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https://github.com/meilisearch/meilisearch.git
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Index the geo points
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parent
8d9c2c4425
commit
44d6b6ae9e
@ -298,7 +298,7 @@ impl Index {
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/* geo rtree */
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pub(crate) fn put_geo_rtree<A: AsRef<[u8]>>(
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pub(crate) fn put_geo_rtree(
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&self,
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wtxn: &mut RwTxn,
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rtree: &RTree<GeoPoint>,
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@ -0,0 +1,46 @@
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use std::fs::File;
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use std::io;
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use concat_arrays::concat_arrays;
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use log::warn;
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use serde_json::Value;
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use super::helpers::{create_writer, writer_into_reader, GrenadParameters};
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use crate::{FieldId, InternalError, Result};
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/// Extracts the geographical coordinates contained in each document under the `_geo` field.
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///
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/// Returns the generated grenad reader containing the docid as key associated to the (latitude, longitude)
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pub fn extract_geo_points<R: io::Read>(
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mut obkv_documents: grenad::Reader<R>,
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indexer: GrenadParameters,
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geo_field_id: Option<FieldId>, // faire un grenad vide
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) -> Result<grenad::Reader<File>> {
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let mut writer = tempfile::tempfile().and_then(|file| {
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create_writer(indexer.chunk_compression_type, indexer.chunk_compression_level, file)
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})?;
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// we never encountered any documents with a `_geo` field. We can skip entirely this step
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if geo_field_id.is_none() {
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return Ok(writer_into_reader(writer)?);
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}
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let geo_field_id = geo_field_id.unwrap();
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while let Some((docid_bytes, value)) = obkv_documents.next()? {
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let obkv = obkv::KvReader::new(value);
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let point = obkv.get(geo_field_id).unwrap(); // TODO: TAMO where should we handle this error?
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let point: Value = serde_json::from_slice(point).map_err(InternalError::SerdeJson)?;
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if let Some((lat, long)) = point["lat"].as_f64().zip(point["long"].as_f64()) {
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// this will create an array of 16 bytes (two 8 bytes floats)
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let bytes: [u8; 16] = concat_arrays![lat.to_le_bytes(), long.to_le_bytes()];
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writer.insert(docid_bytes, bytes)?;
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} else {
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// TAMO: improve the warn
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warn!("Malformed `_geo` field");
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continue;
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}
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}
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Ok(writer_into_reader(writer)?)
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}
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@ -3,6 +3,7 @@ mod extract_facet_number_docids;
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mod extract_facet_string_docids;
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mod extract_fid_docid_facet_values;
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mod extract_fid_word_count_docids;
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mod extract_geo_points;
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mod extract_word_docids;
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mod extract_word_level_position_docids;
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mod extract_word_pair_proximity_docids;
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@ -19,6 +20,7 @@ use self::extract_facet_number_docids::extract_facet_number_docids;
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use self::extract_facet_string_docids::extract_facet_string_docids;
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use self::extract_fid_docid_facet_values::extract_fid_docid_facet_values;
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use self::extract_fid_word_count_docids::extract_fid_word_count_docids;
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use self::extract_geo_points::extract_geo_points;
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use self::extract_word_docids::extract_word_docids;
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use self::extract_word_level_position_docids::extract_word_level_position_docids;
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use self::extract_word_pair_proximity_docids::extract_word_pair_proximity_docids;
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@ -37,6 +39,7 @@ pub(crate) fn data_from_obkv_documents(
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lmdb_writer_sx: Sender<Result<TypedChunk>>,
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searchable_fields: Option<HashSet<FieldId>>,
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faceted_fields: HashSet<FieldId>,
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geo_field_id: Option<FieldId>,
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stop_words: Option<fst::Set<&[u8]>>,
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) -> Result<()> {
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let result: Result<(Vec<_>, (Vec<_>, Vec<_>))> = obkv_chunks
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@ -54,7 +57,7 @@ pub(crate) fn data_from_obkv_documents(
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.collect();
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let (
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docid_word_positions_chunks,
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(docid_word_positions_chunks),
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(docid_fid_facet_numbers_chunks, docid_fid_facet_strings_chunks),
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) = result?;
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@ -118,6 +121,16 @@ pub(crate) fn data_from_obkv_documents(
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"field-id-facet-number-docids",
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);
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spawn_extraction_task(
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documents_chunk,
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indexer.clone(),
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lmdb_writer_sx.clone(),
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move |documents, indexer| extract_geo_points(documents, indexer, geo_field_id),
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merge_cbo_roaring_bitmaps,
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TypedChunk::GeoPoints,
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"geo-points",
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);
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Ok(())
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}
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@ -233,6 +233,8 @@ impl<'t, 'u, 'i, 'a> IndexDocuments<'t, 'u, 'i, 'a> {
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self.index.searchable_fields_ids(self.wtxn)?.map(HashSet::from_iter);
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// get filterable fields for facet databases
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let faceted_fields = self.index.faceted_fields_ids(self.wtxn)?;
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// get the fid of the `_geo` field.
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let geo_field_id = self.index.fields_ids_map(self.wtxn)?.id("_geo");
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let stop_words = self.index.stop_words(self.wtxn)?;
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// let stop_words = stop_words.as_ref();
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@ -261,6 +263,7 @@ impl<'t, 'u, 'i, 'a> IndexDocuments<'t, 'u, 'i, 'a> {
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lmdb_writer_sx.clone(),
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searchable_fields,
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faceted_fields,
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geo_field_id,
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stop_words,
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)
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});
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@ -6,11 +6,12 @@ use heed::{BytesDecode, RwTxn};
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use roaring::RoaringBitmap;
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use super::helpers::{
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roaring_bitmap_from_u32s_array, serialize_roaring_bitmap, valid_lmdb_key, CursorClonableMmap,
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self, roaring_bitmap_from_u32s_array, serialize_roaring_bitmap, valid_lmdb_key,
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CursorClonableMmap,
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};
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use crate::heed_codec::facet::{decode_prefix_string, encode_prefix_string};
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use crate::update::index_documents::helpers::into_clonable_grenad;
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use crate::{BoRoaringBitmapCodec, CboRoaringBitmapCodec, Index, Result};
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use crate::{BoRoaringBitmapCodec, CboRoaringBitmapCodec, GeoPoint, Index, Result};
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pub(crate) enum TypedChunk {
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DocidWordPositions(grenad::Reader<CursorClonableMmap>),
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@ -24,6 +25,7 @@ pub(crate) enum TypedChunk {
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WordPairProximityDocids(grenad::Reader<File>),
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FieldIdFacetStringDocids(grenad::Reader<File>),
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FieldIdFacetNumberDocids(grenad::Reader<File>),
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GeoPoints(grenad::Reader<File>),
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}
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/// Write typed chunk in the corresponding LMDB database of the provided index.
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@ -177,6 +179,22 @@ pub(crate) fn write_typed_chunk_into_index(
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)?;
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is_merged_database = true;
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}
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TypedChunk::GeoPoints(mut geo_points) => {
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// TODO: TAMO: we should create the rtree with the `RTree::bulk_load` function
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let mut rtree = index.geo_rtree(&index.read_txn()?)?.unwrap_or_default();
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while let Some((key, value)) = geo_points.next()? {
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// convert the key back to a u32 (4 bytes)
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let (key, _) = helpers::try_split_array_at::<u8, 4>(key).unwrap();
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let key = u32::from_le_bytes(key);
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// convert the latitude and longitude back to a f64 (8 bytes)
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let (lat, tail) = helpers::try_split_array_at::<u8, 8>(value).unwrap();
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let (long, _) = helpers::try_split_array_at::<u8, 8>(tail).unwrap();
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let point = [f64::from_le_bytes(lat), f64::from_le_bytes(long)];
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rtree.insert(GeoPoint::new(point, key));
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}
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index.put_geo_rtree(wtxn, &rtree)?;
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}
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}
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Ok((RoaringBitmap::new(), is_merged_database))
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