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https://github.com/meilisearch/MeiliSearch
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Merge #607
607: Better threshold r=Kerollmops a=irevoire # Pull Request ## What does this PR do? Fixes #570 This PR tries to improve the threshold used to trigger the real deletion of documents. The deletion is now triggered in two cases; - 10% of the total available space is used by soft deleted documents - 90% of the total available space is used. In this context, « total available space » means the `map_size` of lmdb. And the size used by the soft deleted documents is actually an estimation. We can't determine precisely the size used by one document thus what we do is; take the total space used, divide it by the number of documents + soft deleted documents to estimate the size of one average document. Then multiply the size of one avg document by the number of soft deleted document. -------- <img width="808" alt="image" src="https://user-images.githubusercontent.com/7032172/185083075-92cf379e-8ae1-4bfc-9ca6-93b54e6ab4e9.png"> Here we can see we have a ~10GB drift in the end between the space used by the soft deleted and the real space used by the documents. Personally I don’t think that's a big issue because once the red line reach 90GB everything will be freed but now you know. If you have an idea on how to improve this estimation I would love to hear it. It look like the difference is linear so maybe we could simply multiply the current estimation by two? Co-authored-by: Irevoire <tamo@meilisearch.com>
This commit is contained in:
commit
79094bcbcf
@ -5,7 +5,7 @@ use std::fs::{create_dir_all, remove_dir_all};
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use std::path::Path;
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use criterion::{criterion_group, criterion_main, Criterion};
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use heed::{EnvOpenOptions, RwTxn};
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use milli::heed::{EnvOpenOptions, RwTxn};
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use milli::update::{
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DeleteDocuments, IndexDocuments, IndexDocumentsConfig, IndexerConfig, Settings,
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};
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@ -6,8 +6,8 @@ use std::num::ParseFloatError;
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use std::path::Path;
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use criterion::BenchmarkId;
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use heed::EnvOpenOptions;
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use milli::documents::{DocumentsBatchBuilder, DocumentsBatchReader};
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use milli::heed::EnvOpenOptions;
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use milli::update::{
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IndexDocuments, IndexDocumentsConfig, IndexDocumentsMethod, IndexerConfig, Settings,
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};
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@ -11,7 +11,6 @@ byte-unit = { version = "4.0.14", features = ["serde"] }
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color-eyre = "0.6.1"
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csv = "1.1.6"
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eyre = "0.6.7"
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heed = { git = "https://github.com/meilisearch/heed", tag = "v0.12.1", default-features = false, features = ["lmdb", "sync-read-txn"] }
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indicatif = "0.16.2"
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milli = { path = "../milli" }
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mimalloc = { version = "0.1.29", default-features = false }
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@ -13,7 +13,7 @@ use milli::update::UpdateIndexingStep::{
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ComputeIdsAndMergeDocuments, IndexDocuments, MergeDataIntoFinalDatabase, RemapDocumentAddition,
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};
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use milli::update::{self, IndexDocumentsConfig, IndexDocumentsMethod, IndexerConfig};
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use milli::{Index, Object};
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use milli::{heed, Index, Object};
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use structopt::StructOpt;
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#[global_allocator]
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@ -9,7 +9,6 @@ publish = false
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[dependencies]
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anyhow = "1.0.56"
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byte-unit = { version = "4.0.14", default-features = false, features = ["std"] }
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heed = { git = "https://github.com/meilisearch/heed", tag = "v0.12.1" }
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milli = { path = "../milli" }
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mimalloc = { version = "0.1.29", default-features = false }
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stderrlog = "0.5.1"
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@ -1,7 +1,7 @@
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use std::path::PathBuf;
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use byte_unit::Byte;
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use heed::{CompactionOption, Env, EnvOpenOptions};
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use milli::heed::{CompactionOption, Env, EnvOpenOptions};
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use structopt::StructOpt;
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use Command::*;
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@ -10,7 +10,6 @@ publish = false
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anyhow = "1.0.56"
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byte-unit = { version = "4.0.14", default-features = false, features = ["std"] }
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crossbeam-channel = "0.5.2"
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heed = { git = "https://github.com/meilisearch/heed", tag = "v0.12.1" }
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memmap2 = "0.5.3"
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milli = { path = "../milli" }
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mimalloc = { version = "0.1.29", default-features = false }
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@ -17,8 +17,8 @@ use byte_unit::Byte;
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use either::Either;
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use flate2::read::GzDecoder;
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use futures::{stream, FutureExt, StreamExt};
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use heed::EnvOpenOptions;
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use milli::documents::{DocumentsBatchBuilder, DocumentsBatchReader};
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use milli::heed::EnvOpenOptions;
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use milli::tokenizer::TokenizerBuilder;
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use milli::update::UpdateIndexingStep::*;
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use milli::update::{
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@ -6,6 +6,7 @@ use std::sync::Arc;
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use crossbeam_channel::Sender;
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use heed::types::{ByteSlice, DecodeIgnore, OwnedType, SerdeJson};
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use heed::{Database, Env, EnvOpenOptions};
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use milli::heed;
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use serde::{Deserialize, Serialize};
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pub type BEU64 = heed::zerocopy::U64<heed::byteorder::BE>;
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@ -9,7 +9,6 @@ publish = false
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anyhow = "1.0.56"
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byte-unit = { version = "4.0.14", default-features = false, features = ["std"] }
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csv = "1.1.6"
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heed = { git = "https://github.com/meilisearch/heed", tag = "v0.12.1" }
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milli = { path = "../milli" }
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mimalloc = { version = "0.1.29", default-features = false }
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roaring = "0.9.0"
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@ -7,7 +7,7 @@ use byte_unit::Byte;
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use heed::EnvOpenOptions;
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use milli::facet::FacetType;
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use milli::index::db_name::*;
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use milli::{FieldId, Index};
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use milli::{heed, FieldId, Index};
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use structopt::StructOpt;
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use Command::*;
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@ -18,7 +18,7 @@ fst = "0.4.7"
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fxhash = "0.2.1"
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geoutils = "0.4.1"
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grenad = { version = "0.4.2", default-features = false, features = ["tempfile"] }
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heed = { git = "https://github.com/meilisearch/heed", tag = "v0.12.1", default-features = false, features = ["lmdb", "sync-read-txn"] }
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heed = { git = "https://github.com/meilisearch/heed", tag = "v0.12.3", default-features = false, features = ["lmdb", "sync-read-txn"] }
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json-depth-checker = { path = "../json-depth-checker" }
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levenshtein_automata = { version = "0.2.1", features = ["fst_automaton"] }
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memmap2 = "0.5.3"
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@ -116,6 +116,8 @@ only composed of alphanumeric characters (a-z A-Z 0-9), hyphens (-) and undersco
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}
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)]
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InvalidSortableAttribute { field: String, valid_fields: BTreeSet<String> },
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#[error("{}", HeedError::BadOpenOptions)]
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InvalidLmdbOpenOptions,
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#[error("The sort ranking rule must be specified in the ranking rules settings to use the sort parameter at search time.")]
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SortRankingRuleMissing,
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#[error("The database file is in an invalid state.")]
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@ -244,6 +246,7 @@ impl From<HeedError> for Error {
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HeedError::Decoding => InternalError(Serialization(Decoding { db_name: None })),
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HeedError::InvalidDatabaseTyping => InternalError(InvalidDatabaseTyping),
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HeedError::DatabaseClosing => InternalError(DatabaseClosing),
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HeedError::BadOpenOptions => UserError(InvalidLmdbOpenOptions),
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}
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}
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}
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@ -223,6 +223,16 @@ impl Index {
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self.env.path()
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}
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/// Returns the size used by the index without the cached pages.
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pub fn used_size(&self) -> Result<u64> {
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Ok(self.env.non_free_pages_size()?)
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}
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/// Returns the real size used by the index.
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pub fn on_disk_size(&self) -> Result<u64> {
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Ok(self.env.real_disk_size()?)
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}
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pub fn copy_to_path<P: AsRef<Path>>(&self, path: P, option: CompactionOption) -> Result<File> {
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self.env.copy_to_path(path, option).map_err(Into::into)
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}
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@ -20,10 +20,6 @@ use crate::{
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RoaringBitmapCodec, SmallString32, BEU32,
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};
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/// The threshold we use to determine after which number of documents we want to clear the
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/// soft-deleted database and delete documents for real.
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const DELETE_DOCUMENTS_THRESHOLD: u64 = 10_000;
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pub struct DeleteDocuments<'t, 'u, 'i> {
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wtxn: &'t mut heed::RwTxn<'i, 'u>,
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index: &'i Index,
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@ -129,7 +125,27 @@ impl<'t, 'u, 'i> DeleteDocuments<'t, 'u, 'i> {
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// if we have less documents to delete than the threshold we simply save them in
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// the `soft_deleted_documents_ids` bitmap and early exit.
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if soft_deleted_docids.len() < DELETE_DOCUMENTS_THRESHOLD {
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let size_used = self.index.used_size()?;
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let map_size = self.index.env.map_size()? as u64;
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let nb_documents = self.index.number_of_documents(&self.wtxn)?;
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let nb_soft_deleted = soft_deleted_docids.len();
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let percentage_available = 100 - (size_used * 100 / map_size);
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let estimated_document_size = size_used / (nb_documents + nb_soft_deleted);
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let estimated_size_used_by_soft_deleted = estimated_document_size * nb_soft_deleted;
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let percentage_used_by_soft_deleted_documents =
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estimated_size_used_by_soft_deleted * 100 / map_size;
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// if we have more than 10% of disk space available and the soft deleted
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// documents uses less than 10% of the total space available,
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// we skip the deletion. Eg.
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// - With 100Go of disk and 20Go used including 5Go of soft-deleted documents
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// We don’t delete anything.
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// - With 100Go of disk and 95Go used including 1mo of soft-deleted documents
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// We run the deletion.
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// - With 100Go of disk and 50Go used including 15Go of soft-deleted documents
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// We run the deletion.
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if percentage_available > 10 && percentage_used_by_soft_deleted_documents < 10 {
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self.index.put_soft_deleted_documents_ids(self.wtxn, &soft_deleted_docids)?;
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return Ok(DocumentDeletionResult {
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deleted_documents: self.to_delete_docids.len(),
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@ -278,27 +278,30 @@ where
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let stop_words = self.index.stop_words(self.wtxn)?;
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let exact_attributes = self.index.exact_attributes_ids(self.wtxn)?;
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let pool_params = GrenadParameters {
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chunk_compression_type: self.indexer_config.chunk_compression_type,
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chunk_compression_level: self.indexer_config.chunk_compression_level,
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max_memory: self.indexer_config.max_memory,
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max_nb_chunks: self.indexer_config.max_nb_chunks, // default value, may be chosen.
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};
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let documents_chunk_size =
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self.indexer_config.documents_chunk_size.unwrap_or(1024 * 1024 * 4); // 4MiB
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let max_positions_per_attributes = self.indexer_config.max_positions_per_attributes;
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// Run extraction pipeline in parallel.
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pool.install(|| {
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let params = GrenadParameters {
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chunk_compression_type: self.indexer_config.chunk_compression_type,
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chunk_compression_level: self.indexer_config.chunk_compression_level,
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max_memory: self.indexer_config.max_memory,
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max_nb_chunks: self.indexer_config.max_nb_chunks, // default value, may be chosen.
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};
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// split obkv file into several chunks
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let original_chunk_iter = grenad_obkv_into_chunks(
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original_documents,
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params.clone(),
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self.indexer_config.documents_chunk_size.unwrap_or(1024 * 1024 * 4), // 4MiB
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pool_params.clone(),
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documents_chunk_size,
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);
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// split obkv file into several chunks
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let flattened_chunk_iter = grenad_obkv_into_chunks(
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flattened_documents,
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params.clone(),
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self.indexer_config.documents_chunk_size.unwrap_or(1024 * 1024 * 4), // 4MiB
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pool_params.clone(),
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documents_chunk_size,
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);
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let result = original_chunk_iter
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@ -308,14 +311,14 @@ where
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extract::data_from_obkv_documents(
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original_chunk,
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flattened_chunk,
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params,
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pool_params,
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lmdb_writer_sx.clone(),
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searchable_fields,
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faceted_fields,
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primary_key_id,
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geo_fields_ids,
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stop_words,
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self.indexer_config.max_positions_per_attributes,
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max_positions_per_attributes,
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exact_attributes,
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)
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});
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