mirror of
https://github.com/meilisearch/meilisearch.git
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653 lines
27 KiB
Rust
653 lines
27 KiB
Rust
//! This module contains helpers iterators for facet strings.
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//!
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//! The purpose is to help iterate over the quite complex system of facets strings. A simple
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//! description of the system would be that every facet string value is stored into an LMDB database
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//! and that every value is associated with the document ids which are associated with this facet
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//! string value.
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//!
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//! In reality it is a little bit more complex as we have to create aggregations of runs of facet
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//! string values, those aggregations helps in choosing the right groups of facets to follow.
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//!
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//! ## A typical algorithm run
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//!
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//! If a group of aggregated facets values contains one of the documents ids, we must continue
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//! iterating over the sub-groups.
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//!
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//! If this group is the lowest level and contain at least one document id we yield the associated
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//! facet documents ids.
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//!
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//! If the group doesn't contain one of our documents ids, we continue to the next group at this
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//! same level.
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//!
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//! ## The complexity comes from the strings
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//!
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//! This algorithm is exactly the one that we use for facet numbers. It is quite easy to create
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//! aggregated facet number, groups of facets are easy to define in the LMDB key, we just put the
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//! two numbers bounds, the left and the right bound of the group, both inclusive.
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//!
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//! It is easy to make sure that the groups are ordered, LMDB sort its keys lexicographically and
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//! puting two numbers big-endian encoded one after the other gives us ordered groups. The values
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//! are simple unions of the documents ids coming from the groups below.
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//!
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//! ### Example of what a facet number LMDB database contain
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//!
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//! | level | left-bound | right-bound | documents ids |
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//! |-------|------------|-------------|------------------|
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//! | 0 | 0 | _skipped_ | 1, 2 |
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//! | 0 | 1 | _skipped_ | 6, 7 |
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//! | 0 | 3 | _skipped_ | 4, 7 |
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//! | 0 | 5 | _skipped_ | 2, 3, 4 |
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//! | 1 | 0 | 1 | 1, 2, 6, 7 |
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//! | 1 | 3 | 5 | 2, 3, 4, 7 |
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//! | 2 | 0 | 5 | 1, 2, 3, 4, 6, 7 |
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//!
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//! As you can see the level 0 have two equal bounds, therefore we skip serializing the second
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//! bound, that's the base level where you can directly fetch the documents ids associated with an
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//! exact number.
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//!
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//! The next levels have two different bounds and the associated documents ids are simply the result
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//! of an union of all the documents ids associated with the aggregated groups above.
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//!
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//! ## The complexity of defining groups for facet strings
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//!
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//! As explained above, defining groups of facet numbers is easy, LMDB stores the keys in
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//! lexicographical order, it means that whatever the key represent the bytes are read in their raw
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//! form and a simple `strcmp` will define the order in which keys will be read from the store.
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//!
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//! That's easy for types with a known size, like floats or integers, they are 64 bytes long and
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//! appending one after the other in big-endian is consistent. LMDB will simply sort the keys by the
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//! first number then by the second if the the first number is equal on two keys.
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//!
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//! For strings it is a lot more complex as those types are unsized, it means that the size of facet
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//! strings is different for each facet value.
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//!
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//! ### Basic approach: padding the keys
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//!
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//! A first approach would be to simply define the maximum size of a facet string and pad the keys
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//! with zeroes. The big problem of this approach is that it:
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//! 1. reduces the maximum size of facet strings by half, as we need to put two keys one after the
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//! other.
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//! 2. makes the keys of facet strings very big (approximately 250 bytes), impacting a lot LMDB
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//! performances.
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//!
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//! ### Better approach: number the facet groups
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//!
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//! A better approach would be to number the groups, this way we don't have the downsides of the
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//! previously described approach but we need to be able to describe the groups by using a number.
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//!
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//! #### Example of facet strings with numbered groups
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//!
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//! | level | left-bound | right-bound | left-string | right-string | documents ids |
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//! |-------|------------|-------------|-------------|--------------|------------------|
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//! | 0 | alpha | _skipped_ | _skipped_ | _skipped_ | 1, 2 |
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//! | 0 | beta | _skipped_ | _skipped_ | _skipped_ | 6, 7 |
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//! | 0 | gamma | _skipped_ | _skipped_ | _skipped_ | 4, 7 |
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//! | 0 | omega | _skipped_ | _skipped_ | _skipped_ | 2, 3, 4 |
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//! | 1 | 0 | 1 | alpha | beta | 1, 2, 6, 7 |
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//! | 1 | 2 | 3 | gamma | omega | 2, 3, 4, 7 |
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//! | 2 | 0 | 3 | _skipped_ | _skipped_ | 1, 2, 3, 4, 6, 7 |
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//!
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//! As you can see the level 0 doesn't actually change much, we skip nearly everything, we do not
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//! need to store the facet string value two times.
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//!
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//! The number in the left-bound and right-bound columns are incremental numbers representing the
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//! level 0 strings, .i.e. alpha is 0, beta is 1. Those numbers are just here to keep the ordering
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//! of the LMDB keys.
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//!
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//! In the value, not in the key, you can see that we added two new values: the left-string and the
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//! right-string, which defines the original facet strings associated with the given group.
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//!
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//! We put those two strings inside of the value, this way we do not limit the maximum size of the
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//! facet string values, and the impact on performances is not important as, IIRC, LMDB put big
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//! values on another page, this helps in iterating over keys fast enough and only fetch the page
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//! with the values when required.
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//!
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//! The other little advantage with this solution is that there is no a big overhead, compared with
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//! the facet number levels, we only duplicate the facet strings once for the level 1.
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//!
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//! #### A typical algorithm run
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//!
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//! Note that the algorithm is always moving from the highest level to the lowest one, one level
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//! by one level, this is why it is ok to only store the facets string on the level 1.
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//!
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//! If a group of aggregated facets values, a group with numbers contains one of the documents ids,
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//! we must continue iterating over the sub-groups. To do so:
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//! - If we are at a level >= 2, we just do the same as with the facet numbers, get both bounds
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//! and iterate over the facet groups defined by these numbers over the current level - 1.
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//! - If we are at level 1, we retrieve both keys, the left-string and right-string, from the
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//! value and just do the same as with the facet numbers but with strings: iterate over the
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//! current level - 1 with both keys.
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//!
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//! If this group is the lowest level (level 0) and contain at least one document id we yield the
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//! associated facet documents ids.
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//!
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//! If the group doesn't contain one of our documents ids, we continue to the next group at this
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//! same level.
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//!
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use std::num::NonZeroU8;
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use std::ops::Bound;
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use std::ops::Bound::{Excluded, Included, Unbounded};
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use either::{Either, Left, Right};
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use heed::types::{ByteSlice, DecodeIgnore};
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use heed::{Database, LazyDecode, RoRange, RoRevRange};
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use roaring::RoaringBitmap;
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use crate::heed_codec::facet::{
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FacetLevelValueU32Codec, FacetStringLevelZeroCodec, FacetStringLevelZeroValueCodec,
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FacetStringZeroBoundsValueCodec,
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};
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use crate::heed_codec::CboRoaringBitmapCodec;
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use crate::{FieldId, Index};
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/// An iterator that is used to explore the facets level strings
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/// from the level 1 to infinity.
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///
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/// It yields the level, group id that an entry covers, the optional group strings
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/// that it covers of the level 0 only if it is an entry from the level 1 and
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/// the roaring bitmap associated.
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pub struct FacetStringGroupRange<'t> {
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iter: RoRange<
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't,
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FacetLevelValueU32Codec,
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LazyDecode<FacetStringZeroBoundsValueCodec<CboRoaringBitmapCodec>>,
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>,
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end: Bound<u32>,
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}
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impl<'t> FacetStringGroupRange<'t> {
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pub fn new<X, Y>(
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rtxn: &'t heed::RoTxn,
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db: Database<X, Y>,
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field_id: FieldId,
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level: NonZeroU8,
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left: Bound<u32>,
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right: Bound<u32>,
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) -> heed::Result<FacetStringGroupRange<'t>> {
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let db = db.remap_types::<
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FacetLevelValueU32Codec,
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FacetStringZeroBoundsValueCodec<CboRoaringBitmapCodec>,
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>();
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let left_bound = match left {
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Included(left) => Included((field_id, level, left, u32::MIN)),
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Excluded(left) => Excluded((field_id, level, left, u32::MIN)),
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Unbounded => Included((field_id, level, u32::MIN, u32::MIN)),
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};
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let right_bound = Included((field_id, level, u32::MAX, u32::MAX));
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let iter = db.lazily_decode_data().range(rtxn, &(left_bound, right_bound))?;
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Ok(FacetStringGroupRange { iter, end: right })
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}
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}
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impl<'t> Iterator for FacetStringGroupRange<'t> {
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type Item = heed::Result<((NonZeroU8, u32, u32), (Option<(&'t str, &'t str)>, RoaringBitmap))>;
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fn next(&mut self) -> Option<Self::Item> {
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match self.iter.next() {
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Some(Ok(((_fid, level, left, right), docids))) => {
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let must_be_returned = match self.end {
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Included(end) => right <= end,
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Excluded(end) => right < end,
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Unbounded => true,
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};
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if must_be_returned {
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match docids.decode() {
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Ok((bounds, docids)) => Some(Ok(((level, left, right), (bounds, docids)))),
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Err(e) => Some(Err(e)),
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}
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} else {
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None
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}
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}
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Some(Err(e)) => Some(Err(e)),
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None => None,
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}
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}
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}
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pub struct FacetStringGroupRevRange<'t> {
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iter: RoRevRange<
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't,
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FacetLevelValueU32Codec,
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LazyDecode<FacetStringZeroBoundsValueCodec<CboRoaringBitmapCodec>>,
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>,
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end: Bound<u32>,
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}
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impl<'t> FacetStringGroupRevRange<'t> {
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pub fn new<X, Y>(
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rtxn: &'t heed::RoTxn,
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db: Database<X, Y>,
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field_id: FieldId,
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level: NonZeroU8,
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left: Bound<u32>,
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right: Bound<u32>,
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) -> heed::Result<FacetStringGroupRevRange<'t>> {
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let db = db.remap_types::<
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FacetLevelValueU32Codec,
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FacetStringZeroBoundsValueCodec<CboRoaringBitmapCodec>,
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>();
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let left_bound = match left {
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Included(left) => Included((field_id, level, left, u32::MIN)),
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Excluded(left) => Excluded((field_id, level, left, u32::MIN)),
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Unbounded => Included((field_id, level, u32::MIN, u32::MIN)),
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};
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let right_bound = Included((field_id, level, u32::MAX, u32::MAX));
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let iter = db.lazily_decode_data().rev_range(rtxn, &(left_bound, right_bound))?;
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Ok(FacetStringGroupRevRange { iter, end: right })
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}
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}
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impl<'t> Iterator for FacetStringGroupRevRange<'t> {
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type Item = heed::Result<((NonZeroU8, u32, u32), (Option<(&'t str, &'t str)>, RoaringBitmap))>;
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fn next(&mut self) -> Option<Self::Item> {
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loop {
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match self.iter.next() {
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Some(Ok(((_fid, level, left, right), docids))) => {
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let must_be_returned = match self.end {
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Included(end) => right <= end,
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Excluded(end) => right < end,
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Unbounded => true,
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};
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if must_be_returned {
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match docids.decode() {
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Ok((bounds, docids)) => {
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return Some(Ok(((level, left, right), (bounds, docids))))
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}
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Err(e) => return Some(Err(e)),
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}
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}
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continue;
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}
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Some(Err(e)) => return Some(Err(e)),
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None => return None,
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}
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}
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}
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}
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/// An iterator that is used to explore the level 0 of the facets string database.
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///
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/// It yields the facet string and the roaring bitmap associated with it.
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pub struct FacetStringLevelZeroRange<'t> {
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iter: RoRange<'t, FacetStringLevelZeroCodec, FacetStringLevelZeroValueCodec>,
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}
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impl<'t> FacetStringLevelZeroRange<'t> {
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pub fn new<X, Y>(
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rtxn: &'t heed::RoTxn,
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db: Database<X, Y>,
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field_id: FieldId,
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left: Bound<&str>,
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right: Bound<&str>,
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) -> heed::Result<FacetStringLevelZeroRange<'t>> {
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fn encode_value<'a>(buffer: &'a mut Vec<u8>, field_id: FieldId, value: &str) -> &'a [u8] {
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buffer.extend_from_slice(&field_id.to_be_bytes());
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buffer.push(0);
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buffer.extend_from_slice(value.as_bytes());
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&buffer[..]
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}
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let mut left_buffer = Vec::new();
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let left_bound = match left {
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Included(value) => Included(encode_value(&mut left_buffer, field_id, value)),
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Excluded(value) => Excluded(encode_value(&mut left_buffer, field_id, value)),
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Unbounded => {
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left_buffer.extend_from_slice(&field_id.to_be_bytes());
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left_buffer.push(0);
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Included(&left_buffer[..])
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}
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};
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let mut right_buffer = Vec::new();
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let right_bound = match right {
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Included(value) => Included(encode_value(&mut right_buffer, field_id, value)),
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Excluded(value) => Excluded(encode_value(&mut right_buffer, field_id, value)),
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Unbounded => {
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right_buffer.extend_from_slice(&field_id.to_be_bytes());
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right_buffer.push(1); // we must only get the level 0
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Excluded(&right_buffer[..])
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}
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};
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let iter = db
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.remap_key_type::<ByteSlice>()
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.range(rtxn, &(left_bound, right_bound))?
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.remap_types::<FacetStringLevelZeroCodec, FacetStringLevelZeroValueCodec>();
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Ok(FacetStringLevelZeroRange { iter })
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}
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}
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impl<'t> Iterator for FacetStringLevelZeroRange<'t> {
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type Item = heed::Result<(&'t str, &'t str, RoaringBitmap)>;
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fn next(&mut self) -> Option<Self::Item> {
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match self.iter.next() {
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Some(Ok(((_fid, normalized), (original, docids)))) => {
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Some(Ok((normalized, original, docids)))
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}
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Some(Err(e)) => Some(Err(e)),
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None => None,
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}
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}
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}
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pub struct FacetStringLevelZeroRevRange<'t> {
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iter: RoRevRange<'t, FacetStringLevelZeroCodec, FacetStringLevelZeroValueCodec>,
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}
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impl<'t> FacetStringLevelZeroRevRange<'t> {
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pub fn new<X, Y>(
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rtxn: &'t heed::RoTxn,
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db: Database<X, Y>,
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field_id: FieldId,
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left: Bound<&str>,
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right: Bound<&str>,
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) -> heed::Result<FacetStringLevelZeroRevRange<'t>> {
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fn encode_value<'a>(buffer: &'a mut Vec<u8>, field_id: FieldId, value: &str) -> &'a [u8] {
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buffer.extend_from_slice(&field_id.to_be_bytes());
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buffer.push(0);
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buffer.extend_from_slice(value.as_bytes());
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&buffer[..]
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}
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let mut left_buffer = Vec::new();
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let left_bound = match left {
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Included(value) => Included(encode_value(&mut left_buffer, field_id, value)),
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Excluded(value) => Excluded(encode_value(&mut left_buffer, field_id, value)),
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Unbounded => {
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left_buffer.extend_from_slice(&field_id.to_be_bytes());
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left_buffer.push(0);
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Included(&left_buffer[..])
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}
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};
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let mut right_buffer = Vec::new();
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let right_bound = match right {
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Included(value) => Included(encode_value(&mut right_buffer, field_id, value)),
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Excluded(value) => Excluded(encode_value(&mut right_buffer, field_id, value)),
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Unbounded => {
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right_buffer.extend_from_slice(&field_id.to_be_bytes());
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right_buffer.push(1); // we must only get the level 0
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Excluded(&right_buffer[..])
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}
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};
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let iter = db
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.remap_key_type::<ByteSlice>()
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.rev_range(rtxn, &(left_bound, right_bound))?
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.remap_types::<FacetStringLevelZeroCodec, FacetStringLevelZeroValueCodec>();
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Ok(FacetStringLevelZeroRevRange { iter })
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}
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}
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impl<'t> Iterator for FacetStringLevelZeroRevRange<'t> {
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type Item = heed::Result<(&'t str, &'t str, RoaringBitmap)>;
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fn next(&mut self) -> Option<Self::Item> {
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match self.iter.next() {
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Some(Ok(((_fid, normalized), (original, docids)))) => {
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Some(Ok((normalized, original, docids)))
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}
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Some(Err(e)) => Some(Err(e)),
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None => None,
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}
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}
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}
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type EitherStringRange<'t> = Either<FacetStringGroupRange<'t>, FacetStringLevelZeroRange<'t>>;
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type EitherStringRevRange<'t> =
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Either<FacetStringGroupRevRange<'t>, FacetStringLevelZeroRevRange<'t>>;
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/// An iterator that is used to explore the facet strings level by level,
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/// it will only return facets strings that are associated with the
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/// candidates documents ids given.
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pub struct FacetStringIter<'t> {
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rtxn: &'t heed::RoTxn<'t>,
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db: Database<ByteSlice, ByteSlice>,
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field_id: FieldId,
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level_iters: Vec<(RoaringBitmap, Either<EitherStringRange<'t>, EitherStringRevRange<'t>>)>,
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must_reduce: bool,
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}
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impl<'t> FacetStringIter<'t> {
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pub fn new_reducing(
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rtxn: &'t heed::RoTxn,
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index: &'t Index,
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field_id: FieldId,
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documents_ids: RoaringBitmap,
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) -> heed::Result<FacetStringIter<'t>> {
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let db = index.facet_id_string_docids.remap_types::<ByteSlice, ByteSlice>();
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let highest_iter = Self::highest_iter(rtxn, index, db, field_id)?;
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Ok(FacetStringIter {
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rtxn,
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db,
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field_id,
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level_iters: vec![(documents_ids, Left(highest_iter))],
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must_reduce: true,
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})
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}
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pub fn new_reverse_reducing(
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rtxn: &'t heed::RoTxn,
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index: &'t Index,
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field_id: FieldId,
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documents_ids: RoaringBitmap,
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) -> heed::Result<FacetStringIter<'t>> {
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let db = index.facet_id_string_docids.remap_types::<ByteSlice, ByteSlice>();
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let highest_reverse_iter = Self::highest_reverse_iter(rtxn, index, db, field_id)?;
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Ok(FacetStringIter {
|
|
rtxn,
|
|
db,
|
|
field_id,
|
|
level_iters: vec![(documents_ids, Right(highest_reverse_iter))],
|
|
must_reduce: true,
|
|
})
|
|
}
|
|
|
|
pub fn new_non_reducing(
|
|
rtxn: &'t heed::RoTxn,
|
|
index: &'t Index,
|
|
field_id: FieldId,
|
|
documents_ids: RoaringBitmap,
|
|
) -> heed::Result<FacetStringIter<'t>> {
|
|
let db = index.facet_id_string_docids.remap_types::<ByteSlice, ByteSlice>();
|
|
let highest_iter = Self::highest_iter(rtxn, index, db, field_id)?;
|
|
Ok(FacetStringIter {
|
|
rtxn,
|
|
db,
|
|
field_id,
|
|
level_iters: vec![(documents_ids, Left(highest_iter))],
|
|
must_reduce: false,
|
|
})
|
|
}
|
|
|
|
fn highest_level<X, Y>(
|
|
rtxn: &'t heed::RoTxn,
|
|
db: Database<X, Y>,
|
|
fid: FieldId,
|
|
) -> heed::Result<Option<u8>> {
|
|
Ok(db
|
|
.remap_types::<ByteSlice, DecodeIgnore>()
|
|
.prefix_iter(rtxn, &fid.to_be_bytes())? // the field id is the first two bits
|
|
.last()
|
|
.transpose()?
|
|
.map(|(key_bytes, _)| key_bytes[2])) // the level is the third bit
|
|
}
|
|
|
|
fn highest_iter<X, Y>(
|
|
rtxn: &'t heed::RoTxn,
|
|
index: &'t Index,
|
|
db: Database<X, Y>,
|
|
field_id: FieldId,
|
|
) -> heed::Result<Either<FacetStringGroupRange<'t>, FacetStringLevelZeroRange<'t>>> {
|
|
let highest_level = Self::highest_level(rtxn, db, field_id)?.unwrap_or(0);
|
|
match NonZeroU8::new(highest_level) {
|
|
Some(highest_level) => FacetStringGroupRange::new(
|
|
rtxn,
|
|
index.facet_id_string_docids,
|
|
field_id,
|
|
highest_level,
|
|
Unbounded,
|
|
Unbounded,
|
|
)
|
|
.map(Left),
|
|
None => FacetStringLevelZeroRange::new(
|
|
rtxn,
|
|
index.facet_id_string_docids,
|
|
field_id,
|
|
Unbounded,
|
|
Unbounded,
|
|
)
|
|
.map(Right),
|
|
}
|
|
}
|
|
|
|
fn highest_reverse_iter<X, Y>(
|
|
rtxn: &'t heed::RoTxn,
|
|
index: &'t Index,
|
|
db: Database<X, Y>,
|
|
field_id: FieldId,
|
|
) -> heed::Result<Either<FacetStringGroupRevRange<'t>, FacetStringLevelZeroRevRange<'t>>> {
|
|
let highest_level = Self::highest_level(rtxn, db, field_id)?.unwrap_or(0);
|
|
match NonZeroU8::new(highest_level) {
|
|
Some(highest_level) => FacetStringGroupRevRange::new(
|
|
rtxn,
|
|
index.facet_id_string_docids,
|
|
field_id,
|
|
highest_level,
|
|
Unbounded,
|
|
Unbounded,
|
|
)
|
|
.map(Left),
|
|
None => FacetStringLevelZeroRevRange::new(
|
|
rtxn,
|
|
index.facet_id_string_docids,
|
|
field_id,
|
|
Unbounded,
|
|
Unbounded,
|
|
)
|
|
.map(Right),
|
|
}
|
|
}
|
|
}
|
|
|
|
impl<'t> Iterator for FacetStringIter<'t> {
|
|
type Item = heed::Result<(&'t str, &'t str, RoaringBitmap)>;
|
|
|
|
fn next(&mut self) -> Option<Self::Item> {
|
|
'outer: loop {
|
|
let (documents_ids, last) = self.level_iters.last_mut()?;
|
|
let is_ascending = last.is_left();
|
|
|
|
// We remap the different iterator types to make
|
|
// the algorithm less complex to understand.
|
|
let last = match last {
|
|
Left(ascending) => match ascending {
|
|
Left(group) => Left(Left(group)),
|
|
Right(zero_level) => Right(Left(zero_level)),
|
|
},
|
|
Right(descending) => match descending {
|
|
Left(group) => Left(Right(group)),
|
|
Right(zero_level) => Right(Right(zero_level)),
|
|
},
|
|
};
|
|
|
|
match last {
|
|
Left(group) => {
|
|
for result in group {
|
|
match result {
|
|
Ok(((level, left, right), (string_bounds, mut docids))) => {
|
|
docids &= &*documents_ids;
|
|
if !docids.is_empty() {
|
|
if self.must_reduce {
|
|
*documents_ids -= &docids;
|
|
}
|
|
|
|
let result = if is_ascending {
|
|
match string_bounds {
|
|
Some((left, right)) => FacetStringLevelZeroRange::new(
|
|
self.rtxn,
|
|
self.db,
|
|
self.field_id,
|
|
Included(left),
|
|
Included(right),
|
|
)
|
|
.map(Right),
|
|
None => FacetStringGroupRange::new(
|
|
self.rtxn,
|
|
self.db,
|
|
self.field_id,
|
|
NonZeroU8::new(level.get() - 1).unwrap(),
|
|
Included(left),
|
|
Included(right),
|
|
)
|
|
.map(Left),
|
|
}
|
|
.map(Left)
|
|
} else {
|
|
match string_bounds {
|
|
Some((left, right)) => {
|
|
FacetStringLevelZeroRevRange::new(
|
|
self.rtxn,
|
|
self.db,
|
|
self.field_id,
|
|
Included(left),
|
|
Included(right),
|
|
)
|
|
.map(Right)
|
|
}
|
|
None => FacetStringGroupRevRange::new(
|
|
self.rtxn,
|
|
self.db,
|
|
self.field_id,
|
|
NonZeroU8::new(level.get() - 1).unwrap(),
|
|
Included(left),
|
|
Included(right),
|
|
)
|
|
.map(Left),
|
|
}
|
|
.map(Right)
|
|
};
|
|
|
|
match result {
|
|
Ok(iter) => {
|
|
self.level_iters.push((docids, iter));
|
|
continue 'outer;
|
|
}
|
|
Err(e) => return Some(Err(e)),
|
|
}
|
|
}
|
|
}
|
|
Err(e) => return Some(Err(e)),
|
|
}
|
|
}
|
|
}
|
|
Right(zero_level) => {
|
|
// level zero only
|
|
for result in zero_level {
|
|
match result {
|
|
Ok((normalized, original, mut docids)) => {
|
|
docids &= &*documents_ids;
|
|
if !docids.is_empty() {
|
|
if self.must_reduce {
|
|
*documents_ids -= &docids;
|
|
}
|
|
return Some(Ok((normalized, original, docids)));
|
|
}
|
|
}
|
|
Err(e) => return Some(Err(e)),
|
|
}
|
|
}
|
|
}
|
|
}
|
|
|
|
self.level_iters.pop();
|
|
}
|
|
}
|
|
}
|