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:
bors[bot] 2022-08-17 16:31:04 +00:00 committed by GitHub
commit 79094bcbcf
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GPG Key ID: 4AEE18F83AFDEB23
16 changed files with 58 additions and 29 deletions

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@ -5,7 +5,7 @@ use std::fs::{create_dir_all, remove_dir_all};
use std::path::Path;
use criterion::{criterion_group, criterion_main, Criterion};
use heed::{EnvOpenOptions, RwTxn};
use milli::heed::{EnvOpenOptions, RwTxn};
use milli::update::{
DeleteDocuments, IndexDocuments, IndexDocumentsConfig, IndexerConfig, Settings,
};

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@ -6,8 +6,8 @@ use std::num::ParseFloatError;
use std::path::Path;
use criterion::BenchmarkId;
use heed::EnvOpenOptions;
use milli::documents::{DocumentsBatchBuilder, DocumentsBatchReader};
use milli::heed::EnvOpenOptions;
use milli::update::{
IndexDocuments, IndexDocumentsConfig, IndexDocumentsMethod, IndexerConfig, Settings,
};

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@ -11,7 +11,6 @@ byte-unit = { version = "4.0.14", features = ["serde"] }
color-eyre = "0.6.1"
csv = "1.1.6"
eyre = "0.6.7"
heed = { git = "https://github.com/meilisearch/heed", tag = "v0.12.1", default-features = false, features = ["lmdb", "sync-read-txn"] }
indicatif = "0.16.2"
milli = { path = "../milli" }
mimalloc = { version = "0.1.29", default-features = false }

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@ -13,7 +13,7 @@ use milli::update::UpdateIndexingStep::{
ComputeIdsAndMergeDocuments, IndexDocuments, MergeDataIntoFinalDatabase, RemapDocumentAddition,
};
use milli::update::{self, IndexDocumentsConfig, IndexDocumentsMethod, IndexerConfig};
use milli::{Index, Object};
use milli::{heed, Index, Object};
use structopt::StructOpt;
#[global_allocator]

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@ -9,7 +9,6 @@ publish = false
[dependencies]
anyhow = "1.0.56"
byte-unit = { version = "4.0.14", default-features = false, features = ["std"] }
heed = { git = "https://github.com/meilisearch/heed", tag = "v0.12.1" }
milli = { path = "../milli" }
mimalloc = { version = "0.1.29", default-features = false }
stderrlog = "0.5.1"

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@ -1,7 +1,7 @@
use std::path::PathBuf;
use byte_unit::Byte;
use heed::{CompactionOption, Env, EnvOpenOptions};
use milli::heed::{CompactionOption, Env, EnvOpenOptions};
use structopt::StructOpt;
use Command::*;

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@ -10,7 +10,6 @@ publish = false
anyhow = "1.0.56"
byte-unit = { version = "4.0.14", default-features = false, features = ["std"] }
crossbeam-channel = "0.5.2"
heed = { git = "https://github.com/meilisearch/heed", tag = "v0.12.1" }
memmap2 = "0.5.3"
milli = { path = "../milli" }
mimalloc = { version = "0.1.29", default-features = false }

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@ -17,8 +17,8 @@ use byte_unit::Byte;
use either::Either;
use flate2::read::GzDecoder;
use futures::{stream, FutureExt, StreamExt};
use heed::EnvOpenOptions;
use milli::documents::{DocumentsBatchBuilder, DocumentsBatchReader};
use milli::heed::EnvOpenOptions;
use milli::tokenizer::TokenizerBuilder;
use milli::update::UpdateIndexingStep::*;
use milli::update::{

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@ -6,6 +6,7 @@ use std::sync::Arc;
use crossbeam_channel::Sender;
use heed::types::{ByteSlice, DecodeIgnore, OwnedType, SerdeJson};
use heed::{Database, Env, EnvOpenOptions};
use milli::heed;
use serde::{Deserialize, Serialize};
pub type BEU64 = heed::zerocopy::U64<heed::byteorder::BE>;

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@ -9,7 +9,6 @@ publish = false
anyhow = "1.0.56"
byte-unit = { version = "4.0.14", default-features = false, features = ["std"] }
csv = "1.1.6"
heed = { git = "https://github.com/meilisearch/heed", tag = "v0.12.1" }
milli = { path = "../milli" }
mimalloc = { version = "0.1.29", default-features = false }
roaring = "0.9.0"

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@ -7,7 +7,7 @@ use byte_unit::Byte;
use heed::EnvOpenOptions;
use milli::facet::FacetType;
use milli::index::db_name::*;
use milli::{FieldId, Index};
use milli::{heed, FieldId, Index};
use structopt::StructOpt;
use Command::*;

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@ -18,7 +18,7 @@ fst = "0.4.7"
fxhash = "0.2.1"
geoutils = "0.4.1"
grenad = { version = "0.4.2", default-features = false, features = ["tempfile"] }
heed = { git = "https://github.com/meilisearch/heed", tag = "v0.12.1", default-features = false, features = ["lmdb", "sync-read-txn"] }
heed = { git = "https://github.com/meilisearch/heed", tag = "v0.12.3", default-features = false, features = ["lmdb", "sync-read-txn"] }
json-depth-checker = { path = "../json-depth-checker" }
levenshtein_automata = { version = "0.2.1", features = ["fst_automaton"] }
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
}
)]
InvalidSortableAttribute { field: String, valid_fields: BTreeSet<String> },
#[error("{}", HeedError::BadOpenOptions)]
InvalidLmdbOpenOptions,
#[error("The sort ranking rule must be specified in the ranking rules settings to use the sort parameter at search time.")]
SortRankingRuleMissing,
#[error("The database file is in an invalid state.")]
@ -244,6 +246,7 @@ impl From<HeedError> for Error {
HeedError::Decoding => InternalError(Serialization(Decoding { db_name: None })),
HeedError::InvalidDatabaseTyping => InternalError(InvalidDatabaseTyping),
HeedError::DatabaseClosing => InternalError(DatabaseClosing),
HeedError::BadOpenOptions => UserError(InvalidLmdbOpenOptions),
}
}
}

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@ -223,6 +223,16 @@ impl Index {
self.env.path()
}
/// Returns the size used by the index without the cached pages.
pub fn used_size(&self) -> Result<u64> {
Ok(self.env.non_free_pages_size()?)
}
/// Returns the real size used by the index.
pub fn on_disk_size(&self) -> Result<u64> {
Ok(self.env.real_disk_size()?)
}
pub fn copy_to_path<P: AsRef<Path>>(&self, path: P, option: CompactionOption) -> Result<File> {
self.env.copy_to_path(path, option).map_err(Into::into)
}

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@ -20,10 +20,6 @@ use crate::{
RoaringBitmapCodec, SmallString32, BEU32,
};
/// The threshold we use to determine after which number of documents we want to clear the
/// soft-deleted database and delete documents for real.
const DELETE_DOCUMENTS_THRESHOLD: u64 = 10_000;
pub struct DeleteDocuments<'t, 'u, 'i> {
wtxn: &'t mut heed::RwTxn<'i, 'u>,
index: &'i Index,
@ -129,7 +125,27 @@ impl<'t, 'u, 'i> DeleteDocuments<'t, 'u, 'i> {
// if we have less documents to delete than the threshold we simply save them in
// the `soft_deleted_documents_ids` bitmap and early exit.
if soft_deleted_docids.len() < DELETE_DOCUMENTS_THRESHOLD {
let size_used = self.index.used_size()?;
let map_size = self.index.env.map_size()? as u64;
let nb_documents = self.index.number_of_documents(&self.wtxn)?;
let nb_soft_deleted = soft_deleted_docids.len();
let percentage_available = 100 - (size_used * 100 / map_size);
let estimated_document_size = size_used / (nb_documents + nb_soft_deleted);
let estimated_size_used_by_soft_deleted = estimated_document_size * nb_soft_deleted;
let percentage_used_by_soft_deleted_documents =
estimated_size_used_by_soft_deleted * 100 / map_size;
// if we have more than 10% of disk space available and the soft deleted
// documents uses less than 10% of the total space available,
// we skip the deletion. Eg.
// - With 100Go of disk and 20Go used including 5Go of soft-deleted documents
// We dont delete anything.
// - With 100Go of disk and 95Go used including 1mo of soft-deleted documents
// We run the deletion.
// - With 100Go of disk and 50Go used including 15Go of soft-deleted documents
// We run the deletion.
if percentage_available > 10 && percentage_used_by_soft_deleted_documents < 10 {
self.index.put_soft_deleted_documents_ids(self.wtxn, &soft_deleted_docids)?;
return Ok(DocumentDeletionResult {
deleted_documents: self.to_delete_docids.len(),

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@ -278,27 +278,30 @@ where
let stop_words = self.index.stop_words(self.wtxn)?;
let exact_attributes = self.index.exact_attributes_ids(self.wtxn)?;
let pool_params = GrenadParameters {
chunk_compression_type: self.indexer_config.chunk_compression_type,
chunk_compression_level: self.indexer_config.chunk_compression_level,
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 max_positions_per_attributes = self.indexer_config.max_positions_per_attributes;
// Run extraction pipeline in parallel.
pool.install(|| {
let params = GrenadParameters {
chunk_compression_type: self.indexer_config.chunk_compression_type,
chunk_compression_level: self.indexer_config.chunk_compression_level,
max_memory: self.indexer_config.max_memory,
max_nb_chunks: self.indexer_config.max_nb_chunks, // default value, may be chosen.
};
// split obkv file into several chunks
let original_chunk_iter = grenad_obkv_into_chunks(
original_documents,
params.clone(),
self.indexer_config.documents_chunk_size.unwrap_or(1024 * 1024 * 4), // 4MiB
pool_params.clone(),
documents_chunk_size,
);
// split obkv file into several chunks
let flattened_chunk_iter = grenad_obkv_into_chunks(
flattened_documents,
params.clone(),
self.indexer_config.documents_chunk_size.unwrap_or(1024 * 1024 * 4), // 4MiB
pool_params.clone(),
documents_chunk_size,
);
let result = original_chunk_iter
@ -308,14 +311,14 @@ where
extract::data_from_obkv_documents(
original_chunk,
flattened_chunk,
params,
pool_params,
lmdb_writer_sx.clone(),
searchable_fields,
faceted_fields,
primary_key_id,
geo_fields_ids,
stop_words,
self.indexer_config.max_positions_per_attributes,
max_positions_per_attributes,
exact_attributes,
)
});