mirror of
https://github.com/meilisearch/MeiliSearch
synced 2024-06-15 17:19:50 +02:00
137 lines
5.1 KiB
Rust
137 lines
5.1 KiB
Rust
use heed::Result;
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use roaring::RoaringBitmap;
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use super::{get_first_facet_value, get_highest_level};
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use crate::heed_codec::facet::{
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FacetGroupKey, FacetGroupKeyCodec, FacetGroupValue, FacetGroupValueCodec,
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};
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use crate::heed_codec::ByteSliceRefCodec;
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/// Return an iterator which iterates over the given candidate documents in
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/// ascending order of their facet value for the given field id.
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///
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/// The documents returned by the iterator are grouped by the facet values that
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/// determined their rank. For example, given the documents:
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///
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/// ```ignore
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/// 0: { "colour": ["blue", "green"] }
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/// 1: { "colour": ["blue", "red"] }
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/// 2: { "colour": ["orange", "red"] }
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/// 3: { "colour": ["green", "red"] }
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/// 4: { "colour": ["blue", "orange", "red"] }
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/// ```
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/// Then calling the function on the candidates `[0, 2, 3, 4]` will return an iterator
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/// over the following elements:
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/// ```ignore
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/// [0, 4] // corresponds to all the documents within the candidates that have the facet value "blue"
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/// [3] // same for "green"
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/// [2] // same for "orange"
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/// END
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/// ```
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/// Note that once a document id is returned by the iterator, it is never returned again.
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pub fn ascending_facet_sort<'t>(
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rtxn: &'t heed::RoTxn<'t>,
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db: heed::Database<FacetGroupKeyCodec<ByteSliceRefCodec>, FacetGroupValueCodec>,
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field_id: u16,
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candidates: RoaringBitmap,
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) -> Result<Box<dyn Iterator<Item = Result<RoaringBitmap>> + 't>> {
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let highest_level = get_highest_level(rtxn, db, field_id)?;
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if let Some(first_bound) = get_first_facet_value::<ByteSliceRefCodec>(rtxn, db, field_id)? {
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let first_key = FacetGroupKey { field_id, level: highest_level, left_bound: first_bound };
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let iter = db.range(rtxn, &(first_key..)).unwrap().take(usize::MAX);
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Ok(Box::new(AscendingFacetSort { rtxn, db, field_id, stack: vec![(candidates, iter)] }))
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} else {
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Ok(Box::new(std::iter::empty()))
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}
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}
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struct AscendingFacetSort<'t, 'e> {
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rtxn: &'t heed::RoTxn<'e>,
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db: heed::Database<FacetGroupKeyCodec<ByteSliceRefCodec>, FacetGroupValueCodec>,
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field_id: u16,
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stack: Vec<(
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RoaringBitmap,
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std::iter::Take<
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heed::RoRange<'t, FacetGroupKeyCodec<ByteSliceRefCodec>, FacetGroupValueCodec>,
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>,
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)>,
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}
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impl<'t, 'e> Iterator for AscendingFacetSort<'t, 'e> {
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type Item = Result<RoaringBitmap>;
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fn next(&mut self) -> Option<Self::Item> {
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'outer: loop {
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let (documents_ids, deepest_iter) = self.stack.last_mut()?;
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for result in deepest_iter {
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let (
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FacetGroupKey { level, left_bound, field_id },
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FacetGroupValue { size: group_size, mut bitmap },
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) = result.unwrap();
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// The range is unbounded on the right and the group size for the highest level is MAX,
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// so we need to check that we are not iterating over the next field id
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if field_id != self.field_id {
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return None;
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}
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// If the last iterator found an empty set of documents it means
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// that we found all the documents in the sub level iterations already,
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// we can pop this level iterator.
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if documents_ids.is_empty() {
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break;
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}
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bitmap &= &*documents_ids;
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if !bitmap.is_empty() {
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*documents_ids -= &bitmap;
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if level == 0 {
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return Some(Ok(bitmap));
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}
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let starting_key_below =
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FacetGroupKey { field_id: self.field_id, level: level - 1, left_bound };
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let iter = match self.db.range(&self.rtxn, &(starting_key_below..)) {
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Ok(iter) => iter,
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Err(e) => return Some(Err(e.into())),
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}
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.take(group_size as usize);
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self.stack.push((bitmap, iter));
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continue 'outer;
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}
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}
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self.stack.pop();
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}
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}
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}
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#[cfg(test)]
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mod tests {
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use roaring::RoaringBitmap;
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use crate::milli_snap;
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use crate::search::facet::facet_sort_ascending::ascending_facet_sort;
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use crate::search::facet::tests::{get_random_looking_index, get_simple_index};
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use crate::snapshot_tests::display_bitmap;
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#[test]
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fn filter_sort() {
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let indexes = [get_simple_index(), get_random_looking_index()];
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for (i, index) in indexes.iter().enumerate() {
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let txn = index.env.read_txn().unwrap();
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let candidates = (200..=300).into_iter().collect::<RoaringBitmap>();
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let mut results = String::new();
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let iter = ascending_facet_sort(&txn, index.content, 0, candidates).unwrap();
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for el in iter {
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let docids = el.unwrap();
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results.push_str(&display_bitmap(&docids));
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results.push('\n');
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}
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milli_snap!(results, i);
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txn.commit().unwrap();
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}
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}
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}
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