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Use a vecDeque in wpp database
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parent
df9e5c8651
commit
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@ -1,5 +1,5 @@
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use std::cmp::Ordering;
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use std::collections::HashMap;
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use std::collections::{HashMap, VecDeque};
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use std::fs::File;
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use std::io::BufReader;
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use std::{cmp, io};
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@ -37,7 +37,8 @@ pub fn extract_word_pair_proximity_docids<R: io::Read + io::Seek>(
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max_memory.map(|m| m / 2),
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);
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let mut word_positions: Vec<(String, u16)> = Vec::with_capacity(MAX_DISTANCE as usize);
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let mut word_positions: VecDeque<(String, u16)> =
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VecDeque::with_capacity(MAX_DISTANCE as usize);
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let mut word_pair_proximity = HashMap::new();
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let mut current_document_id = None;
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@ -80,7 +81,7 @@ pub fn extract_word_pair_proximity_docids<R: io::Read + io::Seek>(
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// insert the new word.
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let word = std::str::from_utf8(word)?;
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word_positions.push((word.to_string(), position));
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word_positions.push_back((word.to_string(), position));
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}
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}
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@ -123,10 +124,10 @@ fn document_word_positions_into_sorter(
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}
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fn word_positions_into_word_pair_proximity(
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word_positions: &mut Vec<(String, u16)>,
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word_positions: &mut VecDeque<(String, u16)>,
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word_pair_proximity: &mut HashMap<(String, String), u8>,
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) -> Result<()> {
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let (head_word, head_position) = word_positions.remove(0);
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let (head_word, head_position) = word_positions.pop_front().unwrap();
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for (word, position) in word_positions.iter() {
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let prox = positions_proximity(head_position as u32, *position as u32) as u8;
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word_pair_proximity
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@ -138,29 +139,3 @@ fn word_positions_into_word_pair_proximity(
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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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