mirror of
https://github.com/meilisearch/MeiliSearch
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3009981d31
Add clippy job Add clippy job to CI
179 lines
6.5 KiB
Rust
179 lines
6.5 KiB
Rust
use std::cmp::Ordering;
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use std::collections::{BinaryHeap, HashMap};
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use std::fs::File;
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use std::{cmp, io, mem, str, vec};
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use super::helpers::{
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create_sorter, merge_cbo_roaring_bitmaps, read_u32_ne_bytes, sorter_into_reader,
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try_split_array_at, GrenadParameters, MergeFn,
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};
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use crate::error::SerializationError;
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use crate::index::db_name::DOCID_WORD_POSITIONS;
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use crate::proximity::{positions_proximity, MAX_DISTANCE};
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use crate::{DocumentId, Result};
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/// Extracts the best proximity between pairs of words and the documents ids where this pair appear.
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///
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/// Returns a grenad reader with the list of extracted word pairs proximities and
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/// documents ids from the given chunk of docid word positions.
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#[logging_timer::time]
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pub fn extract_word_pair_proximity_docids<R: io::Read + io::Seek>(
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docid_word_positions: grenad::Reader<R>,
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indexer: GrenadParameters,
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) -> Result<grenad::Reader<File>> {
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let max_memory = indexer.max_memory_by_thread();
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let mut word_pair_proximity_docids_sorter = create_sorter(
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grenad::SortAlgorithm::Unstable,
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merge_cbo_roaring_bitmaps,
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indexer.chunk_compression_type,
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indexer.chunk_compression_level,
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indexer.max_nb_chunks,
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max_memory.map(|m| m / 2),
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);
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// This map is assumed to not consume a lot of memory.
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let mut document_word_positions_heap = BinaryHeap::new();
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let mut current_document_id = None;
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let mut cursor = docid_word_positions.into_cursor()?;
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while let Some((key, value)) = cursor.move_on_next()? {
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let (document_id_bytes, word_bytes) = try_split_array_at(key)
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.ok_or(SerializationError::Decoding { db_name: Some(DOCID_WORD_POSITIONS) })?;
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let document_id = u32::from_be_bytes(document_id_bytes);
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let word = str::from_utf8(word_bytes)?;
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let curr_document_id = *current_document_id.get_or_insert(document_id);
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if curr_document_id != document_id {
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let document_word_positions_heap = mem::take(&mut document_word_positions_heap);
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document_word_positions_into_sorter(
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curr_document_id,
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document_word_positions_heap,
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&mut word_pair_proximity_docids_sorter,
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)?;
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current_document_id = Some(document_id);
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}
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let word = word.to_string();
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let mut positions: Vec<_> = read_u32_ne_bytes(value).collect();
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positions.sort_unstable();
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let mut iter = positions.into_iter();
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if let Some(position) = iter.next() {
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document_word_positions_heap.push(PeekedWordPosition { word, position, iter });
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}
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}
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if let Some(document_id) = current_document_id {
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// We must make sure that don't lose the current document field id
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// word count map if we break because we reached the end of the chunk.
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let document_word_positions_heap = mem::take(&mut document_word_positions_heap);
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document_word_positions_into_sorter(
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document_id,
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document_word_positions_heap,
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&mut word_pair_proximity_docids_sorter,
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)?;
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}
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sorter_into_reader(word_pair_proximity_docids_sorter, indexer)
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}
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/// Fills the list of all pairs of words with the shortest proximity between 1 and 7 inclusive.
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///
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/// This list is used by the engine to calculate the documents containing words that are
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/// close to each other.
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fn document_word_positions_into_sorter(
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document_id: DocumentId,
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mut word_positions_heap: BinaryHeap<PeekedWordPosition<vec::IntoIter<u32>>>,
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word_pair_proximity_docids_sorter: &mut grenad::Sorter<MergeFn>,
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) -> Result<()> {
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let mut word_pair_proximity = HashMap::new();
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let mut ordered_peeked_word_positions = Vec::new();
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while !word_positions_heap.is_empty() {
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while let Some(peeked_word_position) = word_positions_heap.pop() {
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ordered_peeked_word_positions.push(peeked_word_position);
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if ordered_peeked_word_positions.len() == 7 {
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break;
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}
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}
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if let Some((head, tail)) = ordered_peeked_word_positions.split_first() {
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for PeekedWordPosition { word, position, .. } in tail {
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let prox = positions_proximity(head.position, *position);
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if prox > 0 && prox < MAX_DISTANCE {
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word_pair_proximity
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.entry((head.word.clone(), word.clone()))
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.and_modify(|p| {
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*p = cmp::min(*p, prox);
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})
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.or_insert(prox);
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}
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}
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// Push the tail in the heap.
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let tail_iter = ordered_peeked_word_positions.drain(1..);
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word_positions_heap.extend(tail_iter);
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// Advance the head and push it in the heap.
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if let Some(mut head) = ordered_peeked_word_positions.pop() {
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if let Some(next_position) = head.iter.next() {
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let prox = positions_proximity(head.position, next_position);
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if prox > 0 && prox < MAX_DISTANCE {
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word_pair_proximity
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.entry((head.word.clone(), head.word.clone()))
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.and_modify(|p| {
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*p = cmp::min(*p, prox);
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})
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.or_insert(prox);
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}
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word_positions_heap.push(PeekedWordPosition {
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word: head.word,
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position: next_position,
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iter: head.iter,
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});
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}
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}
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}
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}
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let mut key_buffer = Vec::new();
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for ((w1, w2), prox) in word_pair_proximity {
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key_buffer.clear();
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key_buffer.push(prox as u8);
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key_buffer.extend_from_slice(w1.as_bytes());
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key_buffer.push(0);
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key_buffer.extend_from_slice(w2.as_bytes());
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word_pair_proximity_docids_sorter.insert(&key_buffer, document_id.to_ne_bytes())?;
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}
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Ok(())
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}
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struct PeekedWordPosition<I> {
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word: String,
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position: u32,
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iter: I,
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}
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impl<I> Ord for PeekedWordPosition<I> {
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fn cmp(&self, other: &Self) -> Ordering {
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self.position.cmp(&other.position).reverse()
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}
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}
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impl<I> PartialOrd for PeekedWordPosition<I> {
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fn partial_cmp(&self, other: &Self) -> Option<Ordering> {
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Some(self.cmp(other))
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}
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}
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impl<I> Eq for PeekedWordPosition<I> {}
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impl<I> PartialEq for PeekedWordPosition<I> {
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fn eq(&self, other: &Self) -> bool {
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self.position == other.position
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}
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}
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