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Code Issues Releases Wiki Activity

Intern more values

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This commit is contained in:
Loïc Lecrenier 2023-03-09 11:12:31 +01:00
parent 2099991dd1
commit 0465ba4a05
12 changed files with 879 additions and 328 deletions
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77
milli/src/search/new/db_cache.rs
View File

@ -5,9 +5,8 @@ use fxhash::FxHashMap;
use heed::types::ByteSlice;
use heed::{BytesEncode, Database, RoTxn};
use super::interner::Interned;
use super::SearchContext;
use crate::Result;
use super::interner::{Interned, Interner};
use crate::{Index, Result};
/// A cache storing pointers to values in the LMDB databases.
///
@ -26,7 +25,7 @@ pub struct DatabaseCache<'search> {
pub exact_word_docids: FxHashMap<Interned<String>, Option<&'search [u8]>>,
pub word_prefix_docids: FxHashMap<Interned<String>, Option<&'search [u8]>>,
}
impl<'search> SearchContext<'search> {
impl<'search> DatabaseCache<'search> {
fn get_value<'v, K1, KC>(
txn: &'search RoTxn,
cache_key: K1,
@ -50,82 +49,92 @@ impl<'search> SearchContext<'search> {
}
/// Retrieve or insert the given value in the `word_docids` database.
pub fn get_word_docids(&mut self, word: Interned<String>) -> Result<Option<&'search [u8]>> {
pub fn get_word_docids(
&mut self,
index: &Index,
txn: &'search RoTxn,
word_interner: &Interner<String>,
word: Interned<String>,
) -> Result<Option<&'search [u8]>> {
Self::get_value(
self.txn,
txn,
word,
self.word_interner.get(word).as_str(),
&mut self.db_cache.word_docids,
self.index.word_docids.remap_data_type::<ByteSlice>(),
word_interner.get(word).as_str(),
&mut self.word_docids,
index.word_docids.remap_data_type::<ByteSlice>(),
)
}
/// Retrieve or insert the given value in the `word_prefix_docids` database.
pub fn get_word_prefix_docids(
&mut self,
index: &Index,
txn: &'search RoTxn,
word_interner: &Interner<String>,
prefix: Interned<String>,
) -> Result<Option<&'search [u8]>> {
Self::get_value(
self.txn,
txn,
prefix,
self.word_interner.get(prefix).as_str(),
&mut self.db_cache.word_prefix_docids,
self.index.word_prefix_docids.remap_data_type::<ByteSlice>(),
word_interner.get(prefix).as_str(),
&mut self.word_prefix_docids,
index.word_prefix_docids.remap_data_type::<ByteSlice>(),
)
}
pub fn get_word_pair_proximity_docids(
&mut self,
index: &Index,
txn: &'search RoTxn,
word_interner: &Interner<String>,
word1: Interned<String>,
word2: Interned<String>,
proximity: u8,
) -> Result<Option<&'search [u8]>> {
Self::get_value(
self.txn,
txn,
(proximity, word1, word2),
&(
proximity,
self.word_interner.get(word1).as_str(),
self.word_interner.get(word2).as_str(),
),
&mut self.db_cache.word_pair_proximity_docids,
self.index.word_pair_proximity_docids.remap_data_type::<ByteSlice>(),
&(proximity, word_interner.get(word1).as_str(), word_interner.get(word2).as_str()),
&mut self.word_pair_proximity_docids,
index.word_pair_proximity_docids.remap_data_type::<ByteSlice>(),
)
}
pub fn get_word_prefix_pair_proximity_docids(
&mut self,
index: &Index,
txn: &'search RoTxn,
word_interner: &Interner<String>,
word1: Interned<String>,
prefix2: Interned<String>,
proximity: u8,
) -> Result<Option<&'search [u8]>> {
Self::get_value(
self.txn,
txn,
(proximity, word1, prefix2),
&(
proximity,
self.word_interner.get(word1).as_str(),
self.word_interner.get(prefix2).as_str(),
),
&mut self.db_cache.word_prefix_pair_proximity_docids,
self.index.word_prefix_pair_proximity_docids.remap_data_type::<ByteSlice>(),
&(proximity, word_interner.get(word1).as_str(), word_interner.get(prefix2).as_str()),
&mut self.word_prefix_pair_proximity_docids,
index.word_prefix_pair_proximity_docids.remap_data_type::<ByteSlice>(),
)
}
pub fn get_prefix_word_pair_proximity_docids(
&mut self,
index: &Index,
txn: &'search RoTxn,
word_interner: &Interner<String>,
left_prefix: Interned<String>,
right: Interned<String>,
proximity: u8,
) -> Result<Option<&'search [u8]>> {
Self::get_value(
self.txn,
txn,
(proximity, left_prefix, right),
&(
proximity,
self.word_interner.get(left_prefix).as_str(),
self.word_interner.get(right).as_str(),
word_interner.get(left_prefix).as_str(),
word_interner.get(right).as_str(),
),
&mut self.db_cache.prefix_word_pair_proximity_docids,
self.index.prefix_word_pair_proximity_docids.remap_data_type::<ByteSlice>(),
&mut self.prefix_word_pair_proximity_docids,
index.prefix_word_pair_proximity_docids.remap_data_type::<ByteSlice>(),
)
}
}

9
milli/src/search/new/logger/detailed.rs
View File

@ -432,7 +432,10 @@ results.{random} {{
file: &mut File,
) {
match &node {
QueryNode::Term(LocatedQueryTerm { value, .. }) => match value {
QueryNode::Term(LocatedQueryTerm { value, .. }) => match ctx
.query_term_interner
.get(*value)
{
QueryTerm::Phrase { phrase } => {
let phrase = ctx.phrase_interner.get(*phrase);
let phrase_str = phrase.description(&ctx.word_interner);
@ -593,7 +596,7 @@ shape: class"
graph.edges_store[edge_idx as usize].as_ref().unwrap();
let source_node = &graph.query_graph.nodes[*source_node as usize];
let source_node_desc = match source_node {
QueryNode::Term(term) => match &term.value {
QueryNode::Term(term) => match ctx.query_term_interner.get(term.value) {
QueryTerm::Phrase { phrase } => {
let phrase = ctx.phrase_interner.get(*phrase);
phrase.description(&ctx.word_interner)
@ -608,7 +611,7 @@ shape: class"
};
let dest_node = &graph.query_graph.nodes[*dest_node as usize];
let dest_node_desc = match dest_node {
QueryNode::Term(term) => match &term.value {
QueryNode::Term(term) => match ctx.query_term_interner.get(term.value) {
QueryTerm::Phrase { phrase } => {
let phrase = ctx.phrase_interner.get(*phrase);
phrase.description(&ctx.word_interner)

387
milli/src/search/new/mod.rs
View File

@ -5,10 +5,14 @@ mod logger;
mod query_graph;
mod query_term;
mod ranking_rule_graph;
mod ranking_rules;
mod resolve_query_graph;
// TODO: documentation + comments
mod small_bitmap;
// TODO: documentation + comments
mod sort;
// TODO: documentation + comments
mod words;
pub use logger::{DefaultSearchLogger, SearchLogger};
@ -19,16 +23,16 @@ use charabia::Tokenize;
use db_cache::DatabaseCache;
use heed::RoTxn;
use query_graph::{QueryGraph, QueryNode};
pub use ranking_rules::{
apply_ranking_rules, RankingRule, RankingRuleOutput, RankingRuleOutputIter,
RankingRuleOutputIterWrapper, RankingRuleQueryTrait,
};
pub use ranking_rules::{bucket_sort, RankingRule, RankingRuleOutput, RankingRuleQueryTrait};
use roaring::RoaringBitmap;
use self::interner::Interner;
use self::query_term::Phrase;
use self::resolve_query_graph::{resolve_query_graph, NodeDocIdsCache};
use self::query_term::{Phrase, WordDerivations};
use self::resolve_query_graph::{resolve_query_graph, QueryTermDocIdsCache};
use crate::search::new::graph_based_ranking_rule::GraphBasedRankingRule;
use crate::search::new::query_term::located_query_terms_from_string;
use crate::search::new::ranking_rule_graph::{ProximityGraph, TypoGraph};
use crate::search::new::words::Words;
use crate::{Filter, Index, Result, TermsMatchingStrategy};
pub enum BitmapOrAllRef<'s> {
@ -42,7 +46,8 @@ pub struct SearchContext<'search> {
pub db_cache: DatabaseCache<'search>,
pub word_interner: Interner<String>,
pub phrase_interner: Interner<Phrase>,
pub node_docids_cache: NodeDocIdsCache,
pub derivations_interner: Interner<WordDerivations>,
pub query_term_docids: QueryTermDocIdsCache,
}
impl<'search> SearchContext<'search> {
pub fn new(index: &'search Index, txn: &'search RoTxn<'search>) -> Self {
@ -52,7 +57,8 @@ impl<'search> SearchContext<'search> {
db_cache: <_>::default(),
word_interner: <_>::default(),
phrase_interner: <_>::default(),
node_docids_cache: <_>::default(),
derivations_interner: <_>::default(),
query_term_docids: <_>::default(),
}
}
}
@ -129,5 +135,368 @@ pub fn execute_search<'search>(
logger.initial_universe(&universe);
apply_ranking_rules(ctx, &graph, &universe, from, length, logger)
let words = &mut Words::new(TermsMatchingStrategy::Last);
// let sort = &mut Sort::new(index, txn, "release_date".to_owned(), true)?;
let proximity = &mut GraphBasedRankingRule::<ProximityGraph>::new("proximity".to_owned());
let typo = &mut GraphBasedRankingRule::<TypoGraph>::new("typo".to_owned());
// TODO: ranking rules given as argument
let ranking_rules: Vec<&mut dyn RankingRule<'search, QueryGraph>> =
vec![words, typo, proximity /*sort*/];
bucket_sort(ctx, ranking_rules, &graph, &universe, from, length, logger)
}
#[cfg(test)]
mod tests {
// use crate::allocator::ALLOC;
use std::fs::File;
use std::io::{BufRead, BufReader, Cursor, Seek};
use std::time::Instant;
use big_s::S;
use heed::EnvOpenOptions;
use maplit::hashset;
use crate::documents::{DocumentsBatchBuilder, DocumentsBatchReader};
// use crate::search::new::logger::detailed::DetailedSearchLogger;
use crate::search::new::logger::DefaultSearchLogger;
use crate::search::new::{execute_search, SearchContext};
use crate::update::{IndexDocuments, IndexDocumentsConfig, IndexerConfig, Settings};
use crate::{Criterion, Index, Object, Search, TermsMatchingStrategy};
#[test]
fn search_wiki_new() {
let mut options = EnvOpenOptions::new();
options.map_size(100 * 1024 * 1024 * 1024); // 100 GB
let index = Index::new(options, "data_wiki").unwrap();
let txn = index.read_txn().unwrap();
println!("nbr docids: {}", index.documents_ids(&txn).unwrap().len());
// loop {
let start = Instant::now();
let mut logger = crate::search::new::logger::detailed::DetailedSearchLogger::new("log");
let mut ctx = SearchContext::new(&index, &txn);
let results = execute_search(
&mut ctx,
"zero config",
None,
0,
20,
// &mut DefaultSearchLogger,
&mut logger,
)
.unwrap();
logger.write_d2_description(&mut ctx);
let elapsed = start.elapsed();
println!("{}us", elapsed.as_micros());
let _documents = index
.documents(&txn, results.iter().copied())
.unwrap()
.into_iter()
.map(|(id, obkv)| {
let mut object = serde_json::Map::default();
for (fid, fid_name) in index.fields_ids_map(&txn).unwrap().iter() {
let value = obkv.get(fid).unwrap();
let value: serde_json::Value = serde_json::from_slice(value).unwrap();
object.insert(fid_name.to_owned(), value);
}
(id, serde_json::to_string_pretty(&object).unwrap())
})
.collect::<Vec<_>>();
println!("{}us: {:?}", elapsed.as_micros(), results);
// }
// for (id, _document) in documents {
// println!("{id}:");
// // println!("{document}");
// }
}
#[test]
fn search_wiki_old() {
let mut options = EnvOpenOptions::new();
options.map_size(100 * 1024 * 1024 * 1024); // 100 GB
let index = Index::new(options, "data_wiki").unwrap();
let txn = index.read_txn().unwrap();
let rr = index.criteria(&txn).unwrap();
println!("{rr:?}");
let start = Instant::now();
let mut s = Search::new(&txn, &index);
s.query("which a the releases from poison by the government");
s.terms_matching_strategy(TermsMatchingStrategy::Last);
s.criterion_implementation_strategy(crate::CriterionImplementationStrategy::OnlySetBased);
let docs = s.execute().unwrap();
let elapsed = start.elapsed();
let documents = index
.documents(&txn, docs.documents_ids.iter().copied())
.unwrap()
.into_iter()
.map(|(id, obkv)| {
let mut object = serde_json::Map::default();
for (fid, fid_name) in index.fields_ids_map(&txn).unwrap().iter() {
let value = obkv.get(fid).unwrap();
let value: serde_json::Value = serde_json::from_slice(value).unwrap();
object.insert(fid_name.to_owned(), value);
}
(id, serde_json::to_string_pretty(&object).unwrap())
})
.collect::<Vec<_>>();
println!("{}us: {:?}", elapsed.as_micros(), docs.documents_ids);
for (id, _document) in documents {
println!("{id}:");
// println!("{document}");
}
}
#[test]
fn search_movies_new() {
let mut options = EnvOpenOptions::new();
options.map_size(100 * 1024 * 1024 * 1024); // 100 GB
let index = Index::new(options, "data_movies").unwrap();
let txn = index.read_txn().unwrap();
// let primary_key = index.primary_key(&txn).unwrap().unwrap();
// let primary_key = index.fields_ids_map(&txn).unwrap().id(primary_key).unwrap();
// loop {
let start = Instant::now();
let mut logger = crate::search::new::logger::detailed::DetailedSearchLogger::new("log");
let mut ctx = SearchContext::new(&index, &txn);
let results = execute_search(
&mut ctx,
"releases from poison by the government",
None,
0,
20,
// &mut DefaultSearchLogger,
&mut logger,
)
.unwrap();
logger.write_d2_description(&mut ctx);
let elapsed = start.elapsed();
// let ids = index
// .documents(&txn, results.iter().copied())
// .unwrap()
// .into_iter()
// .map(|x| {
// let obkv = &x.1;
// let id = obkv.get(primary_key).unwrap();
// let id: serde_json::Value = serde_json::from_slice(id).unwrap();
// id.as_str().unwrap().to_owned()
// })
// .collect::<Vec<_>>();
println!("{}us: {results:?}", elapsed.as_micros());
// println!("external ids: {ids:?}");
// }
}
#[test]
fn search_movies_old() {
let mut options = EnvOpenOptions::new();
options.map_size(100 * 1024 * 1024 * 1024); // 100 GB
let index = Index::new(options, "data_movies").unwrap();
let txn = index.read_txn().unwrap();
let rr = index.criteria(&txn).unwrap();
println!("{rr:?}");
let primary_key = index.primary_key(&txn).unwrap().unwrap();
let primary_key = index.fields_ids_map(&txn).unwrap().id(primary_key).unwrap();
let start = Instant::now();
let mut s = Search::new(&txn, &index);
s.query("which a the releases from poison by the government");
s.terms_matching_strategy(TermsMatchingStrategy::Last);
s.criterion_implementation_strategy(crate::CriterionImplementationStrategy::OnlySetBased);
let docs = s.execute().unwrap();
let elapsed = start.elapsed();
let ids = index
.documents(&txn, docs.documents_ids.iter().copied())
.unwrap()
.into_iter()
.map(|x| {
let obkv = &x.1;
let id = obkv.get(primary_key).unwrap();
let id: serde_json::Value = serde_json::from_slice(id).unwrap();
id.as_str().unwrap().to_owned()
})
.collect::<Vec<_>>();
println!("{}us: {:?}", elapsed.as_micros(), docs.documents_ids);
println!("external ids: {ids:?}");
}
#[test]
fn _settings_movies() {
let mut options = EnvOpenOptions::new();
options.map_size(100 * 1024 * 1024 * 1024); // 100 GB
let index = Index::new(options, "data_movies").unwrap();
let mut wtxn = index.write_txn().unwrap();
let config = IndexerConfig::default();
let mut builder = Settings::new(&mut wtxn, &index, &config);
builder.set_min_word_len_one_typo(5);
builder.set_min_word_len_two_typos(100);
builder.set_sortable_fields(hashset! { S("release_date") });
builder.set_criteria(vec![
Criterion::Words,
Criterion::Typo,
Criterion::Proximity,
Criterion::Asc("release_date".to_owned()),
]);
builder.execute(|_| (), || false).unwrap();
wtxn.commit().unwrap();
}
#[test]
fn _index_movies() {
let mut options = EnvOpenOptions::new();
options.map_size(100 * 1024 * 1024 * 1024); // 100 GB
let index = Index::new(options, "data_movies").unwrap();
let mut wtxn = index.write_txn().unwrap();
let primary_key = "id";
let searchable_fields = vec!["title", "overview"];
let filterable_fields = vec!["release_date", "genres"];
let config = IndexerConfig::default();
let mut builder = Settings::new(&mut wtxn, &index, &config);
builder.set_primary_key(primary_key.to_owned());
let searchable_fields = searchable_fields.iter().map(|s| s.to_string()).collect();
builder.set_searchable_fields(searchable_fields);
let filterable_fields = filterable_fields.iter().map(|s| s.to_string()).collect();
builder.set_filterable_fields(filterable_fields);
builder.set_min_word_len_one_typo(5);
builder.set_min_word_len_two_typos(100);
builder.set_criteria(vec![Criterion::Words, Criterion::Proximity]);
builder.execute(|_| (), || false).unwrap();
let config = IndexerConfig::default();
let indexing_config = IndexDocumentsConfig::default();
let builder =
IndexDocuments::new(&mut wtxn, &index, &config, indexing_config, |_| (), || false)
.unwrap();
let documents = documents_from(
"/Users/meilisearch/Documents/milli2/benchmarks/datasets/movies.json",
"json",
);
let (builder, user_error) = builder.add_documents(documents).unwrap();
user_error.unwrap();
builder.execute().unwrap();
wtxn.commit().unwrap();
index.prepare_for_closing().wait();
}
#[test]
fn _index_wiki() {
let mut options = EnvOpenOptions::new();
options.map_size(100 * 1024 * 1024 * 1024); // 100 GB
let index = Index::new(options, "data_wiki").unwrap();
let mut wtxn = index.write_txn().unwrap();
// let primary_key = "id";
let searchable_fields = vec!["body", "title", "url"];
// let filterable_fields = vec![];
let config = IndexerConfig::default();
let mut builder = Settings::new(&mut wtxn, &index, &config);
// builder.set_primary_key(primary_key.to_owned());
let searchable_fields = searchable_fields.iter().map(|s| s.to_string()).collect();
builder.set_searchable_fields(searchable_fields);
// let filterable_fields = filterable_fields.iter().map(|s| s.to_string()).collect();
// builder.set_filterable_fields(filterable_fields);
// builder.set_min_word_len_one_typo(5);
// builder.set_min_word_len_two_typos(100);
builder.set_criteria(vec![Criterion::Words, Criterion::Typo, Criterion::Proximity]);
builder.execute(|_| (), || false).unwrap();
let config = IndexerConfig::default();
let indexing_config =
IndexDocumentsConfig { autogenerate_docids: true, ..Default::default() };
let builder =
IndexDocuments::new(&mut wtxn, &index, &config, indexing_config, |_| (), || false)
.unwrap();
let documents = documents_from(
"/Users/meilisearch/Documents/milli2/benchmarks/datasets/smol-wiki-articles.csv",
"csv",
);
let (builder, user_error) = builder.add_documents(documents).unwrap();
user_error.unwrap();
builder.execute().unwrap();
wtxn.commit().unwrap();
index.prepare_for_closing().wait();
}
fn documents_from(filename: &str, filetype: &str) -> DocumentsBatchReader<impl BufRead + Seek> {
let reader = File::open(filename)
.unwrap_or_else(|_| panic!("could not find the dataset in: {}", filename));
let reader = BufReader::new(reader);
let documents = match filetype {
"csv" => documents_from_csv(reader).unwrap(),
"json" => documents_from_json(reader).unwrap(),
"jsonl" => documents_from_jsonl(reader).unwrap(),
otherwise => panic!("invalid update format {:?}", otherwise),
};
DocumentsBatchReader::from_reader(Cursor::new(documents)).unwrap()
}
fn documents_from_jsonl(reader: impl BufRead) -> crate::Result<Vec<u8>> {
let mut documents = DocumentsBatchBuilder::new(Vec::new());
for result in serde_json::Deserializer::from_reader(reader).into_iter::<Object>() {
let object = result.unwrap();
documents.append_json_object(&object)?;
}
documents.into_inner().map_err(Into::into)
}
fn documents_from_json(reader: impl BufRead) -> crate::Result<Vec<u8>> {
let mut documents = DocumentsBatchBuilder::new(Vec::new());
documents.append_json_array(reader)?;
documents.into_inner().map_err(Into::into)
}
fn documents_from_csv(reader: impl BufRead) -> crate::Result<Vec<u8>> {
let csv = csv::Reader::from_reader(reader);
let mut documents = DocumentsBatchBuilder::new(Vec::new());
documents.append_csv(csv)?;
documents.into_inner().map_err(Into::into)
}
}

19
milli/src/search/new/query_graph.rs
View File

@ -3,7 +3,7 @@ use super::small_bitmap::SmallBitmap;
use super::SearchContext;
use crate::Result;
const QUERY_GRAPH_NODE_LENGTH_LIMIT: u16 = 64;
pub const QUERY_GRAPH_NODE_LENGTH_LIMIT: u16 = 64;
/// A node of the [`QueryGraph`].
///
@ -148,7 +148,7 @@ impl QueryGraph {
let mut new_nodes = vec![];
let new_node_idx = graph.add_node(&prev0, QueryNode::Term(term0.clone()));
new_nodes.push(new_node_idx);
if term0.is_empty() {
if term0.is_empty(&ctx.derivations_interner) {
empty_nodes.push(new_node_idx);
}
@ -159,7 +159,7 @@ impl QueryGraph {
if word_set.contains(ctx.word_interner.get(ngram2_str)) {
let ngram2 = LocatedQueryTerm {
value: QueryTerm::Word {
derivations: WordDerivations {
derivations: ctx.derivations_interner.insert(WordDerivations {
original: ngram2_str,
// TODO: could add a typo if it's an ngram?
zero_typo: Box::new([ngram2_str]),
@ -168,7 +168,7 @@ impl QueryGraph {
use_prefix_db: false,
synonyms: Box::new([]), // TODO: ngram synonyms
split_words: None, // TODO: maybe ngram split words?
},
}),
},
positions: ngram2_pos,
};
@ -187,7 +187,7 @@ impl QueryGraph {
if word_set.contains(ctx.word_interner.get(ngram3_str)) {
let ngram3 = LocatedQueryTerm {
value: QueryTerm::Word {
derivations: WordDerivations {
derivations: ctx.derivations_interner.insert(WordDerivations {
original: ngram3_str,
// TODO: could add a typo if it's an ngram?
zero_typo: Box::new([ngram3_str]),
@ -197,7 +197,7 @@ impl QueryGraph {
synonyms: Box::new([]), // TODO: ngram synonyms
split_words: None, // TODO: maybe ngram split words?
// would be nice for typos like su nflower
},
}),
},
positions: ngram3_pos,
};
@ -277,9 +277,10 @@ impl QueryGraph {
loop {
let mut nodes_to_remove = vec![];
for (node_idx, node) in self.nodes.iter().enumerate() {
if !matches!(node, QueryNode::End | QueryNode::Deleted)
&& (self.edges[node_idx].successors.is_empty()
|| self.edges[node_idx].predecessors.is_empty())
if (!matches!(node, QueryNode::End | QueryNode::Deleted)
&& self.edges[node_idx].successors.is_empty())
|| (!matches!(node, QueryNode::Start | QueryNode::Deleted)
&& self.edges[node_idx].predecessors.is_empty())
{
nodes_to_remove.push(node_idx as u16);
}

74
milli/src/search/new/query_term.rs
View File

@ -29,7 +29,7 @@ impl Phrase {
/// A structure storing all the different ways to match
/// a term in the user's search query.
#[derive(Clone)]
#[derive(Clone, PartialEq, Eq, Hash)]
pub struct WordDerivations {
/// The original word
pub original: Interned<String>,
@ -59,12 +59,12 @@ impl WordDerivations {
/// Return an iterator over all the single words derived from the original word.
///
/// This excludes synonyms, split words, and words stored in the prefix databases.
pub fn all_derivations_except_prefix_db(
pub fn all_single_word_derivations_except_prefix_db(
&'_ self,
) -> impl Iterator<Item = Interned<String>> + Clone + '_ {
self.zero_typo.iter().chain(self.one_typo.iter()).chain(self.two_typos.iter()).copied()
}
fn is_empty(&self) -> bool {
pub fn is_empty(&self) -> bool {
self.zero_typo.is_empty()
&& self.one_typo.is_empty()
&& self.two_typos.is_empty()
@ -101,10 +101,10 @@ pub fn word_derivations(
let prefix = Str::new(word).starts_with();
let mut stream = fst.search(prefix).into_stream();
while let Some(word) = stream.next() {
let word = std::str::from_utf8(word)?.to_owned();
let word_interned = ctx.word_interner.insert(word);
zero_typo.push(word_interned);
while let Some(derived_word) = stream.next() {
let derived_word = std::str::from_utf8(derived_word)?.to_owned();
let derived_word_interned = ctx.word_interner.insert(derived_word);
zero_typo.push(derived_word_interned);
}
} else if fst.contains(word) {
zero_typo.push(word_interned);
@ -113,17 +113,19 @@ pub fn word_derivations(
let dfa = build_dfa(word, 1, is_prefix);
let starts = StartsWith(Str::new(get_first(word)));
let mut stream = fst.search_with_state(Intersection(starts, &dfa)).into_stream();
// TODO: There may be wayyy too many matches (e.g. in the thousands), how to reduce them?
while let Some((derived_word, state)) = stream.next() {
let derived_word = std::str::from_utf8(derived_word)?;
while let Some((word, state)) = stream.next() {
let word = std::str::from_utf8(word)?;
let word_interned = ctx.word_interner.insert(word.to_owned());
let d = dfa.distance(state.1);
let derived_word_interned = ctx.word_interner.insert(derived_word.to_owned());
match d.to_u8() {
0 => {
zero_typo.push(word_interned);
zero_typo.push(derived_word_interned);
}
1 => {
one_typo.push(word_interned);
one_typo.push(derived_word_interned);
}
_ => panic!(),
}
@ -136,27 +138,28 @@ pub fn word_derivations(
let automaton = Union(first, &second);
let mut stream = fst.search_with_state(automaton).into_stream();
// TODO: There may be wayyy too many matches (e.g. in the thousands), how to reduce them?
while let Some((found_word, state)) = stream.next() {
let found_word = std::str::from_utf8(found_word)?;
let found_word_interned = ctx.word_interner.insert(found_word.to_owned());
while let Some((derived_word, state)) = stream.next() {
let derived_word = std::str::from_utf8(derived_word)?;
let derived_word_interned = ctx.word_interner.insert(derived_word.to_owned());
// in the case the typo is on the first letter, we know the number of typo
// is two
if get_first(found_word) != get_first(word) {
two_typos.push(found_word_interned);
if get_first(derived_word) != get_first(word) {
two_typos.push(derived_word_interned);
} else {
// Else, we know that it is the second dfa that matched and compute the
// correct distance
let d = second_dfa.distance((state.1).0);
match d.to_u8() {
0 => {
zero_typo.push(found_word_interned);
zero_typo.push(derived_word_interned);
}
1 => {
one_typo.push(found_word_interned);
one_typo.push(derived_word_interned);
}
2 => {
two_typos.push(found_word_interned);
two_typos.push(derived_word_interned);
}
_ => panic!(),
}
@ -223,10 +226,11 @@ fn split_best_frequency(
Ok(best.map(|(_, left, right)| (left.to_owned(), right.to_owned())))
}
#[derive(Clone)]
#[derive(Clone, PartialEq, Eq, Hash)]
pub enum QueryTerm {
Phrase { phrase: Interned<Phrase> },
Word { derivations: WordDerivations },
// TODO: change to `Interned<WordDerivations>`?
Word { derivations: Interned<WordDerivations> },
}
impl QueryTerm {
@ -234,10 +238,12 @@ impl QueryTerm {
pub fn original_single_word<'interner>(
&self,
word_interner: &'interner Interner<String>,
derivations_interner: &'interner Interner<WordDerivations>,
) -> Option<&'interner str> {
match self {
QueryTerm::Phrase { phrase: _ } => None,
QueryTerm::Word { derivations } => {
let derivations = derivations_interner.get(*derivations);
if derivations.is_empty() {
None
} else {
@ -257,12 +263,12 @@ pub struct LocatedQueryTerm {
impl LocatedQueryTerm {
/// Return `true` iff the word derivations within the query term are empty
pub fn is_empty(&self) -> bool {
match &self.value {
pub fn is_empty(&self, interner: &Interner<WordDerivations>) -> bool {
match self.value {
// TODO: phrases should be greedily computed, so that they can be excluded from
// the query graph right from the start?
QueryTerm::Phrase { phrase: _ } => false,
QueryTerm::Word { derivations, .. } => derivations.is_empty(),
QueryTerm::Word { derivations, .. } => interner.get(derivations).is_empty(),
}
}
}
@ -336,7 +342,9 @@ pub fn located_query_terms_from_string<'search>(
let word = token.lemma();
let derivations = word_derivations(ctx, word, nbr_typos(word), false)?;
let located_term = LocatedQueryTerm {
value: QueryTerm::Word { derivations },
value: QueryTerm::Word {
derivations: ctx.derivations_interner.insert(derivations),
},
positions: position..=position,
};
located_terms.push(located_term);
@ -347,7 +355,9 @@ pub fn located_query_terms_from_string<'search>(
let word = token.lemma();
let derivations = word_derivations(ctx, word, nbr_typos(word), true)?;
let located_term = LocatedQueryTerm {
value: QueryTerm::Word { derivations },
value: QueryTerm::Word {
derivations: ctx.derivations_interner.insert(derivations),
},
positions: position..=position,
};
located_terms.push(located_term);
@ -409,8 +419,8 @@ pub fn ngram2(
return None;
}
match (
&x.value.original_single_word(&ctx.word_interner),
&y.value.original_single_word(&ctx.word_interner),
&x.value.original_single_word(&ctx.word_interner, &ctx.derivations_interner),
&y.value.original_single_word(&ctx.word_interner, &ctx.derivations_interner),
) {
(Some(w1), Some(w2)) => {
let term = (
@ -436,9 +446,9 @@ pub fn ngram3(
return None;
}
match (
&x.value.original_single_word(&ctx.word_interner),
&y.value.original_single_word(&ctx.word_interner),
&z.value.original_single_word(&ctx.word_interner),
&x.value.original_single_word(&ctx.word_interner, &ctx.derivations_interner),
&y.value.original_single_word(&ctx.word_interner, &ctx.derivations_interner),
&z.value.original_single_word(&ctx.word_interner, &ctx.derivations_interner),
) {
(Some(w1), Some(w2), Some(w3)) => {
let term = (

64
milli/src/search/new/ranking_rule_graph/proximity/build.rs
View File

@ -14,8 +14,11 @@ pub fn visit_from_node(
from_node: &QueryNode,
) -> Result<Option<(WordDerivations, i8)>> {
Ok(Some(match from_node {
QueryNode::Term(LocatedQueryTerm { value: value1, positions: pos1 }) => match value1 {
QueryTerm::Word { derivations } => (derivations.clone(), *pos1.end()),
QueryNode::Term(LocatedQueryTerm { value: value1, positions: pos1 }) => {
match value1 {
QueryTerm::Word { derivations } => {
(ctx.derivations_interner.get(*derivations).clone(), *pos1.end())
}
QueryTerm::Phrase { phrase: phrase1 } => {
let phrase1 = ctx.phrase_interner.get(*phrase1);
if let Some(original) = *phrase1.words.last().unwrap() {
@ -36,7 +39,8 @@ pub fn visit_from_node(
return Ok(None);
}
}
},
}
}
QueryNode::Start => (
WordDerivations {
original: ctx.word_interner.insert(String::new()),
@ -58,6 +62,10 @@ pub fn visit_to_node<'search, 'from_data>(
to_node: &QueryNode,
from_node_data: &'from_data (WordDerivations, i8),
) -> Result<Vec<(u8, EdgeCondition<ProximityEdge>)>> {
let SearchContext { index, txn, db_cache, word_interner, derivations_interner, .. } = ctx;
// IMPORTANT! TODO: split words support
let (derivations1, pos1) = from_node_data;
let term2 = match &to_node {
QueryNode::End => return Ok(vec![(0, EdgeCondition::Unconditional)]),
@ -67,7 +75,9 @@ pub fn visit_to_node<'search, 'from_data>(
let LocatedQueryTerm { value: value2, positions: pos2 } = term2;
let (derivations2, pos2, ngram_len2) = match value2 {
QueryTerm::Word { derivations } => (derivations.clone(), *pos2.start(), pos2.len()),
QueryTerm::Word { derivations } => {
(derivations_interner.get(*derivations).clone(), *pos2.start(), pos2.len())
}
QueryTerm::Phrase { phrase: phrase2 } => {
let phrase2 = ctx.phrase_interner.get(*phrase2);
if let Some(original) = *phrase2.words.first().unwrap() {
@ -105,7 +115,8 @@ pub fn visit_to_node<'search, 'from_data>(
// left term cannot be a prefix
assert!(!updb1);
let derivations1 = derivations1.all_derivations_except_prefix_db();
// TODO: IMPORTANT! split words and synonyms support
let derivations1 = derivations1.all_single_word_derivations_except_prefix_db();
// TODO: eventually, we want to get rid of the uses from `orginal`
let mut cost_proximity_word_pairs = BTreeMap::<u8, BTreeMap<u8, Vec<WordPair>>>::new();
@ -115,8 +126,11 @@ pub fn visit_to_node<'search, 'from_data>(
let cost = (proximity + ngram_len2 - 1) as u8;
// TODO: if we had access to the universe here, we could already check whether
// the bitmap corresponding to this word pair is disjoint with the universe or not
if ctx
if db_cache
.get_word_prefix_pair_proximity_docids(
index,
txn,
word_interner,
word1,
derivations2.original,
proximity as u8,
@ -133,8 +147,11 @@ pub fn visit_to_node<'search, 'from_data>(
right_prefix: derivations2.original,
});
}
if ctx
if db_cache
.get_prefix_word_pair_proximity_docids(
index,
txn,
word_interner,
derivations2.original,
word1,
proximity as u8 - 1,
@ -155,14 +172,30 @@ pub fn visit_to_node<'search, 'from_data>(
}
}
let derivations2 = derivations2.all_derivations_except_prefix_db();
// TODO: add safeguard in case the cartesian product is too large?
// TODO: important! support split words and synonyms as well
let derivations2 = derivations2.all_single_word_derivations_except_prefix_db();
// TODO: add safeguard in case the cartesian product is too large!
// even if we restrict the word derivations to a maximum of 100, the size of the
// caterisan product could reach a maximum of 10_000 derivations, which is way too much.
// mMaybe prioritise the product of zero typo derivations, then the product of zero-typo/one-typo
// + one-typo/zero-typo, then one-typo/one-typo, then ... until an arbitrary limit has been
// reached
let product_derivations = derivations1.cartesian_product(derivations2);
for (word1, word2) in product_derivations {
for proximity in 1..=(8 - ngram_len2) {
let cost = (proximity + ngram_len2 - 1) as u8;
if ctx.get_word_pair_proximity_docids(word1, word2, proximity as u8)?.is_some() {
if db_cache
.get_word_pair_proximity_docids(
index,
txn,
word_interner,
word1,
word2,
proximity as u8,
)?
.is_some()
{
cost_proximity_word_pairs
.entry(cost)
.or_default()
@ -171,7 +204,16 @@ pub fn visit_to_node<'search, 'from_data>(
.push(WordPair::Words { left: word1, right: word2 });
}
if proximity > 1
&& ctx.get_word_pair_proximity_docids(word2, word1, proximity as u8 - 1)?.is_some()
&& db_cache
.get_word_pair_proximity_docids(
index,
txn,
word_interner,
word2,
word1,
proximity as u8 - 1,
)?
.is_some()
{
cost_proximity_word_pairs
.entry(cost)

36
milli/src/search/new/ranking_rule_graph/proximity/compute_docids.rs
View File

@ -9,19 +9,37 @@ pub fn compute_docids<'search>(
edge: &ProximityEdge,
universe: &RoaringBitmap,
) -> Result<RoaringBitmap> {
let SearchContext { index, txn, db_cache, word_interner, .. } = ctx;
let ProximityEdge { pairs, proximity } = edge;
let mut pair_docids = RoaringBitmap::new();
for pair in pairs.iter() {
let bytes = match pair {
WordPair::Words { left, right } => {
ctx.get_word_pair_proximity_docids(*left, *right, *proximity)
}
WordPair::WordPrefix { left, right_prefix } => {
ctx.get_word_prefix_pair_proximity_docids(*left, *right_prefix, *proximity)
}
WordPair::WordPrefixSwapped { left_prefix, right } => {
ctx.get_prefix_word_pair_proximity_docids(*left_prefix, *right, *proximity)
}
WordPair::Words { left, right } => db_cache.get_word_pair_proximity_docids(
index,
txn,
word_interner,
*left,
*right,
*proximity,
),
WordPair::WordPrefix { left, right_prefix } => db_cache
.get_word_prefix_pair_proximity_docids(
index,
txn,
word_interner,
*left,
*right_prefix,
*proximity,
),
WordPair::WordPrefixSwapped { left_prefix, right } => db_cache
.get_prefix_word_pair_proximity_docids(
index,
txn,
word_interner,
*left_prefix,
*right,
*proximity,
),
}?;
// TODO: deserialize bitmap within a universe, and (maybe) using a bump allocator?
let bitmap = universe

137
milli/src/search/new/ranking_rule_graph/typo/mod.rs
View File

@ -1,4 +1,3 @@
use heed::BytesDecode;
use roaring::RoaringBitmap;
use super::empty_paths_cache::EmptyPathsCache;
@ -6,15 +5,14 @@ use super::{EdgeCondition, RankingRuleGraph, RankingRuleGraphTrait};
use crate::search::new::interner::Interned;
use crate::search::new::logger::SearchLogger;
use crate::search::new::query_term::{LocatedQueryTerm, Phrase, QueryTerm, WordDerivations};
use crate::search::new::resolve_query_graph::resolve_phrase;
use crate::search::new::small_bitmap::SmallBitmap;
use crate::search::new::{QueryGraph, QueryNode, SearchContext};
use crate::{Result, RoaringBitmapCodec};
use crate::Result;
#[derive(Clone)]
pub enum TypoEdge {
Phrase { phrase: Interned<Phrase> },
Word { derivations: WordDerivations, nbr_typos: u8 },
Word { derivations: Interned<WordDerivations>, nbr_typos: u8 },
}
pub enum TypoGraph {}
@ -35,32 +33,37 @@ impl RankingRuleGraphTrait for TypoGraph {
edge: &Self::EdgeCondition,
universe: &RoaringBitmap,
) -> Result<RoaringBitmap> {
let SearchContext {
index,
txn,
db_cache,
word_interner,
phrase_interner,
derivations_interner,
query_term_docids,
} = ctx;
match edge {
TypoEdge::Phrase { phrase } => resolve_phrase(ctx, *phrase),
TypoEdge::Word { derivations, nbr_typos } => {
let words = match nbr_typos {
0 => &derivations.zero_typo,
1 => &derivations.one_typo,
2 => &derivations.two_typos,
_ => panic!(),
};
let mut docids = RoaringBitmap::new();
for word in words.iter().copied() {
let Some(bytes) = ctx.get_word_docids(word)? else { continue };
// TODO: deserialize bitmap within a universe
let bitmap = universe
& RoaringBitmapCodec::bytes_decode(bytes).ok_or(heed::Error::Decoding)?;
docids |= bitmap;
}
if *nbr_typos == 0 {
if let Some(bytes) = ctx.get_word_prefix_docids(derivations.original)? {
// TODO: deserialize bitmap within a universe
let bitmap = universe
& RoaringBitmapCodec::bytes_decode(bytes)
.ok_or(heed::Error::Decoding)?;
docids |= bitmap;
}
}
&TypoEdge::Phrase { phrase } => Ok(universe
& query_term_docids.get_phrase_docids(
index,
txn,
db_cache,
word_interner,
phrase_interner,
phrase,
)?),
TypoEdge::Word { derivations, .. } => {
let docids = universe
& query_term_docids.get_word_derivations_docids(
index,
txn,
db_cache,
word_interner,
derivations_interner,
phrase_interner,
*derivations,
)?;
Ok(docids)
}
}
@ -74,43 +77,71 @@ impl RankingRuleGraphTrait for TypoGraph {
}
fn build_step_visit_destination_node<'from_data, 'search: 'from_data>(
_ctx: &mut SearchContext<'search>,
ctx: &mut SearchContext<'search>,
to_node: &QueryNode,
_from_node_data: &'from_data Self::BuildVisitedFromNode,
) -> Result<Vec<(u8, EdgeCondition<Self::EdgeCondition>)>> {
let SearchContext { derivations_interner, .. } = ctx;
match to_node {
QueryNode::Term(LocatedQueryTerm { value, .. }) => match value {
&QueryTerm::Phrase { phrase } => {
QueryNode::Term(LocatedQueryTerm { value, .. }) => match *value {
QueryTerm::Phrase { phrase } => {
Ok(vec![(0, EdgeCondition::Conditional(TypoEdge::Phrase { phrase }))])
}
QueryTerm::Word { derivations } => {
let mut edges = vec![];
if !derivations.zero_typo.is_empty() || derivations.use_prefix_db {
for nbr_typos in 0..=2 {
let derivations = derivations_interner.get(derivations).clone();
let new_derivations = match nbr_typos {
0 => {
// TODO: think about how split words and synonyms should be handled here
// TODO: what about ngrams?
// Maybe 2grams should have one typo by default and 3grams 2 typos by default
WordDerivations {
original: derivations.original,
synonyms: derivations.synonyms,
split_words: None,
zero_typo: derivations.zero_typo,
one_typo: Box::new([]),
two_typos: Box::new([]),
use_prefix_db: derivations.use_prefix_db,
}
}
1 => {
// What about split words and synonyms here?
WordDerivations {
original: derivations.original,
synonyms: Box::new([]),
split_words: derivations.split_words,
zero_typo: Box::new([]),
one_typo: derivations.one_typo,
two_typos: Box::new([]),
use_prefix_db: false, // false because all items from use_prefix_db haev 0 typos
}
}
2 => {
// What about split words and synonyms here?
WordDerivations {
original: derivations.original,
synonyms: Box::new([]),
split_words: None,
zero_typo: Box::new([]),
one_typo: Box::new([]),
two_typos: derivations.two_typos,
use_prefix_db: false, // false because all items from use_prefix_db haev 0 typos
}
}
_ => panic!(),
};
if !new_derivations.is_empty() {
edges.push((
0,
nbr_typos,
EdgeCondition::Conditional(TypoEdge::Word {
derivations: derivations.clone(),
nbr_typos: 0,
derivations: derivations_interner.insert(new_derivations),
nbr_typos,
}),
))
}
if !derivations.one_typo.is_empty() {
edges.push((
1,
EdgeCondition::Conditional(TypoEdge::Word {
derivations: derivations.clone(),
nbr_typos: 1,
}),
))
}
if !derivations.two_typos.is_empty() {
edges.push((
2,
EdgeCondition::Conditional(TypoEdge::Word {
derivations: derivations.clone(),
nbr_typos: 2,
}),
))
}
Ok(edges)
}

62
milli/src/search/new/ranking_rules.rs
View File

@ -2,42 +2,23 @@ use roaring::RoaringBitmap;
use super::logger::SearchLogger;
use super::{QueryGraph, SearchContext};
use crate::search::new::graph_based_ranking_rule::GraphBasedRankingRule;
use crate::search::new::ranking_rule_graph::{ProximityGraph, TypoGraph};
use crate::search::new::words::Words;
// use crate::search::new::sort::Sort;
use crate::{Result, TermsMatchingStrategy};
pub trait RankingRuleOutputIter<'search, Query> {
fn next_bucket(&mut self) -> Result<Option<RankingRuleOutput<Query>>>;
}
pub struct RankingRuleOutputIterWrapper<'search, Query> {
iter: Box<dyn Iterator<Item = Result<RankingRuleOutput<Query>>> + 'search>,
}
impl<'search, Query> RankingRuleOutputIterWrapper<'search, Query> {
pub fn new(iter: Box<dyn Iterator<Item = Result<RankingRuleOutput<Query>>> + 'search>) -> Self {
Self { iter }
}
}
impl<'search, Query> RankingRuleOutputIter<'search, Query>
for RankingRuleOutputIterWrapper<'search, Query>
{
fn next_bucket(&mut self) -> Result<Option<RankingRuleOutput<Query>>> {
match self.iter.next() {
Some(x) => x.map(Some),
None => Ok(None),
}
}
}
use crate::Result;
/// An internal trait implemented by only [`PlaceholderQuery`] and [`QueryGraph`]
pub trait RankingRuleQueryTrait: Sized + Clone + 'static {}
/// A type describing a placeholder search
#[derive(Clone)]
pub struct PlaceholderQuery;
impl RankingRuleQueryTrait for PlaceholderQuery {}
impl RankingRuleQueryTrait for QueryGraph {}
/// A trait that must be implemented by all ranking rules.
///
/// It is generic over `'search`, the lifetime of the search context
/// (i.e. the read transaction and the cache) and over `Query`, which
/// can be either [`PlaceholderQuery`] or [`QueryGraph`].
pub trait RankingRule<'search, Query: RankingRuleQueryTrait> {
fn id(&self) -> String;
@ -76,6 +57,8 @@ pub trait RankingRule<'search, Query: RankingRuleQueryTrait> {
);
}
/// Output of a ranking rule, consisting of the query to be used
/// by the child ranking rule and a set of document ids.
#[derive(Debug)]
pub struct RankingRuleOutput<Q> {
/// The query corresponding to the current bucket for the child ranking rule
@ -84,25 +67,16 @@ pub struct RankingRuleOutput<Q> {
pub candidates: RoaringBitmap,
}
// TODO: can make it generic over the query type (either query graph or placeholder) fairly easily
#[allow(clippy::too_many_arguments)]
pub fn apply_ranking_rules<'search>(
pub fn bucket_sort<'search, Q: RankingRuleQueryTrait>(
ctx: &mut SearchContext<'search>,
// TODO: ranking rules parameter
query_graph: &QueryGraph,
mut ranking_rules: Vec<&mut dyn RankingRule<'search, Q>>,
query_graph: &Q,
universe: &RoaringBitmap,
from: usize,
length: usize,
logger: &mut dyn SearchLogger<QueryGraph>,
logger: &mut dyn SearchLogger<Q>,
) -> Result<Vec<u32>> {
logger.initial_query(query_graph);
let words = &mut Words::new(TermsMatchingStrategy::Last);
// let sort = &mut Sort::new(index, txn, "release_date".to_owned(), true)?;
let proximity = &mut GraphBasedRankingRule::<ProximityGraph>::new("proximity".to_owned());
let typo = &mut GraphBasedRankingRule::<TypoGraph>::new("typo".to_owned());
// TODO: ranking rules given as argument
let mut ranking_rules: Vec<&mut dyn RankingRule<'search, QueryGraph>> =
vec![words, typo, proximity /*sort*/];
logger.ranking_rules(&ranking_rules);
@ -119,6 +93,9 @@ pub fn apply_ranking_rules<'search>(
let mut cur_ranking_rule_index = 0;
/// Finish iterating over the current ranking rule, yielding
/// control to the parent (or finishing the search if not possible).
/// Update the candidates accordingly and inform the logger.
macro_rules! back {
() => {
assert!(candidates[cur_ranking_rule_index].is_empty());
@ -140,8 +117,8 @@ pub fn apply_ranking_rules<'search>(
let mut results = vec![];
let mut cur_offset = 0usize;
// Add the candidates to the results. Take the `from`, `limit`, and `cur_offset`
// into account and inform the logger.
/// Add the candidates to the results. Take the `from`, `limit`, and `cur_offset`
/// into account and inform the logger.
macro_rules! maybe_add_to_results {
($candidates:expr) => {
let candidates = $candidates;
@ -193,7 +170,6 @@ pub fn apply_ranking_rules<'search>(
}
let Some(next_bucket) = ranking_rules[cur_ranking_rule_index].next_bucket(ctx, logger, &candidates[cur_ranking_rule_index])? else {
// TODO: add remaining candidates automatically here?
back!();
continue;
};

193
milli/src/search/new/resolve_query_graph.rs
View File

@ -1,52 +1,79 @@
#![allow(clippy::too_many_arguments)]
use std::collections::VecDeque;
use fxhash::FxHashMap;
use heed::BytesDecode;
use heed::{BytesDecode, RoTxn};
use roaring::{MultiOps, RoaringBitmap};
use super::interner::Interned;
use super::db_cache::DatabaseCache;
use super::interner::{Interned, Interner};
use super::query_graph::QUERY_GRAPH_NODE_LENGTH_LIMIT;
use super::query_term::{Phrase, QueryTerm, WordDerivations};
use super::small_bitmap::SmallBitmap;
use super::{QueryGraph, QueryNode, SearchContext};
use crate::{CboRoaringBitmapCodec, Result, RoaringBitmapCodec};
use crate::{CboRoaringBitmapCodec, Index, Result, RoaringBitmapCodec};
// TODO: manual performance metrics: access to DB, bitmap deserializations/operations, etc.
#[derive(Default)]
pub struct NodeDocIdsCache {
pub cache: FxHashMap<u16, RoaringBitmap>,
pub struct QueryTermDocIdsCache {
pub phrases: FxHashMap<Interned<Phrase>, RoaringBitmap>,
pub derivations: FxHashMap<Interned<WordDerivations>, RoaringBitmap>,
}
impl<'search> SearchContext<'search> {
fn get_node_docids<'cache>(
&'cache mut self,
term: &QueryTerm,
node_idx: u16,
) -> Result<&'cache RoaringBitmap> {
if self.node_docids_cache.cache.contains_key(&node_idx) {
return Ok(&self.node_docids_cache.cache[&node_idx]);
impl QueryTermDocIdsCache {
/// Get the document ids associated with the given phrase
pub fn get_phrase_docids<'s, 'search>(
&'s mut self,
index: &Index,
txn: &'search RoTxn,
db_cache: &mut DatabaseCache<'search>,
word_interner: &Interner<String>,
phrase_interner: &Interner<Phrase>,
phrase: Interned<Phrase>,
) -> Result<&'s RoaringBitmap> {
if self.phrases.contains_key(&phrase) {
return Ok(&self.phrases[&phrase]);
};
let docids = match term {
QueryTerm::Phrase { phrase } => resolve_phrase(self, *phrase)?,
QueryTerm::Word {
derivations:
WordDerivations {
let docids = resolve_phrase(index, txn, db_cache, word_interner, phrase_interner, phrase)?;
let _ = self.phrases.insert(phrase, docids);
let docids = &self.phrases[&phrase];
Ok(docids)
}
/// Get the document ids associated with the given word derivations
pub fn get_word_derivations_docids<'s, 'search>(
&'s mut self,
index: &Index,
txn: &'search RoTxn,
db_cache: &mut DatabaseCache<'search>,
word_interner: &Interner<String>,
derivations_interner: &Interner<WordDerivations>,
phrase_interner: &Interner<Phrase>,
derivations: Interned<WordDerivations>,
) -> Result<&'s RoaringBitmap> {
if self.derivations.contains_key(&derivations) {
return Ok(&self.derivations[&derivations]);
};
let WordDerivations {
original,
synonyms,
split_words,
zero_typo,
one_typo,
two_typos,
use_prefix_db,
synonyms,
split_words,
},
} => {
} = derivations_interner.get(derivations);
let mut or_docids = vec![];
for word in zero_typo.iter().chain(one_typo.iter()).chain(two_typos.iter()).copied()
{
if let Some(word_docids) = self.get_word_docids(word)? {
for word in zero_typo.iter().chain(one_typo.iter()).chain(two_typos.iter()).copied() {
if let Some(word_docids) = db_cache.get_word_docids(index, txn, word_interner, word)? {
or_docids.push(word_docids);
}
}
if *use_prefix_db {
if let Some(prefix_docids) = self.get_word_prefix_docids(*original)? {
// TODO: this will change if we decide to change from (original, zero_typo) to:
// (debug_original, prefix_of, zero_typo)
if let Some(prefix_docids) =
db_cache.get_word_prefix_docids(index, txn, word_interner, *original)?
{
or_docids.push(prefix_docids);
}
}
@ -56,19 +83,58 @@ impl<'search> SearchContext<'search> {
.collect::<Vec<_>>();
for synonym in synonyms.iter().copied() {
// TODO: cache resolve_phrase?
docids.push(resolve_phrase(self, synonym)?);
docids.push(resolve_phrase(
index,
txn,
db_cache,
word_interner,
phrase_interner,
synonym,
)?);
}
if let Some(split_words) = split_words {
docids.push(resolve_phrase(self, *split_words)?);
docids.push(resolve_phrase(
index,
txn,
db_cache,
word_interner,
phrase_interner,
*split_words,
)?);
}
MultiOps::union(docids)
}
};
let _ = self.node_docids_cache.cache.insert(node_idx, docids);
let docids = &self.node_docids_cache.cache[&node_idx];
let docids = MultiOps::union(docids);
let _ = self.derivations.insert(derivations, docids);
let docids = &self.derivations[&derivations];
Ok(docids)
}
/// Get the document ids associated with the given query term.
fn get_query_term_docids<'s, 'search>(
&'s mut self,
index: &Index,
txn: &'search RoTxn,
db_cache: &mut DatabaseCache<'search>,
word_interner: &Interner<String>,
derivations_interner: &Interner<WordDerivations>,
phrase_interner: &Interner<Phrase>,
term: &QueryTerm,
) -> Result<&'s RoaringBitmap> {
match *term {
QueryTerm::Phrase { phrase } => {
self.get_phrase_docids(index, txn, db_cache, word_interner, phrase_interner, phrase)
}
QueryTerm::Word { derivations } => self.get_word_derivations_docids(
index,
txn,
db_cache,
word_interner,
derivations_interner,
phrase_interner,
derivations,
),
}
}
}
pub fn resolve_query_graph<'search>(
@ -76,14 +142,23 @@ pub fn resolve_query_graph<'search>(
q: &QueryGraph,
universe: &RoaringBitmap,
) -> Result<RoaringBitmap> {
// TODO: there is definitely a faster way to compute this big
let SearchContext {
index,
txn,
db_cache,
word_interner,
phrase_interner,
derivations_interner,
query_term_docids,
} = ctx;
// TODO: there is a faster way to compute this big
// roaring bitmap expression
let mut nodes_resolved = SmallBitmap::new(64);
let mut nodes_resolved = SmallBitmap::new(QUERY_GRAPH_NODE_LENGTH_LIMIT);
let mut path_nodes_docids = vec![RoaringBitmap::new(); q.nodes.len()];
let mut next_nodes_to_visit = VecDeque::new();
next_nodes_to_visit.push_front(q.root_node);
next_nodes_to_visit.push_back(q.root_node);
while let Some(node) = next_nodes_to_visit.pop_front() {
let predecessors = &q.edges[node as usize].predecessors;
@ -101,8 +176,15 @@ pub fn resolve_query_graph<'search>(
let node_docids = match n {
QueryNode::Term(located_term) => {
let term = &located_term.value;
let derivations_docids = ctx.get_node_docids(term, node)?;
let derivations_docids = query_term_docids.get_query_term_docids(
index,
txn,
db_cache,
word_interner,
derivations_interner,
phrase_interner,
&located_term.value,
)?;
predecessors_docids & derivations_docids
}
QueryNode::Deleted => {
@ -122,19 +204,24 @@ pub fn resolve_query_graph<'search>(
}
}
// This is currently slow but could easily be implemented very efficiently
for prec in q.edges[node as usize].predecessors.iter() {
if q.edges[prec as usize].successors.is_subset(&nodes_resolved) {
path_nodes_docids[prec as usize].clear();
}
}
}
panic!()
}
pub fn resolve_phrase(ctx: &mut SearchContext, phrase: Interned<Phrase>) -> Result<RoaringBitmap> {
let Phrase { words } = ctx.phrase_interner.get(phrase).clone();
pub fn resolve_phrase<'search>(
index: &Index,
txn: &'search RoTxn,
db_cache: &mut DatabaseCache<'search>,
word_interner: &Interner<String>,
phrase_interner: &Interner<Phrase>,
phrase: Interned<Phrase>,
) -> Result<RoaringBitmap> {
let Phrase { words } = phrase_interner.get(phrase).clone();
let mut candidates = RoaringBitmap::new();
let mut first_iter = true;
let winsize = words.len().min(3);
@ -158,7 +245,14 @@ pub fn resolve_phrase(ctx: &mut SearchContext, phrase: Interned<Phrase>) -> Resu
.filter_map(|(index, word)| word.as_ref().map(|word| (index, word)))
{
if dist == 0 {
match ctx.get_word_pair_proximity_docids(s1, s2, 1)? {
match db_cache.get_word_pair_proximity_docids(
index,
txn,
word_interner,
s1,
s2,
1,
)? {
Some(m) => bitmaps.push(CboRoaringBitmapCodec::deserialize_from(m)?),
// If there are no documents for this pair, there will be no
// results for the phrase query.
@ -167,9 +261,14 @@ pub fn resolve_phrase(ctx: &mut SearchContext, phrase: Interned<Phrase>) -> Resu
} else {
let mut bitmap = RoaringBitmap::new();
for dist in 0..=dist {
if let Some(m) =
ctx.get_word_pair_proximity_docids(s1, s2, dist as u8 + 1)?
{
if let Some(m) = db_cache.get_word_pair_proximity_docids(
index,
txn,
word_interner,
s1,
s2,
dist as u8 + 1,
)? {
bitmap |= CboRoaringBitmapCodec::deserialize_from(m)?;
}
}

28
milli/src/search/new/small_bitmap.rs
View File

@ -18,13 +18,6 @@ impl SmallBitmap {
}
s
}
pub fn from_array(xs: &[u16], universe_length: u16) -> Self {
let mut s = Self::new(universe_length);
for x in xs {
s.insert(*x);
}
s
}
pub fn is_empty(&self) -> bool {
match self {
SmallBitmap::Tiny(set) => *set == 0,
@ -81,27 +74,6 @@ impl SmallBitmap {
};
*set &= !(0b1 << x);
}
// fn iter_single(mut set: u64, mut visit: impl FnMut(u16) -> Result<()>) -> Result<()> {
// while set > 0 {
// let idx = set.trailing_zeros() as u16;
// visit(idx)?;
// set &= set - 1;
// }
// Ok(())
// }
// pub fn iter(&self, mut visit: impl FnMut(u16) -> Result<()>) -> Result<()> {
// match self {
// SmallBitmap::Tiny(set) => Self::iter_single(*set, &mut visit),
// SmallBitmap::Small(sets) => {
// let mut base = 0;
// for set in sets.iter() {
// Self::iter_single(*set, |x| visit(base + x))?;
// base += 64;
// }
// Ok(())
// }
// }
// }
pub fn intersection(&mut self, other: &SmallBitmap) {
self.apply_op(other, |a, b| *a &= b);

29
milli/src/search/new/sort.rs
View File

@ -1,10 +1,31 @@
use roaring::RoaringBitmap;
use super::logger::SearchLogger;
use super::{
RankingRule, RankingRuleOutput, RankingRuleOutputIter, RankingRuleOutputIterWrapper,
RankingRuleQueryTrait, SearchContext,
};
use super::{RankingRule, RankingRuleOutput, RankingRuleQueryTrait, SearchContext};
pub trait RankingRuleOutputIter<'search, Query> {
fn next_bucket(&mut self) -> Result<Option<RankingRuleOutput<Query>>>;
}
pub struct RankingRuleOutputIterWrapper<'search, Query> {
iter: Box<dyn Iterator<Item = Result<RankingRuleOutput<Query>>> + 'search>,
}
impl<'search, Query> RankingRuleOutputIterWrapper<'search, Query> {
pub fn new(iter: Box<dyn Iterator<Item = Result<RankingRuleOutput<Query>>> + 'search>) -> Self {
Self { iter }
}
}
impl<'search, Query> RankingRuleOutputIter<'search, Query>
for RankingRuleOutputIterWrapper<'search, Query>
{
fn next_bucket(&mut self) -> Result<Option<RankingRuleOutput<Query>>> {
match self.iter.next() {
Some(x) => x.map(Some),
None => Ok(None),
}
}
}
use crate::{
// facet::FacetType,
heed_codec::{facet::FacetGroupKeyCodec, ByteSliceRefCodec},