mirror of
https://github.com/meilisearch/MeiliSearch
synced 2024-11-24 05:44:25 +01:00
124 lines
3.8 KiB
Rust
124 lines
3.8 KiB
Rust
use heed::types::{ByteSlice, Str, Unit};
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use heed::{Database, RoPrefix, RoTxn};
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use roaring::RoaringBitmap;
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const FID_SIZE: usize = 2;
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const DOCID_SIZE: usize = 4;
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use crate::heed_codec::facet::{
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FacetGroupKey, FacetGroupKeyCodec, FacetGroupValueCodec, FieldDocIdFacetCodec,
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};
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use crate::heed_codec::ByteSliceRefCodec;
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use crate::{Index, Result, SearchContext};
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pub struct DistinctOutput {
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pub remaining: RoaringBitmap,
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pub excluded: RoaringBitmap,
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}
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/// Return a [`DistinctOutput`] containing:
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/// - `remaining`: a set of docids built such that exactly one element from `candidates`
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/// is kept for each distinct value inside the given field. If the field does not exist, it
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/// is considered unique.
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/// - `excluded`: the set of document ids that contain a value for the given field that occurs
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/// in the given candidates.
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pub fn apply_distinct_rule(
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ctx: &mut SearchContext,
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field_id: u16,
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candidates: &RoaringBitmap,
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) -> Result<DistinctOutput> {
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let mut excluded = RoaringBitmap::new();
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let mut remaining = RoaringBitmap::new();
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for docid in candidates {
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if excluded.contains(docid) {
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continue;
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}
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distinct_single_docid(ctx.index, ctx.txn, field_id, docid, &mut excluded)?;
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remaining.push(docid);
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}
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Ok(DistinctOutput { remaining, excluded })
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}
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/// Apply the distinct rule defined by [`apply_distinct_rule`] for a single document id.
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pub fn distinct_single_docid(
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index: &Index,
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txn: &RoTxn,
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field_id: u16,
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docid: u32,
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excluded: &mut RoaringBitmap,
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) -> Result<()> {
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for item in facet_string_values(docid, field_id, index, txn)? {
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let ((_, _, facet_value), _) = item?;
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if let Some(facet_docids) = facet_value_docids(
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index.facet_id_string_docids.remap_types(),
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txn,
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field_id,
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facet_value,
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)? {
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*excluded |= facet_docids;
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}
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}
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for item in facet_number_values(docid, field_id, index, txn)? {
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let ((_, _, facet_value), _) = item?;
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if let Some(facet_docids) =
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facet_value_docids(index.facet_id_f64_docids.remap_types(), txn, field_id, facet_value)?
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{
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*excluded |= facet_docids;
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}
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}
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Ok(())
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}
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/// Return all the docids containing the given value in the given field
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fn facet_value_docids(
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database: Database<FacetGroupKeyCodec<ByteSliceRefCodec>, FacetGroupValueCodec>,
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txn: &RoTxn,
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field_id: u16,
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facet_value: &[u8],
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) -> heed::Result<Option<RoaringBitmap>> {
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database
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.get(txn, &FacetGroupKey { field_id, level: 0, left_bound: facet_value })
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.map(|opt| opt.map(|v| v.bitmap))
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}
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/// Return an iterator over each number value in the given field of the given document.
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fn facet_number_values<'a>(
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docid: u32,
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field_id: u16,
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index: &Index,
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txn: &'a RoTxn,
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) -> Result<RoPrefix<'a, FieldDocIdFacetCodec<ByteSliceRefCodec>, Unit>> {
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let key = facet_values_prefix_key(field_id, docid);
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let iter = index
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.field_id_docid_facet_f64s
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.remap_key_type::<ByteSlice>()
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.prefix_iter(txn, &key)?
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.remap_key_type();
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Ok(iter)
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}
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/// Return an iterator over each string value in the given field of the given document.
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fn facet_string_values<'a>(
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docid: u32,
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field_id: u16,
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index: &Index,
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txn: &'a RoTxn,
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) -> Result<RoPrefix<'a, FieldDocIdFacetCodec<ByteSliceRefCodec>, Str>> {
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let key = facet_values_prefix_key(field_id, docid);
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let iter = index
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.field_id_docid_facet_strings
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.remap_key_type::<ByteSlice>()
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.prefix_iter(txn, &key)?
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.remap_types();
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Ok(iter)
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}
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#[allow(clippy::drop_non_drop)]
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fn facet_values_prefix_key(distinct: u16, id: u32) -> [u8; FID_SIZE + DOCID_SIZE] {
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concat_arrays::concat_arrays!(distinct.to_be_bytes(), id.to_be_bytes())
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}
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