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https://github.com/meilisearch/MeiliSearch
synced 2024-12-24 13:40:31 +01:00
Reduce the deepness of the word position document ids
This helps reduce the number of allocations.
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parent
7178b6c2c4
commit
b12bfcb03b
@ -1,5 +1,5 @@
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use std::collections::hash_map::Entry;
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use std::collections::{HashMap, BTreeSet, BTreeMap};
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use std::collections::{HashMap, BTreeSet};
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use std::convert::{TryFrom, TryInto};
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use std::fs::File;
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use std::path::PathBuf;
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@ -11,11 +11,12 @@ use fst::{Streamer, IntoStreamer};
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use heed::EnvOpenOptions;
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use heed::types::*;
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use oxidized_mtbl::{Reader, ReaderOptions, Writer, Merger, MergerOptions};
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use rayon::prelude::*;
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use roaring::RoaringBitmap;
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use slice_group_by::StrGroupBy;
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use structopt::StructOpt;
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use mega_mini_indexer::{FastMap4, SmallVec32, Index, DocumentId, AttributeId};
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use mega_mini_indexer::{FastMap4, SmallVec32, Index, DocumentId, Position};
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const LMDB_MAX_KEY_LENGTH: usize = 512;
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const ONE_MILLION: usize = 1_000_000;
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@ -50,8 +51,8 @@ struct Opt {
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struct Indexed {
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fst: fst::Set<Vec<u8>>,
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postings_attrs: FastMap4<SmallVec32<u8>, RoaringBitmap>,
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postings_ids: FastMap4<SmallVec32<u8>, FastMap4<AttributeId, RoaringBitmap>>,
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word_positions: FastMap4<SmallVec32<u8>, RoaringBitmap>,
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word_position_docids: FastMap4<(SmallVec32<u8>, Position), RoaringBitmap>,
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headers: Vec<u8>,
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documents: Vec<(DocumentId, Vec<u8>)>,
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}
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@ -79,12 +80,12 @@ impl MtblKvStore {
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// we iterate over the fst to read the words in order
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let mut stream = indexed.fst.stream();
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while let Some(word) = stream.next() {
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if let Some(attrs) = indexed.postings_attrs.remove(word) {
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if let Some(positions) = indexed.word_positions.get(word) {
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key.truncate(1);
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key.extend_from_slice(word);
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// We serialize the attrs ids into a buffer
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// We serialize the positions into a buffer
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buffer.clear();
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attrs.serialize_into(&mut buffer)?;
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positions.serialize_into(&mut buffer)?;
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// that we write under the generated key into MTBL
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out.add(&key, &buffer).unwrap();
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}
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@ -98,26 +99,27 @@ impl MtblKvStore {
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while let Some(word) = stream.next() {
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key.truncate(1);
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key.extend_from_slice(word);
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if let Some(attrs) = indexed.postings_ids.remove(word) {
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let attrs: BTreeMap<_, _> = attrs.into_iter().collect();
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if let Some(positions) = indexed.word_positions.remove(word) {
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// We iterate over all the attributes containing the documents ids
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for (attr, ids) in attrs {
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// we postfix the word by the attribute id
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key.extend_from_slice(&attr.to_be_bytes());
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for pos in positions {
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let ids = indexed.word_position_docids.remove(&(SmallVec32::from(word), pos)).unwrap();
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// we postfix the word by the positions it appears in
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let position_bytes = pos.to_be_bytes();
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key.extend_from_slice(&position_bytes);
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// We serialize the document ids into a buffer
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buffer.clear();
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ids.serialize_into(&mut buffer)?;
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// that we write under the generated key into MTBL
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out.add(&key, &buffer).unwrap();
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// And cleanup the attribute id afterward (u32 = 4 * u8)
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key.truncate(key.len() - 4);
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// And cleanup the position afterward
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key.truncate(key.len() - position_bytes.len());
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}
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}
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}
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// postings ids keys are all prefixed by a '4'
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// postings ids keys are all prefixed
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key[0] = 5;
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indexed.documents.sort_unstable();
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indexed.documents.sort_unstable_by_key(|(id, _)| *id);
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for (id, content) in indexed.documents {
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key.truncate(1);
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key.extend_from_slice(&id.to_be_bytes());
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@ -204,8 +206,8 @@ fn index_csv(
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eprintln!("{:?}: Indexing into an Indexed...", thread_index);
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let mut document = csv::StringRecord::new();
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let mut postings_attrs = FastMap4::default();
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let mut postings_ids = FastMap4::default();
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let mut word_positions = FastMap4::default();
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let mut word_position_docids = FastMap4::default();
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let mut documents = Vec::new();
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// Write the headers into a Vec of bytes.
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@ -234,12 +236,11 @@ fn index_csv(
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let position = (attr * MAX_POSITION + pos) as u32;
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// We save the positions where this word has been seen.
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postings_attrs.entry(SmallVec32::from(word.as_bytes()))
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word_positions.entry(SmallVec32::from(word.as_bytes()))
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.or_insert_with(RoaringBitmap::new).insert(position);
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// We save the documents ids under the position and word we have seen it.
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postings_ids.entry(SmallVec32::from(word.as_bytes()))
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.or_insert_with(FastMap4::default).entry(position) // positions
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word_position_docids.entry((SmallVec32::from(word.as_bytes()), position)) // word + position
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.or_insert_with(RoaringBitmap::new).insert(document_id); // document ids
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}
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}
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@ -253,14 +254,10 @@ fn index_csv(
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}
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// We store the words from the postings.
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let mut new_words = BTreeSet::default();
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for (word, _new_ids) in &postings_ids {
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new_words.insert(word.clone());
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}
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let new_words: BTreeSet<_> = word_position_docids.iter().map(|((w, _), _)| w).collect();
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let fst = fst::Set::from_iter(new_words)?;
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let new_words_fst = fst::Set::from_iter(new_words.iter().map(SmallVec32::as_ref))?;
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let indexed = Indexed { fst: new_words_fst, headers, postings_attrs, postings_ids, documents };
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let indexed = Indexed { fst, headers, word_positions, word_position_docids, documents };
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eprintln!("{:?}: Indexed created!", thread_index);
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MtblKvStore::from_indexed(indexed).map(|x| vec![x])
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@ -371,7 +368,7 @@ fn main() -> anyhow::Result<()> {
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let csv_readers: Vec<_> = (0..num_threads).map(|_| csv::Reader::from_path(&file)).collect::<Result<_, _>>()?;
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let stores: Vec<_> = csv_readers
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.into_iter()
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.into_par_iter()
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.enumerate()
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.map(|(i, rdr)| index_csv(rdr, i, num_threads))
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.collect::<Result<_, _>>()?;
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@ -34,6 +34,7 @@ pub type SmallVec16<T> = smallvec::SmallVec<[T; 16]>;
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pub type BEU32 = heed::zerocopy::U32<heed::byteorder::BE>;
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pub type DocumentId = u32;
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pub type AttributeId = u32;
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pub type Position = u32;
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#[derive(Clone)]
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pub struct Index {
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