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Before improving fields AttrCount

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Removing the fields_count fetching reduced by 2 times the serach time, we should look at lazily pulling them form the criterions in needs

ugly-test: Make the fields_count fetching lazy

Just before running the exactness criterion
This commit is contained in:
Clément Renault 2019-11-29 16:31:47 +01:00 committed by Clément Renault
parent 11f3d7782d
commit ef6a4db182
No known key found for this signature in database
GPG Key ID: 0151CDAB43460DAE
4 changed files with 79 additions and 60 deletions
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11
meilisearch-core/src/automaton/mod.rs
View File

@ -2,7 +2,7 @@ mod dfa;
mod query_enhancer;
use std::cmp::Reverse;
use std::{cmp, vec};
use std::{cmp, fmt, vec};
use fst::{IntoStreamer, Streamer};
use levenshtein_automata::DFA;
@ -68,7 +68,6 @@ impl AutomatonGroup {
}
}
#[derive(Debug)]
pub struct Automaton {
pub index: usize,
pub ngram: usize,
@ -78,6 +77,14 @@ pub struct Automaton {
pub query: String,
}
impl fmt::Debug for Automaton {
fn fmt(&self, f: &mut fmt::Formatter<'_>) -> fmt::Result {
f.debug_struct("Automaton")
.field("query", &self.query)
.finish()
}
}
impl Automaton {
pub fn dfa(&self) -> DFA {
if self.is_prefix {

21
meilisearch-core/src/criterion/exact.rs
View File

@ -1,18 +1,17 @@
use std::cmp::Ordering;
use meilisearch_schema::SchemaAttr;
use sdset::Set;
use slice_group_by::GroupBy;
use crate::criterion::Criterion;
use crate::RawDocument;
use crate::{AttrCount, RawDocument};
#[inline]
fn number_exact_matches(
query_index: &[u32],
attribute: &[u16],
is_exact: &[bool],
fields_counts: &Set<(SchemaAttr, u16)>,
fields_counts: &Set<AttrCount>,
) -> usize {
let mut count = 0;
let mut index = 0;
@ -25,8 +24,8 @@ fn number_exact_matches(
if *is_exact {
found_exact = true;
let attr = &attribute[index + pos];
if let Ok(pos) = fields_counts.binary_search_by_key(attr, |(a, _)| a.0) {
let (_, count) = fields_counts[pos];
if let Ok(pos) = fields_counts.binary_search_by_key(attr, |ac| ac.attr) {
let AttrCount { count, .. } = fields_counts[pos];
if count == 1 {
return usize::max_value();
}
@ -50,7 +49,7 @@ impl Criterion for Exact {
let query_index = lhs.query_index();
let is_exact = lhs.is_exact();
let attribute = lhs.attribute();
let fields_counts = &lhs.fields_counts;
let fields_counts = lhs.fields_counts.as_ref().unwrap();
number_exact_matches(query_index, attribute, is_exact, fields_counts)
};
@ -59,7 +58,7 @@ impl Criterion for Exact {
let query_index = rhs.query_index();
let is_exact = rhs.is_exact();
let attribute = rhs.attribute();
let fields_counts = &rhs.fields_counts;
let fields_counts = rhs.fields_counts.as_ref().unwrap();
number_exact_matches(query_index, attribute, is_exact, fields_counts)
};
@ -86,7 +85,7 @@ mod tests {
let query_index = &[0];
let attribute = &[0];
let is_exact = &[true];
let fields_counts = Set::new(&[(SchemaAttr(0), 2)]).unwrap();
let fields_counts = Set::new(&[AttrCount { attr: 0, count: 2 }]).unwrap();
number_exact_matches(query_index, attribute, is_exact, fields_counts)
};
@ -95,7 +94,7 @@ mod tests {
let query_index = &[0];
let attribute = &[0];
let is_exact = &[false];
let fields_counts = Set::new(&[(SchemaAttr(0), 2)]).unwrap();
let fields_counts = Set::new(&[AttrCount { attr: 0, count: 2 }]).unwrap();
number_exact_matches(query_index, attribute, is_exact, fields_counts)
};
@ -113,7 +112,7 @@ mod tests {
let query_index = &[0];
let attribute = &[0];
let is_exact = &[true];
let fields_counts = Set::new(&[(SchemaAttr(0), 1)]).unwrap();
let fields_counts = Set::new(&[AttrCount { attr: 0, count: 1 }]).unwrap();
number_exact_matches(query_index, attribute, is_exact, fields_counts)
};
@ -122,7 +121,7 @@ mod tests {
let query_index = &[0];
let attribute = &[0];
let is_exact = &[true];
let fields_counts = Set::new(&[(SchemaAttr(0), 4)]).unwrap();
let fields_counts = Set::new(&[AttrCount { attr: 0, count: 4 }]).unwrap();
number_exact_matches(query_index, attribute, is_exact, fields_counts)
};

64
meilisearch-core/src/query_builder.rs
View File

@ -6,6 +6,7 @@ use std::time::{Duration, Instant};
use std::{cmp, mem};
use fst::{IntoStreamer, Streamer};
use log::debug;
use sdset::SetBuf;
use slice_group_by::{GroupBy, GroupByMut};
@ -14,7 +15,7 @@ use crate::automaton::{Automaton, AutomatonGroup, AutomatonProducer, QueryEnhanc
use crate::distinct_map::{BufferedDistinctMap, DistinctMap};
use crate::levenshtein::prefix_damerau_levenshtein;
use crate::raw_document::{raw_documents_from, RawDocument};
use crate::{criterion::Criteria, Document, DocumentId, Highlight, TmpMatch};
use crate::{criterion::Criteria, Document, DocumentId, Highlight, TmpMatch, AttrCount};
use crate::{reordered_attrs::ReorderedAttrs, store, MResult};
pub struct QueryBuilder<'c, 'f, 'd> {
@ -146,27 +147,18 @@ fn fetch_raw_documents(
searchables: Option<&ReorderedAttrs>,
main_store: store::Main,
postings_lists_store: store::PostingsLists,
documents_fields_counts_store: store::DocumentsFieldsCounts,
) -> MResult<Vec<RawDocument>> {
let mut matches = Vec::new();
let mut highlights = Vec::new();
let before_automatons_groups_loop = Instant::now();
for group in automatons_groups {
let AutomatonGroup {
is_phrase_query,
automatons,
} = group;
let AutomatonGroup { is_phrase_query, automatons } = group;
let phrase_query_len = automatons.len();
let mut tmp_matches = Vec::new();
for (id, automaton) in automatons.into_iter().enumerate() {
let Automaton {
index,
is_exact,
query_len,
query,
..
} = automaton;
let Automaton { index, is_exact, query_len, query, .. } = automaton;
let dfa = automaton.dfa();
let words = match main_store.words_fst(reader)? {
@ -250,26 +242,26 @@ fn fetch_raw_documents(
}
}
}
debug!("automatons_groups_loop took {:.02?}", before_automatons_groups_loop.elapsed());
let before_multiword_rewrite_matches = Instant::now();
let matches = multiword_rewrite_matches(matches, &query_enhancer);
debug!("multiword_rewrite_matches took {:.02?}", before_multiword_rewrite_matches.elapsed());
let before_highlight_sorting = Instant::now();
let highlights = {
highlights.sort_unstable_by_key(|(id, _)| *id);
SetBuf::new_unchecked(highlights)
};
debug!("highlight_sorting {:.02?}", before_highlight_sorting.elapsed());
let fields_counts = {
let mut fields_counts = Vec::new();
for group in matches.linear_group_by_key(|(id, ..)| *id) {
let id = group[0].0;
for result in documents_fields_counts_store.document_fields_counts(reader, id)? {
let (attr, count) = result?;
fields_counts.push((id, attr, count));
}
}
SetBuf::new(fields_counts).unwrap()
};
Ok(raw_documents_from(matches, highlights, fields_counts))
let before_raw_documents = Instant::now();
let raw_documents = raw_documents_from(matches, highlights);
debug!("raw_documents took {:.02?}", before_raw_documents.elapsed());
debug!("documents to worry about: {}", raw_documents.len());
Ok(raw_documents)
}
impl<'c, 'f, 'd> QueryBuilder<'c, 'f, 'd> {
@ -434,6 +426,11 @@ where
for auts in automaton_producer {
automatons.push(auts);
for (i, group) in automatons.iter().enumerate() {
debug!("group {} automatons {:?}", i, group.automatons);
}
let before_fetch_raw_documents = Instant::now();
// we must retrieve the documents associated
// with the current automatons
let mut raw_documents = fetch_raw_documents(
@ -443,8 +440,8 @@ where
searchable_attrs.as_ref(),
main_store,
postings_lists_store,
documents_fields_counts_store,
)?;
debug!("fetch_raw_documents took {:.02?}", before_fetch_raw_documents.elapsed());
// stop processing when time is running out
if let Some(timeout) = timeout {
@ -468,6 +465,20 @@ where
continue;
}
// we must pull the fields counts of these documents
// TODO it would be great to had a "dependency" thing for each criterion
// and make it so that we can be lazy on pulling/computing some data.
if criterion.name() == "Exact" {
for document in group.iter_mut() {
let mut fields_counts = Vec::new();
for result in documents_fields_counts_store.document_fields_counts(reader, document.id)? {
let (attr, count) = result?;
fields_counts.push(AttrCount { attr: attr.0, count });
}
document.fields_counts = Some(SetBuf::new(fields_counts).unwrap());
}
}
group.sort_unstable_by(|a, b| criterion.evaluate(a, b));
for group in group.binary_group_by_mut(|a, b| criterion.eq(a, b)) {
@ -561,7 +572,6 @@ where
searchable_attrs.as_ref(),
main_store,
postings_lists_store,
documents_fields_counts_store,
)?;
// stop processing when time is running out

43
meilisearch-core/src/raw_document.rs
View File

@ -1,18 +1,18 @@
use std::fmt;
use std::sync::Arc;
use meilisearch_schema::SchemaAttr;
use sdset::SetBuf;
use slice_group_by::GroupBy;
use log::debug;
use crate::{DocumentId, Highlight, TmpMatch};
use crate::{DocumentId, Highlight, TmpMatch, AttrCount};
#[derive(Clone)]
pub struct RawDocument {
pub id: DocumentId,
pub matches: SharedMatches,
pub highlights: Vec<Highlight>,
pub fields_counts: SetBuf<(SchemaAttr, u16)>,
pub fields_counts: Option<SetBuf<AttrCount>>,
}
impl RawDocument {
@ -100,44 +100,47 @@ impl fmt::Debug for RawDocument {
pub fn raw_documents_from(
matches: SetBuf<(DocumentId, TmpMatch)>,
highlights: SetBuf<(DocumentId, Highlight)>,
fields_counts: SetBuf<(DocumentId, SchemaAttr, u16)>,
highlights: SetBuf<(DocumentId, Highlight)>
) -> Vec<RawDocument> {
let mut docs_ranges: Vec<(_, Range, _, _)> = Vec::new();
let mut matches2 = Matches::with_capacity(matches.len());
let matches = matches.linear_group_by_key(|(id, _)| *id);
let highlights = highlights.linear_group_by_key(|(id, _)| *id);
let fields_counts = fields_counts.linear_group_by_key(|(id, _, _)| *id);
for ((mgroup, hgroup), fgroup) in matches.zip(highlights).zip(fields_counts) {
debug_assert_eq!(mgroup[0].0, hgroup[0].0);
debug_assert_eq!(mgroup[0].0, fgroup[0].0);
let mut loops_count = 0;
for (mgroup, hgroup) in matches.zip(highlights) {
loops_count += 1;
assert_eq!(mgroup[0].0, hgroup[0].0);
let document_id = mgroup[0].0;
let start = docs_ranges.last().map(|(_, r, _, _)| r.end).unwrap_or(0);
let end = start + mgroup.len();
let highlights = hgroup.iter().map(|(_, h)| *h).collect();
let fields_counts = SetBuf::new(fgroup.iter().map(|(_, a, c)| (*a, *c)).collect()).unwrap();
let fields_counts = None;
docs_ranges.push((document_id, Range { start, end }, highlights, fields_counts));
// TODO we could try to keep both data
// - the data oriented one and the raw one,
// - the one that comes from the arguments of this function
// This way we would be able to only produce data oriented lazily.
//
// For example the default first criterion is `SumOfTypos`
// and just needs the `query_index` and the `distance` fields.
// It would probably be good to avoid wasting time sorting other fields of documents
// that will never ever reach the second criterion.
matches2.extend_from_slice(mgroup);
}
debug!("loops_counts number is {}", loops_count);
let matches = Arc::new(matches2);
docs_ranges
.into_iter()
.map(|(id, range, highlights, fields_counts)| {
let matches = SharedMatches {
range,
matches: matches.clone(),
};
RawDocument {
id,
matches,
highlights,
fields_counts,
}
let matches = SharedMatches { range, matches: matches.clone() };
RawDocument { id, matches, highlights, fields_counts }
})
.collect()
}