4350: Make several indexing optimizations r=Kerollmops a=ManyTheFish

# Summary

Implement several enhancements to reduce the indexing time.

# Steps

- Compute the indexing chunk size dynamically based on the available threads and the data size
- Remove the merging step before the writing step and merge at the writing time
- Remove append function
- Make Facet search indexing incremental

# Running Indexing process

## `main`
Each type of data is written after a merging phase:
![Capture d’écran 2024-01-23 à 10 18 08](https://github.com/meilisearch/meilisearch/assets/6482087/6203c3ce-407c-46b4-8b83-04282da1bb16)

> Highlighted parts are the writings

## `remove-merging-phase-from-indexing`
When the extraction of a chunk is finished, the data is written:
![Capture d’écran 2024-01-23 à 10 18 18](https://github.com/meilisearch/meilisearch/assets/6482087/ab1307b4-d0a9-42ac-abbb-fdeb27ddf0d4)

> Highlighted parts are the writings

## Related

This PR removes the appending writes on several indexing parts, which may fix https://github.com/meilisearch/meilisearch/issues/4300. However, all of the appending writes are not removed. There are 2 remaining calls that could trigger this bug:
- When [putting embedders in the settings](b6fc181993/milli/src/update/settings.rs (L996))
- when [bulk indexing the facets](b6fc181993/milli/src/update/facet/bulk.rs (L150))


Co-authored-by: ManyTheFish <many@meilisearch.com>
Co-authored-by: Louis Dureuil <louis@meilisearch.com>
Co-authored-by: Many the fish <many@meilisearch.com>
This commit is contained in:
meili-bors[bot] 2024-02-14 14:12:48 +00:00 committed by GitHub
commit 72c1674a31
No known key found for this signature in database
GPG Key ID: B5690EEEBB952194
15 changed files with 998 additions and 805 deletions

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@ -1,7 +1,7 @@
use std::fs::File;
use std::io::BufReader;
use grenad::CompressionType;
use grenad::{CompressionType, Merger};
use heed::types::Bytes;
use heed::{BytesDecode, BytesEncode, Error, PutFlags, RoTxn, RwTxn};
use roaring::RoaringBitmap;
@ -14,6 +14,7 @@ use crate::heed_codec::facet::{
use crate::heed_codec::BytesRefCodec;
use crate::update::del_add::{DelAdd, KvReaderDelAdd};
use crate::update::index_documents::{create_writer, valid_lmdb_key, writer_into_reader};
use crate::update::MergeFn;
use crate::{CboRoaringBitmapCodec, CboRoaringBitmapLenCodec, FieldId, Index, Result};
/// Algorithm to insert elememts into the `facet_id_(string/f64)_docids` databases
@ -28,7 +29,7 @@ pub struct FacetsUpdateBulk<'i> {
facet_type: FacetType,
field_ids: Vec<FieldId>,
// None if level 0 does not need to be updated
delta_data: Option<grenad::Reader<BufReader<File>>>,
delta_data: Option<Merger<BufReader<File>, MergeFn>>,
}
impl<'i> FacetsUpdateBulk<'i> {
@ -36,7 +37,7 @@ impl<'i> FacetsUpdateBulk<'i> {
index: &'i Index,
field_ids: Vec<FieldId>,
facet_type: FacetType,
delta_data: grenad::Reader<BufReader<File>>,
delta_data: Merger<BufReader<File>, MergeFn>,
group_size: u8,
min_level_size: u8,
) -> FacetsUpdateBulk<'i> {
@ -65,7 +66,7 @@ impl<'i> FacetsUpdateBulk<'i> {
}
}
#[logging_timer::time("FacetsUpdateBulk::{}")]
#[tracing::instrument(level = "trace", skip_all, target = "indexing::facets::bulk")]
pub fn execute(self, wtxn: &mut heed::RwTxn) -> Result<()> {
let Self { index, field_ids, group_size, min_level_size, facet_type, delta_data } = self;
@ -89,7 +90,7 @@ impl<'i> FacetsUpdateBulk<'i> {
/// Implementation of `FacetsUpdateBulk` that is independent of milli's `Index` type
pub(crate) struct FacetsUpdateBulkInner<R: std::io::Read + std::io::Seek> {
pub db: heed::Database<FacetGroupKeyCodec<BytesRefCodec>, FacetGroupValueCodec>,
pub delta_data: Option<grenad::Reader<R>>,
pub delta_data: Option<Merger<R, MergeFn>>,
pub group_size: u8,
pub min_level_size: u8,
}
@ -129,8 +130,8 @@ impl<R: std::io::Read + std::io::Seek> FacetsUpdateBulkInner<R> {
if self.db.is_empty(wtxn)? {
let mut buffer = Vec::new();
let mut database = self.db.iter_mut(wtxn)?.remap_types::<Bytes, Bytes>();
let mut cursor = delta_data.into_cursor()?;
while let Some((key, value)) = cursor.move_on_next()? {
let mut iter = delta_data.into_stream_merger_iter()?;
while let Some((key, value)) = iter.next()? {
if !valid_lmdb_key(key) {
continue;
}
@ -154,8 +155,8 @@ impl<R: std::io::Read + std::io::Seek> FacetsUpdateBulkInner<R> {
let mut buffer = Vec::new();
let database = self.db.remap_types::<Bytes, Bytes>();
let mut cursor = delta_data.into_cursor()?;
while let Some((key, value)) = cursor.move_on_next()? {
let mut iter = delta_data.into_stream_merger_iter()?;
while let Some((key, value)) = iter.next()? {
if !valid_lmdb_key(key) {
continue;
}

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@ -1,6 +1,7 @@
use std::fs::File;
use std::io::BufReader;
use grenad::Merger;
use heed::types::{Bytes, DecodeIgnore};
use heed::{BytesDecode, Error, RoTxn, RwTxn};
use obkv::KvReader;
@ -14,6 +15,7 @@ use crate::heed_codec::BytesRefCodec;
use crate::search::facet::get_highest_level;
use crate::update::del_add::DelAdd;
use crate::update::index_documents::valid_lmdb_key;
use crate::update::MergeFn;
use crate::{CboRoaringBitmapCodec, Index, Result};
enum InsertionResult {
@ -31,14 +33,14 @@ enum DeletionResult {
/// `facet_id_(string/f64)_docids` databases.
pub struct FacetsUpdateIncremental {
inner: FacetsUpdateIncrementalInner,
delta_data: grenad::Reader<BufReader<File>>,
delta_data: Merger<BufReader<File>, MergeFn>,
}
impl FacetsUpdateIncremental {
pub fn new(
index: &Index,
facet_type: FacetType,
delta_data: grenad::Reader<BufReader<File>>,
delta_data: Merger<BufReader<File>, MergeFn>,
group_size: u8,
min_level_size: u8,
max_group_size: u8,
@ -61,16 +63,18 @@ impl FacetsUpdateIncremental {
}
}
#[tracing::instrument(level = "trace", skip_all, target = "indexing::facets::incremental")]
pub fn execute(self, wtxn: &mut RwTxn) -> crate::Result<()> {
let mut cursor = self.delta_data.into_cursor()?;
while let Some((key, value)) = cursor.move_on_next()? {
let mut iter = self.delta_data.into_stream_merger_iter()?;
while let Some((key, value)) = iter.next()? {
if !valid_lmdb_key(key) {
continue;
}
let key = FacetGroupKeyCodec::<BytesRefCodec>::bytes_decode(key)
.map_err(heed::Error::Encoding)?;
let value = KvReader::new(value);
let docids_to_delete = value
.get(DelAdd::Deletion)
.map(CboRoaringBitmapCodec::bytes_decode)

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@ -79,12 +79,9 @@ pub const FACET_MIN_LEVEL_SIZE: u8 = 5;
use std::collections::BTreeSet;
use std::fs::File;
use std::io::BufReader;
use std::iter::FromIterator;
use charabia::normalizer::{Normalize, NormalizerOption};
use grenad::{CompressionType, SortAlgorithm};
use heed::types::{Bytes, DecodeIgnore, SerdeJson};
use heed::BytesEncode;
use grenad::Merger;
use heed::types::{Bytes, DecodeIgnore};
use time::OffsetDateTime;
use tracing::debug;
@ -93,9 +90,9 @@ use super::FacetsUpdateBulk;
use crate::facet::FacetType;
use crate::heed_codec::facet::{FacetGroupKey, FacetGroupKeyCodec, FacetGroupValueCodec};
use crate::heed_codec::BytesRefCodec;
use crate::update::index_documents::create_sorter;
use crate::update::merge_btreeset_string;
use crate::{BEU16StrCodec, Index, Result, MAX_FACET_VALUE_LENGTH};
use crate::update::del_add::{DelAdd, KvReaderDelAdd};
use crate::update::MergeFn;
use crate::{try_split_array_at, FieldId, Index, Result};
pub mod bulk;
pub mod incremental;
@ -108,16 +105,20 @@ pub struct FacetsUpdate<'i> {
index: &'i Index,
database: heed::Database<FacetGroupKeyCodec<BytesRefCodec>, FacetGroupValueCodec>,
facet_type: FacetType,
delta_data: grenad::Reader<BufReader<File>>,
delta_data: Merger<BufReader<File>, MergeFn>,
normalized_delta_data: Option<Merger<BufReader<File>, MergeFn>>,
group_size: u8,
max_group_size: u8,
min_level_size: u8,
data_size: u64,
}
impl<'i> FacetsUpdate<'i> {
pub fn new(
index: &'i Index,
facet_type: FacetType,
delta_data: grenad::Reader<BufReader<File>>,
delta_data: Merger<BufReader<File>, MergeFn>,
normalized_delta_data: Option<Merger<BufReader<File>, MergeFn>>,
data_size: u64,
) -> Self {
let database = match facet_type {
FacetType::String => {
@ -135,18 +136,20 @@ impl<'i> FacetsUpdate<'i> {
min_level_size: FACET_MIN_LEVEL_SIZE,
facet_type,
delta_data,
normalized_delta_data,
data_size,
}
}
pub fn execute(self, wtxn: &mut heed::RwTxn) -> Result<()> {
if self.delta_data.is_empty() {
if self.data_size == 0 {
return Ok(());
}
debug!("Computing and writing the facet values levels docids into LMDB on disk...");
self.index.set_updated_at(wtxn, &OffsetDateTime::now_utc())?;
// See self::comparison_bench::benchmark_facet_indexing
if self.delta_data.len() >= (self.database.len(wtxn)? / 50) {
if self.data_size >= (self.database.len(wtxn)? / 50) {
let field_ids =
self.index.faceted_fields_ids(wtxn)?.iter().copied().collect::<Vec<_>>();
let bulk_update = FacetsUpdateBulk::new(
@ -170,96 +173,110 @@ impl<'i> FacetsUpdate<'i> {
incremental_update.execute(wtxn)?;
}
// We clear the list of normalized-for-search facets
// and the previous FSTs to compute everything from scratch
self.index.facet_id_normalized_string_strings.clear(wtxn)?;
self.index.facet_id_string_fst.clear(wtxn)?;
// As we can't use the same write transaction to read and write in two different databases
// we must create a temporary sorter that we will write into LMDB afterward.
// As multiple unnormalized facet values can become the same normalized facet value
// we must merge them together.
let mut sorter = create_sorter(
SortAlgorithm::Unstable,
merge_btreeset_string,
CompressionType::None,
None,
None,
None,
);
// We iterate on the list of original, semi-normalized, facet values
// and normalize them for search, inserting them in LMDB in any given order.
let options = NormalizerOption { lossy: true, ..Default::default() };
let database = self.index.facet_id_string_docids.remap_data_type::<DecodeIgnore>();
for result in database.iter(wtxn)? {
let (facet_group_key, ()) = result?;
if let FacetGroupKey { field_id, level: 0, left_bound } = facet_group_key {
let mut normalized_facet = left_bound.normalize(&options);
let normalized_truncated_facet: String;
if normalized_facet.len() > MAX_FACET_VALUE_LENGTH {
normalized_truncated_facet = normalized_facet
.char_indices()
.take_while(|(idx, _)| *idx < MAX_FACET_VALUE_LENGTH)
.map(|(_, c)| c)
.collect();
normalized_facet = normalized_truncated_facet.into();
}
let set = BTreeSet::from_iter(std::iter::once(left_bound));
let key = (field_id, normalized_facet.as_ref());
let key = BEU16StrCodec::bytes_encode(&key).map_err(heed::Error::Encoding)?;
let val = SerdeJson::bytes_encode(&set).map_err(heed::Error::Encoding)?;
sorter.insert(key, val)?;
}
match self.normalized_delta_data {
Some(data) => index_facet_search(wtxn, data, self.index),
None => Ok(()),
}
// In this loop we don't need to take care of merging bitmaps
// as the grenad sorter already merged them for us.
let mut merger_iter = sorter.into_stream_merger_iter()?;
while let Some((key_bytes, btreeset_bytes)) = merger_iter.next()? {
self.index.facet_id_normalized_string_strings.remap_types::<Bytes, Bytes>().put(
wtxn,
key_bytes,
btreeset_bytes,
)?;
}
// We compute one FST by string facet
let mut text_fsts = vec![];
let mut current_fst: Option<(u16, fst::SetBuilder<Vec<u8>>)> = None;
let database =
self.index.facet_id_normalized_string_strings.remap_data_type::<DecodeIgnore>();
for result in database.iter(wtxn)? {
let ((field_id, normalized_facet), _) = result?;
current_fst = match current_fst.take() {
Some((fid, fst_builder)) if fid != field_id => {
let fst = fst_builder.into_set();
text_fsts.push((fid, fst));
Some((field_id, fst::SetBuilder::memory()))
}
Some((field_id, fst_builder)) => Some((field_id, fst_builder)),
None => Some((field_id, fst::SetBuilder::memory())),
};
if let Some((_, fst_builder)) = current_fst.as_mut() {
fst_builder.insert(normalized_facet)?;
}
}
if let Some((field_id, fst_builder)) = current_fst {
let fst = fst_builder.into_set();
text_fsts.push((field_id, fst));
}
// We write those FSTs in LMDB now
for (field_id, fst) in text_fsts {
self.index.facet_id_string_fst.put(wtxn, &field_id, &fst)?;
}
Ok(())
}
}
fn index_facet_search(
wtxn: &mut heed::RwTxn,
normalized_delta_data: Merger<BufReader<File>, MergeFn>,
index: &Index,
) -> Result<()> {
let mut iter = normalized_delta_data.into_stream_merger_iter()?;
while let Some((key_bytes, delta_bytes)) = iter.next()? {
let deladd_reader = KvReaderDelAdd::new(delta_bytes);
let database_set = index
.facet_id_normalized_string_strings
.remap_key_type::<Bytes>()
.get(wtxn, key_bytes)?
.unwrap_or_default();
let add_set = deladd_reader
.get(DelAdd::Addition)
.and_then(|bytes| serde_json::from_slice::<BTreeSet<String>>(bytes).ok())
.unwrap_or_default();
let del_set = match deladd_reader
.get(DelAdd::Deletion)
.and_then(|bytes| serde_json::from_slice::<BTreeSet<String>>(bytes).ok())
{
Some(del_set) => {
let (field_id_bytes, _) = try_split_array_at(key_bytes).unwrap();
let field_id = FieldId::from_be_bytes(field_id_bytes);
let mut set = BTreeSet::new();
for facet in del_set {
let key = FacetGroupKey { field_id, level: 0, left_bound: facet.as_str() };
// Check if the referenced value doesn't exist anymore before deleting it.
if index
.facet_id_string_docids
.remap_data_type::<DecodeIgnore>()
.get(wtxn, &key)?
.is_none()
{
set.insert(facet);
}
}
set
}
None => BTreeSet::new(),
};
let set: BTreeSet<_> =
database_set.difference(&del_set).chain(add_set.iter()).cloned().collect();
if set.is_empty() {
index
.facet_id_normalized_string_strings
.remap_key_type::<Bytes>()
.delete(wtxn, key_bytes)?;
} else {
index
.facet_id_normalized_string_strings
.remap_key_type::<Bytes>()
.put(wtxn, key_bytes, &set)?;
}
}
// We clear the FST of normalized-for-search to compute everything from scratch.
index.facet_id_string_fst.clear(wtxn)?;
// We compute one FST by string facet
let mut text_fsts = vec![];
let mut current_fst: Option<(u16, fst::SetBuilder<Vec<u8>>)> = None;
let database = index.facet_id_normalized_string_strings.remap_data_type::<DecodeIgnore>();
for result in database.iter(wtxn)? {
let ((field_id, normalized_facet), _) = result?;
current_fst = match current_fst.take() {
Some((fid, fst_builder)) if fid != field_id => {
let fst = fst_builder.into_set();
text_fsts.push((fid, fst));
Some((field_id, fst::SetBuilder::memory()))
}
Some((field_id, fst_builder)) => Some((field_id, fst_builder)),
None => Some((field_id, fst::SetBuilder::memory())),
};
if let Some((_, fst_builder)) = current_fst.as_mut() {
fst_builder.insert(normalized_facet)?;
}
}
if let Some((field_id, fst_builder)) = current_fst {
let fst = fst_builder.into_set();
text_fsts.push((field_id, fst));
}
// We write those FSTs in LMDB now
for (field_id, fst) in text_fsts {
index.facet_id_string_fst.put(wtxn, &field_id, &fst)?;
}
Ok(())
}
#[cfg(test)]
pub(crate) mod test_helpers {
use std::cell::Cell;
@ -268,6 +285,7 @@ pub(crate) mod test_helpers {
use std::marker::PhantomData;
use std::rc::Rc;
use grenad::MergerBuilder;
use heed::types::Bytes;
use heed::{BytesDecode, BytesEncode, Env, RoTxn, RwTxn};
use roaring::RoaringBitmap;
@ -280,7 +298,8 @@ pub(crate) mod test_helpers {
use crate::search::facet::get_highest_level;
use crate::snapshot_tests::display_bitmap;
use crate::update::del_add::{DelAdd, KvWriterDelAdd};
use crate::update::FacetsUpdateIncrementalInner;
use crate::update::index_documents::merge_deladd_cbo_roaring_bitmaps;
use crate::update::{FacetsUpdateIncrementalInner, MergeFn};
use crate::CboRoaringBitmapCodec;
/// Utility function to generate a string whose position in a lexicographically
@ -463,10 +482,13 @@ pub(crate) mod test_helpers {
}
writer.finish().unwrap();
let reader = grenad::Reader::new(std::io::Cursor::new(new_data)).unwrap();
let mut builder = MergerBuilder::new(merge_deladd_cbo_roaring_bitmaps as MergeFn);
builder.push(reader.into_cursor().unwrap());
let merger = builder.build();
let update = FacetsUpdateBulkInner {
db: self.content,
delta_data: Some(reader),
delta_data: Some(merger),
group_size: self.group_size.get(),
min_level_size: self.min_level_size.get(),
};

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@ -26,7 +26,7 @@ pub fn extract_docid_word_positions<R: io::Read + io::Seek>(
obkv_documents: grenad::Reader<R>,
indexer: GrenadParameters,
searchable_fields: &Option<HashSet<FieldId>>,
stop_words: Option<&fst::Set<&[u8]>>,
stop_words: Option<&fst::Set<Vec<u8>>>,
allowed_separators: Option<&[&str]>,
dictionary: Option<&[&str]>,
max_positions_per_attributes: Option<u32>,
@ -181,11 +181,11 @@ fn searchable_fields_changed(
/// Factorize tokenizer building.
fn tokenizer_builder<'a>(
stop_words: Option<&'a fst::Set<&[u8]>>,
stop_words: Option<&'a fst::Set<Vec<u8>>>,
allowed_separators: Option<&'a [&str]>,
dictionary: Option<&'a [&str]>,
script_language: Option<&'a HashMap<Script, Vec<Language>>>,
) -> TokenizerBuilder<'a, &'a [u8]> {
) -> TokenizerBuilder<'a, Vec<u8>> {
let mut tokenizer_builder = TokenizerBuilder::new();
if let Some(stop_words) = stop_words {
tokenizer_builder.stop_words(stop_words);
@ -211,7 +211,7 @@ fn lang_safe_tokens_from_document<'a>(
obkv: &KvReader<FieldId>,
searchable_fields: &Option<HashSet<FieldId>>,
tokenizer: &Tokenizer,
stop_words: Option<&fst::Set<&[u8]>>,
stop_words: Option<&fst::Set<Vec<u8>>>,
allowed_separators: Option<&[&str]>,
dictionary: Option<&[&str]>,
max_positions_per_attributes: u32,

View File

@ -1,15 +1,21 @@
use std::collections::BTreeSet;
use std::fs::File;
use std::io::BufReader;
use std::iter::FromIterator;
use std::{io, str};
use charabia::normalizer::{Normalize, NormalizerOption};
use heed::types::SerdeJson;
use heed::BytesEncode;
use super::helpers::{create_sorter, sorter_into_reader, try_split_array_at, GrenadParameters};
use crate::heed_codec::facet::{FacetGroupKey, FacetGroupKeyCodec};
use crate::heed_codec::StrRefCodec;
use crate::update::del_add::{KvReaderDelAdd, KvWriterDelAdd};
use crate::update::index_documents::helpers::merge_deladd_cbo_roaring_bitmaps;
use crate::{FieldId, Result};
use crate::heed_codec::{BEU16StrCodec, StrRefCodec};
use crate::update::del_add::{DelAdd, KvReaderDelAdd, KvWriterDelAdd};
use crate::update::index_documents::helpers::{
merge_deladd_btreeset_string, merge_deladd_cbo_roaring_bitmaps,
};
use crate::{FieldId, Result, MAX_FACET_VALUE_LENGTH};
/// Extracts the facet string and the documents ids where this facet string appear.
///
@ -19,10 +25,11 @@ use crate::{FieldId, Result};
pub fn extract_facet_string_docids<R: io::Read + io::Seek>(
docid_fid_facet_string: grenad::Reader<R>,
indexer: GrenadParameters,
) -> Result<grenad::Reader<BufReader<File>>> {
) -> Result<(grenad::Reader<BufReader<File>>, grenad::Reader<BufReader<File>>)> {
puffin::profile_function!();
let max_memory = indexer.max_memory_by_thread();
let options = NormalizerOption { lossy: true, ..Default::default() };
let mut facet_string_docids_sorter = create_sorter(
grenad::SortAlgorithm::Stable,
@ -30,12 +37,30 @@ pub fn extract_facet_string_docids<R: io::Read + io::Seek>(
indexer.chunk_compression_type,
indexer.chunk_compression_level,
indexer.max_nb_chunks,
max_memory,
max_memory.map(|m| m / 2),
);
let mut normalized_facet_string_docids_sorter = create_sorter(
grenad::SortAlgorithm::Stable,
merge_deladd_btreeset_string,
indexer.chunk_compression_type,
indexer.chunk_compression_level,
indexer.max_nb_chunks,
max_memory.map(|m| m / 2),
);
let mut buffer = Vec::new();
let mut cursor = docid_fid_facet_string.into_cursor()?;
while let Some((key, deladd_original_value_bytes)) = cursor.move_on_next()? {
let deladd_reader = KvReaderDelAdd::new(deladd_original_value_bytes);
// nothing to do if we delete and re-add the value.
if deladd_reader.get(DelAdd::Deletion).is_some()
&& deladd_reader.get(DelAdd::Addition).is_some()
{
continue;
}
let (field_id_bytes, bytes) = try_split_array_at(key).unwrap();
let field_id = FieldId::from_be_bytes(field_id_bytes);
@ -44,17 +69,46 @@ pub fn extract_facet_string_docids<R: io::Read + io::Seek>(
let document_id = u32::from_be_bytes(document_id_bytes);
let normalized_value = str::from_utf8(normalized_value_bytes)?;
// Facet search normalization
{
let mut hyper_normalized_value = normalized_value.normalize(&options);
let normalized_truncated_facet: String;
if hyper_normalized_value.len() > MAX_FACET_VALUE_LENGTH {
normalized_truncated_facet = hyper_normalized_value
.char_indices()
.take_while(|(idx, _)| *idx < MAX_FACET_VALUE_LENGTH)
.map(|(_, c)| c)
.collect();
hyper_normalized_value = normalized_truncated_facet.into();
}
let set = BTreeSet::from_iter(std::iter::once(normalized_value));
buffer.clear();
let mut obkv = KvWriterDelAdd::new(&mut buffer);
for (deladd_key, _) in deladd_reader.iter() {
let val = SerdeJson::bytes_encode(&set).map_err(heed::Error::Encoding)?;
obkv.insert(deladd_key, val)?;
}
obkv.finish()?;
let key = (field_id, hyper_normalized_value.as_ref());
let key_bytes = BEU16StrCodec::bytes_encode(&key).map_err(heed::Error::Encoding)?;
normalized_facet_string_docids_sorter.insert(key_bytes, &buffer)?;
}
let key = FacetGroupKey { field_id, level: 0, left_bound: normalized_value };
let key_bytes = FacetGroupKeyCodec::<StrRefCodec>::bytes_encode(&key).unwrap();
buffer.clear();
let mut obkv = KvWriterDelAdd::new(&mut buffer);
for (deladd_key, _) in KvReaderDelAdd::new(deladd_original_value_bytes).iter() {
for (deladd_key, _) in deladd_reader.iter() {
obkv.insert(deladd_key, document_id.to_ne_bytes())?;
}
obkv.finish()?;
facet_string_docids_sorter.insert(&key_bytes, &buffer)?;
}
sorter_into_reader(facet_string_docids_sorter, indexer)
let normalized = sorter_into_reader(normalized_facet_string_docids_sorter, indexer)?;
sorter_into_reader(facet_string_docids_sorter, indexer).map(|s| (s, normalized))
}

View File

@ -257,6 +257,7 @@ fn push_vectors_diff(
key_buffer: &mut Vec<u8>,
delta: VectorStateDelta,
) -> Result<()> {
puffin::profile_function!();
let (must_remove, prompt, (mut del_vectors, mut add_vectors)) = delta.into_values();
if must_remove {
key_buffer.truncate(TRUNCATE_SIZE);
@ -332,13 +333,14 @@ fn extract_vectors(
}
}
#[logging_timer::time]
#[tracing::instrument(level = "trace", skip_all, target = "indexing::extract")]
pub fn extract_embeddings<R: io::Read + io::Seek>(
// docid, prompt
prompt_reader: grenad::Reader<R>,
indexer: GrenadParameters,
embedder: Arc<Embedder>,
) -> Result<grenad::Reader<BufReader<File>>> {
puffin::profile_function!();
let n_chunks = embedder.chunk_count_hint(); // chunk level parallelism
let n_vectors_per_chunk = embedder.prompt_count_in_chunk_hint(); // number of vectors in a single chunk

View File

@ -15,7 +15,6 @@ use std::io::BufReader;
use crossbeam_channel::Sender;
use rayon::prelude::*;
use tracing::debug;
use self::extract_docid_word_positions::extract_docid_word_positions;
use self::extract_facet_number_docids::extract_facet_number_docids;
@ -29,10 +28,7 @@ use self::extract_vector_points::{
use self::extract_word_docids::extract_word_docids;
use self::extract_word_pair_proximity_docids::extract_word_pair_proximity_docids;
use self::extract_word_position_docids::extract_word_position_docids;
use super::helpers::{
as_cloneable_grenad, merge_deladd_cbo_roaring_bitmaps, CursorClonableMmap, GrenadParameters,
MergeFn, MergeableReader,
};
use super::helpers::{as_cloneable_grenad, CursorClonableMmap, GrenadParameters};
use super::{helpers, TypedChunk};
use crate::proximity::ProximityPrecision;
use crate::vector::EmbeddingConfigs;
@ -52,7 +48,7 @@ pub(crate) fn data_from_obkv_documents(
primary_key_id: FieldId,
geo_fields_ids: Option<(FieldId, FieldId)>,
field_id_map: FieldsIdsMap,
stop_words: Option<fst::Set<&[u8]>>,
stop_words: Option<fst::Set<Vec<u8>>>,
allowed_separators: Option<&[&str]>,
dictionary: Option<&[&str]>,
max_positions_per_attributes: Option<u32>,
@ -62,201 +58,154 @@ pub(crate) fn data_from_obkv_documents(
) -> Result<()> {
puffin::profile_function!();
original_obkv_chunks
.par_bridge()
.map(|original_documents_chunk| {
send_original_documents_data(
original_documents_chunk,
indexer,
lmdb_writer_sx.clone(),
field_id_map.clone(),
embedders.clone(),
)
})
.collect::<Result<()>>()?;
#[allow(clippy::type_complexity)]
let result: Result<(Vec<_>, (Vec<_>, (Vec<_>, (Vec<_>, (Vec<_>, Vec<_>)))))> =
flattened_obkv_chunks
.par_bridge()
.map(|flattened_obkv_chunks| {
send_and_extract_flattened_documents_data(
flattened_obkv_chunks,
indexer,
lmdb_writer_sx.clone(),
&searchable_fields,
&faceted_fields,
primary_key_id,
geo_fields_ids,
&stop_words,
&allowed_separators,
&dictionary,
max_positions_per_attributes,
)
})
.collect();
let (
docid_word_positions_chunks,
(
fid_docid_facet_numbers_chunks,
(
fid_docid_facet_strings_chunks,
(
facet_is_null_docids_chunks,
(facet_is_empty_docids_chunks, facet_exists_docids_chunks),
),
),
),
) = result?;
// merge facet_exists_docids and send them as a typed chunk
{
let lmdb_writer_sx = lmdb_writer_sx.clone();
rayon::spawn(move || {
debug!(database = "facet-id-exists-docids", "merge");
match facet_exists_docids_chunks.merge(merge_deladd_cbo_roaring_bitmaps, &indexer) {
Ok(reader) => {
let _ = lmdb_writer_sx.send(Ok(TypedChunk::FieldIdFacetExistsDocids(reader)));
}
Err(e) => {
let _ = lmdb_writer_sx.send(Err(e));
}
}
});
}
// merge facet_is_null_docids and send them as a typed chunk
{
let lmdb_writer_sx = lmdb_writer_sx.clone();
rayon::spawn(move || {
debug!(database = "facet-id-is-null-docids", "merge");
match facet_is_null_docids_chunks.merge(merge_deladd_cbo_roaring_bitmaps, &indexer) {
Ok(reader) => {
let _ = lmdb_writer_sx.send(Ok(TypedChunk::FieldIdFacetIsNullDocids(reader)));
}
Err(e) => {
let _ = lmdb_writer_sx.send(Err(e));
}
}
});
}
// merge facet_is_empty_docids and send them as a typed chunk
{
let lmdb_writer_sx = lmdb_writer_sx.clone();
rayon::spawn(move || {
debug!(database = "facet-id-is-empty-docids", "merge");
match facet_is_empty_docids_chunks.merge(merge_deladd_cbo_roaring_bitmaps, &indexer) {
Ok(reader) => {
let _ = lmdb_writer_sx.send(Ok(TypedChunk::FieldIdFacetIsEmptyDocids(reader)));
}
Err(e) => {
let _ = lmdb_writer_sx.send(Err(e));
}
}
});
}
if proximity_precision == ProximityPrecision::ByWord {
spawn_extraction_task::<_, _, Vec<grenad::Reader<BufReader<File>>>>(
docid_word_positions_chunks.clone(),
indexer,
lmdb_writer_sx.clone(),
extract_word_pair_proximity_docids,
merge_deladd_cbo_roaring_bitmaps,
TypedChunk::WordPairProximityDocids,
"word-pair-proximity-docids",
);
}
spawn_extraction_task::<_, _, Vec<grenad::Reader<BufReader<File>>>>(
docid_word_positions_chunks.clone(),
indexer,
lmdb_writer_sx.clone(),
extract_fid_word_count_docids,
merge_deladd_cbo_roaring_bitmaps,
TypedChunk::FieldIdWordCountDocids,
"field-id-wordcount-docids",
);
spawn_extraction_task::<
_,
_,
Vec<(
grenad::Reader<BufReader<File>>,
grenad::Reader<BufReader<File>>,
grenad::Reader<BufReader<File>>,
)>,
>(
docid_word_positions_chunks.clone(),
indexer,
lmdb_writer_sx.clone(),
move |doc_word_pos, indexer| extract_word_docids(doc_word_pos, indexer, &exact_attributes),
merge_deladd_cbo_roaring_bitmaps,
|(word_docids_reader, exact_word_docids_reader, word_fid_docids_reader)| {
TypedChunk::WordDocids {
word_docids_reader,
exact_word_docids_reader,
word_fid_docids_reader,
}
let (original_pipeline_result, flattened_pipeline_result): (Result<_>, Result<_>) = rayon::join(
|| {
original_obkv_chunks
.par_bridge()
.map(|original_documents_chunk| {
send_original_documents_data(
original_documents_chunk,
indexer,
lmdb_writer_sx.clone(),
field_id_map.clone(),
embedders.clone(),
)
})
.collect::<Result<()>>()
},
|| {
flattened_obkv_chunks
.par_bridge()
.map(|flattened_obkv_chunks| {
send_and_extract_flattened_documents_data(
flattened_obkv_chunks,
indexer,
lmdb_writer_sx.clone(),
&searchable_fields,
&faceted_fields,
primary_key_id,
geo_fields_ids,
&stop_words,
&allowed_separators,
&dictionary,
max_positions_per_attributes,
)
})
.map(|result| {
if let Ok((
ref docid_word_positions_chunk,
(ref fid_docid_facet_numbers_chunk, ref fid_docid_facet_strings_chunk),
)) = result
{
run_extraction_task::<_, _, grenad::Reader<BufReader<File>>>(
docid_word_positions_chunk.clone(),
indexer,
lmdb_writer_sx.clone(),
extract_fid_word_count_docids,
TypedChunk::FieldIdWordCountDocids,
"field-id-wordcount-docids",
);
let exact_attributes = exact_attributes.clone();
run_extraction_task::<
_,
_,
(
grenad::Reader<BufReader<File>>,
grenad::Reader<BufReader<File>>,
grenad::Reader<BufReader<File>>,
),
>(
docid_word_positions_chunk.clone(),
indexer,
lmdb_writer_sx.clone(),
move |doc_word_pos, indexer| {
extract_word_docids(doc_word_pos, indexer, &exact_attributes)
},
|(
word_docids_reader,
exact_word_docids_reader,
word_fid_docids_reader,
)| {
TypedChunk::WordDocids {
word_docids_reader,
exact_word_docids_reader,
word_fid_docids_reader,
}
},
"word-docids",
);
run_extraction_task::<_, _, grenad::Reader<BufReader<File>>>(
docid_word_positions_chunk.clone(),
indexer,
lmdb_writer_sx.clone(),
extract_word_position_docids,
TypedChunk::WordPositionDocids,
"word-position-docids",
);
run_extraction_task::<
_,
_,
(grenad::Reader<BufReader<File>>, grenad::Reader<BufReader<File>>),
>(
fid_docid_facet_strings_chunk.clone(),
indexer,
lmdb_writer_sx.clone(),
extract_facet_string_docids,
TypedChunk::FieldIdFacetStringDocids,
"field-id-facet-string-docids",
);
run_extraction_task::<_, _, grenad::Reader<BufReader<File>>>(
fid_docid_facet_numbers_chunk.clone(),
indexer,
lmdb_writer_sx.clone(),
extract_facet_number_docids,
TypedChunk::FieldIdFacetNumberDocids,
"field-id-facet-number-docids",
);
if proximity_precision == ProximityPrecision::ByWord {
run_extraction_task::<_, _, grenad::Reader<BufReader<File>>>(
docid_word_positions_chunk.clone(),
indexer,
lmdb_writer_sx.clone(),
extract_word_pair_proximity_docids,
TypedChunk::WordPairProximityDocids,
"word-pair-proximity-docids",
);
}
}
Ok(())
})
.collect::<Result<()>>()
},
"word-docids",
);
spawn_extraction_task::<_, _, Vec<grenad::Reader<BufReader<File>>>>(
docid_word_positions_chunks.clone(),
indexer,
lmdb_writer_sx.clone(),
extract_word_position_docids,
merge_deladd_cbo_roaring_bitmaps,
TypedChunk::WordPositionDocids,
"word-position-docids",
);
spawn_extraction_task::<_, _, Vec<grenad::Reader<BufReader<File>>>>(
fid_docid_facet_strings_chunks,
indexer,
lmdb_writer_sx.clone(),
extract_facet_string_docids,
merge_deladd_cbo_roaring_bitmaps,
TypedChunk::FieldIdFacetStringDocids,
"field-id-facet-string-docids",
);
spawn_extraction_task::<_, _, Vec<grenad::Reader<BufReader<File>>>>(
fid_docid_facet_numbers_chunks,
indexer,
lmdb_writer_sx,
extract_facet_number_docids,
merge_deladd_cbo_roaring_bitmaps,
TypedChunk::FieldIdFacetNumberDocids,
"field-id-facet-number-docids",
);
Ok(())
original_pipeline_result.and(flattened_pipeline_result)
}
/// Spawn a new task to extract data for a specific DB using extract_fn.
/// Generated grenad chunks are merged using the merge_fn.
/// The result of merged chunks is serialized as TypedChunk using the serialize_fn
/// and sent into lmdb_writer_sx.
fn spawn_extraction_task<FE, FS, M>(
chunks: Vec<grenad::Reader<CursorClonableMmap>>,
fn run_extraction_task<FE, FS, M>(
chunk: grenad::Reader<CursorClonableMmap>,
indexer: GrenadParameters,
lmdb_writer_sx: Sender<Result<TypedChunk>>,
extract_fn: FE,
merge_fn: MergeFn,
serialize_fn: FS,
name: &'static str,
) where
FE: Fn(grenad::Reader<CursorClonableMmap>, GrenadParameters) -> Result<M::Output>
FE: Fn(grenad::Reader<CursorClonableMmap>, GrenadParameters) -> Result<M>
+ Sync
+ Send
+ 'static,
FS: Fn(M::Output) -> TypedChunk + Sync + Send + 'static,
M: MergeableReader + FromParallelIterator<M::Output> + Send + 'static,
M::Output: Send,
FS: Fn(M) -> TypedChunk + Sync + Send + 'static,
M: Send,
{
let current_span = tracing::Span::current();
@ -264,25 +213,16 @@ fn spawn_extraction_task<FE, FS, M>(
let child_span =
tracing::trace_span!(target: "", parent: &current_span, "extract_multiple_chunks");
let _entered = child_span.enter();
puffin::profile_scope!("extract_multiple_chunksdexing::details, ", name);
let chunks: Result<M> =
chunks.into_par_iter().map(|chunk| extract_fn(chunk, indexer)).collect();
let current_span = tracing::Span::current();
rayon::spawn(move || match chunks {
Ok(chunks) => {
let child_span = tracing::trace_span!(target: "", parent: &current_span, "merge_multiple_chunks");
let _entered = child_span.enter();
debug!(database = name, "merge");
puffin::profile_scope!("merge_multiple_chunks", name);
let reader = chunks.merge(merge_fn, &indexer);
let _ = lmdb_writer_sx.send(reader.map(serialize_fn));
puffin::profile_scope!("extract_multiple_chunks", name);
match extract_fn(chunk, indexer) {
Ok(chunk) => {
let _ = lmdb_writer_sx.send(Ok(serialize_fn(chunk)));
}
Err(e) => {
let _ = lmdb_writer_sx.send(Err(e));
}
})
});
}
})
}
/// Extract chunked data and send it into lmdb_writer_sx sender:
@ -340,7 +280,7 @@ fn send_original_documents_data(
});
// TODO: create a custom internal error
lmdb_writer_sx.send(Ok(TypedChunk::Documents(original_documents_chunk))).unwrap();
let _ = lmdb_writer_sx.send(Ok(TypedChunk::Documents(original_documents_chunk)));
Ok(())
}
@ -360,22 +300,13 @@ fn send_and_extract_flattened_documents_data(
faceted_fields: &HashSet<FieldId>,
primary_key_id: FieldId,
geo_fields_ids: Option<(FieldId, FieldId)>,
stop_words: &Option<fst::Set<&[u8]>>,
stop_words: &Option<fst::Set<Vec<u8>>>,
allowed_separators: &Option<&[&str]>,
dictionary: &Option<&[&str]>,
max_positions_per_attributes: Option<u32>,
) -> Result<(
grenad::Reader<CursorClonableMmap>,
(
grenad::Reader<CursorClonableMmap>,
(
grenad::Reader<CursorClonableMmap>,
(
grenad::Reader<BufReader<File>>,
(grenad::Reader<BufReader<File>>, grenad::Reader<BufReader<File>>),
),
),
),
(grenad::Reader<CursorClonableMmap>, grenad::Reader<CursorClonableMmap>),
)> {
let flattened_documents_chunk =
flattened_documents_chunk.and_then(|c| unsafe { as_cloneable_grenad(&c) })?;
@ -446,16 +377,17 @@ fn send_and_extract_flattened_documents_data(
fid_docid_facet_strings_chunk.clone(),
)));
Ok((
fid_docid_facet_numbers_chunk,
(
fid_docid_facet_strings_chunk,
(
fid_facet_is_null_docids_chunk,
(fid_facet_is_empty_docids_chunk, fid_facet_exists_docids_chunk),
),
),
))
let _ = lmdb_writer_sx
.send(Ok(TypedChunk::FieldIdFacetIsNullDocids(fid_facet_is_null_docids_chunk)));
let _ = lmdb_writer_sx.send(Ok(TypedChunk::FieldIdFacetIsEmptyDocids(
fid_facet_is_empty_docids_chunk,
)));
let _ = lmdb_writer_sx
.send(Ok(TypedChunk::FieldIdFacetExistsDocids(fid_facet_exists_docids_chunk)));
Ok((fid_docid_facet_numbers_chunk, fid_docid_facet_strings_chunk))
},
);

View File

@ -90,90 +90,6 @@ pub unsafe fn as_cloneable_grenad(
Ok(reader)
}
pub trait MergeableReader
where
Self: Sized,
{
type Output;
fn merge(self, merge_fn: MergeFn, indexer: &GrenadParameters) -> Result<Self::Output>;
}
impl MergeableReader for Vec<grenad::Reader<BufReader<File>>> {
type Output = grenad::Reader<BufReader<File>>;
fn merge(self, merge_fn: MergeFn, params: &GrenadParameters) -> Result<Self::Output> {
let mut merger = MergerBuilder::new(merge_fn);
self.into_iter().try_for_each(|r| merger.push(r))?;
merger.finish(params)
}
}
impl MergeableReader for Vec<(grenad::Reader<BufReader<File>>, grenad::Reader<BufReader<File>>)> {
type Output = (grenad::Reader<BufReader<File>>, grenad::Reader<BufReader<File>>);
fn merge(self, merge_fn: MergeFn, params: &GrenadParameters) -> Result<Self::Output> {
let mut m1 = MergerBuilder::new(merge_fn);
let mut m2 = MergerBuilder::new(merge_fn);
for (r1, r2) in self.into_iter() {
m1.push(r1)?;
m2.push(r2)?;
}
Ok((m1.finish(params)?, m2.finish(params)?))
}
}
impl MergeableReader
for Vec<(
grenad::Reader<BufReader<File>>,
grenad::Reader<BufReader<File>>,
grenad::Reader<BufReader<File>>,
)>
{
type Output = (
grenad::Reader<BufReader<File>>,
grenad::Reader<BufReader<File>>,
grenad::Reader<BufReader<File>>,
);
fn merge(self, merge_fn: MergeFn, params: &GrenadParameters) -> Result<Self::Output> {
let mut m1 = MergerBuilder::new(merge_fn);
let mut m2 = MergerBuilder::new(merge_fn);
let mut m3 = MergerBuilder::new(merge_fn);
for (r1, r2, r3) in self.into_iter() {
m1.push(r1)?;
m2.push(r2)?;
m3.push(r3)?;
}
Ok((m1.finish(params)?, m2.finish(params)?, m3.finish(params)?))
}
}
struct MergerBuilder<R>(grenad::MergerBuilder<R, MergeFn>);
impl<R: io::Read + io::Seek> MergerBuilder<R> {
fn new(merge_fn: MergeFn) -> Self {
Self(grenad::MergerBuilder::new(merge_fn))
}
fn push(&mut self, reader: grenad::Reader<R>) -> Result<()> {
self.0.push(reader.into_cursor()?);
Ok(())
}
fn finish(self, params: &GrenadParameters) -> Result<grenad::Reader<BufReader<File>>> {
let merger = self.0.build();
let mut writer = create_writer(
params.chunk_compression_type,
params.chunk_compression_level,
tempfile::tempfile()?,
);
merger.write_into_stream_writer(&mut writer)?;
writer_into_reader(writer)
}
}
#[derive(Debug, Clone, Copy)]
pub struct GrenadParameters {
pub chunk_compression_type: CompressionType,

View File

@ -35,27 +35,6 @@ pub fn merge_roaring_bitmaps<'a>(_key: &[u8], values: &[Cow<'a, [u8]>]) -> Resul
}
}
pub fn merge_btreeset_string<'a>(_key: &[u8], values: &[Cow<'a, [u8]>]) -> Result<Cow<'a, [u8]>> {
if values.len() == 1 {
Ok(values[0].clone())
} else {
// TODO improve the perf by using a `#[borrow] Cow<str>`.
let strings: BTreeSet<String> = values
.iter()
.map(AsRef::as_ref)
.map(serde_json::from_slice::<BTreeSet<String>>)
.map(StdResult::unwrap)
.reduce(|mut current, new| {
for x in new {
current.insert(x);
}
current
})
.unwrap();
Ok(Cow::Owned(serde_json::to_vec(&strings).unwrap()))
}
}
pub fn keep_first<'a>(_key: &[u8], values: &[Cow<'a, [u8]>]) -> Result<Cow<'a, [u8]>> {
Ok(values[0].clone())
}
@ -243,3 +222,40 @@ pub fn merge_deladd_cbo_roaring_bitmaps_into_cbo_roaring_bitmap<'a>(
buffer,
)?)
}
/// Do a union of BtreeSet on both sides of a DelAdd obkv
/// separately and outputs a new DelAdd with both unions.
pub fn merge_deladd_btreeset_string<'a>(
_key: &[u8],
values: &[Cow<'a, [u8]>],
) -> Result<Cow<'a, [u8]>> {
if values.len() == 1 {
Ok(values[0].clone())
} else {
// Retrieve the bitmaps from both sides
let mut del_set = BTreeSet::new();
let mut add_set = BTreeSet::new();
for value in values {
let obkv = KvReaderDelAdd::new(value);
if let Some(bytes) = obkv.get(DelAdd::Deletion) {
let set = serde_json::from_slice::<BTreeSet<String>>(bytes).unwrap();
for value in set {
del_set.insert(value);
}
}
if let Some(bytes) = obkv.get(DelAdd::Addition) {
let set = serde_json::from_slice::<BTreeSet<String>>(bytes).unwrap();
for value in set {
add_set.insert(value);
}
}
}
let mut output_deladd_obkv = KvWriterDelAdd::memory();
let del = serde_json::to_vec(&del_set).unwrap();
output_deladd_obkv.insert(DelAdd::Deletion, &del)?;
let add = serde_json::to_vec(&add_set).unwrap();
output_deladd_obkv.insert(DelAdd::Addition, &add)?;
output_deladd_obkv.into_inner().map(Cow::from).map_err(Into::into)
}
}

View File

@ -10,10 +10,10 @@ use fst::{IntoStreamer, Streamer};
pub use grenad_helpers::{
as_cloneable_grenad, create_sorter, create_writer, grenad_obkv_into_chunks,
merge_ignore_values, sorter_into_reader, write_sorter_into_database, writer_into_reader,
GrenadParameters, MergeableReader,
GrenadParameters,
};
pub use merge_functions::{
keep_first, keep_latest_obkv, merge_btreeset_string, merge_cbo_roaring_bitmaps,
keep_first, keep_latest_obkv, merge_cbo_roaring_bitmaps, merge_deladd_btreeset_string,
merge_deladd_cbo_roaring_bitmaps, merge_deladd_cbo_roaring_bitmaps_into_cbo_roaring_bitmap,
merge_roaring_bitmaps, obkvs_keep_last_addition_merge_deletions,
obkvs_merge_additions_and_deletions, MergeFn,

View File

@ -5,29 +5,29 @@ mod transform;
mod typed_chunk;
use std::collections::{HashMap, HashSet};
use std::io::{Cursor, Read, Seek};
use std::io::{Read, Seek};
use std::iter::FromIterator;
use std::num::NonZeroU32;
use std::result::Result as StdResult;
use crossbeam_channel::{Receiver, Sender};
use grenad::{Merger, MergerBuilder};
use heed::types::Str;
use heed::Database;
use rand::SeedableRng;
use roaring::RoaringBitmap;
use serde::{Deserialize, Serialize};
use slice_group_by::GroupBy;
use tracing::debug_span;
use typed_chunk::{write_typed_chunk_into_index, TypedChunk};
use tracing::debug;
use typed_chunk::{write_typed_chunk_into_index, ChunkAccumulator, TypedChunk};
use self::enrich::enrich_documents_batch;
pub use self::enrich::{extract_finite_float_from_value, DocumentId};
pub use self::helpers::{
as_cloneable_grenad, create_sorter, create_writer, fst_stream_into_hashset,
fst_stream_into_vec, merge_btreeset_string, merge_cbo_roaring_bitmaps,
merge_deladd_cbo_roaring_bitmaps, merge_deladd_cbo_roaring_bitmaps_into_cbo_roaring_bitmap,
merge_roaring_bitmaps, valid_lmdb_key, write_sorter_into_database, writer_into_reader,
ClonableMmap, MergeFn,
fst_stream_into_vec, merge_cbo_roaring_bitmaps, merge_deladd_cbo_roaring_bitmaps,
merge_deladd_cbo_roaring_bitmaps_into_cbo_roaring_bitmap, merge_roaring_bitmaps,
valid_lmdb_key, write_sorter_into_database, writer_into_reader, MergeFn,
};
use self::helpers::{grenad_obkv_into_chunks, GrenadParameters};
pub use self::transform::{Transform, TransformOutput};
@ -95,8 +95,8 @@ pub struct IndexDocumentsConfig {
impl<'t, 'i, 'a, FP, FA> IndexDocuments<'t, 'i, 'a, FP, FA>
where
FP: Fn(UpdateIndexingStep) + Sync,
FA: Fn() -> bool + Sync,
FP: Fn(UpdateIndexingStep) + Sync + Send,
FA: Fn() -> bool + Sync + Send,
{
pub fn new(
wtxn: &'t mut heed::RwTxn<'i>,
@ -326,9 +326,6 @@ where
}
};
let original_documents = grenad::Reader::new(original_documents)?;
let flattened_documents = grenad::Reader::new(flattened_documents)?;
// create LMDB writer channel
let (lmdb_writer_sx, lmdb_writer_rx): (
Sender<Result<TypedChunk>>,
@ -367,11 +364,7 @@ where
let stop_words = self.index.stop_words(self.wtxn)?;
let separators = self.index.allowed_separators(self.wtxn)?;
let separators: Option<Vec<_>> =
separators.as_ref().map(|x| x.iter().map(String::as_str).collect());
let dictionary = self.index.dictionary(self.wtxn)?;
let dictionary: Option<Vec<_>> =
dictionary.as_ref().map(|x| x.iter().map(String::as_str).collect());
let exact_attributes = self.index.exact_attributes_ids(self.wtxn)?;
let proximity_precision = self.index.proximity_precision(self.wtxn)?.unwrap_or_default();
@ -381,141 +374,204 @@ where
max_memory: self.indexer_config.max_memory,
max_nb_chunks: self.indexer_config.max_nb_chunks, // default value, may be chosen.
};
let documents_chunk_size =
self.indexer_config.documents_chunk_size.unwrap_or(1024 * 1024 * 4); // 4MiB
let documents_chunk_size = match self.indexer_config.documents_chunk_size {
Some(chunk_size) => chunk_size,
None => {
let default_chunk_size = 1024 * 1024 * 4; // 4MiB
let min_chunk_size = 1024 * 512; // 512KiB
// compute the chunk size from the number of available threads and the inputed data size.
let total_size = flattened_documents.metadata().map(|m| m.len());
let current_num_threads = pool.current_num_threads();
// if we have more than 2 thread, create a number of chunk equal to 3/4 threads count
let chunk_count = if current_num_threads > 2 {
(current_num_threads * 3 / 4).max(2)
} else {
current_num_threads
};
total_size
.map_or(default_chunk_size, |size| (size as usize) / chunk_count)
.max(min_chunk_size)
}
};
let original_documents = grenad::Reader::new(original_documents)?;
let flattened_documents = grenad::Reader::new(flattened_documents)?;
let max_positions_per_attributes = self.indexer_config.max_positions_per_attributes;
let cloned_embedder = self.embedders.clone();
let mut final_documents_ids = RoaringBitmap::new();
let mut databases_seen = 0;
let mut word_position_docids = None;
let mut word_fid_docids = None;
let mut word_docids = None;
let mut exact_word_docids = None;
let mut chunk_accumulator = ChunkAccumulator::default();
let mut dimension = HashMap::new();
let stop_words = stop_words.map(|sw| sw.map_data(Vec::from).unwrap());
let current_span = tracing::Span::current();
// Run extraction pipeline in parallel.
pool.install(|| {
let child_span = tracing::trace_span!(target: "indexing::details", parent: &current_span, "extract_and_send_grenad_chunks");
rayon::spawn(move || {
let child_span = tracing::trace_span!(target: "indexing::details", parent: &current_span, "extract_and_send_grenad_chunks");
let _enter = child_span.enter();
puffin::profile_scope!("extract_and_send_grenad_chunks");
// split obkv file into several chunks
let original_chunk_iter =
grenad_obkv_into_chunks(original_documents, pool_params, documents_chunk_size);
// split obkv file into several chunks
let original_chunk_iter =
grenad_obkv_into_chunks(original_documents, pool_params, documents_chunk_size);
// split obkv file into several chunks
let flattened_chunk_iter =
grenad_obkv_into_chunks(flattened_documents, pool_params, documents_chunk_size);
// split obkv file into several chunks
let flattened_chunk_iter =
grenad_obkv_into_chunks(flattened_documents, pool_params, documents_chunk_size);
let result = original_chunk_iter.and_then(|original_chunk| {
let flattened_chunk = flattened_chunk_iter?;
// extract all databases from the chunked obkv douments
extract::data_from_obkv_documents(
original_chunk,
flattened_chunk,
pool_params,
lmdb_writer_sx.clone(),
searchable_fields,
faceted_fields,
primary_key_id,
geo_fields_ids,
field_id_map,
stop_words,
separators.as_deref(),
dictionary.as_deref(),
max_positions_per_attributes,
exact_attributes,
proximity_precision,
cloned_embedder,
)
let separators: Option<Vec<_>> =
separators.as_ref().map(|x| x.iter().map(String::as_str).collect());
let dictionary: Option<Vec<_>> =
dictionary.as_ref().map(|x| x.iter().map(String::as_str).collect());
let result = original_chunk_iter.and_then(|original_chunk| {
let flattened_chunk = flattened_chunk_iter?;
// extract all databases from the chunked obkv douments
extract::data_from_obkv_documents(
original_chunk,
flattened_chunk,
pool_params,
lmdb_writer_sx.clone(),
searchable_fields,
faceted_fields,
primary_key_id,
geo_fields_ids,
field_id_map,
stop_words,
separators.as_deref(),
dictionary.as_deref(),
max_positions_per_attributes,
exact_attributes,
proximity_precision,
cloned_embedder,
)
});
if let Err(e) = result {
let _ = lmdb_writer_sx.send(Err(e));
}
// needs to be dropped to avoid channel waiting lock.
drop(lmdb_writer_sx);
});
if let Err(e) = result {
let _ = lmdb_writer_sx.send(Err(e));
}
(self.progress)(UpdateIndexingStep::MergeDataIntoFinalDatabase {
databases_seen,
total_databases: TOTAL_POSTING_DATABASE_COUNT,
});
// needs to be dropped to avoid channel waiting lock.
drop(lmdb_writer_sx);
});
loop {
if (self.should_abort)() {
return Err(Error::InternalError(InternalError::AbortedIndexation));
}
let index_is_empty = self.index.number_of_documents(self.wtxn)? == 0;
let mut final_documents_ids = RoaringBitmap::new();
match lmdb_writer_rx.clone().recv_timeout(std::time::Duration::from_millis(500)) {
Err(status) => {
if let Some(typed_chunks) = chunk_accumulator.pop_longest() {
let (docids, is_merged_database) =
write_typed_chunk_into_index(typed_chunks, self.index, self.wtxn)?;
if !docids.is_empty() {
final_documents_ids |= docids;
let documents_seen_count = final_documents_ids.len();
(self.progress)(UpdateIndexingStep::IndexDocuments {
documents_seen: documents_seen_count as usize,
total_documents: documents_count,
});
debug!(documents = documents_seen_count, total = documents_count, "Seen");
}
if is_merged_database {
databases_seen += 1;
(self.progress)(UpdateIndexingStep::MergeDataIntoFinalDatabase {
databases_seen,
total_databases: TOTAL_POSTING_DATABASE_COUNT,
});
}
// If no more chunk remains in the chunk accumulator and the channel is disconected, break.
} else if status == crossbeam_channel::RecvTimeoutError::Disconnected {
break;
} else {
rayon::yield_now();
}
}
Ok(result) => {
let typed_chunk = match result? {
TypedChunk::WordDocids {
word_docids_reader,
exact_word_docids_reader,
word_fid_docids_reader,
} => {
let cloneable_chunk =
unsafe { as_cloneable_grenad(&word_docids_reader)? };
let word_docids = word_docids.get_or_insert_with(|| {
MergerBuilder::new(merge_deladd_cbo_roaring_bitmaps as MergeFn)
});
word_docids.push(cloneable_chunk.into_cursor()?);
let cloneable_chunk =
unsafe { as_cloneable_grenad(&exact_word_docids_reader)? };
let exact_word_docids =
exact_word_docids.get_or_insert_with(|| {
MergerBuilder::new(
merge_deladd_cbo_roaring_bitmaps as MergeFn,
)
});
exact_word_docids.push(cloneable_chunk.into_cursor()?);
let cloneable_chunk =
unsafe { as_cloneable_grenad(&word_fid_docids_reader)? };
let word_fid_docids = word_fid_docids.get_or_insert_with(|| {
MergerBuilder::new(merge_deladd_cbo_roaring_bitmaps as MergeFn)
});
word_fid_docids.push(cloneable_chunk.into_cursor()?);
TypedChunk::WordDocids {
word_docids_reader,
exact_word_docids_reader,
word_fid_docids_reader,
}
}
TypedChunk::WordPositionDocids(chunk) => {
let cloneable_chunk = unsafe { as_cloneable_grenad(&chunk)? };
let word_position_docids =
word_position_docids.get_or_insert_with(|| {
MergerBuilder::new(
merge_deladd_cbo_roaring_bitmaps as MergeFn,
)
});
word_position_docids.push(cloneable_chunk.into_cursor()?);
TypedChunk::WordPositionDocids(chunk)
}
TypedChunk::VectorPoints {
expected_dimension,
remove_vectors,
embeddings,
manual_vectors,
embedder_name,
} => {
dimension.insert(embedder_name.clone(), expected_dimension);
TypedChunk::VectorPoints {
remove_vectors,
embeddings,
expected_dimension,
manual_vectors,
embedder_name,
}
}
otherwise => otherwise,
};
let mut databases_seen = 0;
(self.progress)(UpdateIndexingStep::MergeDataIntoFinalDatabase {
databases_seen,
total_databases: TOTAL_POSTING_DATABASE_COUNT,
});
let mut word_position_docids = None;
let mut word_fid_docids = None;
let mut word_docids = None;
let mut exact_word_docids = None;
let mut dimension = HashMap::new();
for result in lmdb_writer_rx {
if (self.should_abort)() {
return Err(Error::InternalError(InternalError::AbortedIndexation));
}
let typed_chunk = match result? {
TypedChunk::WordDocids {
word_docids_reader,
exact_word_docids_reader,
word_fid_docids_reader,
} => {
let cloneable_chunk = unsafe { as_cloneable_grenad(&word_docids_reader)? };
word_docids = Some(cloneable_chunk);
let cloneable_chunk =
unsafe { as_cloneable_grenad(&exact_word_docids_reader)? };
exact_word_docids = Some(cloneable_chunk);
let cloneable_chunk = unsafe { as_cloneable_grenad(&word_fid_docids_reader)? };
word_fid_docids = Some(cloneable_chunk);
TypedChunk::WordDocids {
word_docids_reader,
exact_word_docids_reader,
word_fid_docids_reader,
chunk_accumulator.insert(typed_chunk);
}
}
TypedChunk::WordPositionDocids(chunk) => {
let cloneable_chunk = unsafe { as_cloneable_grenad(&chunk)? };
word_position_docids = Some(cloneable_chunk);
TypedChunk::WordPositionDocids(chunk)
}
TypedChunk::VectorPoints {
expected_dimension,
remove_vectors,
embeddings,
manual_vectors,
embedder_name,
} => {
dimension.insert(embedder_name.clone(), expected_dimension);
TypedChunk::VectorPoints {
remove_vectors,
embeddings,
expected_dimension,
manual_vectors,
embedder_name,
}
}
otherwise => otherwise,
};
}
let (docids, is_merged_database) =
write_typed_chunk_into_index(typed_chunk, self.index, self.wtxn, index_is_empty)?;
if !docids.is_empty() {
final_documents_ids |= docids;
let documents_seen_count = final_documents_ids.len();
(self.progress)(UpdateIndexingStep::IndexDocuments {
documents_seen: documents_seen_count as usize,
total_documents: documents_count,
});
debug_span!("Seen", documents = documents_seen_count, total = documents_count);
}
if is_merged_database {
databases_seen += 1;
(self.progress)(UpdateIndexingStep::MergeDataIntoFinalDatabase {
databases_seen,
total_databases: TOTAL_POSTING_DATABASE_COUNT,
});
}
}
Ok(())
})?;
// We write the field distribution into the main database
self.index.put_field_distribution(self.wtxn, &field_distribution)?;
@ -548,10 +604,10 @@ where
}
self.execute_prefix_databases(
word_docids,
exact_word_docids,
word_position_docids,
word_fid_docids,
word_docids.map(MergerBuilder::build),
exact_word_docids.map(MergerBuilder::build),
word_position_docids.map(MergerBuilder::build),
word_fid_docids.map(MergerBuilder::build),
)?;
Ok(number_of_documents)
@ -565,10 +621,10 @@ where
)]
pub fn execute_prefix_databases(
self,
word_docids: Option<grenad::Reader<CursorClonableMmap>>,
exact_word_docids: Option<grenad::Reader<CursorClonableMmap>>,
word_position_docids: Option<grenad::Reader<CursorClonableMmap>>,
word_fid_docids: Option<grenad::Reader<CursorClonableMmap>>,
word_docids: Option<Merger<CursorClonableMmap, MergeFn>>,
exact_word_docids: Option<Merger<CursorClonableMmap, MergeFn>>,
word_position_docids: Option<Merger<CursorClonableMmap, MergeFn>>,
word_fid_docids: Option<Merger<CursorClonableMmap, MergeFn>>,
) -> Result<()>
where
FP: Fn(UpdateIndexingStep) + Sync,
@ -751,7 +807,7 @@ where
)]
fn execute_word_prefix_docids(
txn: &mut heed::RwTxn,
reader: grenad::Reader<Cursor<ClonableMmap>>,
merger: Merger<CursorClonableMmap, MergeFn>,
word_docids_db: Database<Str, CboRoaringBitmapCodec>,
word_prefix_docids_db: Database<Str, CboRoaringBitmapCodec>,
indexer_config: &IndexerConfig,
@ -761,13 +817,12 @@ fn execute_word_prefix_docids(
) -> Result<()> {
puffin::profile_function!();
let cursor = reader.into_cursor()?;
let mut builder = WordPrefixDocids::new(txn, word_docids_db, word_prefix_docids_db);
builder.chunk_compression_type = indexer_config.chunk_compression_type;
builder.chunk_compression_level = indexer_config.chunk_compression_level;
builder.max_nb_chunks = indexer_config.max_nb_chunks;
builder.max_memory = indexer_config.max_memory;
builder.execute(cursor, new_prefix_fst_words, common_prefix_fst_words, del_prefix_fst_words)?;
builder.execute(merger, new_prefix_fst_words, common_prefix_fst_words, del_prefix_fst_words)?;
Ok(())
}

View File

@ -5,27 +5,64 @@ use std::io::{self, BufReader};
use bytemuck::allocation::pod_collect_to_vec;
use charabia::{Language, Script};
use grenad::MergerBuilder;
use grenad::{Merger, MergerBuilder};
use heed::types::Bytes;
use heed::{PutFlags, RwTxn};
use heed::RwTxn;
use obkv::{KvReader, KvWriter};
use roaring::RoaringBitmap;
use super::helpers::{
self, merge_deladd_cbo_roaring_bitmaps_into_cbo_roaring_bitmap, merge_ignore_values,
valid_lmdb_key, CursorClonableMmap,
self, keep_first, merge_deladd_btreeset_string, merge_deladd_cbo_roaring_bitmaps,
merge_deladd_cbo_roaring_bitmaps_into_cbo_roaring_bitmap, merge_ignore_values, valid_lmdb_key,
CursorClonableMmap,
};
use super::{ClonableMmap, MergeFn};
use super::MergeFn;
use crate::external_documents_ids::{DocumentOperation, DocumentOperationKind};
use crate::facet::FacetType;
use crate::index::db_name::DOCUMENTS;
use crate::update::del_add::{deladd_serialize_add_side, DelAdd, KvReaderDelAdd};
use crate::update::facet::FacetsUpdate;
use crate::update::index_documents::helpers::{as_cloneable_grenad, try_split_array_at};
use crate::update::index_documents::helpers::{
as_cloneable_grenad, keep_latest_obkv, try_split_array_at,
};
use crate::{
lat_lng_to_xyz, DocumentId, FieldId, GeoPoint, Index, InternalError, Result, SerializationError,
};
/// This struct accumulates and group the TypedChunks
/// and is able to give the biggest accumulated group to index them all together
/// with a merger.
#[derive(Default)]
pub(crate) struct ChunkAccumulator {
inner: Vec<Vec<TypedChunk>>,
}
impl ChunkAccumulator {
pub fn pop_longest(&mut self) -> Option<Vec<TypedChunk>> {
match self.inner.iter().max_by_key(|v| v.len()) {
Some(left) => {
let position = self.inner.iter().position(|right| left.len() == right.len());
position.map(|p| self.inner.remove(p)).filter(|v| !v.is_empty())
}
None => None,
}
}
pub fn insert(&mut self, chunk: TypedChunk) {
match self
.inner
.iter()
.position(|right| right.first().map_or(false, |right| chunk.mergeable_with(right)))
{
Some(position) => {
let v = self.inner.get_mut(position).unwrap();
v.push(chunk);
}
None => self.inner.push(vec![chunk]),
}
}
}
pub(crate) enum TypedChunk {
FieldIdDocidFacetStrings(grenad::Reader<CursorClonableMmap>),
FieldIdDocidFacetNumbers(grenad::Reader<CursorClonableMmap>),
@ -38,7 +75,7 @@ pub(crate) enum TypedChunk {
},
WordPositionDocids(grenad::Reader<BufReader<File>>),
WordPairProximityDocids(grenad::Reader<BufReader<File>>),
FieldIdFacetStringDocids(grenad::Reader<BufReader<File>>),
FieldIdFacetStringDocids((grenad::Reader<BufReader<File>>, grenad::Reader<BufReader<File>>)),
FieldIdFacetNumberDocids(grenad::Reader<BufReader<File>>),
FieldIdFacetExistsDocids(grenad::Reader<BufReader<File>>),
FieldIdFacetIsNullDocids(grenad::Reader<BufReader<File>>),
@ -54,6 +91,33 @@ pub(crate) enum TypedChunk {
ScriptLanguageDocids(HashMap<(Script, Language), (RoaringBitmap, RoaringBitmap)>),
}
impl TypedChunk {
fn mergeable_with(&self, other: &Self) -> bool {
use TypedChunk::*;
match (self, other) {
(FieldIdDocidFacetStrings(_), FieldIdDocidFacetStrings(_))
| (FieldIdDocidFacetNumbers(_), FieldIdDocidFacetNumbers(_))
| (Documents(_), Documents(_))
| (FieldIdWordCountDocids(_), FieldIdWordCountDocids(_))
| (WordDocids { .. }, WordDocids { .. })
| (WordPositionDocids(_), WordPositionDocids(_))
| (WordPairProximityDocids(_), WordPairProximityDocids(_))
| (FieldIdFacetStringDocids(_), FieldIdFacetStringDocids(_))
| (FieldIdFacetNumberDocids(_), FieldIdFacetNumberDocids(_))
| (FieldIdFacetExistsDocids(_), FieldIdFacetExistsDocids(_))
| (FieldIdFacetIsNullDocids(_), FieldIdFacetIsNullDocids(_))
| (FieldIdFacetIsEmptyDocids(_), FieldIdFacetIsEmptyDocids(_))
| (GeoPoints(_), GeoPoints(_))
| (ScriptLanguageDocids(_), ScriptLanguageDocids(_)) => true,
(
VectorPoints { embedder_name: left, expected_dimension: left_dim, .. },
VectorPoints { embedder_name: right, expected_dimension: right_dim, .. },
) => left == right && left_dim == right_dim,
_ => false,
}
}
}
impl TypedChunk {
pub fn to_debug_string(&self) -> String {
match self {
@ -85,7 +149,7 @@ impl TypedChunk {
TypedChunk::WordPairProximityDocids(grenad) => {
format!("WordPairProximityDocids {{ number_of_entries: {} }}", grenad.len())
}
TypedChunk::FieldIdFacetStringDocids(grenad) => {
TypedChunk::FieldIdFacetStringDocids((grenad, _)) => {
format!("FieldIdFacetStringDocids {{ number_of_entries: {} }}", grenad.len())
}
TypedChunk::FieldIdFacetNumberDocids(grenad) => {
@ -117,23 +181,32 @@ impl TypedChunk {
/// Return new documents seen.
#[tracing::instrument(level = "trace", skip_all, target = "indexing::write_db")]
pub(crate) fn write_typed_chunk_into_index(
typed_chunk: TypedChunk,
typed_chunks: Vec<TypedChunk>,
index: &Index,
wtxn: &mut RwTxn,
index_is_empty: bool,
) -> Result<(RoaringBitmap, bool)> {
puffin::profile_function!(typed_chunk.to_debug_string());
puffin::profile_function!(typed_chunks[0].to_debug_string());
let mut is_merged_database = false;
match typed_chunk {
TypedChunk::Documents(obkv_documents_iter) => {
match typed_chunks[0] {
TypedChunk::Documents(_) => {
let span = tracing::trace_span!(target: "indexing::write_db", "documents");
let _entered = span.enter();
let mut builder = MergerBuilder::new(keep_latest_obkv as MergeFn);
for typed_chunk in typed_chunks {
let TypedChunk::Documents(chunk) = typed_chunk else {
unreachable!();
};
builder.push(chunk.into_cursor()?);
}
let merger = builder.build();
let mut operations: Vec<DocumentOperation> = Default::default();
let mut docids = index.documents_ids(wtxn)?;
let mut cursor = obkv_documents_iter.into_cursor()?;
while let Some((key, reader)) = cursor.move_on_next()? {
let mut iter = merger.into_stream_merger_iter()?;
while let Some((key, reader)) = iter.next()? {
let mut writer: KvWriter<_, FieldId> = KvWriter::memory();
let reader: KvReader<FieldId> = KvReader::new(reader);
@ -174,59 +247,91 @@ pub(crate) fn write_typed_chunk_into_index(
external_documents_docids.apply(wtxn, operations)?;
index.put_documents_ids(wtxn, &docids)?;
}
TypedChunk::FieldIdWordCountDocids(fid_word_count_docids_iter) => {
TypedChunk::FieldIdWordCountDocids(_) => {
let span =
tracing::trace_span!(target: "indexing::write_db", "field_id_word_count_docids");
let _entered = span.enter();
append_entries_into_database(
fid_word_count_docids_iter,
let mut builder = MergerBuilder::new(merge_deladd_cbo_roaring_bitmaps as MergeFn);
for typed_chunk in typed_chunks {
let TypedChunk::FieldIdWordCountDocids(chunk) = typed_chunk else {
unreachable!();
};
builder.push(chunk.into_cursor()?);
}
let merger = builder.build();
write_entries_into_database(
merger,
&index.field_id_word_count_docids,
wtxn,
index_is_empty,
deladd_serialize_add_side,
merge_deladd_cbo_roaring_bitmaps_into_cbo_roaring_bitmap,
)?;
is_merged_database = true;
}
TypedChunk::WordDocids {
word_docids_reader,
exact_word_docids_reader,
word_fid_docids_reader,
} => {
TypedChunk::WordDocids { .. } => {
let span = tracing::trace_span!(target: "indexing::write_db", "word_docids");
let _entered = span.enter();
let word_docids_iter = unsafe { as_cloneable_grenad(&word_docids_reader) }?;
append_entries_into_database(
word_docids_iter.clone(),
let mut word_docids_builder =
MergerBuilder::new(merge_deladd_cbo_roaring_bitmaps as MergeFn);
let mut exact_word_docids_builder =
MergerBuilder::new(merge_deladd_cbo_roaring_bitmaps as MergeFn);
let mut word_fid_docids_builder =
MergerBuilder::new(merge_deladd_cbo_roaring_bitmaps as MergeFn);
let mut fst_merger_builder = MergerBuilder::new(merge_ignore_values as MergeFn);
for typed_chunk in typed_chunks {
let TypedChunk::WordDocids {
word_docids_reader,
exact_word_docids_reader,
word_fid_docids_reader,
} = typed_chunk
else {
unreachable!();
};
let clonable_word_docids = unsafe { as_cloneable_grenad(&word_docids_reader) }?;
let clonable_exact_word_docids =
unsafe { as_cloneable_grenad(&exact_word_docids_reader) }?;
word_docids_builder.push(word_docids_reader.into_cursor()?);
exact_word_docids_builder.push(exact_word_docids_reader.into_cursor()?);
word_fid_docids_builder.push(word_fid_docids_reader.into_cursor()?);
fst_merger_builder.push(clonable_word_docids.into_cursor()?);
fst_merger_builder.push(clonable_exact_word_docids.into_cursor()?);
}
let word_docids_merger = word_docids_builder.build();
write_entries_into_database(
word_docids_merger,
&index.word_docids,
wtxn,
index_is_empty,
deladd_serialize_add_side,
merge_deladd_cbo_roaring_bitmaps_into_cbo_roaring_bitmap,
)?;
let exact_word_docids_iter = unsafe { as_cloneable_grenad(&exact_word_docids_reader) }?;
append_entries_into_database(
exact_word_docids_iter.clone(),
let exact_word_docids_merger = exact_word_docids_builder.build();
write_entries_into_database(
exact_word_docids_merger,
&index.exact_word_docids,
wtxn,
index_is_empty,
deladd_serialize_add_side,
merge_deladd_cbo_roaring_bitmaps_into_cbo_roaring_bitmap,
)?;
let word_fid_docids_iter = unsafe { as_cloneable_grenad(&word_fid_docids_reader) }?;
append_entries_into_database(
word_fid_docids_iter,
let word_fid_docids_merger = word_fid_docids_builder.build();
write_entries_into_database(
word_fid_docids_merger,
&index.word_fid_docids,
wtxn,
index_is_empty,
deladd_serialize_add_side,
merge_deladd_cbo_roaring_bitmaps_into_cbo_roaring_bitmap,
)?;
// create fst from word docids
let fst = merge_word_docids_reader_into_fst(word_docids_iter, exact_word_docids_iter)?;
let fst_merger = fst_merger_builder.build();
let fst = merge_word_docids_reader_into_fst(fst_merger)?;
let db_fst = index.words_fst(wtxn)?;
// merge new fst with database fst
@ -237,98 +342,202 @@ pub(crate) fn write_typed_chunk_into_index(
index.put_words_fst(wtxn, &fst)?;
is_merged_database = true;
}
TypedChunk::WordPositionDocids(word_position_docids_iter) => {
TypedChunk::WordPositionDocids(_) => {
let span = tracing::trace_span!(target: "indexing::write_db", "word_position_docids");
let _entered = span.enter();
append_entries_into_database(
word_position_docids_iter,
let mut builder = MergerBuilder::new(merge_deladd_cbo_roaring_bitmaps as MergeFn);
for typed_chunk in typed_chunks {
let TypedChunk::WordPositionDocids(chunk) = typed_chunk else {
unreachable!();
};
builder.push(chunk.into_cursor()?);
}
let merger = builder.build();
write_entries_into_database(
merger,
&index.word_position_docids,
wtxn,
index_is_empty,
deladd_serialize_add_side,
merge_deladd_cbo_roaring_bitmaps_into_cbo_roaring_bitmap,
)?;
is_merged_database = true;
}
TypedChunk::FieldIdFacetNumberDocids(facet_id_number_docids_iter) => {
TypedChunk::FieldIdFacetNumberDocids(_) => {
let span =
tracing::trace_span!(target: "indexing::write_db","field_id_facet_number_docids");
let _entered = span.enter();
let indexer = FacetsUpdate::new(index, FacetType::Number, facet_id_number_docids_iter);
let mut builder = MergerBuilder::new(merge_deladd_cbo_roaring_bitmaps as MergeFn);
let mut data_size = 0;
for typed_chunk in typed_chunks {
let TypedChunk::FieldIdFacetNumberDocids(facet_id_number_docids) = typed_chunk
else {
unreachable!();
};
data_size += facet_id_number_docids.len();
builder.push(facet_id_number_docids.into_cursor()?);
}
let merger = builder.build();
let indexer = FacetsUpdate::new(index, FacetType::Number, merger, None, data_size);
indexer.execute(wtxn)?;
is_merged_database = true;
}
TypedChunk::FieldIdFacetStringDocids(facet_id_string_docids_iter) => {
TypedChunk::FieldIdFacetStringDocids(_) => {
let span =
tracing::trace_span!(target: "indexing::write_db", "field_id_facet_string_docids");
let _entered = span.enter();
let indexer = FacetsUpdate::new(index, FacetType::String, facet_id_string_docids_iter);
let mut facet_id_string_builder =
MergerBuilder::new(merge_deladd_cbo_roaring_bitmaps as MergeFn);
let mut normalized_facet_id_string_builder =
MergerBuilder::new(merge_deladd_btreeset_string as MergeFn);
let mut data_size = 0;
for typed_chunk in typed_chunks {
let TypedChunk::FieldIdFacetStringDocids((
facet_id_string_docids,
normalized_facet_id_string_docids,
)) = typed_chunk
else {
unreachable!();
};
data_size += facet_id_string_docids.len();
facet_id_string_builder.push(facet_id_string_docids.into_cursor()?);
normalized_facet_id_string_builder
.push(normalized_facet_id_string_docids.into_cursor()?);
}
let facet_id_string_merger = facet_id_string_builder.build();
let normalized_facet_id_string_merger = normalized_facet_id_string_builder.build();
let indexer = FacetsUpdate::new(
index,
FacetType::String,
facet_id_string_merger,
Some(normalized_facet_id_string_merger),
data_size,
);
indexer.execute(wtxn)?;
is_merged_database = true;
}
TypedChunk::FieldIdFacetExistsDocids(facet_id_exists_docids) => {
TypedChunk::FieldIdFacetExistsDocids(_) => {
let span =
tracing::trace_span!(target: "indexing::write_db", "field_id_facet_exists_docids");
let _entered = span.enter();
append_entries_into_database(
facet_id_exists_docids,
let mut builder = MergerBuilder::new(merge_deladd_cbo_roaring_bitmaps as MergeFn);
for typed_chunk in typed_chunks {
let TypedChunk::FieldIdFacetExistsDocids(chunk) = typed_chunk else {
unreachable!();
};
builder.push(chunk.into_cursor()?);
}
let merger = builder.build();
write_entries_into_database(
merger,
&index.facet_id_exists_docids,
wtxn,
index_is_empty,
deladd_serialize_add_side,
merge_deladd_cbo_roaring_bitmaps_into_cbo_roaring_bitmap,
)?;
is_merged_database = true;
}
TypedChunk::FieldIdFacetIsNullDocids(facet_id_is_null_docids) => {
TypedChunk::FieldIdFacetIsNullDocids(_) => {
let span =
tracing::trace_span!(target: "indexing::write_db", "field_id_facet_is_null_docids");
let _entered = span.enter();
append_entries_into_database(
facet_id_is_null_docids,
let mut builder = MergerBuilder::new(merge_deladd_cbo_roaring_bitmaps as MergeFn);
for typed_chunk in typed_chunks {
let TypedChunk::FieldIdFacetIsNullDocids(chunk) = typed_chunk else {
unreachable!();
};
builder.push(chunk.into_cursor()?);
}
let merger = builder.build();
write_entries_into_database(
merger,
&index.facet_id_is_null_docids,
wtxn,
index_is_empty,
deladd_serialize_add_side,
merge_deladd_cbo_roaring_bitmaps_into_cbo_roaring_bitmap,
)?;
is_merged_database = true;
}
TypedChunk::FieldIdFacetIsEmptyDocids(facet_id_is_empty_docids) => {
TypedChunk::FieldIdFacetIsEmptyDocids(_) => {
let span = tracing::trace_span!(target: "profile::indexing::write_db", "field_id_facet_is_empty_docids");
let _entered = span.enter();
append_entries_into_database(
facet_id_is_empty_docids,
let mut builder = MergerBuilder::new(merge_deladd_cbo_roaring_bitmaps as MergeFn);
for typed_chunk in typed_chunks {
let TypedChunk::FieldIdFacetIsEmptyDocids(chunk) = typed_chunk else {
unreachable!();
};
builder.push(chunk.into_cursor()?);
}
let merger = builder.build();
write_entries_into_database(
merger,
&index.facet_id_is_empty_docids,
wtxn,
index_is_empty,
deladd_serialize_add_side,
merge_deladd_cbo_roaring_bitmaps_into_cbo_roaring_bitmap,
)?;
is_merged_database = true;
}
TypedChunk::WordPairProximityDocids(word_pair_proximity_docids_iter) => {
TypedChunk::WordPairProximityDocids(_) => {
let span =
tracing::trace_span!(target: "indexing::write_db", "word_pair_proximity_docids");
let _entered = span.enter();
append_entries_into_database(
word_pair_proximity_docids_iter,
let mut builder = MergerBuilder::new(merge_deladd_cbo_roaring_bitmaps as MergeFn);
for typed_chunk in typed_chunks {
let TypedChunk::WordPairProximityDocids(chunk) = typed_chunk else {
unreachable!();
};
builder.push(chunk.into_cursor()?);
}
let merger = builder.build();
write_entries_into_database(
merger,
&index.word_pair_proximity_docids,
wtxn,
index_is_empty,
deladd_serialize_add_side,
merge_deladd_cbo_roaring_bitmaps_into_cbo_roaring_bitmap,
)?;
is_merged_database = true;
}
TypedChunk::FieldIdDocidFacetNumbers(fid_docid_facet_number) => {
TypedChunk::FieldIdDocidFacetNumbers(_) => {
let span =
tracing::trace_span!(target: "indexing::write_db", "field_id_docid_facet_numbers");
let _entered = span.enter();
let mut builder = MergerBuilder::new(keep_first as MergeFn);
for typed_chunk in typed_chunks {
let TypedChunk::FieldIdDocidFacetNumbers(chunk) = typed_chunk else {
unreachable!();
};
builder.push(chunk.into_cursor()?);
}
let merger = builder.build();
let index_fid_docid_facet_numbers =
index.field_id_docid_facet_f64s.remap_types::<Bytes, Bytes>();
let mut cursor = fid_docid_facet_number.into_cursor()?;
while let Some((key, value)) = cursor.move_on_next()? {
let mut iter = merger.into_stream_merger_iter()?;
while let Some((key, value)) = iter.next()? {
let reader = KvReaderDelAdd::new(value);
if valid_lmdb_key(key) {
match (reader.get(DelAdd::Deletion), reader.get(DelAdd::Addition)) {
@ -344,14 +553,25 @@ pub(crate) fn write_typed_chunk_into_index(
}
}
}
TypedChunk::FieldIdDocidFacetStrings(fid_docid_facet_string) => {
TypedChunk::FieldIdDocidFacetStrings(_) => {
let span =
tracing::trace_span!(target: "indexing::write_db", "field_id_docid_facet_strings");
let _entered = span.enter();
let mut builder = MergerBuilder::new(keep_first as MergeFn);
for typed_chunk in typed_chunks {
let TypedChunk::FieldIdDocidFacetStrings(chunk) = typed_chunk else {
unreachable!();
};
builder.push(chunk.into_cursor()?);
}
let merger = builder.build();
let index_fid_docid_facet_strings =
index.field_id_docid_facet_strings.remap_types::<Bytes, Bytes>();
let mut cursor = fid_docid_facet_string.into_cursor()?;
while let Some((key, value)) = cursor.move_on_next()? {
let mut iter = merger.into_stream_merger_iter()?;
while let Some((key, value)) = iter.next()? {
let reader = KvReaderDelAdd::new(value);
if valid_lmdb_key(key) {
match (reader.get(DelAdd::Deletion), reader.get(DelAdd::Addition)) {
@ -367,14 +587,25 @@ pub(crate) fn write_typed_chunk_into_index(
}
}
}
TypedChunk::GeoPoints(geo_points) => {
TypedChunk::GeoPoints(_) => {
let span = tracing::trace_span!(target: "indexing::write_db", "geo_points");
let _entered = span.enter();
let mut builder = MergerBuilder::new(keep_first as MergeFn);
for typed_chunk in typed_chunks {
let TypedChunk::GeoPoints(chunk) = typed_chunk else {
unreachable!();
};
builder.push(chunk.into_cursor()?);
}
let merger = builder.build();
let mut rtree = index.geo_rtree(wtxn)?.unwrap_or_default();
let mut geo_faceted_docids = index.geo_faceted_documents_ids(wtxn)?;
let mut cursor = geo_points.into_cursor()?;
while let Some((key, value)) = cursor.move_on_next()? {
let mut iter = merger.into_stream_merger_iter()?;
while let Some((key, value)) = iter.next()? {
// convert the key back to a u32 (4 bytes)
let docid = key.try_into().map(DocumentId::from_be_bytes).unwrap();
@ -393,15 +624,38 @@ pub(crate) fn write_typed_chunk_into_index(
index.put_geo_rtree(wtxn, &rtree)?;
index.put_geo_faceted_documents_ids(wtxn, &geo_faceted_docids)?;
}
TypedChunk::VectorPoints {
remove_vectors,
manual_vectors,
embeddings,
expected_dimension,
embedder_name,
} => {
TypedChunk::VectorPoints { .. } => {
let span = tracing::trace_span!(target: "indexing::write_db", "vector_points");
let _entered = span.enter();
let mut remove_vectors_builder = MergerBuilder::new(keep_first as MergeFn);
let mut manual_vectors_builder = MergerBuilder::new(keep_first as MergeFn);
let mut embeddings_builder = MergerBuilder::new(keep_first as MergeFn);
let mut params = None;
for typed_chunk in typed_chunks {
let TypedChunk::VectorPoints {
remove_vectors,
manual_vectors,
embeddings,
expected_dimension,
embedder_name,
} = typed_chunk
else {
unreachable!();
};
params = Some((expected_dimension, embedder_name));
remove_vectors_builder.push(remove_vectors.into_cursor()?);
manual_vectors_builder.push(manual_vectors.into_cursor()?);
if let Some(embeddings) = embeddings {
embeddings_builder.push(embeddings.into_cursor()?);
}
}
// typed chunks has always at least 1 chunk.
let Some((expected_dimension, embedder_name)) = params else { unreachable!() };
let embedder_index = index.embedder_category_id.get(wtxn, &embedder_name)?.ok_or(
InternalError::DatabaseMissingEntry { db_name: "embedder_category_id", key: None },
)?;
@ -419,8 +673,9 @@ pub(crate) fn write_typed_chunk_into_index(
let writers = writers?;
// remove vectors for docids we want them removed
let mut cursor = remove_vectors.into_cursor()?;
while let Some((key, _)) = cursor.move_on_next()? {
let merger = remove_vectors_builder.build();
let mut iter = merger.into_stream_merger_iter()?;
while let Some((key, _)) = iter.next()? {
let docid = key.try_into().map(DocumentId::from_be_bytes).unwrap();
for writer in &writers {
@ -432,40 +687,39 @@ pub(crate) fn write_typed_chunk_into_index(
}
// add generated embeddings
if let Some(embeddings) = embeddings {
let mut cursor = embeddings.into_cursor()?;
while let Some((key, value)) = cursor.move_on_next()? {
let docid = key.try_into().map(DocumentId::from_be_bytes).unwrap();
let data = pod_collect_to_vec(value);
// it is a code error to have embeddings and not expected_dimension
let embeddings =
crate::vector::Embeddings::from_inner(data, expected_dimension)
// code error if we somehow got the wrong dimension
.unwrap();
let merger = embeddings_builder.build();
let mut iter = merger.into_stream_merger_iter()?;
while let Some((key, value)) = iter.next()? {
let docid = key.try_into().map(DocumentId::from_be_bytes).unwrap();
let data = pod_collect_to_vec(value);
// it is a code error to have embeddings and not expected_dimension
let embeddings = crate::vector::Embeddings::from_inner(data, expected_dimension)
// code error if we somehow got the wrong dimension
.unwrap();
if embeddings.embedding_count() > usize::from(u8::MAX) {
let external_docid = if let Ok(Some(Ok(index))) = index
.external_id_of(wtxn, std::iter::once(docid))
.map(|it| it.into_iter().next())
{
index
} else {
format!("internal docid={docid}")
};
return Err(crate::Error::UserError(crate::UserError::TooManyVectors(
external_docid,
embeddings.embedding_count(),
)));
}
for (embedding, writer) in embeddings.iter().zip(&writers) {
writer.add_item(wtxn, docid, embedding)?;
}
if embeddings.embedding_count() > usize::from(u8::MAX) {
let external_docid = if let Ok(Some(Ok(index))) = index
.external_id_of(wtxn, std::iter::once(docid))
.map(|it| it.into_iter().next())
{
index
} else {
format!("internal docid={docid}")
};
return Err(crate::Error::UserError(crate::UserError::TooManyVectors(
external_docid,
embeddings.embedding_count(),
)));
}
for (embedding, writer) in embeddings.iter().zip(&writers) {
writer.add_item(wtxn, docid, embedding)?;
}
}
// perform the manual diff
let mut cursor = manual_vectors.into_cursor()?;
while let Some((key, value)) = cursor.move_on_next()? {
let merger = manual_vectors_builder.build();
let mut iter = merger.into_stream_merger_iter()?;
while let Some((key, value)) = iter.next()? {
// convert the key back to a u32 (4 bytes)
let (left, _index) = try_split_array_at(key).unwrap();
let docid = DocumentId::from_be_bytes(left);
@ -519,26 +773,30 @@ pub(crate) fn write_typed_chunk_into_index(
tracing::debug!("Finished vector chunk for {}", embedder_name);
}
TypedChunk::ScriptLanguageDocids(sl_map) => {
TypedChunk::ScriptLanguageDocids(_) => {
let span = tracing::trace_span!(target: "indexing::write_db", "script_language_docids");
let _entered = span.enter();
for (key, (deletion, addition)) in sl_map {
let mut db_key_exists = false;
let final_value = match index.script_language_docids.get(wtxn, &key)? {
Some(db_values) => {
db_key_exists = true;
(db_values - deletion) | addition
}
None => addition,
};
if final_value.is_empty() {
// If the database entry exists, delete it.
if db_key_exists {
index.script_language_docids.delete(wtxn, &key)?;
for typed_chunk in typed_chunks {
let TypedChunk::ScriptLanguageDocids(sl_map) = typed_chunk else { unreachable!() };
for (key, (deletion, addition)) in sl_map {
let mut db_key_exists = false;
let final_value = match index.script_language_docids.get(wtxn, &key)? {
Some(db_values) => {
db_key_exists = true;
(db_values - deletion) | addition
}
None => addition,
};
if final_value.is_empty() {
// If the database entry exists, delete it.
if db_key_exists {
index.script_language_docids.delete(wtxn, &key)?;
}
} else {
index.script_language_docids.put(wtxn, &key, &final_value)?;
}
} else {
index.script_language_docids.put(wtxn, &key, &final_value)?;
}
}
}
@ -557,13 +815,9 @@ fn extract_geo_point(value: &[u8], docid: DocumentId) -> GeoPoint {
}
fn merge_word_docids_reader_into_fst(
word_docids_iter: grenad::Reader<io::Cursor<ClonableMmap>>,
exact_word_docids_iter: grenad::Reader<io::Cursor<ClonableMmap>>,
merger: Merger<CursorClonableMmap, MergeFn>,
) -> Result<fst::Set<Vec<u8>>> {
let mut merger_builder = MergerBuilder::new(merge_ignore_values as MergeFn);
merger_builder.push(word_docids_iter.into_cursor()?);
merger_builder.push(exact_word_docids_iter.into_cursor()?);
let mut iter = merger_builder.build().into_stream_merger_iter()?;
let mut iter = merger.into_stream_merger_iter()?;
let mut builder = fst::SetBuilder::memory();
while let Some((k, _)) = iter.next()? {
@ -577,10 +831,9 @@ fn merge_word_docids_reader_into_fst(
/// merge_values function is used if an entry already exist in the database.
#[tracing::instrument(level = "trace", skip_all, target = "indexing::write_db")]
fn write_entries_into_database<R, K, V, FS, FM>(
data: grenad::Reader<R>,
merger: Merger<R, MergeFn>,
database: &heed::Database<K, V>,
wtxn: &mut RwTxn,
index_is_empty: bool,
serialize_value: FS,
merge_values: FM,
) -> Result<()>
@ -589,22 +842,17 @@ where
FS: for<'a> Fn(&'a [u8], &'a mut Vec<u8>) -> Result<&'a [u8]>,
FM: for<'a> Fn(&[u8], &[u8], &'a mut Vec<u8>) -> Result<Option<&'a [u8]>>,
{
puffin::profile_function!(format!("number of entries: {}", data.len()));
puffin::profile_function!();
let mut buffer = Vec::new();
let database = database.remap_types::<Bytes, Bytes>();
let mut cursor = data.into_cursor()?;
while let Some((key, value)) = cursor.move_on_next()? {
let mut iter = merger.into_stream_merger_iter()?;
while let Some((key, value)) = iter.next()? {
if valid_lmdb_key(key) {
buffer.clear();
let value = if index_is_empty {
Some(serialize_value(value, &mut buffer)?)
} else {
match database.get(wtxn, key)? {
Some(prev_value) => merge_values(value, prev_value, &mut buffer)?,
None => Some(serialize_value(value, &mut buffer)?),
}
let value = match database.get(wtxn, key)? {
Some(prev_value) => merge_values(value, prev_value, &mut buffer)?,
None => Some(serialize_value(value, &mut buffer)?),
};
match value {
Some(value) => database.put(wtxn, key, value)?,
@ -614,62 +862,5 @@ where
}
}
}
Ok(())
}
/// Write provided entries in database using serialize_value function.
/// merge_values function is used if an entry already exist in the database.
/// All provided entries must be ordered.
/// If the index is not empty, write_entries_into_database is called instead.
#[tracing::instrument(level = "trace", skip_all, target = "indexing::write_db")]
fn append_entries_into_database<R, K, V, FS, FM>(
data: grenad::Reader<R>,
database: &heed::Database<K, V>,
wtxn: &mut RwTxn,
index_is_empty: bool,
serialize_value: FS,
merge_values: FM,
) -> Result<()>
where
R: io::Read + io::Seek,
FS: for<'a> Fn(&'a [u8], &'a mut Vec<u8>) -> Result<&'a [u8]>,
FM: for<'a> Fn(&[u8], &[u8], &'a mut Vec<u8>) -> Result<Option<&'a [u8]>>,
K: for<'a> heed::BytesDecode<'a>,
{
puffin::profile_function!(format!("number of entries: {}", data.len()));
if !index_is_empty {
return write_entries_into_database(
data,
database,
wtxn,
false,
serialize_value,
merge_values,
);
}
let mut buffer = Vec::new();
let mut database = database.iter_mut(wtxn)?.remap_types::<Bytes, Bytes>();
let mut cursor = data.into_cursor()?;
while let Some((key, value)) = cursor.move_on_next()? {
if valid_lmdb_key(key) {
debug_assert!(
K::bytes_decode(key).is_ok(),
"Couldn't decode key with the database decoder, key length: {} - key bytes: {:x?}",
key.len(),
&key
);
buffer.clear();
let value = serialize_value(value, &mut buffer)?;
unsafe {
// safety: We do not keep a reference to anything that lives inside the database
database.put_current_with_options::<Bytes>(PutFlags::APPEND, key, value)?
};
}
}
Ok(())
}

View File

@ -3,9 +3,8 @@ pub use self::clear_documents::ClearDocuments;
pub use self::facet::bulk::FacetsUpdateBulk;
pub use self::facet::incremental::FacetsUpdateIncrementalInner;
pub use self::index_documents::{
merge_btreeset_string, merge_cbo_roaring_bitmaps, merge_roaring_bitmaps,
DocumentAdditionResult, DocumentId, IndexDocuments, IndexDocumentsConfig, IndexDocumentsMethod,
MergeFn,
merge_cbo_roaring_bitmaps, merge_roaring_bitmaps, DocumentAdditionResult, DocumentId,
IndexDocuments, IndexDocumentsConfig, IndexDocumentsMethod, MergeFn,
};
pub use self::indexer_config::IndexerConfig;
pub use self::settings::{validate_embedding_settings, Setting, Settings};

View File

@ -47,7 +47,7 @@ impl<'t, 'i> WordPrefixDocids<'t, 'i> {
)]
pub fn execute(
self,
mut new_word_docids_iter: grenad::ReaderCursor<CursorClonableMmap>,
new_word_docids: grenad::Merger<CursorClonableMmap, MergeFn>,
new_prefix_fst_words: &[String],
common_prefix_fst_words: &[&[String]],
del_prefix_fst_words: &HashSet<Vec<u8>>,
@ -68,7 +68,8 @@ impl<'t, 'i> WordPrefixDocids<'t, 'i> {
if !common_prefix_fst_words.is_empty() {
let mut current_prefixes: Option<&&[String]> = None;
let mut prefixes_cache = HashMap::new();
while let Some((word, data)) = new_word_docids_iter.move_on_next()? {
let mut new_word_docids_iter = new_word_docids.into_stream_merger_iter()?;
while let Some((word, data)) = new_word_docids_iter.next()? {
current_prefixes = match current_prefixes.take() {
Some(prefixes) if word.starts_with(prefixes[0].as_bytes()) => Some(prefixes),
_otherwise => {

View File

@ -52,7 +52,7 @@ impl<'t, 'i> WordPrefixIntegerDocids<'t, 'i> {
)]
pub fn execute(
self,
new_word_integer_docids: grenad::Reader<CursorClonableMmap>,
new_word_integer_docids: grenad::Merger<CursorClonableMmap, MergeFn>,
new_prefix_fst_words: &[String],
common_prefix_fst_words: &[&[String]],
del_prefix_fst_words: &HashSet<Vec<u8>>,
@ -69,14 +69,14 @@ impl<'t, 'i> WordPrefixIntegerDocids<'t, 'i> {
self.max_memory,
);
let mut new_word_integer_docids_iter = new_word_integer_docids.into_cursor()?;
if !common_prefix_fst_words.is_empty() {
// We fetch all the new common prefixes between the previous and new prefix fst.
let mut buffer = Vec::new();
let mut current_prefixes: Option<&&[String]> = None;
let mut prefixes_cache = HashMap::new();
while let Some((key, data)) = new_word_integer_docids_iter.move_on_next()? {
let mut new_word_integer_docids_iter =
new_word_integer_docids.into_stream_merger_iter()?;
while let Some((key, data)) = new_word_integer_docids_iter.next()? {
let (word, pos) =
StrBEU16Codec::bytes_decode(key).map_err(heed::Error::Decoding)?;