mirror of
https://github.com/meilisearch/meilisearch.git
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111 lines
4.2 KiB
Rust
111 lines
4.2 KiB
Rust
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use anyhow::Context;
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use csv::StringRecord;
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use heed::types::*;
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use heed::{PolyDatabase, Database};
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use roaring::RoaringBitmap;
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use crate::Search;
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use crate::{BEU32, DocumentId};
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use crate::{
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RoaringBitmapCodec, BEU32StrCodec, StrStrU8Codec, ObkvCodec,
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CsvStringRecordCodec, BoRoaringBitmapCodec, CboRoaringBitmapCodec,
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};
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pub const WORDS_FST_KEY: &str = "words-fst";
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pub const HEADERS_KEY: &str = "headers";
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pub const DOCUMENTS_IDS_KEY: &str = "documents-ids";
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#[derive(Clone)]
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pub struct Index {
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/// Contains many different types (e.g. the documents CSV headers).
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pub main: PolyDatabase,
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/// A word and all the documents ids containing the word.
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pub word_docids: Database<Str, RoaringBitmapCodec>,
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/// Maps a word and a document id (u32) to all the positions where the given word appears.
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pub docid_word_positions: Database<BEU32StrCodec, BoRoaringBitmapCodec>,
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/// Maps the proximity between a pair of words with all the docids where this relation appears.
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pub word_pair_proximity_docids: Database<StrStrU8Codec, CboRoaringBitmapCodec>,
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/// Maps the document id to the document as a CSV line.
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pub documents: Database<OwnedType<BEU32>, ByteSlice>,
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}
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impl Index {
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pub fn new(env: &heed::Env) -> anyhow::Result<Index> {
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Ok(Index {
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main: env.create_poly_database(Some("main"))?,
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word_docids: env.create_database(Some("word-docids"))?,
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docid_word_positions: env.create_database(Some("docid-word-positions"))?,
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word_pair_proximity_docids: env.create_database(Some("word-pair-proximity-docids"))?,
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documents: env.create_database(Some("documents"))?,
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})
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}
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pub fn documents_ids(&self, rtxn: &heed::RoTxn) -> anyhow::Result<Option<RoaringBitmap>> {
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Ok(self.main.get::<_, Str, RoaringBitmapCodec>(rtxn, DOCUMENTS_IDS_KEY)?)
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}
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pub fn put_headers(&self, wtxn: &mut heed::RwTxn, headers: &StringRecord) -> heed::Result<()> {
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self.main.put::<_, Str, CsvStringRecordCodec>(wtxn, HEADERS_KEY, headers)
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}
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pub fn headers(&self, rtxn: &heed::RoTxn) -> heed::Result<Option<StringRecord>> {
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self.main.get::<_, Str, CsvStringRecordCodec>(rtxn, HEADERS_KEY)
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}
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pub fn number_of_attributes(&self, rtxn: &heed::RoTxn) -> anyhow::Result<Option<usize>> {
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match self.headers(rtxn)? {
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Some(headers) => Ok(Some(headers.len())),
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None => Ok(None),
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}
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}
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pub fn put_fst<A: AsRef<[u8]>>(&self, wtxn: &mut heed::RwTxn, fst: &fst::Set<A>) -> anyhow::Result<()> {
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Ok(self.main.put::<_, Str, ByteSlice>(wtxn, WORDS_FST_KEY, fst.as_fst().as_bytes())?)
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}
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pub fn fst<'t>(&self, rtxn: &'t heed::RoTxn) -> anyhow::Result<Option<fst::Set<&'t [u8]>>> {
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match self.main.get::<_, Str, ByteSlice>(rtxn, WORDS_FST_KEY)? {
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Some(bytes) => Ok(Some(fst::Set::new(bytes)?)),
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None => Ok(None),
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}
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}
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/// Returns a [`Vec`] of the requested documents. Returns an error if a document is missing.
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pub fn documents<'t>(
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&self,
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rtxn: &'t heed::RoTxn,
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iter: impl IntoIterator<Item=DocumentId>,
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) -> anyhow::Result<Vec<(DocumentId, StringRecord)>>
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{
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let ids: Vec<_> = iter.into_iter().collect();
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let mut content = Vec::new();
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for id in ids.iter().cloned() {
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let document_content = self.documents.get(rtxn, &BEU32::new(id))?
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.with_context(|| format!("Could not find document {}", id))?;
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content.extend_from_slice(document_content);
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}
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let mut rdr = csv::ReaderBuilder::new().has_headers(false).from_reader(&content[..]);
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let mut documents = Vec::with_capacity(ids.len());
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for (id, result) in ids.into_iter().zip(rdr.records()) {
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documents.push((id, result?));
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}
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Ok(documents)
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}
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/// Returns the number of documents indexed in the database.
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pub fn number_of_documents(&self, rtxn: &heed::RoTxn) -> anyhow::Result<usize> {
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match self.documents_ids(rtxn)? {
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Some(docids) => Ok(docids.len() as usize),
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None => Ok(0),
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}
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}
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pub fn search<'a>(&'a self, rtxn: &'a heed::RoTxn) -> Search<'a> {
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Search::new(rtxn, self)
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}
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}
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