MeiliSearch/milli/src/search/criteria/asc_desc.rs

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use std::collections::HashMap;
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use std::mem::take;
use anyhow::{bail, Context as _};
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use itertools::Itertools;
use log::debug;
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use ordered_float::OrderedFloat;
use roaring::RoaringBitmap;
use crate::facet::FacetType;
use crate::heed_codec::facet::FieldDocIdFacetF64Codec;
use crate::search::criteria::{resolve_query_tree, CriteriaBuilder};
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use crate::search::facet::FacetIter;
use crate::search::query_tree::Operation;
use crate::{FieldsIdsMap, FieldId, Index};
use super::{Criterion, CriterionParameters, CriterionResult};
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/// Threshold on the number of candidates that will make
/// the system to choose between one algorithm or another.
const CANDIDATES_THRESHOLD: u64 = 1000;
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pub struct AscDesc<'t> {
index: &'t Index,
rtxn: &'t heed::RoTxn<'t>,
field_name: String,
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field_id: FieldId,
facet_type: FacetType,
ascending: bool,
query_tree: Option<Operation>,
candidates: Box<dyn Iterator<Item = heed::Result<RoaringBitmap>> + 't>,
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bucket_candidates: RoaringBitmap,
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faceted_candidates: RoaringBitmap,
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parent: Box<dyn Criterion + 't>,
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}
impl<'t> AscDesc<'t> {
pub fn asc(
index: &'t Index,
rtxn: &'t heed::RoTxn,
parent: Box<dyn Criterion + 't>,
field_name: String,
) -> anyhow::Result<Self>
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{
Self::new(index, rtxn, parent, field_name, true)
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}
pub fn desc(
index: &'t Index,
rtxn: &'t heed::RoTxn,
parent: Box<dyn Criterion + 't>,
field_name: String,
) -> anyhow::Result<Self>
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{
Self::new(index, rtxn, parent, field_name, false)
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}
fn new(
index: &'t Index,
rtxn: &'t heed::RoTxn,
parent: Box<dyn Criterion + 't>,
field_name: String,
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ascending: bool,
) -> anyhow::Result<Self>
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{
let fields_ids_map = index.fields_ids_map(rtxn)?;
let faceted_fields = index.faceted_fields(rtxn)?;
let (field_id, facet_type) = field_id_facet_type(&fields_ids_map, &faceted_fields, &field_name)?;
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Ok(AscDesc {
index,
rtxn,
field_name,
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field_id,
facet_type,
ascending,
query_tree: None,
candidates: Box::new(std::iter::empty()),
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faceted_candidates: index.faceted_documents_ids(rtxn, field_id)?,
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bucket_candidates: RoaringBitmap::new(),
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parent,
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})
}
}
impl<'t> Criterion for AscDesc<'t> {
#[logging_timer::time("AscDesc::{}")]
fn next(&mut self, params: &mut CriterionParameters) -> anyhow::Result<Option<CriterionResult>> {
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loop {
debug!("Facet {}({}) iteration",
if self.ascending { "Asc" } else { "Desc" }, self.field_name
);
match self.candidates.next().transpose()? {
None => {
match self.parent.next(params)? {
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Some(CriterionResult { query_tree, candidates, bucket_candidates }) => {
let candidates_is_some = candidates.is_some();
self.query_tree = query_tree;
let candidates = match (&self.query_tree, candidates) {
(_, Some(mut candidates)) => {
candidates.intersect_with(&self.faceted_candidates);
candidates
},
(Some(qt), None) => {
let context = CriteriaBuilder::new(&self.rtxn, &self.index)?;
let mut candidates = resolve_query_tree(&context, qt, &mut HashMap::new(), params.wdcache)?;
candidates -= params.excluded_candidates;
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candidates.intersect_with(&self.faceted_candidates);
candidates
},
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(None, None) => take(&mut self.faceted_candidates),
};
// If our parent returns candidates it means that the bucket
// candidates were already computed before and we can use them.
//
// If not, we must use the just computed candidates as our bucket
// candidates.
if candidates_is_some {
self.bucket_candidates.union_with(&bucket_candidates);
} else {
self.bucket_candidates.union_with(&candidates);
}
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if candidates.is_empty() {
continue;
}
self.candidates = facet_ordered(
self.index,
self.rtxn,
self.field_id,
self.facet_type,
self.ascending,
candidates,
)?;
},
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None => return Ok(None),
}
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},
Some(mut candidates) => {
candidates -= params.excluded_candidates;
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return Ok(Some(CriterionResult {
query_tree: self.query_tree.clone(),
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candidates: Some(candidates),
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bucket_candidates: take(&mut self.bucket_candidates),
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}));
},
}
}
}
}
fn field_id_facet_type(
fields_ids_map: &FieldsIdsMap,
faceted_fields: &HashMap<String, FacetType>,
field: &str,
) -> anyhow::Result<(FieldId, FacetType)>
{
let id = fields_ids_map.id(field).with_context(|| {
format!("field {:?} isn't registered", field)
})?;
let facet_type = faceted_fields.get(field).with_context(|| {
format!("field {:?} isn't faceted", field)
})?;
Ok((id, *facet_type))
}
/// Returns an iterator over groups of the given candidates in ascending or descending order.
///
/// It will either use an iterative or a recursive method on the whole facet database depending
/// on the number of candidates to rank.
fn facet_ordered<'t>(
index: &'t Index,
rtxn: &'t heed::RoTxn,
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field_id: FieldId,
facet_type: FacetType,
ascending: bool,
candidates: RoaringBitmap,
) -> anyhow::Result<Box<dyn Iterator<Item = heed::Result<RoaringBitmap>> + 't>>
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{
match facet_type {
FacetType::Number => {
if candidates.len() <= CANDIDATES_THRESHOLD {
let iter = iterative_facet_ordered_iter(
index, rtxn, field_id, ascending, candidates,
)?;
Ok(Box::new(iter.map(Ok)) as Box<dyn Iterator<Item = _>>)
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} else {
let facet_fn = if ascending {
FacetIter::new_reducing
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} else {
FacetIter::new_reverse_reducing
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};
let iter = facet_fn(rtxn, index, field_id, candidates)?;
Ok(Box::new(iter.map(|res| res.map(|(_, docids)| docids))))
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}
},
FacetType::String => bail!("criteria facet type must be a number"),
}
}
/// Fetch the whole list of candidates facet values one by one and order them by it.
///
/// This function is fast when the amount of candidates to rank is small.
fn iterative_facet_ordered_iter<'t>(
index: &'t Index,
rtxn: &'t heed::RoTxn,
field_id: FieldId,
ascending: bool,
candidates: RoaringBitmap,
) -> anyhow::Result<impl Iterator<Item = RoaringBitmap> + 't>
{
let db = index.field_id_docid_facet_values.remap_key_type::<FieldDocIdFacetF64Codec>();
let mut docids_values = Vec::with_capacity(candidates.len() as usize);
for docid in candidates.iter() {
let left = (field_id, docid, f64::MIN);
let right = (field_id, docid, f64::MAX);
let mut iter = db.range(rtxn, &(left..=right))?;
let entry = if ascending { iter.next() } else { iter.last() };
if let Some(((_, _, value), ())) = entry.transpose()? {
docids_values.push((docid, OrderedFloat(value)));
}
}
docids_values.sort_unstable_by_key(|(_, v)| v.clone());
let iter = docids_values.into_iter();
let iter = if ascending {
Box::new(iter) as Box<dyn Iterator<Item = _>>
} else {
Box::new(iter.rev())
};
// The itertools GroupBy iterator doesn't provide an owned version, we are therefore
// required to collect the result into an owned collection (a Vec).
// https://github.com/rust-itertools/itertools/issues/499
let vec: Vec<_> = iter.group_by(|(_, v)| v.clone())
.into_iter()
.map(|(_, ids)| ids.map(|(id, _)| id).collect())
.collect();
Ok(vec.into_iter())
}