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Code Issues Releases Wiki Activity

Compute edges of proximity graph lazily

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This commit is contained in:
Loïc Lecrenier 2023-03-21 10:44:40 +01:00
parent 272cd7ebbd
commit 83e5b4ed0d
12 changed files with 345 additions and 841 deletions
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1
milli/src/search/mod.rs
View File

@ -367,6 +367,7 @@ pub fn word_derivations<'c>(
match cache.entry((word.to_string(), is_prefix, max_typo)) {
Entry::Occupied(entry) => Ok(entry.into_mut()),
Entry::Vacant(entry) => {
// println!("word derivations {word} {is_prefix} {max_typo}");
let mut derived_words = Vec::new();
if max_typo == 0 {
if is_prefix {

7
milli/src/search/new/graph_based_ranking_rule.rs
View File

@ -318,9 +318,10 @@ impl<'ctx, G: RankingRuleGraphTrait> RankingRule<'ctx, QueryGraph> for GraphBase
let mut used_words = HashSet::new();
let mut used_phrases = HashSet::new();
for condition in used_conditions.iter() {
let condition = graph.conditions_interner.get(condition);
used_words.extend(G::words_used_by_condition(ctx, condition)?);
used_phrases.extend(G::phrases_used_by_condition(ctx, condition)?);
let (ws, ps) =
condition_docids_cache.get_condition_used_words_and_phrases(condition);
used_words.extend(ws);
used_phrases.extend(ps);
}
// 2. Remove the unused words and phrases from all the nodes in the graph
let mut nodes_to_remove = vec![];

2
milli/src/search/new/interner.rs
View File

@ -30,7 +30,7 @@ impl<T> Interned<T> {
#[derive(Clone)]
pub struct DedupInterner<T> {
stable_store: Vec<T>,
lookup: FxHashMap<T, Interned<T>>,
lookup: FxHashMap<T, Interned<T>>, // TODO: Arc
}
impl<T> Default for DedupInterner<T> {
fn default() -> Self {

365
milli/src/search/new/mod.rs
View File

@ -287,368 +287,3 @@ impl<'a> Search<'a> {
todo!()
}
}
#[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,
"released from prison by the government",
// "which a the releases from poison by the government",
// "sun flower s are the best",
// "zero config",
TermsMatchingStrategy::Last,
None,
0,
20,
&mut DefaultSearchLogger,
&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.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(), 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",
// "sun flower s are the best",
"zero config",
);
s.terms_matching_strategy(TermsMatchingStrategy::Last);
// s.criterion_implementation_strategy(crate::CriterionImplementationStrategy::OnlyIterative);
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",
TermsMatchingStrategy::Last,
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)
}
}

40
milli/src/search/new/ranking_rule_graph/condition_docids_cache.rs
View File

@ -1,19 +1,28 @@
use std::marker::PhantomData;
use fxhash::FxHashMap;
use fxhash::{FxHashMap, FxHashSet};
use roaring::RoaringBitmap;
use super::{RankingRuleGraph, RankingRuleGraphTrait};
use crate::search::new::interner::Interned;
use crate::search::new::query_term::Phrase;
use crate::search::new::SearchContext;
use crate::Result;
// TODO: give a generation to each universe, then be able to get the exact
// delta of docids between two universes of different generations!
#[derive(Default)]
pub struct ComputedCondition {
docids: RoaringBitmap,
universe_len: u64,
used_words: FxHashSet<Interned<String>>,
used_phrases: FxHashSet<Interned<Phrase>>,
}
/// A cache storing the document ids associated with each ranking rule edge
pub struct ConditionDocIdsCache<G: RankingRuleGraphTrait> {
pub cache: FxHashMap<Interned<G::Condition>, (u64, RoaringBitmap)>,
pub cache: FxHashMap<Interned<G::Condition>, ComputedCondition>,
_phantom: PhantomData<G>,
}
impl<G: RankingRuleGraphTrait> Default for ConditionDocIdsCache<G> {
@ -22,6 +31,14 @@ impl<G: RankingRuleGraphTrait> Default for ConditionDocIdsCache<G> {
}
}
impl<G: RankingRuleGraphTrait> ConditionDocIdsCache<G> {
pub fn get_condition_used_words_and_phrases(
&mut self,
interned_condition: Interned<G::Condition>,
) -> (&FxHashSet<Interned<String>>, &FxHashSet<Interned<Phrase>>) {
let ComputedCondition { used_words, used_phrases, .. } = &self.cache[&interned_condition];
(used_words, used_phrases)
}
/// Retrieve the document ids for the given edge condition.
///
/// If the cache does not yet contain these docids, they are computed
@ -30,14 +47,14 @@ impl<G: RankingRuleGraphTrait> ConditionDocIdsCache<G> {
&'s mut self,
ctx: &mut SearchContext<'ctx>,
interned_condition: Interned<G::Condition>,
graph: &RankingRuleGraph<G>,
// TODO: maybe universe doesn't belong here
graph: &mut RankingRuleGraph<G>,
universe: &RoaringBitmap,
) -> Result<&'s RoaringBitmap> {
if self.cache.contains_key(&interned_condition) {
// TODO compare length of universe compared to the one in self
// if it is smaller, then update the value
let (universe_len, docids) = self.cache.entry(interned_condition).or_default();
let ComputedCondition { docids, universe_len, .. } =
self.cache.entry(interned_condition).or_default();
if *universe_len == universe.len() {
return Ok(docids);
} else {
@ -46,12 +63,13 @@ impl<G: RankingRuleGraphTrait> ConditionDocIdsCache<G> {
return Ok(docids);
}
}
// TODO: maybe universe doesn't belong here
let condition = graph.conditions_interner.get(interned_condition);
// TODO: faster way to do this?
let docids = G::resolve_condition(ctx, condition, universe)?;
let _ = self.cache.insert(interned_condition, (universe.len(), docids));
let (_, docids) = &self.cache[&interned_condition];
let condition = graph.conditions_interner.get_mut(interned_condition);
let (docids, used_words, used_phrases) = G::resolve_condition(ctx, condition, universe)?;
let _ = self.cache.insert(
interned_condition,
ComputedCondition { docids, universe_len: universe.len(), used_words, used_phrases },
);
let ComputedCondition { docids, .. } = &self.cache[&interned_condition];
Ok(docids)
}
}

14
milli/src/search/new/ranking_rule_graph/mod.rs
View File

@ -15,11 +15,11 @@ mod proximity;
/// Implementation of the `typo` ranking rule
mod typo;
use std::collections::HashSet;
use std::hash::Hash;
pub use condition_docids_cache::ConditionDocIdsCache;
pub use dead_ends_cache::DeadEndsCache;
use fxhash::FxHashSet;
pub use proximity::{ProximityCondition, ProximityGraph};
use roaring::RoaringBitmap;
pub use typo::{TypoCondition, TypoGraph};
@ -80,23 +80,13 @@ pub trait RankingRuleGraphTrait: Sized {
condition: &Self::Condition,
) -> Result<String>;
fn words_used_by_condition<'ctx>(
ctx: &mut SearchContext<'ctx>,
condition: &Self::Condition,
) -> Result<HashSet<Interned<String>>>;
fn phrases_used_by_condition<'ctx>(
ctx: &mut SearchContext<'ctx>,
condition: &Self::Condition,
) -> Result<HashSet<Interned<Phrase>>>;
/// Compute the document ids associated with the given edge condition,
/// restricted to the given universe.
fn resolve_condition<'ctx>(
ctx: &mut SearchContext<'ctx>,
condition: &Self::Condition,
universe: &RoaringBitmap,
) -> Result<RoaringBitmap>;
) -> Result<(RoaringBitmap, FxHashSet<Interned<String>>, FxHashSet<Interned<Phrase>>)>;
/// Return the costs and conditions of the edges going from the source node to the destination node
fn build_edges<'ctx>(

235
milli/src/search/new/ranking_rule_graph/proximity/build.rs
View File

@ -1,56 +1,18 @@
#![allow(clippy::too_many_arguments)]
use std::collections::BTreeMap;
use heed::RoTxn;
use super::ProximityCondition;
use crate::search::new::db_cache::DatabaseCache;
use crate::search::new::interner::{DedupInterner, Interned};
use crate::search::new::query_graph::QueryNodeData;
use crate::search::new::query_term::{LocatedQueryTerm, Phrase, QueryTerm};
use crate::search::new::ranking_rule_graph::proximity::WordPair;
use crate::search::new::query_term::LocatedQueryTerm;
use crate::search::new::{QueryNode, SearchContext};
use crate::Result;
fn last_word_of_term_iter<'t>(
t: &'t QueryTerm,
phrase_interner: &'t DedupInterner<Phrase>,
) -> impl Iterator<Item = (Option<Interned<Phrase>>, Interned<String>)> + 't {
t.all_single_words_except_prefix_db().map(|w| (None, w)).chain(t.all_phrases().flat_map(
move |p| {
let phrase = phrase_interner.get(p);
phrase.words.last().unwrap().map(|last| (Some(p), last))
},
))
}
fn first_word_of_term_iter<'t>(
t: &'t QueryTerm,
phrase_interner: &'t DedupInterner<Phrase>,
) -> impl Iterator<Item = (Interned<String>, Option<Interned<Phrase>>)> + 't {
t.all_single_words_except_prefix_db().map(|w| (w, None)).chain(t.all_phrases().flat_map(
move |p| {
let phrase = phrase_interner.get(p);
phrase.words.first().unwrap().map(|first| (first, Some(p)))
},
))
}
pub fn build_edges<'ctx>(
ctx: &mut SearchContext<'ctx>,
_ctx: &mut SearchContext<'ctx>,
conditions_interner: &mut DedupInterner<ProximityCondition>,
from_node: &QueryNode,
to_node: &QueryNode,
) -> Result<Vec<(u8, Option<Interned<ProximityCondition>>)>> {
let SearchContext {
index,
txn,
db_cache,
word_interner,
phrase_interner,
term_interner,
term_docids: _,
} = ctx;
let right_term = match &to_node.data {
QueryNodeData::End => return Ok(vec![(0, None)]),
QueryNodeData::Deleted | QueryNodeData::Start => return Ok(vec![]),
@ -59,13 +21,11 @@ pub fn build_edges<'ctx>(
let LocatedQueryTerm { value: right_term_interned, positions: right_positions } = right_term;
let (right_term, right_start_position, right_ngram_length) =
(term_interner.get(*right_term_interned), *right_positions.start(), right_positions.len());
let (right_start_position, right_ngram_length) =
(*right_positions.start(), right_positions.len());
let (left_term, left_end_position) = match &from_node.data {
QueryNodeData::Term(LocatedQueryTerm { value, positions }) => {
(term_interner.get(*value), *positions.end())
}
let (left_term_interned, left_end_position) = match &from_node.data {
QueryNodeData::Term(LocatedQueryTerm { value, positions }) => (*value, *positions.end()),
QueryNodeData::Deleted => return Ok(vec![]),
QueryNodeData::Start => {
return Ok(vec![(
@ -94,175 +54,24 @@ pub fn build_edges<'ctx>(
)]);
}
let mut cost_word_pairs = BTreeMap::<u8, Vec<WordPair>>::new();
if let Some(right_prefix) = right_term.use_prefix_db {
for (left_phrase, left_word) in last_word_of_term_iter(left_term, phrase_interner) {
add_prefix_edges(
index,
txn,
db_cache,
word_interner,
right_ngram_length,
left_word,
right_prefix,
&mut cost_word_pairs,
left_phrase,
)?;
}
}
// 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.
// Maybe 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
for (left_phrase, left_word) in last_word_of_term_iter(left_term, phrase_interner) {
for (right_word, right_phrase) in first_word_of_term_iter(right_term, phrase_interner) {
add_non_prefix_edges(
index,
txn,
db_cache,
word_interner,
right_ngram_length,
left_word,
right_word,
&mut cost_word_pairs,
&[left_phrase, right_phrase].iter().copied().flatten().collect::<Vec<_>>(),
)?;
}
}
let mut new_edges = cost_word_pairs
.into_iter()
.map(|(cost, word_pairs)| {
(
let mut conditions = vec![];
for cost in right_ngram_length..(7 + right_ngram_length) {
let cost = cost as u8;
conditions.push((
cost,
Some(conditions_interner.insert(ProximityCondition::Uninit {
left_term: left_term_interned,
right_term: *right_term_interned,
right_term_ngram_len: right_ngram_length as u8,
cost,
Some(
conditions_interner
.insert(ProximityCondition::Pairs { pairs: word_pairs.into_boxed_slice() }),
),
)
})
.collect::<Vec<_>>();
new_edges.push((
8 + (right_ngram_length - 1) as u8,
})),
))
}
conditions.push((
(7 + right_ngram_length) as u8,
Some(conditions_interner.insert(ProximityCondition::Term { term: *right_term_interned })),
));
Ok(new_edges)
}
fn add_prefix_edges<'ctx>(
index: &mut &crate::Index,
txn: &'ctx RoTxn,
db_cache: &mut DatabaseCache<'ctx>,
word_interner: &mut DedupInterner<String>,
right_ngram_length: usize,
left_word: Interned<String>,
right_prefix: Interned<String>,
cost_proximity_word_pairs: &mut BTreeMap<u8, Vec<WordPair>>,
left_phrase: Option<Interned<Phrase>>,
) -> Result<()> {
for proximity in 1..=(8 - right_ngram_length) {
let cost = (proximity + right_ngram_length - 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 db_cache
.get_word_prefix_pair_proximity_docids(
index,
txn,
word_interner,
left_word,
right_prefix,
proximity as u8,
)?
.is_some()
{
cost_proximity_word_pairs.entry(cost).or_default().push(WordPair::WordPrefix {
phrases: left_phrase.into_iter().collect(),
left: left_word,
right_prefix,
proximity: proximity as u8,
});
}
// No swapping when computing the proximity between a phrase and a word
if left_phrase.is_none()
&& db_cache
.get_prefix_word_pair_proximity_docids(
index,
txn,
word_interner,
right_prefix,
left_word,
proximity as u8 - 1,
)?
.is_some()
{
cost_proximity_word_pairs.entry(cost).or_default().push(WordPair::WordPrefixSwapped {
left_prefix: right_prefix,
right: left_word,
proximity: proximity as u8 - 1,
});
}
}
Ok(())
}
fn add_non_prefix_edges<'ctx>(
index: &mut &crate::Index,
txn: &'ctx RoTxn,
db_cache: &mut DatabaseCache<'ctx>,
word_interner: &mut DedupInterner<String>,
right_ngram_length: usize,
word1: Interned<String>,
word2: Interned<String>,
cost_proximity_word_pairs: &mut BTreeMap<u8, Vec<WordPair>>,
phrases: &[Interned<Phrase>],
) -> Result<()> {
for proximity in 1..=(8 - right_ngram_length) {
let cost = (proximity + right_ngram_length - 1) as u8;
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().push(WordPair::Words {
phrases: phrases.to_vec(),
left: word1,
right: word2,
proximity: proximity as u8,
});
}
if proximity > 1
// no swapping when either term is a phrase
&& phrases.is_empty()
&& 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).or_default().push(WordPair::Words {
phrases: vec![],
left: word2,
right: word1,
proximity: proximity as u8 - 1,
});
}
}
Ok(())
Ok(conditions)
}

331
milli/src/search/new/ranking_rule_graph/proximity/compute_docids.rs
View File

@ -1,6 +1,15 @@
#![allow(clippy::too_many_arguments)]
use std::iter::FromIterator;
use fxhash::FxHashSet;
use heed::RoTxn;
use roaring::RoaringBitmap;
use super::{ProximityCondition, WordPair};
use super::ProximityCondition;
use crate::search::new::db_cache::DatabaseCache;
use crate::search::new::interner::{DedupInterner, Interned};
use crate::search::new::query_term::{Phrase, QueryTerm};
use crate::search::new::SearchContext;
use crate::{CboRoaringBitmapCodec, Result};
@ -8,7 +17,7 @@ pub fn compute_docids<'ctx>(
ctx: &mut SearchContext<'ctx>,
condition: &ProximityCondition,
universe: &RoaringBitmap,
) -> Result<RoaringBitmap> {
) -> Result<(RoaringBitmap, FxHashSet<Interned<String>>, FxHashSet<Interned<Phrase>>)> {
let SearchContext {
index,
txn,
@ -18,96 +27,238 @@ pub fn compute_docids<'ctx>(
phrase_interner,
term_interner,
} = ctx;
let pairs = match condition {
ProximityCondition::Term { term } => {
return term_docids
.get_query_term_docids(
index,
txn,
db_cache,
word_interner,
term_interner,
phrase_interner,
*term,
)
.cloned()
let (left_term, right_term, right_term_ngram_len, cost) = match condition {
ProximityCondition::Uninit { left_term, right_term, right_term_ngram_len, cost } => {
(*left_term, *right_term, *right_term_ngram_len, *cost)
}
ProximityCondition::Term { term } => {
let term_v = term_interner.get(*term);
return Ok((
term_docids
.get_query_term_docids(
index,
txn,
db_cache,
word_interner,
term_interner,
phrase_interner,
*term,
)?
.clone(),
FxHashSet::from_iter(term_v.all_single_words_except_prefix_db()),
FxHashSet::from_iter(term_v.all_phrases()),
));
}
ProximityCondition::Pairs { pairs } => pairs,
};
let mut pair_docids = RoaringBitmap::new();
for pair in pairs.iter() {
let pair = match pair {
WordPair::Words { phrases, left, right, proximity } => {
let mut docids = db_cache
.get_word_pair_proximity_docids(
index,
txn,
word_interner,
*left,
*right,
*proximity,
)?
.map(CboRoaringBitmapCodec::deserialize_from)
.transpose()?
.unwrap_or_default();
if !docids.is_empty() {
for phrase in phrases {
docids &= ctx.term_docids.get_phrase_docids(
index,
txn,
db_cache,
word_interner,
&ctx.phrase_interner,
*phrase,
)?;
}
}
docids
}
WordPair::WordPrefix { phrases, left, right_prefix, proximity } => {
let mut docids = db_cache
.get_word_prefix_pair_proximity_docids(
index,
txn,
word_interner,
*left,
*right_prefix,
*proximity,
)?
.map(CboRoaringBitmapCodec::deserialize_from)
.transpose()?
.unwrap_or_default();
if !docids.is_empty() {
for phrase in phrases {
docids &= ctx.term_docids.get_phrase_docids(
index,
txn,
db_cache,
word_interner,
&ctx.phrase_interner,
*phrase,
)?;
}
}
docids
}
WordPair::WordPrefixSwapped { left_prefix, right, proximity } => db_cache
.get_prefix_word_pair_proximity_docids(
index,
txn,
word_interner,
*left_prefix,
*right,
*proximity,
)?
.map(CboRoaringBitmapCodec::deserialize_from)
.transpose()?
.unwrap_or_default(),
};
// TODO: deserialize bitmap within a universe
let bitmap = universe & pair;
pair_docids |= bitmap;
let left_term = term_interner.get(left_term);
let right_term = term_interner.get(right_term);
// e.g. for the simple words `sun .. flower`
// the cost is 5
// the forward proximity is 5
// the backward proximity is 4
//
// for the 2gram `the sunflower`
// the cost is 5
// the forward proximity is 4
// the backward proximity is 3
let forward_proximity = 1 + cost - right_term_ngram_len;
let backward_proximity = cost - right_term_ngram_len;
let mut used_words = FxHashSet::default();
let mut used_phrases = FxHashSet::default();
let mut docids = RoaringBitmap::new();
if let Some(right_prefix) = right_term.use_prefix_db {
for (left_phrase, left_word) in last_word_of_term_iter(left_term, phrase_interner) {
compute_prefix_edges(
index,
txn,
db_cache,
word_interner,
left_word,
right_prefix,
left_phrase,
forward_proximity,
backward_proximity,
&mut docids,
universe,
&mut used_words,
&mut used_phrases,
)?;
}
}
Ok(pair_docids)
// 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.
// Maybe 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
for (left_phrase, left_word) in last_word_of_term_iter(left_term, phrase_interner) {
for (right_word, right_phrase) in first_word_of_term_iter(right_term, phrase_interner) {
compute_non_prefix_edges(
index,
txn,
db_cache,
word_interner,
left_word,
right_word,
&[left_phrase, right_phrase].iter().copied().flatten().collect::<Vec<_>>(),
forward_proximity,
backward_proximity,
&mut docids,
universe,
&mut used_words,
&mut used_phrases,
)?;
}
}
Ok((docids, used_words, used_phrases))
}
fn compute_prefix_edges<'ctx>(
index: &mut &crate::Index,
txn: &'ctx RoTxn,
db_cache: &mut DatabaseCache<'ctx>,
word_interner: &mut DedupInterner<String>,
left_word: Interned<String>,
right_prefix: Interned<String>,
left_phrase: Option<Interned<Phrase>>,
forward_proximity: u8,
backward_proximity: u8,
docids: &mut RoaringBitmap,
universe: &RoaringBitmap,
used_words: &mut FxHashSet<Interned<String>>,
used_phrases: &mut FxHashSet<Interned<Phrase>>,
) -> Result<()> {
if let Some(phrase) = left_phrase {
// TODO: compute the phrase, take the intersection between
// the phrase and the docids
used_phrases.insert(phrase); // This is not fully correct
}
if let Some(new_docids) = db_cache.get_word_prefix_pair_proximity_docids(
index,
txn,
word_interner,
left_word,
right_prefix,
forward_proximity,
)? {
let new_docids = universe & CboRoaringBitmapCodec::deserialize_from(new_docids)?;
if !new_docids.is_empty() {
used_words.insert(left_word);
used_words.insert(right_prefix);
*docids |= new_docids;
}
}
// No swapping when computing the proximity between a phrase and a word
if left_phrase.is_none() {
if let Some(new_docids) = db_cache.get_prefix_word_pair_proximity_docids(
index,
txn,
word_interner,
right_prefix,
left_word,
backward_proximity,
)? {
let new_docids = universe & CboRoaringBitmapCodec::deserialize_from(new_docids)?;
if !new_docids.is_empty() {
used_words.insert(left_word);
used_words.insert(right_prefix);
*docids |= new_docids;
}
}
}
Ok(())
}
fn compute_non_prefix_edges<'ctx>(
index: &mut &crate::Index,
txn: &'ctx RoTxn,
db_cache: &mut DatabaseCache<'ctx>,
word_interner: &mut DedupInterner<String>,
word1: Interned<String>,
word2: Interned<String>,
phrases: &[Interned<Phrase>],
forward_proximity: u8,
backward_proximity: u8,
docids: &mut RoaringBitmap,
universe: &RoaringBitmap,
used_words: &mut FxHashSet<Interned<String>>,
used_phrases: &mut FxHashSet<Interned<Phrase>>,
) -> Result<()> {
if !phrases.is_empty() {
// TODO: compute the docids associated with these phrases
// take their intersection with the new docids
used_phrases.extend(phrases); // This is not fully correct
}
if let Some(new_docids) = db_cache.get_word_pair_proximity_docids(
index,
txn,
word_interner,
word1,
word2,
forward_proximity,
)? {
let new_docids = universe & CboRoaringBitmapCodec::deserialize_from(new_docids)?;
if !new_docids.is_empty() {
used_words.insert(word1);
used_words.insert(word2);
*docids |= new_docids;
}
}
if backward_proximity >= 1
// no swapping when either term is a phrase
&& phrases.is_empty()
{
if let Some(new_docids) = db_cache.get_word_pair_proximity_docids(
index,
txn,
word_interner,
word2,
word1,
backward_proximity,
)? {
let new_docids = universe & CboRoaringBitmapCodec::deserialize_from(new_docids)?;
if !new_docids.is_empty() {
used_words.insert(word1);
used_words.insert(word2);
*docids |= new_docids;
}
}
}
Ok(())
}
fn last_word_of_term_iter<'t>(
t: &'t QueryTerm,
phrase_interner: &'t DedupInterner<Phrase>,
) -> impl Iterator<Item = (Option<Interned<Phrase>>, Interned<String>)> + 't {
t.all_single_words_except_prefix_db().map(|w| (None, w)).chain(t.all_phrases().flat_map(
move |p| {
let phrase = phrase_interner.get(p);
phrase.words.last().unwrap().map(|last| (Some(p), last))
},
))
}
fn first_word_of_term_iter<'t>(
t: &'t QueryTerm,
phrase_interner: &'t DedupInterner<Phrase>,
) -> impl Iterator<Item = (Interned<String>, Option<Interned<Phrase>>)> + 't {
t.all_single_words_except_prefix_db().map(|w| (w, None)).chain(t.all_phrases().flat_map(
move |p| {
let phrase = phrase_interner.get(p);
phrase.words.first().unwrap().map(|first| (first, Some(p)))
},
))
}

140
milli/src/search/new/ranking_rule_graph/proximity/mod.rs
View File

@ -1,9 +1,7 @@
pub mod build;
pub mod compute_docids;
use std::collections::HashSet;
use std::iter::FromIterator;
use fxhash::FxHashSet;
use roaring::RoaringBitmap;
use super::{DeadEndsCache, RankingRuleGraph, RankingRuleGraphTrait};
@ -13,31 +11,17 @@ use crate::search::new::query_term::{Phrase, QueryTerm};
use crate::search::new::{QueryGraph, QueryNode, SearchContext};
use crate::Result;
#[derive(Debug, Clone, PartialEq, Eq, Hash)]
pub enum WordPair {
Words {
phrases: Vec<Interned<Phrase>>,
left: Interned<String>,
right: Interned<String>,
proximity: u8,
},
WordPrefix {
phrases: Vec<Interned<Phrase>>,
left: Interned<String>,
right_prefix: Interned<String>,
proximity: u8,
},
WordPrefixSwapped {
left_prefix: Interned<String>,
right: Interned<String>,
proximity: u8,
},
}
#[derive(Clone, PartialEq, Eq, Hash)]
pub enum ProximityCondition {
Term { term: Interned<QueryTerm> },
Pairs { pairs: Box<[WordPair]> },
Uninit {
left_term: Interned<QueryTerm>,
right_term: Interned<QueryTerm>,
right_term_ngram_len: u8,
cost: u8,
},
Term {
term: Interned<QueryTerm>,
},
}
pub enum ProximityGraph {}
@ -49,7 +33,8 @@ impl RankingRuleGraphTrait for ProximityGraph {
ctx: &mut SearchContext<'ctx>,
condition: &Self::Condition,
universe: &RoaringBitmap,
) -> Result<roaring::RoaringBitmap> {
) -> Result<(roaring::RoaringBitmap, FxHashSet<Interned<String>>, FxHashSet<Interned<Phrase>>)>
{
compute_docids::compute_docids(ctx, condition, universe)
}
@ -79,107 +64,14 @@ impl RankingRuleGraphTrait for ProximityGraph {
condition: &Self::Condition,
) -> Result<String> {
match condition {
ProximityCondition::Uninit { cost, .. } => {
// TODO
Ok(format!("{cost}: cost"))
}
ProximityCondition::Term { term } => {
let term = ctx.term_interner.get(*term);
Ok(format!("{} : exists", ctx.word_interner.get(term.original)))
}
ProximityCondition::Pairs { pairs } => {
let mut s = String::new();
for pair in pairs.iter() {
match pair {
WordPair::Words { phrases, left, right, proximity } => {
let left = ctx.word_interner.get(*left);
let right = ctx.word_interner.get(*right);
if !phrases.is_empty() {
s.push_str(&format!("{} phrases + ", phrases.len()));
}
s.push_str(&format!("\"{left} {right}\": {proximity}\n"));
}
WordPair::WordPrefix { phrases, left, right_prefix, proximity } => {
let left = ctx.word_interner.get(*left);
let right = ctx.word_interner.get(*right_prefix);
if !phrases.is_empty() {
s.push_str(&format!("{} phrases + ", phrases.len()));
}
s.push_str(&format!("\"{left} {right}...\" : {proximity}\n"));
}
WordPair::WordPrefixSwapped { left_prefix, right, proximity } => {
let left = ctx.word_interner.get(*left_prefix);
let right = ctx.word_interner.get(*right);
s.push_str(&format!("\"{left}... {right}\" : {proximity}\n"));
}
}
}
Ok(s)
}
}
}
fn words_used_by_condition<'ctx>(
ctx: &mut SearchContext<'ctx>,
condition: &Self::Condition,
) -> Result<HashSet<Interned<String>>> {
match condition {
ProximityCondition::Term { term } => {
let term = ctx.term_interner.get(*term);
Ok(HashSet::from_iter(term.all_single_words_except_prefix_db()))
}
ProximityCondition::Pairs { pairs } => {
let mut set = HashSet::new();
for pair in pairs.iter() {
match pair {
WordPair::Words { phrases: _, left, right, proximity: _ } => {
set.insert(*left);
set.insert(*right);
}
WordPair::WordPrefix { phrases: _, left, right_prefix, proximity: _ } => {
set.insert(*left);
// TODO: this is not correct, there should be another trait method for collecting the prefixes
// to be used with the prefix DBs
set.insert(*right_prefix);
}
WordPair::WordPrefixSwapped { left_prefix, right, proximity: _ } => {
// TODO: this is not correct, there should be another trait method for collecting the prefixes
// to be used with the prefix DBs
set.insert(*left_prefix);
set.insert(*right);
}
}
}
Ok(set)
}
}
}
fn phrases_used_by_condition<'ctx>(
ctx: &mut SearchContext<'ctx>,
condition: &Self::Condition,
) -> Result<HashSet<Interned<Phrase>>> {
match condition {
ProximityCondition::Term { term } => {
let term = ctx.term_interner.get(*term);
Ok(HashSet::from_iter(term.all_phrases()))
}
ProximityCondition::Pairs { pairs } => {
let mut set = HashSet::new();
for pair in pairs.iter() {
match pair {
WordPair::Words { phrases, left: _, right: _, proximity: _ } => {
set.extend(phrases.iter().copied());
}
WordPair::WordPrefix {
phrases,
left: _,
right_prefix: _,
proximity: _,
} => {
set.extend(phrases.iter().copied());
}
WordPair::WordPrefixSwapped { left_prefix: _, right: _, proximity: _ } => {}
}
}
Ok(set)
}
}
}
}

44
milli/src/search/new/ranking_rule_graph/typo/mod.rs
View File

@ -1,7 +1,8 @@
use std::collections::HashSet;
// use std::collections::HashSet;
use std::fmt::Write;
use std::iter::FromIterator;
use fxhash::FxHashSet;
use roaring::RoaringBitmap;
use super::{DeadEndsCache, RankingRuleGraph, RankingRuleGraphTrait};
@ -26,7 +27,7 @@ impl RankingRuleGraphTrait for TypoGraph {
ctx: &mut SearchContext<'ctx>,
condition: &Self::Condition,
universe: &RoaringBitmap,
) -> Result<RoaringBitmap> {
) -> Result<(RoaringBitmap, FxHashSet<Interned<String>>, FxHashSet<Interned<Phrase>>)> {
let SearchContext {
index,
txn,
@ -48,7 +49,12 @@ impl RankingRuleGraphTrait for TypoGraph {
condition.term,
)?;
Ok(docids)
let term = term_interner.get(condition.term);
Ok((
docids,
FxHashSet::from_iter(term.all_single_words_except_prefix_db()),
FxHashSet::from_iter(term.all_phrases()),
))
}
fn build_edges<'ctx>(
@ -202,21 +208,21 @@ impl RankingRuleGraphTrait for TypoGraph {
Ok(s)
}
fn words_used_by_condition<'ctx>(
ctx: &mut SearchContext<'ctx>,
condition: &Self::Condition,
) -> Result<HashSet<Interned<String>>> {
let TypoCondition { term, .. } = condition;
let term = ctx.term_interner.get(*term);
Ok(HashSet::from_iter(term.all_single_words_except_prefix_db()))
}
// fn words_used_by_condition<'ctx>(
// ctx: &mut SearchContext<'ctx>,
// condition: &Self::Condition,
// ) -> Result<HashSet<Interned<String>>> {
// let TypoCondition { term, .. } = condition;
// let term = ctx.term_interner.get(*term);
// Ok(HashSet::from_iter(term.all_single_words_except_prefix_db()))
// }
fn phrases_used_by_condition<'ctx>(
ctx: &mut SearchContext<'ctx>,
condition: &Self::Condition,
) -> Result<HashSet<Interned<Phrase>>> {
let TypoCondition { term, .. } = condition;
let term = ctx.term_interner.get(*term);
Ok(HashSet::from_iter(term.all_phrases()))
}
// fn phrases_used_by_condition<'ctx>(
// ctx: &mut SearchContext<'ctx>,
// condition: &Self::Condition,
// ) -> Result<HashSet<Interned<Phrase>>> {
// let TypoCondition { term, .. } = condition;
// let term = ctx.term_interner.get(*term);
// Ok(HashSet::from_iter(term.all_phrases()))
// }
}

3
milli/src/search/new/ranking_rules.rs
View File

@ -125,7 +125,7 @@ pub fn bucket_sort<'ctx, Q: RankingRuleQueryTrait>(
let mut results = vec![];
let mut cur_offset = 0usize;
/// Add the candidates to the results. Take `distinct`, `from`, `limit`, and `cur_offset`
/// Add the candidates to the results. Take `distinct`, `from`, `length`, and `cur_offset`
/// into account and inform the logger.
macro_rules! maybe_add_to_results {
($candidates:expr) => {
@ -181,6 +181,7 @@ pub fn bucket_sort<'ctx, Q: RankingRuleQueryTrait>(
cur_offset += len as usize;
};
}
while results.len() < length {
// The universe for this bucket is zero or one element, so we don't need to sort
// anything, just extend the results and go back to the parent ranking rule.

4
milli/src/search/new/words.rs
View File

@ -9,9 +9,9 @@ use super::{QueryGraph, RankingRule, RankingRuleOutput, SearchContext};
use crate::{Result, TermsMatchingStrategy};
pub struct Words {
exhausted: bool,
exhausted: bool, // TODO: remove
query_graph: Option<QueryGraph>,
iterating: bool,
iterating: bool, // TODO: remove
positions_to_remove: Vec<i8>,
terms_matching_strategy: TermsMatchingStrategy,
}