meilisearch/milli/src/search/new/mod.rs
2023-07-12 10:08:29 +02:00

613 lines
21 KiB
Rust

mod bucket_sort;
mod db_cache;
mod distinct;
mod geo_sort;
mod graph_based_ranking_rule;
mod interner;
mod limits;
mod logger;
pub mod matches;
mod query_graph;
mod query_term;
mod ranking_rule_graph;
mod ranking_rules;
mod resolve_query_graph;
mod small_bitmap;
mod exact_attribute;
mod sort;
#[cfg(test)]
mod tests;
use std::collections::{BTreeSet, HashSet};
use bucket_sort::{bucket_sort, BucketSortOutput};
use charabia::TokenizerBuilder;
use db_cache::DatabaseCache;
use exact_attribute::ExactAttribute;
use graph_based_ranking_rule::{Exactness, Fid, Position, Proximity, Typo};
use heed::RoTxn;
use hnsw::Searcher;
use interner::{DedupInterner, Interner};
pub use logger::visual::VisualSearchLogger;
pub use logger::{DefaultSearchLogger, SearchLogger};
use query_graph::{QueryGraph, QueryNode};
use query_term::{located_query_terms_from_tokens, LocatedQueryTerm, Phrase, QueryTerm};
use ranking_rules::{
BoxRankingRule, PlaceholderQuery, RankingRule, RankingRuleOutput, RankingRuleQueryTrait,
};
use resolve_query_graph::{compute_query_graph_docids, PhraseDocIdsCache};
use roaring::RoaringBitmap;
use sort::Sort;
use space::Neighbor;
use self::geo_sort::GeoSort;
pub use self::geo_sort::Strategy as GeoSortStrategy;
use self::graph_based_ranking_rule::Words;
use self::interner::Interned;
use crate::error::FieldIdMapMissingEntry;
use crate::score_details::{ScoreDetails, ScoringStrategy};
use crate::search::new::distinct::apply_distinct_rule;
use crate::{
normalize_vector, AscDesc, DocumentId, Filter, Index, Member, Result, TermsMatchingStrategy,
UserError, BEU32,
};
/// A structure used throughout the execution of a search query.
pub struct SearchContext<'ctx> {
pub index: &'ctx Index,
pub txn: &'ctx RoTxn<'ctx>,
pub db_cache: DatabaseCache<'ctx>,
pub word_interner: DedupInterner<String>,
pub phrase_interner: DedupInterner<Phrase>,
pub term_interner: Interner<QueryTerm>,
pub phrase_docids: PhraseDocIdsCache,
pub restricted_fids: Option<Vec<u16>>,
}
impl<'ctx> SearchContext<'ctx> {
pub fn new(index: &'ctx Index, txn: &'ctx RoTxn<'ctx>) -> Self {
Self {
index,
txn,
db_cache: <_>::default(),
word_interner: <_>::default(),
phrase_interner: <_>::default(),
term_interner: <_>::default(),
phrase_docids: <_>::default(),
restricted_fids: None,
}
}
pub fn searchable_attributes(&mut self, searchable_attributes: &'ctx [String]) -> Result<()> {
let fids_map = self.index.fields_ids_map(self.txn)?;
let searchable_names = self.index.searchable_fields(self.txn)?;
let mut restricted_fids = Vec::new();
let mut contains_wildcard = false;
for field_name in searchable_attributes {
if field_name == "*" {
contains_wildcard = true;
continue;
}
let searchable_contains_name =
searchable_names.as_ref().map(|sn| sn.iter().any(|name| name == field_name));
let fid = match (fids_map.id(field_name), searchable_contains_name) {
// The Field id exist and the field is searchable
(Some(fid), Some(true)) | (Some(fid), None) => fid,
// The field is searchable but the Field id doesn't exist => Internal Error
(None, Some(true)) => {
return Err(FieldIdMapMissingEntry::FieldName {
field_name: field_name.to_string(),
process: "search",
}
.into())
}
// The field is not searchable => User error
_otherwise => {
let mut valid_fields: BTreeSet<_> =
fids_map.names().map(String::from).collect();
// Filter by the searchable names
if let Some(sn) = searchable_names {
let searchable_names = sn.iter().map(|s| s.to_string()).collect();
valid_fields = &valid_fields & &searchable_names;
}
let searchable_count = valid_fields.len();
// Remove hidden fields
if let Some(dn) = self.index.displayed_fields(self.txn)? {
let displayable_names = dn.iter().map(|s| s.to_string()).collect();
valid_fields = &valid_fields & &displayable_names;
}
let hidden_fields = searchable_count > valid_fields.len();
let field = field_name.to_string();
return Err(UserError::InvalidSearchableAttribute {
field,
valid_fields,
hidden_fields,
}
.into());
}
};
restricted_fids.push(fid);
}
self.restricted_fids = (!contains_wildcard).then_some(restricted_fids);
Ok(())
}
}
#[derive(Clone, Copy, PartialEq, PartialOrd, Ord, Eq)]
pub enum Word {
Original(Interned<String>),
Derived(Interned<String>),
}
impl Word {
pub fn interned(&self) -> Interned<String> {
match self {
Word::Original(word) => *word,
Word::Derived(word) => *word,
}
}
}
/// Apply the [`TermsMatchingStrategy`] to the query graph and resolve it.
fn resolve_maximally_reduced_query_graph(
ctx: &mut SearchContext,
universe: &RoaringBitmap,
query_graph: &QueryGraph,
matching_strategy: TermsMatchingStrategy,
logger: &mut dyn SearchLogger<QueryGraph>,
) -> Result<RoaringBitmap> {
let mut graph = query_graph.clone();
let nodes_to_remove = match matching_strategy {
TermsMatchingStrategy::Last => query_graph
.removal_order_for_terms_matching_strategy_last(ctx)
.iter()
.flat_map(|x| x.iter())
.collect(),
TermsMatchingStrategy::All => vec![],
};
graph.remove_nodes_keep_edges(&nodes_to_remove);
logger.query_for_initial_universe(&graph);
let docids = compute_query_graph_docids(ctx, &graph, universe)?;
Ok(docids)
}
fn resolve_universe(
ctx: &mut SearchContext,
initial_universe: &RoaringBitmap,
query_graph: &QueryGraph,
matching_strategy: TermsMatchingStrategy,
logger: &mut dyn SearchLogger<QueryGraph>,
) -> Result<RoaringBitmap> {
resolve_maximally_reduced_query_graph(
ctx,
initial_universe,
query_graph,
matching_strategy,
logger,
)
}
/// Return the list of initialised ranking rules to be used for a placeholder search.
fn get_ranking_rules_for_placeholder_search<'ctx>(
ctx: &SearchContext<'ctx>,
sort_criteria: &Option<Vec<AscDesc>>,
geo_strategy: geo_sort::Strategy,
) -> Result<Vec<BoxRankingRule<'ctx, PlaceholderQuery>>> {
let mut sort = false;
let mut sorted_fields = HashSet::new();
let mut geo_sorted = false;
let mut ranking_rules: Vec<BoxRankingRule<PlaceholderQuery>> = vec![];
let settings_ranking_rules = ctx.index.criteria(ctx.txn)?;
for rr in settings_ranking_rules {
match rr {
// These rules need a query to have an effect; ignore them in placeholder search
crate::Criterion::Words
| crate::Criterion::Typo
| crate::Criterion::Attribute
| crate::Criterion::Proximity
| crate::Criterion::Exactness => continue,
crate::Criterion::Sort => {
if sort {
continue;
}
resolve_sort_criteria(
sort_criteria,
ctx,
&mut ranking_rules,
&mut sorted_fields,
&mut geo_sorted,
geo_strategy,
)?;
sort = true;
}
crate::Criterion::Asc(field_name) => {
if sorted_fields.contains(&field_name) {
continue;
}
sorted_fields.insert(field_name.clone());
ranking_rules.push(Box::new(Sort::new(ctx.index, ctx.txn, field_name, true)?));
}
crate::Criterion::Desc(field_name) => {
if sorted_fields.contains(&field_name) {
continue;
}
sorted_fields.insert(field_name.clone());
ranking_rules.push(Box::new(Sort::new(ctx.index, ctx.txn, field_name, false)?));
}
}
}
Ok(ranking_rules)
}
/// Return the list of initialised ranking rules to be used for a query graph search.
fn get_ranking_rules_for_query_graph_search<'ctx>(
ctx: &SearchContext<'ctx>,
sort_criteria: &Option<Vec<AscDesc>>,
geo_strategy: geo_sort::Strategy,
terms_matching_strategy: TermsMatchingStrategy,
) -> Result<Vec<BoxRankingRule<'ctx, QueryGraph>>> {
// query graph search
let mut words = false;
let mut typo = false;
let mut proximity = false;
let mut sort = false;
let mut attribute = false;
let mut exactness = false;
let mut sorted_fields = HashSet::new();
let mut geo_sorted = false;
// Don't add the `words` ranking rule if the term matching strategy is `All`
if matches!(terms_matching_strategy, TermsMatchingStrategy::All) {
words = true;
}
let mut ranking_rules: Vec<BoxRankingRule<QueryGraph>> = vec![];
let settings_ranking_rules = ctx.index.criteria(ctx.txn)?;
for rr in settings_ranking_rules {
// Add Words before any of: typo, proximity, attribute
match rr {
crate::Criterion::Typo
| crate::Criterion::Attribute
| crate::Criterion::Proximity
| crate::Criterion::Exactness => {
if !words {
ranking_rules.push(Box::new(Words::new(terms_matching_strategy)));
words = true;
}
}
_ => {}
}
match rr {
crate::Criterion::Words => {
if words {
continue;
}
ranking_rules.push(Box::new(Words::new(terms_matching_strategy)));
words = true;
}
crate::Criterion::Typo => {
if typo {
continue;
}
typo = true;
ranking_rules.push(Box::new(Typo::new(None)));
}
crate::Criterion::Proximity => {
if proximity {
continue;
}
proximity = true;
ranking_rules.push(Box::new(Proximity::new(None)));
}
crate::Criterion::Attribute => {
if attribute {
continue;
}
attribute = true;
ranking_rules.push(Box::new(Fid::new(None)));
ranking_rules.push(Box::new(Position::new(None)));
}
crate::Criterion::Sort => {
if sort {
continue;
}
resolve_sort_criteria(
sort_criteria,
ctx,
&mut ranking_rules,
&mut sorted_fields,
&mut geo_sorted,
geo_strategy,
)?;
sort = true;
}
crate::Criterion::Exactness => {
if exactness {
continue;
}
ranking_rules.push(Box::new(ExactAttribute::new()));
ranking_rules.push(Box::new(Exactness::new()));
exactness = true;
}
crate::Criterion::Asc(field_name) => {
if sorted_fields.contains(&field_name) {
continue;
}
sorted_fields.insert(field_name.clone());
ranking_rules.push(Box::new(Sort::new(ctx.index, ctx.txn, field_name, true)?));
}
crate::Criterion::Desc(field_name) => {
if sorted_fields.contains(&field_name) {
continue;
}
sorted_fields.insert(field_name.clone());
ranking_rules.push(Box::new(Sort::new(ctx.index, ctx.txn, field_name, false)?));
}
}
}
Ok(ranking_rules)
}
fn resolve_sort_criteria<'ctx, Query: RankingRuleQueryTrait>(
sort_criteria: &Option<Vec<AscDesc>>,
ctx: &SearchContext<'ctx>,
ranking_rules: &mut Vec<BoxRankingRule<'ctx, Query>>,
sorted_fields: &mut HashSet<String>,
geo_sorted: &mut bool,
geo_strategy: geo_sort::Strategy,
) -> Result<()> {
let sort_criteria = sort_criteria.clone().unwrap_or_default();
ranking_rules.reserve(sort_criteria.len());
for criterion in sort_criteria {
match criterion {
AscDesc::Asc(Member::Field(field_name)) => {
if sorted_fields.contains(&field_name) {
continue;
}
sorted_fields.insert(field_name.clone());
ranking_rules.push(Box::new(Sort::new(ctx.index, ctx.txn, field_name, true)?));
}
AscDesc::Desc(Member::Field(field_name)) => {
if sorted_fields.contains(&field_name) {
continue;
}
sorted_fields.insert(field_name.clone());
ranking_rules.push(Box::new(Sort::new(ctx.index, ctx.txn, field_name, false)?));
}
AscDesc::Asc(Member::Geo(point)) => {
if *geo_sorted {
continue;
}
let geo_faceted_docids = ctx.index.geo_faceted_documents_ids(ctx.txn)?;
ranking_rules.push(Box::new(GeoSort::new(
geo_strategy,
geo_faceted_docids,
point,
true,
)?));
}
AscDesc::Desc(Member::Geo(point)) => {
if *geo_sorted {
continue;
}
let geo_faceted_docids = ctx.index.geo_faceted_documents_ids(ctx.txn)?;
ranking_rules.push(Box::new(GeoSort::new(
geo_strategy,
geo_faceted_docids,
point,
false,
)?));
}
};
}
Ok(())
}
#[allow(clippy::too_many_arguments)]
pub fn execute_search(
ctx: &mut SearchContext,
query: &Option<String>,
vector: &Option<Vec<f32>>,
terms_matching_strategy: TermsMatchingStrategy,
scoring_strategy: ScoringStrategy,
exhaustive_number_hits: bool,
filters: &Option<Filter>,
sort_criteria: &Option<Vec<AscDesc>>,
geo_strategy: geo_sort::Strategy,
from: usize,
length: usize,
words_limit: Option<usize>,
placeholder_search_logger: &mut dyn SearchLogger<PlaceholderQuery>,
query_graph_logger: &mut dyn SearchLogger<QueryGraph>,
) -> Result<PartialSearchResult> {
let mut universe = if let Some(filters) = filters {
filters.evaluate(ctx.txn, ctx.index)?
} else {
ctx.index.documents_ids(ctx.txn)?
};
check_sort_criteria(ctx, sort_criteria.as_ref())?;
if let Some(vector) = vector {
let mut searcher = Searcher::new();
let hnsw = ctx.index.vector_hnsw(ctx.txn)?.unwrap_or_default();
let ef = hnsw.len().min(100);
let mut dest = vec![Neighbor { index: 0, distance: 0 }; ef];
let vector = normalize_vector(vector.clone());
let neighbors = hnsw.nearest(&vector, ef, &mut searcher, &mut dest[..]);
let mut docids = Vec::new();
let mut uniq_docids = RoaringBitmap::new();
for Neighbor { index, distance: _ } in neighbors.iter() {
let index = BEU32::new(*index as u32);
let docid = ctx.index.vector_id_docid.get(ctx.txn, &index)?.unwrap().get();
if universe.contains(docid) && uniq_docids.insert(docid) {
docids.push(docid);
if docids.len() == (from + length) {
break;
}
}
}
// return the nearest documents that are also part of the candidates
// along with a dummy list of scores that are useless in this context.
let docids: Vec<_> = docids.into_iter().skip(from).take(length).collect();
return Ok(PartialSearchResult {
candidates: universe,
document_scores: vec![Vec::new(); docids.len()],
documents_ids: docids,
located_query_terms: None,
});
}
let mut located_query_terms = None;
let query_terms = if let Some(query) = query {
// We make sure that the analyzer is aware of the stop words
// this ensures that the query builder is able to properly remove them.
let mut tokbuilder = TokenizerBuilder::new();
let stop_words = ctx.index.stop_words(ctx.txn)?;
if let Some(ref stop_words) = stop_words {
tokbuilder.stop_words(stop_words);
}
let script_lang_map = ctx.index.script_language(ctx.txn)?;
if !script_lang_map.is_empty() {
tokbuilder.allow_list(&script_lang_map);
}
let tokenizer = tokbuilder.build();
let tokens = tokenizer.tokenize(query);
let query_terms = located_query_terms_from_tokens(ctx, tokens, words_limit)?;
if query_terms.is_empty() {
// Do a placeholder search instead
None
} else {
Some(query_terms)
}
} else {
None
};
let bucket_sort_output = if let Some(query_terms) = query_terms {
let (graph, new_located_query_terms) = QueryGraph::from_query(ctx, &query_terms)?;
located_query_terms = Some(new_located_query_terms);
let ranking_rules = get_ranking_rules_for_query_graph_search(
ctx,
sort_criteria,
geo_strategy,
terms_matching_strategy,
)?;
universe =
resolve_universe(ctx, &universe, &graph, terms_matching_strategy, query_graph_logger)?;
bucket_sort(
ctx,
ranking_rules,
&graph,
&universe,
from,
length,
scoring_strategy,
query_graph_logger,
)?
} else {
let ranking_rules =
get_ranking_rules_for_placeholder_search(ctx, sort_criteria, geo_strategy)?;
bucket_sort(
ctx,
ranking_rules,
&PlaceholderQuery,
&universe,
from,
length,
scoring_strategy,
placeholder_search_logger,
)?
};
let BucketSortOutput { docids, scores, mut all_candidates } = bucket_sort_output;
let fields_ids_map = ctx.index.fields_ids_map(ctx.txn)?;
// The candidates is the universe unless the exhaustive number of hits
// is requested and a distinct attribute is set.
if exhaustive_number_hits {
if let Some(f) = ctx.index.distinct_field(ctx.txn)? {
if let Some(distinct_fid) = fields_ids_map.id(f) {
all_candidates = apply_distinct_rule(ctx, distinct_fid, &all_candidates)?.remaining;
}
}
}
Ok(PartialSearchResult {
candidates: all_candidates,
document_scores: scores,
documents_ids: docids,
located_query_terms,
})
}
fn check_sort_criteria(ctx: &SearchContext, sort_criteria: Option<&Vec<AscDesc>>) -> Result<()> {
let sort_criteria = if let Some(sort_criteria) = sort_criteria {
sort_criteria
} else {
return Ok(());
};
if sort_criteria.is_empty() {
return Ok(());
}
// We check that the sort ranking rule exists and throw an
// error if we try to use it and that it doesn't.
let sort_ranking_rule_missing = !ctx.index.criteria(ctx.txn)?.contains(&crate::Criterion::Sort);
if sort_ranking_rule_missing {
return Err(UserError::SortRankingRuleMissing.into());
}
// We check that we are allowed to use the sort criteria, we check
// that they are declared in the sortable fields.
let sortable_fields = ctx.index.sortable_fields(ctx.txn)?;
for asc_desc in sort_criteria {
match asc_desc.member() {
Member::Field(ref field) if !crate::is_faceted(field, &sortable_fields) => {
return Err(UserError::InvalidSortableAttribute {
field: field.to_string(),
valid_fields: sortable_fields.into_iter().collect(),
})?
}
Member::Geo(_) if !sortable_fields.contains("_geo") => {
return Err(UserError::InvalidSortableAttribute {
field: "_geo".to_string(),
valid_fields: sortable_fields.into_iter().collect(),
})?
}
_ => (),
}
}
Ok(())
}
pub struct PartialSearchResult {
pub located_query_terms: Option<Vec<LocatedQueryTerm>>,
pub candidates: RoaringBitmap,
pub documents_ids: Vec<DocumentId>,
pub document_scores: Vec<Vec<ScoreDetails>>,
}