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Compute chunk size based on the input data size ant the number of indexing threads

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This commit is contained in:
ManyTheFish
2024-01-22 16:23:12 +01:00
committed by Louis Dureuil
parent 023c2d755f
commit be1b054b05
13 changed files with 991 additions and 795 deletions
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200
milli/src/update/facet/mod.rs
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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(
@ -170,92 +173,94 @@ 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)?;
if let Some(normalized_delta_data) = self.normalized_delta_data {
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);
// 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,
);
let database_set = self
.index
.facet_id_normalized_string_strings
.remap_key_type::<Bytes>()
.get(wtxn, &key_bytes)?
.unwrap_or_default();
// 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 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 self.index.facet_id_string_docids.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() {
self.index
.facet_id_normalized_string_strings
.remap_key_type::<Bytes>()
.delete(wtxn, key_bytes)?;
} else {
self.index
.facet_id_normalized_string_strings
.remap_key_type::<Bytes>()
.put(wtxn, key_bytes, &set)?;
}
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)?;
}
// We clear the FST of normalized-for-search to compute everything from scratch.
self.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 =
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)?;
}
}
// 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(())
}
}
@ -268,6 +273,7 @@ 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 +286,8 @@ 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 +470,13 @@ 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(),
};