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deserialize the rtree only when its needed, and keep it in memory once it has been deserialized

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Tamo 2023-05-02 11:39:35 +02:00 committed by Louis Dureuil
parent c470b67fa2
commit 8875d24a48
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1 changed files with 9 additions and 29 deletions
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38
milli/src/search/new/geo_sort.rs
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@ -111,12 +111,13 @@ impl<Q: RankingRuleQueryTrait> GeoSort<Q> {
// if we had an rtree and the strategy doesn't require one anymore we can drop it
let use_rtree = self.strategy.use_rtree(self.geo_candidates.len() as usize);
if !use_rtree && self.rtree.is_some() {
self.rtree = None;
if use_rtree && self.rtree.is_none() {
self.rtree = Some(ctx.index.geo_rtree(ctx.txn)?.expect("geo candidates but no rtree"));
}
let cache_size = self.strategy.cache_size();
if let Some(ref mut rtree) = self.rtree {
if use_rtree {
let rtree = self.rtree.as_ref().unwrap();
let point = lat_lng_to_xyz(&self.point);
if self.ascending {
@ -169,18 +170,12 @@ impl<Q: RankingRuleQueryTrait> GeoSort<Q> {
))
})
.collect::<Result<Vec<(u32, [f64; 2])>>>()?;
// REVIEW COMMENT: the haversine distance function can be quite expensive, I think, so it's probably faster
// to use `sort_by_cached_key` instead of `sort_by_key`.
// computing the distance between two points is expensive thus we cache the result
documents
.sort_by_cached_key(|(_, p)| distance_between_two_points(&self.point, p) as usize);
self.cached_sorted_docids.extend(documents.into_iter().map(|(doc_id, _)| doc_id));
};
if self.cached_sorted_docids.is_empty() && matches!(self.strategy, Strategy::AlwaysRtree(_))
{
// this shouldn't be possible
self.rtree = None;
}
Ok(())
}
}
@ -210,15 +205,6 @@ impl<'ctx, Q: RankingRuleQueryTrait> RankingRule<'ctx, Q> for GeoSort<Q> {
let lat = fid_map.id("_geo.lat").expect("geo candidates but no fid for lat");
let lng = fid_map.id("_geo.lng").expect("geo candidates but no fid for lng");
self.field_ids = Some([lat, lng]);
if self.strategy.use_rtree(self.geo_candidates.len() as usize) {
// REVIEW COMMENT: I would prefer to always keep the rtree in memory so that we don't have to deserialize it
// every time the geosort ranking rule starts iterating.
// So we'd initialize it in `::new` and never drop it.
//
self.rtree = Some(ctx.index.geo_rtree(ctx.txn)?.expect("geo candidates but no rtree"));
}
self.fill_buffer(ctx)?;
Ok(())
}
@ -256,20 +242,14 @@ impl<'ctx, Q: RankingRuleQueryTrait> RankingRule<'ctx, Q> for GeoSort<Q> {
}
// if we got out of this loop it means we've exhausted our cache.
if self.rtree.is_none() {
// with no rtree it means all geo candidates have been returned. We can return all the non geo-faceted documents
Ok(Some(RankingRuleOutput { query, candidates: universe.clone() }))
} else {
// else, we need to refill our bucket and run the function again
self.fill_buffer(ctx)?;
self.next_bucket(ctx, logger, universe)
}
// we need to refill it and run the function again.
self.fill_buffer(ctx)?;
self.next_bucket(ctx, logger, universe)
}
fn end_iteration(&mut self, _ctx: &mut SearchContext<'ctx>, _logger: &mut dyn SearchLogger<Q>) {
// we do not reset the rtree here, it could be used in a next iteration
self.query = None;
self.rtree = None;
self.cached_sorted_docids.clear();
}
}