mirror of
https://github.com/meilisearch/MeiliSearch
synced 2024-11-23 05:14:27 +01:00
Merge pull request #125 from meilisearch/distinct
Implement distinct attribute
This commit is contained in:
commit
19b6620a92
@ -19,6 +19,7 @@ use crate::{
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pub const CRITERIA_KEY: &str = "criteria";
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pub const DISPLAYED_FIELDS_KEY: &str = "displayed-fields";
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pub const DISTINCT_ATTRIBUTE_KEY: &str = "distinct-attribute-key";
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pub const DOCUMENTS_IDS_KEY: &str = "documents-ids";
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pub const FACETED_DOCUMENTS_IDS_PREFIX: &str = "faceted-documents-ids";
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pub const FACETED_FIELDS_KEY: &str = "faceted-fields";
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@ -342,6 +343,20 @@ impl Index {
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}
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}
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/* Distinct attribute */
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pub(crate) fn put_distinct_attribute(&self, wtxn: &mut RwTxn, distinct_attribute: &str) -> heed::Result<()> {
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self.main.put::<_, Str, Str>(wtxn, DISTINCT_ATTRIBUTE_KEY, distinct_attribute)
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}
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pub fn distinct_attribute<'a>(&self, rtxn: &'a RoTxn) -> heed::Result<Option<&'a str>> {
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self.main.get::<_, Str, Str>(rtxn, DISTINCT_ATTRIBUTE_KEY)
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}
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pub(crate) fn delete_distinct_attribute(&self, wtxn: &mut RwTxn) -> heed::Result<bool> {
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self.main.delete::<_, Str>(wtxn, DISTINCT_ATTRIBUTE_KEY)
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}
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/* criteria */
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pub fn put_criteria(&self, wtxn: &mut RwTxn, criteria: &[Criterion]) -> heed::Result<()> {
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@ -463,13 +478,44 @@ impl Index {
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}
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#[cfg(test)]
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mod tests {
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pub(crate) mod tests {
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use std::ops::Deref;
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use heed::EnvOpenOptions;
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use maplit::hashmap;
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use tempfile::TempDir;
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use crate::Index;
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use crate::update::{IndexDocuments, UpdateFormat};
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pub(crate) struct TempIndex {
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inner: Index,
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_tempdir: TempDir,
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}
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impl Deref for TempIndex {
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type Target = Index;
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fn deref(&self) -> &Self::Target {
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&self.inner
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}
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}
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impl TempIndex {
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/// Creates a temporary index, with a default `4096 * 100` size. This should be enough for
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/// most tests.
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pub fn new() -> Self {
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let mut options = EnvOpenOptions::new();
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options.map_size(100 * 4096);
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let _tempdir = TempDir::new_in(".").unwrap();
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let inner = Index::new(options, _tempdir.path()).unwrap();
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Self {
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inner,
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_tempdir
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}
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}
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}
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#[test]
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fn initial_fields_distribution() {
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let path = tempfile::tempdir().unwrap();
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@ -483,5 +483,4 @@ mod test {
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assert_eq!(criteria.next(&mut wdcache).unwrap(), Some(expected_2));
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}
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}
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@ -5,8 +5,7 @@ use log::debug;
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use roaring::RoaringBitmap;
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use crate::search::query_tree::Operation;
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use crate::search::WordDerivationsCache;
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use super::{resolve_query_tree, Criterion, CriterionResult, Context};
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use super::{resolve_query_tree, Criterion, CriterionResult, Context, WordDerivationsCache};
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pub struct Words<'t> {
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ctx: &'t dyn Context,
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238
milli/src/search/distinct/facet_distinct.rs
Normal file
238
milli/src/search/distinct/facet_distinct.rs
Normal file
@ -0,0 +1,238 @@
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use std::mem::size_of;
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use roaring::RoaringBitmap;
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use crate::heed_codec::facet::*;
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use crate::{facet::FacetType, DocumentId, FieldId, Index};
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use super::{Distinct, DocIter};
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/// A distinct implementer that is backed by facets.
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///
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/// On each iteration, the facet values for the
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/// distinct attribute of the first document are retrieved. The document ids for these facet values
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/// are then retrieved and taken out of the the candidate and added to the excluded set. We take
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/// care to keep the document we are currently on, and remove it from the excluded list. The next
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/// iterations will never contain any occurence of a document with the same distinct value as a
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/// document from previous iterations.
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pub struct FacetDistinct<'a> {
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distinct: FieldId,
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index: &'a Index,
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txn: &'a heed::RoTxn<'a>,
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facet_type: FacetType,
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}
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impl<'a> FacetDistinct<'a> {
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pub fn new(
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distinct: FieldId,
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index: &'a Index,
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txn: &'a heed::RoTxn<'a>,
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facet_type: FacetType,
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) -> Self {
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Self {
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distinct,
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index,
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txn,
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facet_type,
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}
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}
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}
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pub struct FacetDistinctIter<'a> {
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candidates: RoaringBitmap,
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distinct: FieldId,
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excluded: RoaringBitmap,
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facet_type: FacetType,
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index: &'a Index,
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iter_offset: usize,
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txn: &'a heed::RoTxn<'a>,
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}
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impl<'a> FacetDistinctIter<'a> {
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fn get_facet_docids<'c, KC>(&self, key: &'c KC::EItem) -> anyhow::Result<RoaringBitmap>
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where
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KC: heed::BytesEncode<'c>,
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{
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let facet_docids = self
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.index
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.facet_field_id_value_docids
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.remap_key_type::<KC>()
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.get(self.txn, key)?
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.expect("Corrupted data: Facet values must exist");
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Ok(facet_docids)
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}
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fn distinct_string(&mut self, id: DocumentId) -> anyhow::Result<()> {
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let iter = get_facet_values::<FieldDocIdFacetStringCodec>(
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id,
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self.distinct,
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self.index,
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self.txn,
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)?;
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for item in iter {
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let ((_, _, value), _) = item?;
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let key = (self.distinct, value);
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let facet_docids = self.get_facet_docids::<FacetValueStringCodec>(&key)?;
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self.excluded.union_with(&facet_docids);
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}
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self.excluded.remove(id);
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Ok(())
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}
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fn distinct_integer(&mut self, id: DocumentId) -> anyhow::Result<()> {
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let iter = get_facet_values::<FieldDocIdFacetI64Codec>(
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id,
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self.distinct,
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self.index,
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self.txn,
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)?;
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for item in iter {
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let ((_, _, value), _) = item?;
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// get facet docids on level 0
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let key = (self.distinct, 0, value, value);
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let facet_docids = self.get_facet_docids::<FacetLevelValueI64Codec>(&key)?;
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self.excluded.union_with(&facet_docids);
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}
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self.excluded.remove(id);
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Ok(())
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}
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fn distinct_float(&mut self, id: DocumentId) -> anyhow::Result<()> {
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let iter = get_facet_values::<FieldDocIdFacetF64Codec>(id,
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self.distinct,
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self.index,
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self.txn,
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)?;
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for item in iter {
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let ((_, _, value), _) = item?;
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// get facet docids on level 0
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let key = (self.distinct, 0, value, value);
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let facet_docids = self.get_facet_docids::<FacetLevelValueF64Codec>(&key)?;
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self.excluded.union_with(&facet_docids);
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}
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self.excluded.remove(id);
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Ok(())
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}
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/// Performs the next iteration of the facet distinct. This is a convenience method that is
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/// called by the Iterator::next implementation that transposes the result. It makes error
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/// handling easier.
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fn next_inner(&mut self) -> anyhow::Result<Option<DocumentId>> {
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// The first step is to remove all the excluded documents from our candidates
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self.candidates.difference_with(&self.excluded);
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let mut candidates_iter = self.candidates.iter().skip(self.iter_offset);
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match candidates_iter.next() {
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Some(id) => {
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match self.facet_type {
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FacetType::String => self.distinct_string(id)?,
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FacetType::Integer => self.distinct_integer(id)?,
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FacetType::Float => self.distinct_float(id)?,
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};
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// The first document of each iteration is kept, since the next call to
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// `difference_with` will filter out all the documents for that facet value. By
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// increasing the offset we make sure to get the first valid value for the next
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// distinct document to keep.
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self.iter_offset += 1;
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Ok(Some(id))
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}
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// no more candidate at this offset, return.
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None => Ok(None),
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}
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}
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}
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fn get_facet_values<'a, KC>(
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id: DocumentId,
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distinct: FieldId,
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index: &Index,
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txn: &'a heed::RoTxn,
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) -> anyhow::Result<heed::RoPrefix<'a, KC, heed::types::Unit>>
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where
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KC: heed::BytesDecode<'a>,
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{
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const FID_SIZE: usize = size_of::<FieldId>();
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const DOCID_SIZE: usize = size_of::<DocumentId>();
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let mut key = [0; FID_SIZE + DOCID_SIZE];
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key[0..FID_SIZE].copy_from_slice(&distinct.to_be_bytes());
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key[FID_SIZE..].copy_from_slice(&id.to_be_bytes());
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let iter = index
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.field_id_docid_facet_values
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.prefix_iter(txn, &key)?
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.remap_key_type::<KC>();
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Ok(iter)
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}
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impl Iterator for FacetDistinctIter<'_> {
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type Item = anyhow::Result<DocumentId>;
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fn next(&mut self) -> Option<Self::Item> {
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self.next_inner().transpose()
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}
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}
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impl DocIter for FacetDistinctIter<'_> {
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fn into_excluded(self) -> RoaringBitmap {
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self.excluded
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}
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}
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impl<'a> Distinct<'_> for FacetDistinct<'a> {
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type Iter = FacetDistinctIter<'a>;
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fn distinct(&mut self, candidates: RoaringBitmap, excluded: RoaringBitmap) -> Self::Iter {
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FacetDistinctIter {
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candidates,
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distinct: self.distinct,
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excluded,
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facet_type: self.facet_type,
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index: self.index,
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iter_offset: 0,
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txn: self.txn,
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}
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}
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}
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#[cfg(test)]
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mod test {
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use std::collections::HashMap;
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use super::*;
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use super::super::test::{generate_index, validate_distinct_candidates};
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use crate::facet::FacetType;
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macro_rules! test_facet_distinct {
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($name:ident, $distinct:literal, $facet_type:expr) => {
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#[test]
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fn $name() {
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use std::iter::FromIterator;
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let facets = HashMap::from_iter(Some(($distinct.to_string(), $facet_type.to_string())));
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let (index, fid, candidates) = generate_index($distinct, facets);
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let txn = index.read_txn().unwrap();
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let mut map_distinct = FacetDistinct::new(fid, &index, &txn, $facet_type);
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let excluded = RoaringBitmap::new();
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let mut iter = map_distinct.distinct(candidates.clone(), excluded);
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let count = validate_distinct_candidates(iter.by_ref(), fid, &index);
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let excluded = iter.into_excluded();
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assert_eq!(count as u64 + excluded.len(), candidates.len());
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}
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};
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}
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test_facet_distinct!(test_string, "txt", FacetType::String);
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test_facet_distinct!(test_strings, "txts", FacetType::String);
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test_facet_distinct!(test_int, "cat-int", FacetType::Integer);
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test_facet_distinct!(test_ints, "cat-ints", FacetType::Integer);
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}
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138
milli/src/search/distinct/map_distinct.rs
Normal file
138
milli/src/search/distinct/map_distinct.rs
Normal file
@ -0,0 +1,138 @@
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use std::collections::HashMap;
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use roaring::RoaringBitmap;
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use serde_json::Value;
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use super::{Distinct, DocIter};
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use crate::{DocumentId, FieldId, Index};
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/// A distinct implementer that is backed by an `HashMap`.
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///
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/// Each time a document is seen, the value
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/// for its distinct field is added to the map. If the map already contains an entry for this
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/// value, then the document is filtered out, and is added to the excluded set.
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pub struct MapDistinct<'a> {
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distinct: FieldId,
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map: HashMap<String, usize>,
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index: &'a Index,
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txn: &'a heed::RoTxn<'a>,
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}
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impl<'a> MapDistinct<'a> {
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pub fn new(distinct: FieldId, index: &'a Index, txn: &'a heed::RoTxn<'a>) -> Self {
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Self {
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distinct,
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map: HashMap::new(),
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index,
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txn,
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}
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}
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}
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pub struct MapDistinctIter<'a, 'b> {
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distinct: FieldId,
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map: &'b mut HashMap<String, usize>,
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index: &'a Index,
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txn: &'a heed::RoTxn<'a>,
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candidates: roaring::bitmap::IntoIter,
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excluded: RoaringBitmap,
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}
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impl<'a, 'b> MapDistinctIter<'a, 'b> {
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/// Performs the next iteration of the mafacetp distinct. This is a convenience method that is
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/// called by the Iterator::next implementation that transposes the result. It makes error
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/// handling easier.
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fn next_inner(&mut self) -> anyhow::Result<Option<DocumentId>> {
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let map = &mut self.map;
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let mut filter = |value: Value| {
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let entry = map.entry(value.to_string()).or_insert(0);
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*entry += 1;
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*entry <= 1
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};
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while let Some(id) = self.candidates.next() {
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let document = self.index.documents(&self.txn, Some(id))?[0].1;
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let value = document
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.get(self.distinct)
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.map(serde_json::from_slice::<Value>)
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.transpose()?;
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let accept = match value {
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Some(Value::Array(values)) => {
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let mut accept = true;
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for value in values {
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accept &= filter(value);
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}
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accept
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}
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Some(Value::Null) | Some(Value::Object(_)) | None => true,
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Some(value) => filter(value),
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};
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if accept {
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return Ok(Some(id));
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} else {
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self.excluded.insert(id);
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}
|
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}
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Ok(None)
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}
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}
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impl Iterator for MapDistinctIter<'_, '_> {
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type Item = anyhow::Result<DocumentId>;
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fn next(&mut self) -> Option<Self::Item> {
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self.next_inner().transpose()
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}
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}
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impl DocIter for MapDistinctIter<'_, '_> {
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fn into_excluded(self) -> RoaringBitmap {
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self.excluded
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}
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}
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impl<'a, 'b> Distinct<'b> for MapDistinct<'a> {
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type Iter = MapDistinctIter<'a, 'b>;
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fn distinct(&'b mut self, candidates: RoaringBitmap, excluded: RoaringBitmap) -> Self::Iter {
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MapDistinctIter {
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distinct: self.distinct,
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map: &mut self.map,
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index: &self.index,
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txn: &self.txn,
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candidates: candidates.into_iter(),
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excluded,
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}
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}
|
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}
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|
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#[cfg(test)]
|
||||
mod test {
|
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use std::collections::HashMap;
|
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|
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use super::*;
|
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use super::super::test::{generate_index, validate_distinct_candidates};
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|
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macro_rules! test_map_distinct {
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($name:ident, $distinct:literal) => {
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#[test]
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fn $name() {
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let (index, fid, candidates) = generate_index($distinct, HashMap::new());
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let txn = index.read_txn().unwrap();
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let mut map_distinct = MapDistinct::new(fid, &index, &txn);
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let excluded = RoaringBitmap::new();
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let mut iter = map_distinct.distinct(candidates.clone(), excluded);
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let count = validate_distinct_candidates(iter.by_ref(), fid, &index);
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let excluded = iter.into_excluded();
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assert_eq!(count as u64 + excluded.len(), candidates.len());
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}
|
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};
|
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}
|
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|
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test_map_distinct!(test_string, "txt");
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test_map_distinct!(test_strings, "txts");
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test_map_distinct!(test_int, "cat-int");
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test_map_distinct!(test_ints, "cat-ints");
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}
|
144
milli/src/search/distinct/mod.rs
Normal file
144
milli/src/search/distinct/mod.rs
Normal file
@ -0,0 +1,144 @@
|
||||
mod facet_distinct;
|
||||
mod map_distinct;
|
||||
mod noop_distinct;
|
||||
|
||||
use roaring::RoaringBitmap;
|
||||
|
||||
use crate::DocumentId;
|
||||
pub use facet_distinct::FacetDistinct;
|
||||
pub use map_distinct::MapDistinct;
|
||||
pub use noop_distinct::NoopDistinct;
|
||||
|
||||
/// A trait implemented by document interators that are returned by calls to `Distinct::distinct`.
|
||||
/// It provides a way to get back the ownership to the excluded set.
|
||||
pub trait DocIter: Iterator<Item = anyhow::Result<DocumentId>> {
|
||||
/// Returns ownership on the internal exluded set.
|
||||
fn into_excluded(self) -> RoaringBitmap;
|
||||
}
|
||||
|
||||
/// A trait that is implemented by structs that perform a distinct on `candidates`. Calling distinct
|
||||
/// must return an iterator containing only distinct documents, and add the discarded documents to
|
||||
/// the excluded set. The excluded set can later be retrieved by calling `DocIter::excluded` on the
|
||||
/// returned iterator.
|
||||
pub trait Distinct<'a> {
|
||||
type Iter: DocIter;
|
||||
|
||||
fn distinct(&'a mut self, candidates: RoaringBitmap, excluded: RoaringBitmap) -> Self::Iter;
|
||||
}
|
||||
|
||||
#[cfg(test)]
|
||||
mod test {
|
||||
use std::collections::{HashMap, HashSet};
|
||||
|
||||
use once_cell::sync::Lazy;
|
||||
use rand::{seq::SliceRandom, Rng};
|
||||
use roaring::RoaringBitmap;
|
||||
use serde_json::{json, Value};
|
||||
|
||||
use crate::index::{Index, tests::TempIndex};
|
||||
use crate::update::{IndexDocumentsMethod, UpdateBuilder, UpdateFormat};
|
||||
use crate::{BEU32, FieldId, DocumentId};
|
||||
|
||||
static JSON: Lazy<Value> = Lazy::new(generate_json);
|
||||
|
||||
fn generate_json() -> Value {
|
||||
let mut rng = rand::thread_rng();
|
||||
let num_docs = rng.gen_range(10..30);
|
||||
|
||||
let mut documents = Vec::new();
|
||||
|
||||
let txts = ["toto", "titi", "tata"];
|
||||
let cats = (1..10).map(|i| i.to_string()).collect::<Vec<_>>();
|
||||
let cat_ints = (1..10).collect::<Vec<_>>();
|
||||
|
||||
for i in 0..num_docs {
|
||||
let txt = txts.choose(&mut rng).unwrap();
|
||||
let mut sample_txts = cats.clone();
|
||||
sample_txts.shuffle(&mut rng);
|
||||
|
||||
let mut sample_ints = cat_ints.clone();
|
||||
sample_ints.shuffle(&mut rng);
|
||||
|
||||
let doc = json!({
|
||||
"id": i,
|
||||
"txt": txt,
|
||||
"cat-int": rng.gen_range(0..3),
|
||||
"txts": sample_txts[..(rng.gen_range(0..3))],
|
||||
"cat-ints": sample_ints[..(rng.gen_range(0..3))],
|
||||
});
|
||||
documents.push(doc);
|
||||
}
|
||||
|
||||
Value::Array(documents)
|
||||
}
|
||||
|
||||
/// Returns a temporary index populated with random test documents, the FieldId for the
|
||||
/// distinct attribute, and the RoaringBitmap with the document ids.
|
||||
pub(crate) fn generate_index(distinct: &str, facets: HashMap<String, String>) -> (TempIndex, FieldId, RoaringBitmap) {
|
||||
let index = TempIndex::new();
|
||||
let mut txn = index.write_txn().unwrap();
|
||||
|
||||
// set distinct and faceted attributes for the index.
|
||||
let builder = UpdateBuilder::new(0);
|
||||
let mut update = builder.settings(&mut txn, &index);
|
||||
update.set_distinct_attribute(distinct.to_string());
|
||||
if !facets.is_empty() {
|
||||
update.set_faceted_fields(facets)
|
||||
}
|
||||
update.execute(|_, _| ()).unwrap();
|
||||
|
||||
// add documents to the index
|
||||
let builder = UpdateBuilder::new(1);
|
||||
let mut addition = builder.index_documents(&mut txn, &index);
|
||||
|
||||
addition.index_documents_method(IndexDocumentsMethod::ReplaceDocuments);
|
||||
addition.update_format(UpdateFormat::Json);
|
||||
|
||||
addition
|
||||
.execute(JSON.to_string().as_bytes(), |_, _| ())
|
||||
.unwrap();
|
||||
|
||||
let fields_map = index.fields_ids_map(&txn).unwrap();
|
||||
let fid = fields_map.id(&distinct).unwrap();
|
||||
|
||||
let map = (0..JSON.as_array().unwrap().len() as u32).collect();
|
||||
|
||||
txn.commit().unwrap();
|
||||
|
||||
(index, fid, map)
|
||||
}
|
||||
|
||||
|
||||
/// Checks that all the candidates are distinct, and returns the candidates number.
|
||||
pub(crate) fn validate_distinct_candidates(
|
||||
candidates: impl Iterator<Item=anyhow::Result<DocumentId>>,
|
||||
distinct: FieldId,
|
||||
index: &Index,
|
||||
) -> usize {
|
||||
fn test(seen: &mut HashSet<String>, value: &Value) {
|
||||
match value {
|
||||
Value::Null | Value::Object(_) | Value::Bool(_) => (),
|
||||
Value::Number(_) | Value::String(_) => {
|
||||
let s = value.to_string();
|
||||
assert!(seen.insert(s));
|
||||
}
|
||||
Value::Array(values) => {values.into_iter().for_each(|value| test(seen, value))}
|
||||
}
|
||||
}
|
||||
|
||||
let mut seen = HashSet::<String>::new();
|
||||
|
||||
let txn = index.read_txn().unwrap();
|
||||
let mut count = 0;
|
||||
for candidate in candidates {
|
||||
count += 1;
|
||||
let candidate = candidate.unwrap();
|
||||
let id = BEU32::new(candidate);
|
||||
let document = index.documents.get(&txn, &id).unwrap().unwrap();
|
||||
let value = document.get(distinct).unwrap();
|
||||
let value = serde_json::from_slice(value).unwrap();
|
||||
test(&mut seen, &value);
|
||||
}
|
||||
count
|
||||
}
|
||||
}
|
57
milli/src/search/distinct/noop_distinct.rs
Normal file
57
milli/src/search/distinct/noop_distinct.rs
Normal file
@ -0,0 +1,57 @@
|
||||
use roaring::{RoaringBitmap, bitmap::IntoIter};
|
||||
|
||||
use crate::DocumentId;
|
||||
use super::{DocIter, Distinct};
|
||||
|
||||
/// A distinct implementer that does not perform any distinct,
|
||||
/// and simply returns an iterator to the candidates.
|
||||
pub struct NoopDistinct;
|
||||
|
||||
pub struct NoopDistinctIter {
|
||||
candidates: IntoIter,
|
||||
excluded: RoaringBitmap,
|
||||
}
|
||||
|
||||
impl Iterator for NoopDistinctIter {
|
||||
type Item = anyhow::Result<DocumentId>;
|
||||
|
||||
fn next(&mut self) -> Option<Self::Item> {
|
||||
self.candidates.next().map(Ok)
|
||||
}
|
||||
}
|
||||
|
||||
impl DocIter for NoopDistinctIter {
|
||||
fn into_excluded(self) -> RoaringBitmap {
|
||||
self.excluded
|
||||
}
|
||||
}
|
||||
|
||||
impl Distinct<'_> for NoopDistinct {
|
||||
type Iter = NoopDistinctIter;
|
||||
|
||||
fn distinct(&mut self, candidates: RoaringBitmap, excluded: RoaringBitmap) -> Self::Iter {
|
||||
NoopDistinctIter {
|
||||
candidates: candidates.into_iter(),
|
||||
excluded,
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
#[cfg(test)]
|
||||
mod test {
|
||||
use super::*;
|
||||
|
||||
#[test]
|
||||
fn test_noop() {
|
||||
let candidates = (1..10).collect();
|
||||
let excluded = RoaringBitmap::new();
|
||||
let mut iter = NoopDistinct.distinct(candidates, excluded);
|
||||
assert_eq!(
|
||||
iter.by_ref().map(Result::unwrap).collect::<Vec<_>>(),
|
||||
(1..10).collect::<Vec<_>>()
|
||||
);
|
||||
|
||||
let excluded = iter.into_excluded();
|
||||
assert!(excluded.is_empty());
|
||||
}
|
||||
}
|
@ -1,6 +1,7 @@
|
||||
use std::borrow::Cow;
|
||||
use std::collections::hash_map::{HashMap, Entry};
|
||||
use std::fmt;
|
||||
use std::mem::take;
|
||||
use std::str::Utf8Error;
|
||||
use std::time::Instant;
|
||||
|
||||
@ -11,22 +12,24 @@ use meilisearch_tokenizer::{AnalyzerConfig, Analyzer};
|
||||
use once_cell::sync::Lazy;
|
||||
use roaring::bitmap::RoaringBitmap;
|
||||
|
||||
use crate::search::criteria::fetcher::FetcherResult;
|
||||
use crate::search::criteria::fetcher::{FetcherResult, Fetcher};
|
||||
use crate::{Index, DocumentId};
|
||||
use distinct::{MapDistinct, FacetDistinct, Distinct, DocIter, NoopDistinct};
|
||||
use self::query_tree::QueryTreeBuilder;
|
||||
|
||||
pub use self::facet::FacetIter;
|
||||
pub use self::facet::{FacetCondition, FacetDistribution, FacetNumberOperator, FacetStringOperator};
|
||||
pub use self::query_tree::MatchingWords;
|
||||
use self::query_tree::QueryTreeBuilder;
|
||||
|
||||
// Building these factories is not free.
|
||||
static LEVDIST0: Lazy<LevBuilder> = Lazy::new(|| LevBuilder::new(0, true));
|
||||
static LEVDIST1: Lazy<LevBuilder> = Lazy::new(|| LevBuilder::new(1, true));
|
||||
static LEVDIST2: Lazy<LevBuilder> = Lazy::new(|| LevBuilder::new(2, true));
|
||||
|
||||
mod criteria;
|
||||
mod distinct;
|
||||
mod facet;
|
||||
mod query_tree;
|
||||
mod criteria;
|
||||
|
||||
pub struct Search<'a> {
|
||||
query: Option<String>,
|
||||
@ -123,33 +126,60 @@ impl<'a> Search<'a> {
|
||||
};
|
||||
|
||||
let criteria_builder = criteria::CriteriaBuilder::new(self.rtxn, self.index)?;
|
||||
let mut criteria = criteria_builder.build(query_tree, facet_candidates)?;
|
||||
let criteria = criteria_builder.build(query_tree, facet_candidates)?;
|
||||
|
||||
match self.index.distinct_attribute(self.rtxn)? {
|
||||
None => self.perform_sort(NoopDistinct, matching_words, criteria),
|
||||
Some(name) => {
|
||||
let field_ids_map = self.index.fields_ids_map(self.rtxn)?;
|
||||
let id = field_ids_map.id(name).expect("distinct not present in field map");
|
||||
let faceted_fields = self.index.faceted_fields(self.rtxn)?;
|
||||
match faceted_fields.get(name) {
|
||||
Some(facet_type) => {
|
||||
let distinct = FacetDistinct::new(id, self.index, self.rtxn, *facet_type);
|
||||
self.perform_sort(distinct, matching_words, criteria)
|
||||
}
|
||||
None => {
|
||||
let distinct = MapDistinct::new(id, self.index, self.rtxn);
|
||||
self.perform_sort(distinct, matching_words, criteria)
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
fn perform_sort(
|
||||
&self,
|
||||
mut distinct: impl for<'c> Distinct<'c>,
|
||||
matching_words: MatchingWords,
|
||||
mut criteria: Fetcher,
|
||||
) -> anyhow::Result<SearchResult> {
|
||||
|
||||
let mut offset = self.offset;
|
||||
let mut limit = self.limit;
|
||||
let mut documents_ids = Vec::new();
|
||||
let mut initial_candidates = RoaringBitmap::new();
|
||||
let mut excluded_documents = RoaringBitmap::new();
|
||||
let mut documents_ids = Vec::with_capacity(self.limit);
|
||||
|
||||
while let Some(FetcherResult { candidates, bucket_candidates, .. }) = criteria.next()? {
|
||||
|
||||
debug!("Number of candidates found {}", candidates.len());
|
||||
|
||||
let mut len = candidates.len() as usize;
|
||||
let mut candidates = candidates.into_iter();
|
||||
let excluded = take(&mut excluded_documents);
|
||||
|
||||
let mut candidates = distinct.distinct(candidates, excluded);
|
||||
|
||||
initial_candidates.union_with(&bucket_candidates);
|
||||
|
||||
if offset != 0 {
|
||||
candidates.by_ref().take(offset).for_each(drop);
|
||||
offset = offset.saturating_sub(len.min(offset));
|
||||
len = len.saturating_sub(len.min(offset));
|
||||
let discarded = candidates.by_ref().take(offset).count();
|
||||
offset = offset.saturating_sub(discarded);
|
||||
}
|
||||
|
||||
if len != 0 {
|
||||
documents_ids.extend(candidates.take(limit));
|
||||
limit = limit.saturating_sub(len.min(limit));
|
||||
for candidate in candidates.by_ref().take(self.limit - documents_ids.len()) {
|
||||
documents_ids.push(candidate?);
|
||||
}
|
||||
|
||||
if limit == 0 { break }
|
||||
if documents_ids.len() == self.limit { break }
|
||||
excluded_documents = candidates.into_excluded();
|
||||
}
|
||||
|
||||
Ok(SearchResult { matching_words, candidates: initial_candidates, documents_ids })
|
||||
|
@ -70,6 +70,7 @@ pub struct Settings<'a, 't, 'u, 'i> {
|
||||
faceted_fields: Setting<HashMap<String, String>>,
|
||||
criteria: Setting<Vec<String>>,
|
||||
stop_words: Setting<BTreeSet<String>>,
|
||||
distinct_attribute: Setting<String>,
|
||||
}
|
||||
|
||||
impl<'a, 't, 'u, 'i> Settings<'a, 't, 'u, 'i> {
|
||||
@ -94,6 +95,7 @@ impl<'a, 't, 'u, 'i> Settings<'a, 't, 'u, 'i> {
|
||||
faceted_fields: Setting::NotSet,
|
||||
criteria: Setting::NotSet,
|
||||
stop_words: Setting::NotSet,
|
||||
distinct_attribute: Setting::NotSet,
|
||||
update_id,
|
||||
}
|
||||
}
|
||||
@ -142,6 +144,14 @@ impl<'a, 't, 'u, 'i> Settings<'a, 't, 'u, 'i> {
|
||||
}
|
||||
}
|
||||
|
||||
pub fn set_distinct_attribute(&mut self, distinct_attribute: String) {
|
||||
self.distinct_attribute = Setting::Set(distinct_attribute);
|
||||
}
|
||||
|
||||
pub fn reset_distinct_attribute(&mut self) {
|
||||
self.distinct_attribute = Setting::Reset;
|
||||
}
|
||||
|
||||
fn reindex<F>(&mut self, cb: &F, old_fields_ids_map: FieldsIdsMap) -> anyhow::Result<()>
|
||||
where
|
||||
F: Fn(UpdateIndexingStep, u64) + Sync
|
||||
@ -220,6 +230,23 @@ impl<'a, 't, 'u, 'i> Settings<'a, 't, 'u, 'i> {
|
||||
Ok(true)
|
||||
}
|
||||
|
||||
fn update_distinct_attribute(&mut self) -> anyhow::Result<bool> {
|
||||
match self.distinct_attribute {
|
||||
Setting::Set(ref attr) => {
|
||||
let mut fields_ids_map = self.index.fields_ids_map(self.wtxn)?;
|
||||
fields_ids_map
|
||||
.insert(attr)
|
||||
.context("field id limit exceeded")?;
|
||||
|
||||
self.index.put_distinct_attribute(self.wtxn, &attr)?;
|
||||
self.index.put_fields_ids_map(self.wtxn, &fields_ids_map)?;
|
||||
}
|
||||
Setting::Reset => { self.index.delete_distinct_attribute(self.wtxn)?; },
|
||||
Setting::NotSet => return Ok(false),
|
||||
}
|
||||
Ok(true)
|
||||
}
|
||||
|
||||
/// Updates the index's searchable attributes. This causes the field map to be recomputed to
|
||||
/// reflect the order of the searchable attributes.
|
||||
fn update_searchable(&mut self) -> anyhow::Result<bool> {
|
||||
@ -328,6 +355,7 @@ impl<'a, 't, 'u, 'i> Settings<'a, 't, 'u, 'i> {
|
||||
self.update_displayed()?;
|
||||
let stop_words_updated = self.update_stop_words()?;
|
||||
let facets_updated = self.update_facets()?;
|
||||
self.update_distinct_attribute()?;
|
||||
// update_criteria MUST be called after update_facets, since criterion fields must be set
|
||||
// as facets.
|
||||
self.update_criteria()?;
|
||||
|
Loading…
Reference in New Issue
Block a user