion {
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impl<'a, T: Criterion + ?Sized> Criterion for &'a T {
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fn evaluate(&self, lhs: &Document, rhs: &Document) -> Ordering {
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self.deref().evaluate(lhs, rhs)
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(**self).evaluate(lhs, rhs)
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}
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fn eq(&self, lhs: &Document, rhs: &Document) -> bool {
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self.deref().eq(lhs, rhs)
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(**self).eq(lhs, rhs)
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}
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}
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impl<T: Criterion + ?Sized> Criterion for Box<T> {
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fn evaluate(&self, lhs: &Document, rhs: &Document) -> Ordering {
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self.deref().evaluate(lhs, rhs)
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(**self).evaluate(lhs, rhs)
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}
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fn eq(&self, lhs: &Document, rhs: &Document) -> bool {
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self.deref().eq(lhs, rhs)
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(**self).eq(lhs, rhs)
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}
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}
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@ -3,7 +3,7 @@ mod ranked_stream;
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use crate::{Match, DocumentId};
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pub use self::ranked_stream::{RankedStreamBuilder, RankedStream};
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pub use self::ranked_stream::{Config, RankedStream};
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#[inline]
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fn match_query_index(a: &Match, b: &Match) -> bool {
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@ -1,6 +1,8 @@
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use std::collections::HashMap;
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use std::hash::Hash;
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use std::ops::Range;
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use std::rc::Rc;
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use std::{mem, vec, cmp};
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use std::{mem, vec};
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use fnv::FnvHashMap;
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use fst::Streamer;
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@ -9,52 +11,41 @@ use group_by::GroupByMut;
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use crate::automaton::{DfaExt, AutomatonExt};
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use crate::metadata::Metadata;
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use crate::metadata::ops::OpBuilder;
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use crate::rank::criterion::Criterion;
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use crate::rank::criterion::{self, Criterion};
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use crate::rank::Document;
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use crate::Match;
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use crate::{Match, DocumentId};
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#[derive(Clone)]
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pub struct RankedStreamBuilder<'m, C> {
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metadata: &'m Metadata,
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automatons: Vec<Rc<DfaExt>>,
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criteria: Vec<C>,
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pub struct Config<'m, C, F> {
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pub metadata: &'m Metadata,
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pub automatons: Vec<DfaExt>,
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pub criteria: Vec<C>,
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pub distinct: (F, usize),
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}
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impl<'m, C> RankedStreamBuilder<'m, C> {
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pub fn new(metadata: &'m Metadata, automatons: Vec<DfaExt>) -> Self {
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RankedStreamBuilder {
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metadata: metadata,
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automatons: automatons.into_iter().map(Rc::new).collect(),
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criteria: Vec::new(), // hummm... prefer the criterion::default() ones !
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}
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}
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pub struct RankedStream<'m, C, F> {
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stream: crate::metadata::ops::Union<'m>,
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automatons: Vec<Rc<DfaExt>>,
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criteria: Vec<C>,
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distinct: (F, usize),
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}
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pub fn criteria(&mut self, criteria: Vec<C>) {
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self.criteria = criteria;
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}
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pub fn build(&self) -> RankedStream<C> {
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let mut builder = OpBuilder::with_automatons(self.automatons.clone());
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builder.push(self.metadata);
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impl<'m, C, F> RankedStream<'m, C, F> {
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pub fn new(config: Config<'m, C, F>) -> Self {
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let automatons: Vec<_> = config.automatons.into_iter().map(Rc::new).collect();
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let mut builder = OpBuilder::with_automatons(automatons.clone());
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builder.push(config.metadata);
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RankedStream {
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stream: builder.union(),
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automatons: &self.automatons,
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criteria: &self.criteria,
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automatons: automatons,
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criteria: config.criteria,
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distinct: config.distinct,
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}
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}
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}
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pub struct RankedStream<'a, 'm, C> {
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stream: crate::metadata::ops::Union<'m>,
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automatons: &'a [Rc<DfaExt>],
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criteria: &'a [C],
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}
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impl<'a, 'm, C> RankedStream<'a, 'm, C> {
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pub fn retrieve_documents(&mut self, range: Range<usize>) -> Vec<Document>
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where C: Criterion
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{
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impl<'m, C, F> RankedStream<'m, C, F> {
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fn retrieve_all_documents(&mut self) -> Vec<Document> {
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let mut matches = FnvHashMap::default();
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while let Some((string, indexed_values)) = self.stream.next() {
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@ -63,55 +54,133 @@ impl<'a, 'm, C> RankedStream<'a, 'm, C> {
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let distance = automaton.eval(string).to_u8();
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let is_exact = distance == 0 && string.len() == automaton.query_len();
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for di in iv.doc_indexes.as_slice() {
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for doc_index in iv.doc_indexes.as_slice() {
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let match_ = Match {
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query_index: iv.index as u32,
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distance: distance,
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attribute: di.attribute,
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attribute_index: di.attribute_index,
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attribute: doc_index.attribute,
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attribute_index: doc_index.attribute_index,
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is_exact: is_exact,
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};
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matches.entry(di.document).or_insert_with(Vec::new).push(match_);
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matches.entry(doc_index.document_id).or_insert_with(Vec::new).push(match_);
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}
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}
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}
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// collect matches from an HashMap into a Vec
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let mut documents: Vec<_> = matches.into_iter().map(|(id, mut matches)| {
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matches.into_iter().map(|(id, mut matches)| {
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matches.sort_unstable();
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unsafe { Document::from_sorted_matches(id, matches) }
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}).collect();
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}).collect()
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}
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}
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impl<'a, C, F> RankedStream<'a, C, F>
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where C: Criterion
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{
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pub fn retrieve_documents(mut self, range: Range<usize>) -> Vec<Document> {
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let mut documents = self.retrieve_all_documents();
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let mut groups = vec![documents.as_mut_slice()];
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for criterion in self.criteria {
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let tmp_groups = mem::replace(&mut groups, Vec::new());
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let mut current_range = Range { start: 0, end: 0 };
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'grp: for group in tmp_groups {
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current_range.end += group.len();
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// if a part of the current group is in the range returned
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// we must sort it and emit the sub-groups
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if current_range.contains(&range.start) {
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for group in tmp_groups {
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group.sort_unstable_by(|a, b| criterion.evaluate(a, b));
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for group in GroupByMut::new(group, |a, b| criterion.eq(a, b)) {
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groups.push(group);
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if current_range.end >= range.end { break 'grp }
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}
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} else {
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groups.push(group)
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}
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current_range.start = current_range.end;
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}
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}
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// TODO find a better algorithm, here we allocate for too many documents
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// and we do a useless allocation, we should reuse the documents Vec
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let start = cmp::min(range.start, documents.len());
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let mut documents = documents.split_off(start);
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documents.truncate(range.len());
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documents
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documents[range].to_vec()
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}
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pub fn retrieve_distinct_documents<K>(mut self, range: Range<usize>) -> Vec<Document>
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where F: Fn(&DocumentId) -> K,
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K: Hash + Eq,
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{
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let mut documents = self.retrieve_all_documents();
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let mut groups = vec![documents.as_mut_slice()];
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for criterion in self.criteria {
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let tmp_groups = mem::replace(&mut groups, Vec::new());
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for group in tmp_groups {
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group.sort_unstable_by(|a, b| criterion.evaluate(a, b));
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for group in GroupByMut::new(group, |a, b| criterion.eq(a, b)) {
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groups.push(group);
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}
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}
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}
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let mut out_documents = Vec::with_capacity(range.len());
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let (distinct, limit) = self.distinct;
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let mut seen = DistinctMap::new(limit);
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for document in documents {
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let key = distinct(&document.id);
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let accepted = seen.digest(key);
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if accepted {
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if seen.len() == range.end { break }
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if seen.len() >= range.start {
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out_documents.push(document);
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}
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}
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}
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out_documents
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}
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}
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pub struct DistinctMap<K> {
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inner: HashMap<K, usize>,
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limit: usize,
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len: usize,
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}
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impl<K: Hash + Eq> DistinctMap<K> {
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pub fn new(limit: usize) -> Self {
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DistinctMap {
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inner: HashMap::new(),
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limit: limit,
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len: 0,
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}
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}
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pub fn digest(&mut self, key: K) -> bool {
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let seen = self.inner.entry(key).or_insert(0);
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if *seen < self.limit { *seen += 1; self.len += 1; true } else { false }
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}
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pub fn len(&self) -> usize {
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self.len
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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 super::*;
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#[test]
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fn easy_distinct_map() {
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let mut map = DistinctMap::new(2);
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for x in &[1, 1, 1, 2, 3, 4, 5, 6, 6, 6, 6, 6] {
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map.digest(x);
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}
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assert_eq!(map.len(), 8);
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let mut map = DistinctMap::new(2);
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assert_eq!(map.digest(1), true);
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assert_eq!(map.digest(1), true);
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assert_eq!(map.digest(1), false);
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assert_eq!(map.digest(1), false);
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assert_eq!(map.digest(2), true);
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assert_eq!(map.digest(3), true);
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assert_eq!(map.digest(2), true);
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assert_eq!(map.digest(2), false);
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assert_eq!(map.len(), 5);
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}
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}
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