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Merge #5022

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5022: Briging changes from v1.11.0 back to main r=irevoire a=Kerollmops

Fixes https://github.com/meilisearch/meilisearch/issues/5035

...and fixing merge conflicts.

Co-authored-by: Tamo <tamo@meilisearch.com>
Co-authored-by: Louis Dureuil <louis@meilisearch.com>
Co-authored-by: meili-bors[bot] <89034592+meili-bors[bot]@users.noreply.github.com>
Co-authored-by: ManyTheFish <many@meilisearch.com>
Co-authored-by: curquiza <clementine@meilisearch.com>
This commit is contained in:
meili-bors[bot] 2024-11-04 15:34:19 +00:00 committed by GitHub
commit 22229d3046
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GPG Key ID: B5690EEEBB952194
47 changed files with 3034 additions and 2620 deletions
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6
.github/workflows/publish-binaries.yml vendored
View File

@ -65,9 +65,9 @@ jobs:
strategy:
fail-fast: false
matrix:
os: [macos-12, windows-2022]
os: [macos-13, windows-2022]
include:
- os: macos-12
- os: macos-13
artifact_name: meilisearch
asset_name: meilisearch-macos-amd64
- os: windows-2022
@ -90,7 +90,7 @@ jobs:
publish-macos-apple-silicon:
name: Publish binary for macOS silicon
runs-on: macos-12
runs-on: macos-13
needs: check-version
strategy:
matrix:

2
.github/workflows/test-suite.yml vendored
View File

@ -51,7 +51,7 @@ jobs:
strategy:
fail-fast: false
matrix:
os: [macos-12, windows-2022]
os: [macos-13, windows-2022]
steps:
- uses: actions/checkout@v3
- name: Cache dependencies

20
Cargo.lock generated
View File

@ -386,8 +386,9 @@ checksum = "96d30a06541fbafbc7f82ed10c06164cfbd2c401138f6addd8404629c4b16711"
[[package]]
name = "arroy"
version = "0.4.0"
source = "git+https://github.com/meilisearch/arroy/?rev=2386594dfb009ce08821a925ccc89fb8e30bf73d#2386594dfb009ce08821a925ccc89fb8e30bf73d"
version = "0.5.0"
source = "registry+https://github.com/rust-lang/crates.io-index"
checksum = "dfc5f272f38fa063bbff0a7ab5219404e221493de005e2b4078c62d626ef567e"
dependencies = [
"bytemuck",
"byteorder",
@ -3414,6 +3415,7 @@ dependencies = [
"meilisearch-types",
"mimalloc",
"mime",
"mopa-maintained",
"num_cpus",
"obkv",
"once_cell",
@ -3680,6 +3682,12 @@ dependencies = [
"syn 2.0.60",
]
[[package]]
name = "mopa-maintained"
version = "0.2.3"
source = "registry+https://github.com/rust-lang/crates.io-index"
checksum = "79b7f3e22167862cc7c95b21a6f326c22e4bf40da59cbf000b368a310173ba11"
[[package]]
name = "mutually_exclusive_features"
version = "0.0.3"
@ -4581,9 +4589,8 @@ dependencies = [
[[package]]
name = "rhai"
version = "1.19.0"
source = "registry+https://github.com/rust-lang/crates.io-index"
checksum = "61797318be89b1a268a018a92a7657096d83f3ecb31418b9e9c16dcbb043b702"
version = "1.20.0"
source = "git+https://github.com/rhaiscript/rhai?rev=ef3df63121d27aacd838f366f2b83fd65f20a1e4#ef3df63121d27aacd838f366f2b83fd65f20a1e4"
dependencies = [
"ahash 0.8.11",
"bitflags 2.6.0",
@ -4600,8 +4607,7 @@ dependencies = [
[[package]]
name = "rhai_codegen"
version = "2.2.0"
source = "registry+https://github.com/rust-lang/crates.io-index"
checksum = "a5a11a05ee1ce44058fa3d5961d05194fdbe3ad6b40f904af764d81b86450e6b"
source = "git+https://github.com/rhaiscript/rhai?rev=ef3df63121d27aacd838f366f2b83fd65f20a1e4#ef3df63121d27aacd838f366f2b83fd65f20a1e4"
dependencies = [
"proc-macro2",
"quote",

2
bors.toml
View File

@ -1,6 +1,6 @@
status = [
'Tests on ubuntu-20.04',
'Tests on macos-12',
'Tests on macos-13',
'Tests on windows-2022',
'Run Clippy',
'Run Rustfmt',

2
crates/index-scheduler/Cargo.toml
View File

@ -40,7 +40,7 @@ ureq = "2.10.0"
uuid = { version = "1.10.0", features = ["serde", "v4"] }
[dev-dependencies]
arroy = { git = "https://github.com/meilisearch/arroy/", rev = "2386594dfb009ce08821a925ccc89fb8e30bf73d" }
arroy = "0.5.0"
big_s = "1.0.2"
crossbeam = "0.8.4"
insta = { version = "1.39.0", features = ["json", "redactions"] }

2
crates/index-scheduler/src/lib.rs
View File

@ -1263,7 +1263,7 @@ impl IndexScheduler {
#[cfg(test)]
self.maybe_fail(tests::FailureLocation::UpdatingTaskAfterProcessBatchFailure)?;
tracing::info!("Batch failed {}", error);
tracing::error!("Batch failed {}", error);
self.update_task(&mut wtxn, &task)
.map_err(|e| Error::TaskDatabaseUpdate(Box::new(e)))?;

5
crates/meilisearch-types/Cargo.toml
View File

@ -66,5 +66,8 @@ khmer = ["milli/khmer"]
vietnamese = ["milli/vietnamese"]
# force swedish character recomposition
swedish-recomposition = ["milli/swedish-recomposition"]
# force german character recomposition
# allow german tokenization
german = ["milli/german"]
# allow turkish normalization
turkish = ["milli/turkish"]

11
crates/meilisearch/Cargo.toml
View File

@ -75,7 +75,7 @@ reqwest = { version = "0.12.5", features = [
rustls = { version = "0.23.11", features = ["ring"], default-features = false }
rustls-pki-types = { version = "1.7.0", features = ["alloc"] }
rustls-pemfile = "2.1.2"
segment = { version = "0.2.4", optional = true }
segment = { version = "0.2.4" }
serde = { version = "1.0.204", features = ["derive"] }
serde_json = { version = "1.0.120", features = ["preserve_order"] }
sha2 = "0.10.8"
@ -104,6 +104,7 @@ tracing-trace = { version = "0.1.0", path = "../tracing-trace" }
tracing-actix-web = "0.7.11"
build-info = { version = "1.7.0", path = "../build-info" }
roaring = "0.10.2"
mopa-maintained = "0.2.3"
[dev-dependencies]
actix-rt = "2.10.0"
@ -131,8 +132,7 @@ tempfile = { version = "3.10.1", optional = true }
zip = { version = "2.1.3", optional = true }
[features]
default = ["analytics", "meilisearch-types/all-tokenizations", "mini-dashboard"]
analytics = ["segment"]
default = ["meilisearch-types/all-tokenizations", "mini-dashboard"]
mini-dashboard = [
"static-files",
"anyhow",
@ -154,7 +154,8 @@ khmer = ["meilisearch-types/khmer"]
vietnamese = ["meilisearch-types/vietnamese"]
swedish-recomposition = ["meilisearch-types/swedish-recomposition"]
german = ["meilisearch-types/german"]
turkish = ["meilisearch-types/turkish"]
[package.metadata.mini-dashboard]
assets-url = "https://github.com/meilisearch/mini-dashboard/releases/download/v0.2.14/build.zip"
sha1 = "592d1b5a3459d621d0aae1dded8fe3154f5c38fe"
assets-url = "https://github.com/meilisearch/mini-dashboard/releases/download/v0.2.15/build.zip"
sha1 = "d057600b4a839a2e0c0be7a372cd1b2683f3ca7e"

195
crates/meilisearch/src/analytics/mod.rs
View File

@ -1,44 +1,45 @@
mod mock_analytics;
#[cfg(feature = "analytics")]
mod segment_analytics;
pub mod segment_analytics;
use std::fs;
use std::path::{Path, PathBuf};
use std::str::FromStr;
use std::sync::Arc;
use actix_web::HttpRequest;
use index_scheduler::IndexScheduler;
use meilisearch_auth::AuthController;
use meilisearch_types::InstanceUid;
pub use mock_analytics::MockAnalytics;
use mopa::mopafy;
use once_cell::sync::Lazy;
use platform_dirs::AppDirs;
use serde_json::Value;
use crate::routes::indexes::documents::{DocumentEditionByFunction, UpdateDocumentsQuery};
// if the analytics feature is disabled
// the `SegmentAnalytics` point to the mock instead of the real analytics
#[cfg(not(feature = "analytics"))]
pub type SegmentAnalytics = mock_analytics::MockAnalytics;
#[cfg(not(feature = "analytics"))]
pub type SearchAggregator = mock_analytics::SearchAggregator;
#[cfg(not(feature = "analytics"))]
pub type SimilarAggregator = mock_analytics::SimilarAggregator;
#[cfg(not(feature = "analytics"))]
pub type MultiSearchAggregator = mock_analytics::MultiSearchAggregator;
#[cfg(not(feature = "analytics"))]
pub type FacetSearchAggregator = mock_analytics::FacetSearchAggregator;
// if the feature analytics is enabled we use the real analytics
#[cfg(feature = "analytics")]
pub type SegmentAnalytics = segment_analytics::SegmentAnalytics;
#[cfg(feature = "analytics")]
pub type SearchAggregator = segment_analytics::SearchAggregator;
#[cfg(feature = "analytics")]
pub type SimilarAggregator = segment_analytics::SimilarAggregator;
#[cfg(feature = "analytics")]
pub type MultiSearchAggregator = segment_analytics::MultiSearchAggregator;
#[cfg(feature = "analytics")]
pub type FacetSearchAggregator = segment_analytics::FacetSearchAggregator;
use crate::Opt;
/// A macro used to quickly define events that don't aggregate or send anything besides an empty event with its name.
#[macro_export]
macro_rules! empty_analytics {
($struct_name:ident, $event_name:literal) => {
#[derive(Default)]
struct $struct_name {}
impl $crate::analytics::Aggregate for $struct_name {
fn event_name(&self) -> &'static str {
$event_name
}
fn aggregate(self: Box<Self>, _other: Box<Self>) -> Box<Self> {
self
}
fn into_event(self: Box<Self>) -> serde_json::Value {
serde_json::json!({})
}
}
};
}
/// The Meilisearch config dir:
/// `~/.config/Meilisearch` on *NIX or *BSD.
@ -78,60 +79,88 @@ pub enum DocumentFetchKind {
Normal { with_filter: bool, limit: usize, offset: usize, retrieve_vectors: bool },
}
pub trait Analytics: Sync + Send {
fn instance_uid(&self) -> Option<&InstanceUid>;
/// To send an event to segment, your event must be able to aggregate itself with another event of the same type.
pub trait Aggregate: 'static + mopa::Any + Send {
/// The name of the event that will be sent to segment.
fn event_name(&self) -> &'static str;
/// Will be called every time an event has been used twice before segment flushed its buffer.
fn aggregate(self: Box<Self>, new: Box<Self>) -> Box<Self>
where
Self: Sized;
/// Converts your structure to the final event that'll be sent to segment.
fn into_event(self: Box<Self>) -> serde_json::Value;
}
mopafy!(Aggregate);
/// Helper trait to define multiple aggregates with the same content but a different name.
/// Commonly used when you must aggregate a search with POST or with GET, for example.
pub trait AggregateMethod: 'static + Default + Send {
fn event_name() -> &'static str;
}
/// A macro used to quickly define multiple aggregate method with their name
/// Usage:
/// ```rust
/// use meilisearch::aggregate_methods;
///
/// aggregate_methods!(
/// SearchGET => "Documents Searched GET",
/// SearchPOST => "Documents Searched POST",
/// );
/// ```
#[macro_export]
macro_rules! aggregate_methods {
($method:ident => $event_name:literal) => {
#[derive(Default)]
pub struct $method {}
impl $crate::analytics::AggregateMethod for $method {
fn event_name() -> &'static str {
$event_name
}
}
};
($($method:ident => $event_name:literal,)+) => {
$(
aggregate_methods!($method => $event_name);
)+
};
}
#[derive(Clone)]
pub struct Analytics {
segment: Option<Arc<SegmentAnalytics>>,
}
impl Analytics {
pub async fn new(
opt: &Opt,
index_scheduler: Arc<IndexScheduler>,
auth_controller: Arc<AuthController>,
) -> Self {
if opt.no_analytics {
Self { segment: None }
} else {
Self { segment: SegmentAnalytics::new(opt, index_scheduler, auth_controller).await }
}
}
pub fn no_analytics() -> Self {
Self { segment: None }
}
pub fn instance_uid(&self) -> Option<&InstanceUid> {
self.segment.as_ref().map(|segment| segment.instance_uid.as_ref())
}
/// The method used to publish most analytics that do not need to be batched every hours
fn publish(&self, event_name: String, send: Value, request: Option<&HttpRequest>);
/// This method should be called to aggregate a get search
fn get_search(&self, aggregate: SearchAggregator);
/// This method should be called to aggregate a post search
fn post_search(&self, aggregate: SearchAggregator);
/// This method should be called to aggregate a get similar request
fn get_similar(&self, aggregate: SimilarAggregator);
/// This method should be called to aggregate a post similar request
fn post_similar(&self, aggregate: SimilarAggregator);
/// This method should be called to aggregate a post array of searches
fn post_multi_search(&self, aggregate: MultiSearchAggregator);
/// This method should be called to aggregate post facet values searches
fn post_facet_search(&self, aggregate: FacetSearchAggregator);
// this method should be called to aggregate an add documents request
fn add_documents(
&self,
documents_query: &UpdateDocumentsQuery,
index_creation: bool,
request: &HttpRequest,
);
// this method should be called to aggregate a fetch documents request
fn get_fetch_documents(&self, documents_query: &DocumentFetchKind, request: &HttpRequest);
// this method should be called to aggregate a fetch documents request
fn post_fetch_documents(&self, documents_query: &DocumentFetchKind, request: &HttpRequest);
// this method should be called to aggregate a add documents request
fn delete_documents(&self, kind: DocumentDeletionKind, request: &HttpRequest);
// this method should be called to batch an update documents request
fn update_documents(
&self,
documents_query: &UpdateDocumentsQuery,
index_creation: bool,
request: &HttpRequest,
);
// this method should be called to batch an update documents by function request
fn update_documents_by_function(
&self,
documents_query: &DocumentEditionByFunction,
index_creation: bool,
request: &HttpRequest,
);
pub fn publish<T: Aggregate>(&self, event: T, request: &HttpRequest) {
if let Some(ref segment) = self.segment {
let _ = segment.sender.try_send(segment_analytics::Message::new(event, request));
}
}
}

1798
crates/meilisearch/src/analytics/segment_analytics.rs
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File diff suppressed because it is too large Load Diff

6
crates/meilisearch/src/lib.rs
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@ -120,7 +120,7 @@ pub fn create_app(
search_queue: Data<SearchQueue>,
opt: Opt,
logs: (LogRouteHandle, LogStderrHandle),
analytics: Arc<dyn Analytics>,
analytics: Data<Analytics>,
enable_dashboard: bool,
) -> actix_web::App<
impl ServiceFactory<
@ -473,14 +473,14 @@ pub fn configure_data(
search_queue: Data<SearchQueue>,
opt: &Opt,
(logs_route, logs_stderr): (LogRouteHandle, LogStderrHandle),
analytics: Arc<dyn Analytics>,
analytics: Data<Analytics>,
) {
let http_payload_size_limit = opt.http_payload_size_limit.as_u64() as usize;
config
.app_data(index_scheduler)
.app_data(auth)
.app_data(search_queue)
.app_data(web::Data::from(analytics))
.app_data(analytics)
.app_data(web::Data::new(logs_route))
.app_data(web::Data::new(logs_stderr))
.app_data(web::Data::new(opt.clone()))

34
crates/meilisearch/src/main.rs
View File

@ -5,6 +5,7 @@ use std::path::PathBuf;
use std::str::FromStr;
use std::sync::Arc;
use std::thread::available_parallelism;
use std::time::Duration;
use actix_web::http::KeepAlive;
use actix_web::web::Data;
@ -123,19 +124,12 @@ async fn try_main() -> anyhow::Result<()> {
let (index_scheduler, auth_controller) = setup_meilisearch(&opt)?;
#[cfg(all(not(debug_assertions), feature = "analytics"))]
let analytics = if !opt.no_analytics {
analytics::SegmentAnalytics::new(&opt, index_scheduler.clone(), auth_controller.clone())
.await
} else {
analytics::MockAnalytics::new(&opt)
};
#[cfg(any(debug_assertions, not(feature = "analytics")))]
let analytics = analytics::MockAnalytics::new(&opt);
let analytics =
analytics::Analytics::new(&opt, index_scheduler.clone(), auth_controller.clone()).await;
print_launch_resume(&opt, analytics.clone(), config_read_from);
run_http(index_scheduler, auth_controller, opt, log_handle, analytics).await?;
run_http(index_scheduler, auth_controller, opt, log_handle, Arc::new(analytics)).await?;
Ok(())
}
@ -145,16 +139,23 @@ async fn run_http(
auth_controller: Arc<AuthController>,
opt: Opt,
logs: (LogRouteHandle, LogStderrHandle),
analytics: Arc<dyn Analytics>,
analytics: Arc<Analytics>,
) -> anyhow::Result<()> {
let enable_dashboard = &opt.env == "development";
let opt_clone = opt.clone();
let index_scheduler = Data::from(index_scheduler);
let auth_controller = Data::from(auth_controller);
let analytics = Data::from(analytics);
let search_queue = SearchQueue::new(
opt.experimental_search_queue_size,
available_parallelism().unwrap_or(NonZeroUsize::new(2).unwrap()),
);
available_parallelism()
.unwrap_or(NonZeroUsize::new(2).unwrap())
.checked_mul(opt.experimental_nb_searches_per_core)
.unwrap_or(NonZeroUsize::MAX),
)
.with_time_to_abort(Duration::from_secs(
usize::from(opt.experimental_drop_search_after) as u64
));
let search_queue = Data::new(search_queue);
let http_server = HttpServer::new(move || {
@ -180,11 +181,7 @@ async fn run_http(
Ok(())
}
pub fn print_launch_resume(
opt: &Opt,
analytics: Arc<dyn Analytics>,
config_read_from: Option<PathBuf>,
) {
pub fn print_launch_resume(opt: &Opt, analytics: Analytics, config_read_from: Option<PathBuf>) {
let build_info = build_info::BuildInfo::from_build();
let protocol =
@ -226,7 +223,6 @@ pub fn print_launch_resume(
eprintln!("Prototype:\t\t{:?}", prototype);
}
#[cfg(all(not(debug_assertions), feature = "analytics"))]
{
if !opt.no_analytics {
eprintln!(

55
crates/meilisearch/src/option.rs
View File

@ -2,7 +2,7 @@ use std::env::VarError;
use std::ffi::OsStr;
use std::fmt::Display;
use std::io::{BufReader, Read};
use std::num::ParseIntError;
use std::num::{NonZeroUsize, ParseIntError};
use std::ops::Deref;
use std::path::PathBuf;
use std::str::FromStr;
@ -29,7 +29,6 @@ const MEILI_MASTER_KEY: &str = "MEILI_MASTER_KEY";
const MEILI_ENV: &str = "MEILI_ENV";
const MEILI_TASK_WEBHOOK_URL: &str = "MEILI_TASK_WEBHOOK_URL";
const MEILI_TASK_WEBHOOK_AUTHORIZATION_HEADER: &str = "MEILI_TASK_WEBHOOK_AUTHORIZATION_HEADER";
#[cfg(feature = "analytics")]
const MEILI_NO_ANALYTICS: &str = "MEILI_NO_ANALYTICS";
const MEILI_HTTP_PAYLOAD_SIZE_LIMIT: &str = "MEILI_HTTP_PAYLOAD_SIZE_LIMIT";
const MEILI_SSL_CERT_PATH: &str = "MEILI_SSL_CERT_PATH";
@ -55,6 +54,8 @@ const MEILI_EXPERIMENTAL_ENABLE_LOGS_ROUTE: &str = "MEILI_EXPERIMENTAL_ENABLE_LO
const MEILI_EXPERIMENTAL_CONTAINS_FILTER: &str = "MEILI_EXPERIMENTAL_CONTAINS_FILTER";
const MEILI_EXPERIMENTAL_ENABLE_METRICS: &str = "MEILI_EXPERIMENTAL_ENABLE_METRICS";
const MEILI_EXPERIMENTAL_SEARCH_QUEUE_SIZE: &str = "MEILI_EXPERIMENTAL_SEARCH_QUEUE_SIZE";
const MEILI_EXPERIMENTAL_DROP_SEARCH_AFTER: &str = "MEILI_EXPERIMENTAL_DROP_SEARCH_AFTER";
const MEILI_EXPERIMENTAL_NB_SEARCHES_PER_CORE: &str = "MEILI_EXPERIMENTAL_NB_SEARCHES_PER_CORE";
const MEILI_EXPERIMENTAL_REDUCE_INDEXING_MEMORY_USAGE: &str =
"MEILI_EXPERIMENTAL_REDUCE_INDEXING_MEMORY_USAGE";
const MEILI_EXPERIMENTAL_MAX_NUMBER_OF_BATCHED_TASKS: &str =
@ -208,7 +209,6 @@ pub struct Opt {
/// Meilisearch automatically collects data from all instances that do not opt out using this flag.
/// All gathered data is used solely for the purpose of improving Meilisearch, and can be deleted
/// at any time.
#[cfg(feature = "analytics")]
#[serde(default)] // we can't send true
#[clap(long, env = MEILI_NO_ANALYTICS)]
pub no_analytics: bool,
@ -357,10 +357,26 @@ pub struct Opt {
/// Lets you customize the size of the search queue. Meilisearch processes your search requests as fast as possible but once the
/// queue is full it starts returning HTTP 503, Service Unavailable.
/// The default value is 1000.
#[clap(long, env = MEILI_EXPERIMENTAL_SEARCH_QUEUE_SIZE, default_value_t = 1000)]
#[serde(default)]
#[clap(long, env = MEILI_EXPERIMENTAL_SEARCH_QUEUE_SIZE, default_value_t = default_experimental_search_queue_size())]
#[serde(default = "default_experimental_search_queue_size")]
pub experimental_search_queue_size: usize,
/// Experimental drop search after. For more information, see: <https://github.com/orgs/meilisearch/discussions/783>
///
/// Let you customize after how many seconds Meilisearch should consider a search request irrelevant and drop it.
/// The default value is 60.
#[clap(long, env = MEILI_EXPERIMENTAL_DROP_SEARCH_AFTER, default_value_t = default_drop_search_after())]
#[serde(default = "default_drop_search_after")]
pub experimental_drop_search_after: NonZeroUsize,
/// Experimental number of searches per core. For more information, see: <https://github.com/orgs/meilisearch/discussions/784>
///
/// Lets you customize how many search requests can run on each core concurrently.
/// The default value is 4.
#[clap(long, env = MEILI_EXPERIMENTAL_NB_SEARCHES_PER_CORE, default_value_t = default_nb_searches_per_core())]
#[serde(default = "default_nb_searches_per_core")]
pub experimental_nb_searches_per_core: NonZeroUsize,
/// Experimental logs mode feature. For more information, see: <https://github.com/orgs/meilisearch/discussions/723>
///
/// Change the mode of the logs on the console.
@ -407,7 +423,6 @@ pub struct Opt {
impl Opt {
/// Whether analytics should be enabled or not.
#[cfg(all(not(debug_assertions), feature = "analytics"))]
pub fn analytics(&self) -> bool {
!self.no_analytics
}
@ -487,11 +502,12 @@ impl Opt {
ignore_missing_dump: _,
ignore_dump_if_db_exists: _,
config_file_path: _,
#[cfg(feature = "analytics")]
no_analytics,
experimental_contains_filter,
experimental_enable_metrics,
experimental_search_queue_size,
experimental_drop_search_after,
experimental_nb_searches_per_core,
experimental_logs_mode,
experimental_enable_logs_route,
experimental_replication_parameters,
@ -513,10 +529,7 @@ impl Opt {
);
}
#[cfg(feature = "analytics")]
{
export_to_env_if_not_present(MEILI_NO_ANALYTICS, no_analytics.to_string());
}
export_to_env_if_not_present(MEILI_NO_ANALYTICS, no_analytics.to_string());
export_to_env_if_not_present(
MEILI_HTTP_PAYLOAD_SIZE_LIMIT,
http_payload_size_limit.to_string(),
@ -559,6 +572,14 @@ impl Opt {
MEILI_EXPERIMENTAL_SEARCH_QUEUE_SIZE,
experimental_search_queue_size.to_string(),
);
export_to_env_if_not_present(
MEILI_EXPERIMENTAL_DROP_SEARCH_AFTER,
experimental_drop_search_after.to_string(),
);
export_to_env_if_not_present(
MEILI_EXPERIMENTAL_NB_SEARCHES_PER_CORE,
experimental_nb_searches_per_core.to_string(),
);
export_to_env_if_not_present(
MEILI_EXPERIMENTAL_LOGS_MODE,
experimental_logs_mode.to_string(),
@ -890,6 +911,18 @@ fn default_dump_dir() -> PathBuf {
PathBuf::from(DEFAULT_DUMP_DIR)
}
fn default_experimental_search_queue_size() -> usize {
1000
}
fn default_drop_search_after() -> NonZeroUsize {
NonZeroUsize::new(60).unwrap()
}
fn default_nb_searches_per_core() -> NonZeroUsize {
NonZeroUsize::new(4).unwrap()
}
/// Indicates if a snapshot was scheduled, and if yes with which interval.
#[derive(Debug, Default, Copy, Clone, Deserialize, Serialize)]
pub enum ScheduleSnapshot {

7
crates/meilisearch/src/routes/dump.rs
View File

@ -4,7 +4,6 @@ use index_scheduler::IndexScheduler;
use meilisearch_auth::AuthController;
use meilisearch_types::error::ResponseError;
use meilisearch_types::tasks::KindWithContent;
use serde_json::json;
use tracing::debug;
use crate::analytics::Analytics;
@ -18,14 +17,16 @@ pub fn configure(cfg: &mut web::ServiceConfig) {
cfg.service(web::resource("").route(web::post().to(SeqHandler(create_dump))));
}
crate::empty_analytics!(DumpAnalytics, "Dump Created");
pub async fn create_dump(
index_scheduler: GuardedData<ActionPolicy<{ actions::DUMPS_CREATE }>, Data<IndexScheduler>>,
auth_controller: GuardedData<ActionPolicy<{ actions::DUMPS_CREATE }>, Data<AuthController>>,
req: HttpRequest,
opt: web::Data<Opt>,
analytics: web::Data<dyn Analytics>,
analytics: web::Data<Analytics>,
) -> Result<HttpResponse, ResponseError> {
analytics.publish("Dump Created".to_string(), json!({}), Some(&req));
analytics.publish(DumpAnalytics::default(), &req);
let task = KindWithContent::DumpCreation {
keys: auth_controller.list_keys()?,

57
crates/meilisearch/src/routes/features.rs
View File

@ -6,10 +6,10 @@ use index_scheduler::IndexScheduler;
use meilisearch_types::deserr::DeserrJsonError;
use meilisearch_types::error::ResponseError;
use meilisearch_types::keys::actions;
use serde_json::json;
use serde::Serialize;
use tracing::debug;
use crate::analytics::Analytics;
use crate::analytics::{Aggregate, Analytics};
use crate::extractors::authentication::policies::ActionPolicy;
use crate::extractors::authentication::GuardedData;
use crate::extractors::sequential_extractor::SeqHandler;
@ -17,7 +17,7 @@ use crate::extractors::sequential_extractor::SeqHandler;
pub fn configure(cfg: &mut web::ServiceConfig) {
cfg.service(
web::resource("")
.route(web::get().to(SeqHandler(get_features)))
.route(web::get().to(get_features))
.route(web::patch().to(SeqHandler(patch_features))),
);
}
@ -27,12 +27,9 @@ async fn get_features(
ActionPolicy<{ actions::EXPERIMENTAL_FEATURES_GET }>,
Data<IndexScheduler>,
>,
req: HttpRequest,
analytics: Data<dyn Analytics>,
) -> HttpResponse {
let features = index_scheduler.features();
analytics.publish("Experimental features Seen".to_string(), json!(null), Some(&req));
let features = features.runtime_features();
debug!(returns = ?features, "Get features");
HttpResponse::Ok().json(features)
@ -53,6 +50,35 @@ pub struct RuntimeTogglableFeatures {
pub contains_filter: Option<bool>,
}
#[derive(Serialize)]
pub struct PatchExperimentalFeatureAnalytics {
vector_store: bool,
metrics: bool,
logs_route: bool,
edit_documents_by_function: bool,
contains_filter: bool,
}
impl Aggregate for PatchExperimentalFeatureAnalytics {
fn event_name(&self) -> &'static str {
"Experimental features Updated"
}
fn aggregate(self: Box<Self>, new: Box<Self>) -> Box<Self> {
Box::new(Self {
vector_store: new.vector_store,
metrics: new.metrics,
logs_route: new.logs_route,
edit_documents_by_function: new.edit_documents_by_function,
contains_filter: new.contains_filter,
})
}
fn into_event(self: Box<Self>) -> serde_json::Value {
serde_json::to_value(*self).unwrap_or_default()
}
}
async fn patch_features(
index_scheduler: GuardedData<
ActionPolicy<{ actions::EXPERIMENTAL_FEATURES_UPDATE }>,
@ -60,7 +86,7 @@ async fn patch_features(
>,
new_features: AwebJson<RuntimeTogglableFeatures, DeserrJsonError>,
req: HttpRequest,
analytics: Data<dyn Analytics>,
analytics: Data<Analytics>,
) -> Result<HttpResponse, ResponseError> {
let features = index_scheduler.features();
debug!(parameters = ?new_features, "Patch features");
@ -89,15 +115,14 @@ async fn patch_features(
} = new_features;
analytics.publish(
"Experimental features Updated".to_string(),
json!({
"vector_store": vector_store,
"metrics": metrics,
"logs_route": logs_route,
"edit_documents_by_function": edit_documents_by_function,
"contains_filter": contains_filter,
}),
Some(&req),
PatchExperimentalFeatureAnalytics {
vector_store,
metrics,
logs_route,
edit_documents_by_function,
contains_filter,
},
&req,
);
index_scheduler.put_runtime_features(new_features)?;
debug!(returns = ?new_features, "Patch features");

316
crates/meilisearch/src/routes/indexes/documents.rs
View File

@ -1,4 +1,6 @@
use std::collections::HashSet;
use std::io::ErrorKind;
use std::marker::PhantomData;
use actix_web::http::header::CONTENT_TYPE;
use actix_web::web::Data;
@ -23,14 +25,14 @@ use meilisearch_types::tasks::KindWithContent;
use meilisearch_types::{milli, Document, Index};
use mime::Mime;
use once_cell::sync::Lazy;
use serde::Deserialize;
use serde::{Deserialize, Serialize};
use serde_json::Value;
use tempfile::tempfile;
use tokio::fs::File;
use tokio::io::{AsyncSeekExt, AsyncWriteExt, BufWriter};
use tracing::debug;
use crate::analytics::{Analytics, DocumentDeletionKind, DocumentFetchKind};
use crate::analytics::{Aggregate, AggregateMethod, Analytics};
use crate::error::MeilisearchHttpError;
use crate::error::PayloadError::ReceivePayload;
use crate::extractors::authentication::policies::*;
@ -41,7 +43,7 @@ use crate::routes::{
get_task_id, is_dry_run, PaginationView, SummarizedTaskView, PAGINATION_DEFAULT_LIMIT,
};
use crate::search::{parse_filter, RetrieveVectors};
use crate::Opt;
use crate::{aggregate_methods, Opt};
static ACCEPTED_CONTENT_TYPE: Lazy<Vec<String>> = Lazy::new(|| {
vec!["application/json".to_string(), "application/x-ndjson".to_string(), "text/csv".to_string()]
@ -100,12 +102,84 @@ pub struct GetDocument {
retrieve_vectors: Param<bool>,
}
aggregate_methods!(
DocumentsGET => "Documents Fetched GET",
DocumentsPOST => "Documents Fetched POST",
);
#[derive(Serialize)]
pub struct DocumentsFetchAggregator<Method: AggregateMethod> {
// a call on ../documents/:doc_id
per_document_id: bool,
// if a filter was used
per_filter: bool,
#[serde(rename = "vector.retrieve_vectors")]
retrieve_vectors: bool,
// pagination
#[serde(rename = "pagination.max_limit")]
max_limit: usize,
#[serde(rename = "pagination.max_offset")]
max_offset: usize,
marker: std::marker::PhantomData<Method>,
}
#[derive(Copy, Clone, Debug, PartialEq, Eq)]
pub enum DocumentFetchKind {
PerDocumentId { retrieve_vectors: bool },
Normal { with_filter: bool, limit: usize, offset: usize, retrieve_vectors: bool },
}
impl<Method: AggregateMethod> DocumentsFetchAggregator<Method> {
pub fn from_query(query: &DocumentFetchKind) -> Self {
let (limit, offset, retrieve_vectors) = match query {
DocumentFetchKind::PerDocumentId { retrieve_vectors } => (1, 0, *retrieve_vectors),
DocumentFetchKind::Normal { limit, offset, retrieve_vectors, .. } => {
(*limit, *offset, *retrieve_vectors)
}
};
Self {
per_document_id: matches!(query, DocumentFetchKind::PerDocumentId { .. }),
per_filter: matches!(query, DocumentFetchKind::Normal { with_filter, .. } if *with_filter),
max_limit: limit,
max_offset: offset,
retrieve_vectors,
marker: PhantomData,
}
}
}
impl<Method: AggregateMethod> Aggregate for DocumentsFetchAggregator<Method> {
fn event_name(&self) -> &'static str {
Method::event_name()
}
fn aggregate(self: Box<Self>, new: Box<Self>) -> Box<Self> {
Box::new(Self {
per_document_id: self.per_document_id | new.per_document_id,
per_filter: self.per_filter | new.per_filter,
retrieve_vectors: self.retrieve_vectors | new.retrieve_vectors,
max_limit: self.max_limit.max(new.max_limit),
max_offset: self.max_offset.max(new.max_offset),
marker: PhantomData,
})
}
fn into_event(self: Box<Self>) -> serde_json::Value {
serde_json::to_value(*self).unwrap_or_default()
}
}
pub async fn get_document(
index_scheduler: GuardedData<ActionPolicy<{ actions::DOCUMENTS_GET }>, Data<IndexScheduler>>,
document_param: web::Path<DocumentParam>,
params: AwebQueryParameter<GetDocument, DeserrQueryParamError>,
req: HttpRequest,
analytics: web::Data<dyn Analytics>,
analytics: web::Data<Analytics>,
) -> Result<HttpResponse, ResponseError> {
let DocumentParam { index_uid, document_id } = document_param.into_inner();
debug!(parameters = ?params, "Get document");
@ -117,8 +191,15 @@ pub async fn get_document(
let features = index_scheduler.features();
let retrieve_vectors = RetrieveVectors::new(param_retrieve_vectors.0, features)?;
analytics.get_fetch_documents(
&DocumentFetchKind::PerDocumentId { retrieve_vectors: param_retrieve_vectors.0 },
analytics.publish(
DocumentsFetchAggregator::<DocumentsGET> {
retrieve_vectors: param_retrieve_vectors.0,
per_document_id: true,
per_filter: false,
max_limit: 0,
max_offset: 0,
marker: PhantomData,
},
&req,
);
@ -129,17 +210,52 @@ pub async fn get_document(
Ok(HttpResponse::Ok().json(document))
}
#[derive(Serialize)]
pub struct DocumentsDeletionAggregator {
per_document_id: bool,
clear_all: bool,
per_batch: bool,
per_filter: bool,
}
impl Aggregate for DocumentsDeletionAggregator {
fn event_name(&self) -> &'static str {
"Documents Deleted"
}
fn aggregate(self: Box<Self>, new: Box<Self>) -> Box<Self> {
Box::new(Self {
per_document_id: self.per_document_id | new.per_document_id,
clear_all: self.clear_all | new.clear_all,
per_batch: self.per_batch | new.per_batch,
per_filter: self.per_filter | new.per_filter,
})
}
fn into_event(self: Box<Self>) -> serde_json::Value {
serde_json::to_value(*self).unwrap_or_default()
}
}
pub async fn delete_document(
index_scheduler: GuardedData<ActionPolicy<{ actions::DOCUMENTS_DELETE }>, Data<IndexScheduler>>,
path: web::Path<DocumentParam>,
req: HttpRequest,
opt: web::Data<Opt>,
analytics: web::Data<dyn Analytics>,
analytics: web::Data<Analytics>,
) -> Result<HttpResponse, ResponseError> {
let DocumentParam { index_uid, document_id } = path.into_inner();
let index_uid = IndexUid::try_from(index_uid)?;
analytics.delete_documents(DocumentDeletionKind::PerDocumentId, &req);
analytics.publish(
DocumentsDeletionAggregator {
per_document_id: true,
clear_all: false,
per_batch: false,
per_filter: false,
},
&req,
);
let task = KindWithContent::DocumentDeletion {
index_uid: index_uid.to_string(),
@ -190,17 +306,19 @@ pub async fn documents_by_query_post(
index_uid: web::Path<String>,
body: AwebJson<BrowseQuery, DeserrJsonError>,
req: HttpRequest,
analytics: web::Data<dyn Analytics>,
analytics: web::Data<Analytics>,
) -> Result<HttpResponse, ResponseError> {
let body = body.into_inner();
debug!(parameters = ?body, "Get documents POST");
analytics.post_fetch_documents(
&DocumentFetchKind::Normal {
with_filter: body.filter.is_some(),
limit: body.limit,
offset: body.offset,
analytics.publish(
DocumentsFetchAggregator::<DocumentsPOST> {
per_filter: body.filter.is_some(),
retrieve_vectors: body.retrieve_vectors,
max_limit: body.limit,
max_offset: body.offset,
per_document_id: false,
marker: PhantomData,
},
&req,
);
@ -213,7 +331,7 @@ pub async fn get_documents(
index_uid: web::Path<String>,
params: AwebQueryParameter<BrowseQueryGet, DeserrQueryParamError>,
req: HttpRequest,
analytics: web::Data<dyn Analytics>,
analytics: web::Data<Analytics>,
) -> Result<HttpResponse, ResponseError> {
debug!(parameters = ?params, "Get documents GET");
@ -235,12 +353,14 @@ pub async fn get_documents(
filter,
};
analytics.get_fetch_documents(
&DocumentFetchKind::Normal {
with_filter: query.filter.is_some(),
limit: query.limit,
offset: query.offset,
analytics.publish(
DocumentsFetchAggregator::<DocumentsGET> {
per_filter: query.filter.is_some(),
retrieve_vectors: query.retrieve_vectors,
max_limit: query.limit,
max_offset: query.offset,
per_document_id: false,
marker: PhantomData,
},
&req,
);
@ -298,6 +418,39 @@ fn from_char_csv_delimiter(
}
}
aggregate_methods!(
Replaced => "Documents Added",
Updated => "Documents Updated",
);
#[derive(Serialize)]
pub struct DocumentsAggregator<T: AggregateMethod> {
payload_types: HashSet<String>,
primary_key: HashSet<String>,
index_creation: bool,
#[serde(skip)]
method: PhantomData<T>,
}
impl<Method: AggregateMethod> Aggregate for DocumentsAggregator<Method> {
fn event_name(&self) -> &'static str {
Method::event_name()
}
fn aggregate(self: Box<Self>, new: Box<Self>) -> Box<Self> {
Box::new(Self {
payload_types: self.payload_types.union(&new.payload_types).cloned().collect(),
primary_key: self.primary_key.union(&new.primary_key).cloned().collect(),
index_creation: self.index_creation | new.index_creation,
method: PhantomData,
})
}
fn into_event(self: Box<Self>) -> serde_json::Value {
serde_json::to_value(self).unwrap_or_default()
}
}
pub async fn replace_documents(
index_scheduler: GuardedData<ActionPolicy<{ actions::DOCUMENTS_ADD }>, Data<IndexScheduler>>,
index_uid: web::Path<String>,
@ -305,16 +458,32 @@ pub async fn replace_documents(
body: Payload,
req: HttpRequest,
opt: web::Data<Opt>,
analytics: web::Data<dyn Analytics>,
analytics: web::Data<Analytics>,
) -> Result<HttpResponse, ResponseError> {
let index_uid = IndexUid::try_from(index_uid.into_inner())?;
debug!(parameters = ?params, "Replace documents");
let params = params.into_inner();
analytics.add_documents(
&params,
index_scheduler.index_exists(&index_uid).map_or(true, |x| !x),
let mut content_types = HashSet::new();
let content_type = req
.headers()
.get(CONTENT_TYPE)
.and_then(|s| s.to_str().ok())
.unwrap_or("unknown")
.to_string();
content_types.insert(content_type);
let mut primary_keys = HashSet::new();
if let Some(primary_key) = params.primary_key.clone() {
primary_keys.insert(primary_key);
}
analytics.publish(
DocumentsAggregator::<Replaced> {
payload_types: content_types,
primary_key: primary_keys,
index_creation: index_scheduler.index_exists(&index_uid).map_or(true, |x| !x),
method: PhantomData,
},
&req,
);
@ -346,16 +515,32 @@ pub async fn update_documents(
body: Payload,
req: HttpRequest,
opt: web::Data<Opt>,
analytics: web::Data<dyn Analytics>,
analytics: web::Data<Analytics>,
) -> Result<HttpResponse, ResponseError> {
let index_uid = IndexUid::try_from(index_uid.into_inner())?;
let params = params.into_inner();
debug!(parameters = ?params, "Update documents");
analytics.add_documents(
&params,
index_scheduler.index_exists(&index_uid).map_or(true, |x| !x),
let mut content_types = HashSet::new();
let content_type = req
.headers()
.get(CONTENT_TYPE)
.and_then(|s| s.to_str().ok())
.unwrap_or("unknown")
.to_string();
content_types.insert(content_type);
let mut primary_keys = HashSet::new();
if let Some(primary_key) = params.primary_key.clone() {
primary_keys.insert(primary_key);
}
analytics.publish(
DocumentsAggregator::<Updated> {
payload_types: content_types,
primary_key: primary_keys,
index_creation: index_scheduler.index_exists(&index_uid).map_or(true, |x| !x),
method: PhantomData,
},
&req,
);
@ -524,12 +709,20 @@ pub async fn delete_documents_batch(
body: web::Json<Vec<Value>>,
req: HttpRequest,
opt: web::Data<Opt>,
analytics: web::Data<dyn Analytics>,
analytics: web::Data<Analytics>,
) -> Result<HttpResponse, ResponseError> {
debug!(parameters = ?body, "Delete documents by batch");
let index_uid = IndexUid::try_from(index_uid.into_inner())?;
analytics.delete_documents(DocumentDeletionKind::PerBatch, &req);
analytics.publish(
DocumentsDeletionAggregator {
per_batch: true,
per_document_id: false,
clear_all: false,
per_filter: false,
},
&req,
);
let ids = body
.iter()
@ -562,14 +755,22 @@ pub async fn delete_documents_by_filter(
body: AwebJson<DocumentDeletionByFilter, DeserrJsonError>,
req: HttpRequest,
opt: web::Data<Opt>,
analytics: web::Data<dyn Analytics>,
analytics: web::Data<Analytics>,
) -> Result<HttpResponse, ResponseError> {
debug!(parameters = ?body, "Delete documents by filter");
let index_uid = IndexUid::try_from(index_uid.into_inner())?;
let index_uid = index_uid.into_inner();
let filter = body.into_inner().filter;
analytics.delete_documents(DocumentDeletionKind::PerFilter, &req);
analytics.publish(
DocumentsDeletionAggregator {
per_filter: true,
per_document_id: false,
clear_all: false,
per_batch: false,
},
&req,
);
// we ensure the filter is well formed before enqueuing it
crate::search::parse_filter(&filter, Code::InvalidDocumentFilter, index_scheduler.features())?
@ -599,13 +800,41 @@ pub struct DocumentEditionByFunction {
pub function: String,
}
#[derive(Serialize)]
struct EditDocumentsByFunctionAggregator {
// Set to true if at least one request was filtered
filtered: bool,
// Set to true if at least one request contained a context
with_context: bool,
index_creation: bool,
}
impl Aggregate for EditDocumentsByFunctionAggregator {
fn event_name(&self) -> &'static str {
"Documents Edited By Function"
}
fn aggregate(self: Box<Self>, new: Box<Self>) -> Box<Self> {
Box::new(Self {
filtered: self.filtered | new.filtered,
with_context: self.with_context | new.with_context,
index_creation: self.index_creation | new.index_creation,
})
}
fn into_event(self: Box<Self>) -> serde_json::Value {
serde_json::to_value(*self).unwrap_or_default()
}
}
pub async fn edit_documents_by_function(
index_scheduler: GuardedData<ActionPolicy<{ actions::DOCUMENTS_ALL }>, Data<IndexScheduler>>,
index_uid: web::Path<String>,
params: AwebJson<DocumentEditionByFunction, DeserrJsonError>,
req: HttpRequest,
opt: web::Data<Opt>,
analytics: web::Data<dyn Analytics>,
analytics: web::Data<Analytics>,
) -> Result<HttpResponse, ResponseError> {
debug!(parameters = ?params, "Edit documents by function");
@ -617,9 +846,12 @@ pub async fn edit_documents_by_function(
let index_uid = index_uid.into_inner();
let params = params.into_inner();
analytics.update_documents_by_function(
&params,
index_scheduler.index(&index_uid).is_err(),
analytics.publish(
EditDocumentsByFunctionAggregator {
filtered: params.filter.is_some(),
with_context: params.context.is_some(),
index_creation: index_scheduler.index(&index_uid).is_err(),
},
&req,
);
@ -670,10 +902,18 @@ pub async fn clear_all_documents(
index_uid: web::Path<String>,
req: HttpRequest,
opt: web::Data<Opt>,
analytics: web::Data<dyn Analytics>,
analytics: web::Data<Analytics>,
) -> Result<HttpResponse, ResponseError> {
let index_uid = IndexUid::try_from(index_uid.into_inner())?;
analytics.delete_documents(DocumentDeletionKind::ClearAll, &req);
analytics.publish(
DocumentsDeletionAggregator {
clear_all: true,
per_document_id: false,
per_batch: false,
per_filter: false,
},
&req,
);
let task = KindWithContent::DocumentClear { index_uid: index_uid.to_string() };
let uid = get_task_id(&req, &opt)?;

119
crates/meilisearch/src/routes/indexes/facet_search.rs
View File

@ -1,3 +1,5 @@
use std::collections::{BinaryHeap, HashSet};
use actix_web::web::Data;
use actix_web::{web, HttpRequest, HttpResponse};
use deserr::actix_web::AwebJson;
@ -10,14 +12,15 @@ use meilisearch_types::locales::Locale;
use serde_json::Value;
use tracing::debug;
use crate::analytics::{Analytics, FacetSearchAggregator};
use crate::analytics::{Aggregate, Analytics};
use crate::extractors::authentication::policies::*;
use crate::extractors::authentication::GuardedData;
use crate::routes::indexes::search::search_kind;
use crate::search::{
add_search_rules, perform_facet_search, HybridQuery, MatchingStrategy, RankingScoreThreshold,
SearchQuery, DEFAULT_CROP_LENGTH, DEFAULT_CROP_MARKER, DEFAULT_HIGHLIGHT_POST_TAG,
DEFAULT_HIGHLIGHT_PRE_TAG, DEFAULT_SEARCH_LIMIT, DEFAULT_SEARCH_OFFSET,
add_search_rules, perform_facet_search, FacetSearchResult, HybridQuery, MatchingStrategy,
RankingScoreThreshold, SearchQuery, DEFAULT_CROP_LENGTH, DEFAULT_CROP_MARKER,
DEFAULT_HIGHLIGHT_POST_TAG, DEFAULT_HIGHLIGHT_PRE_TAG, DEFAULT_SEARCH_LIMIT,
DEFAULT_SEARCH_OFFSET,
};
use crate::search_queue::SearchQueue;
@ -53,20 +56,122 @@ pub struct FacetSearchQuery {
pub locales: Option<Vec<Locale>>,
}
#[derive(Default)]
pub struct FacetSearchAggregator {
// requests
total_received: usize,
total_succeeded: usize,
time_spent: BinaryHeap<usize>,
// The set of all facetNames that were used
facet_names: HashSet<String>,
// As there been any other parameter than the facetName or facetQuery ones?
additional_search_parameters_provided: bool,
}
impl FacetSearchAggregator {
#[allow(clippy::field_reassign_with_default)]
pub fn from_query(query: &FacetSearchQuery) -> Self {
let FacetSearchQuery {
facet_query: _,
facet_name,
vector,
q,
filter,
matching_strategy,
attributes_to_search_on,
hybrid,
ranking_score_threshold,
locales,
} = query;
Self {
total_received: 1,
facet_names: Some(facet_name.clone()).into_iter().collect(),
additional_search_parameters_provided: q.is_some()
|| vector.is_some()
|| filter.is_some()
|| *matching_strategy != MatchingStrategy::default()
|| attributes_to_search_on.is_some()
|| hybrid.is_some()
|| ranking_score_threshold.is_some()
|| locales.is_some(),
..Default::default()
}
}
pub fn succeed(&mut self, result: &FacetSearchResult) {
let FacetSearchResult { facet_hits: _, facet_query: _, processing_time_ms } = result;
self.total_succeeded = 1;
self.time_spent.push(*processing_time_ms as usize);
}
}
impl Aggregate for FacetSearchAggregator {
fn event_name(&self) -> &'static str {
"Facet Searched POST"
}
fn aggregate(mut self: Box<Self>, new: Box<Self>) -> Box<Self> {
for time in new.time_spent {
self.time_spent.push(time);
}
Box::new(Self {
total_received: self.total_received.saturating_add(new.total_received),
total_succeeded: self.total_succeeded.saturating_add(new.total_succeeded),
time_spent: self.time_spent,
facet_names: self.facet_names.union(&new.facet_names).cloned().collect(),
additional_search_parameters_provided: self.additional_search_parameters_provided
| new.additional_search_parameters_provided,
})
}
fn into_event(self: Box<Self>) -> serde_json::Value {
let Self {
total_received,
total_succeeded,
time_spent,
facet_names,
additional_search_parameters_provided,
} = *self;
// the index of the 99th percentage of value
let percentile_99th = 0.99 * (total_succeeded as f64 - 1.) + 1.;
// we get all the values in a sorted manner
let time_spent = time_spent.into_sorted_vec();
// We are only interested by the slowest value of the 99th fastest results
let time_spent = time_spent.get(percentile_99th as usize);
serde_json::json!({
"requests": {
"99th_response_time": time_spent.map(|t| format!("{:.2}", t)),
"total_succeeded": total_succeeded,
"total_failed": total_received.saturating_sub(total_succeeded), // just to be sure we never panics
"total_received": total_received,
},
"facets": {
"total_distinct_facet_count": facet_names.len(),
"additional_search_parameters_provided": additional_search_parameters_provided,
},
})
}
}
pub async fn search(
index_scheduler: GuardedData<ActionPolicy<{ actions::SEARCH }>, Data<IndexScheduler>>,
search_queue: Data<SearchQueue>,
index_uid: web::Path<String>,
params: AwebJson<FacetSearchQuery, DeserrJsonError>,
req: HttpRequest,
analytics: web::Data<dyn Analytics>,
analytics: web::Data<Analytics>,
) -> Result<HttpResponse, ResponseError> {
let index_uid = IndexUid::try_from(index_uid.into_inner())?;
let query = params.into_inner();
debug!(parameters = ?query, "Facet search");
let mut aggregate = FacetSearchAggregator::from_query(&query, &req);
let mut aggregate = FacetSearchAggregator::from_query(&query);
let facet_query = query.facet_query.clone();
let facet_name = query.facet_name.clone();
@ -100,7 +205,7 @@ pub async fn search(
if let Ok(ref search_result) = search_result {
aggregate.succeed(search_result);
}
analytics.post_facet_search(aggregate);
analytics.publish(aggregate, &req);
let search_result = search_result?;

58
crates/meilisearch/src/routes/indexes/mod.rs
View File

@ -1,3 +1,4 @@
use std::collections::BTreeSet;
use std::convert::Infallible;
use actix_web::web::Data;
@ -13,12 +14,11 @@ use meilisearch_types::index_uid::IndexUid;
use meilisearch_types::milli::{self, FieldDistribution, Index};
use meilisearch_types::tasks::KindWithContent;
use serde::Serialize;
use serde_json::json;
use time::OffsetDateTime;
use tracing::debug;
use super::{get_task_id, Pagination, SummarizedTaskView, PAGINATION_DEFAULT_LIMIT};
use crate::analytics::Analytics;
use crate::analytics::{Aggregate, Analytics};
use crate::extractors::authentication::policies::*;
use crate::extractors::authentication::{AuthenticationError, GuardedData};
use crate::extractors::sequential_extractor::SeqHandler;
@ -28,8 +28,11 @@ use crate::Opt;
pub mod documents;
pub mod facet_search;
pub mod search;
mod search_analytics;
pub mod settings;
mod settings_analytics;
pub mod similar;
mod similar_analytics;
pub fn configure(cfg: &mut web::ServiceConfig) {
cfg.service(
@ -123,12 +126,31 @@ pub struct IndexCreateRequest {
primary_key: Option<String>,
}
#[derive(Serialize)]
struct IndexCreatedAggregate {
primary_key: BTreeSet<String>,
}
impl Aggregate for IndexCreatedAggregate {
fn event_name(&self) -> &'static str {
"Index Created"
}
fn aggregate(self: Box<Self>, new: Box<Self>) -> Box<Self> {
Box::new(Self { primary_key: self.primary_key.union(&new.primary_key).cloned().collect() })
}
fn into_event(self: Box<Self>) -> serde_json::Value {
serde_json::to_value(*self).unwrap_or_default()
}
}
pub async fn create_index(
index_scheduler: GuardedData<ActionPolicy<{ actions::INDEXES_CREATE }>, Data<IndexScheduler>>,
body: AwebJson<IndexCreateRequest, DeserrJsonError>,
req: HttpRequest,
opt: web::Data<Opt>,
analytics: web::Data<dyn Analytics>,
analytics: web::Data<Analytics>,
) -> Result<HttpResponse, ResponseError> {
debug!(parameters = ?body, "Create index");
let IndexCreateRequest { primary_key, uid } = body.into_inner();
@ -136,9 +158,8 @@ pub async fn create_index(
let allow_index_creation = index_scheduler.filters().allow_index_creation(&uid);
if allow_index_creation {
analytics.publish(
"Index Created".to_string(),
json!({ "primary_key": primary_key }),
Some(&req),
IndexCreatedAggregate { primary_key: primary_key.iter().cloned().collect() },
&req,
);
let task = KindWithContent::IndexCreation { index_uid: uid.to_string(), primary_key };
@ -194,21 +215,38 @@ pub async fn get_index(
Ok(HttpResponse::Ok().json(index_view))
}
#[derive(Serialize)]
struct IndexUpdatedAggregate {
primary_key: BTreeSet<String>,
}
impl Aggregate for IndexUpdatedAggregate {
fn event_name(&self) -> &'static str {
"Index Updated"
}
fn aggregate(self: Box<Self>, new: Box<Self>) -> Box<Self> {
Box::new(Self { primary_key: self.primary_key.union(&new.primary_key).cloned().collect() })
}
fn into_event(self: Box<Self>) -> serde_json::Value {
serde_json::to_value(*self).unwrap_or_default()
}
}
pub async fn update_index(
index_scheduler: GuardedData<ActionPolicy<{ actions::INDEXES_UPDATE }>, Data<IndexScheduler>>,
index_uid: web::Path<String>,
body: AwebJson<UpdateIndexRequest, DeserrJsonError>,
req: HttpRequest,
opt: web::Data<Opt>,
analytics: web::Data<dyn Analytics>,
analytics: web::Data<Analytics>,
) -> Result<HttpResponse, ResponseError> {
debug!(parameters = ?body, "Update index");
let index_uid = IndexUid::try_from(index_uid.into_inner())?;
let body = body.into_inner();
analytics.publish(
"Index Updated".to_string(),
json!({ "primary_key": body.primary_key }),
Some(&req),
IndexUpdatedAggregate { primary_key: body.primary_key.iter().cloned().collect() },
&req,
);
let task = KindWithContent::IndexUpdate {

15
crates/meilisearch/src/routes/indexes/search.rs
View File

@ -13,12 +13,13 @@ use meilisearch_types::serde_cs::vec::CS;
use serde_json::Value;
use tracing::debug;
use crate::analytics::{Analytics, SearchAggregator};
use crate::analytics::Analytics;
use crate::error::MeilisearchHttpError;
use crate::extractors::authentication::policies::*;
use crate::extractors::authentication::GuardedData;
use crate::extractors::sequential_extractor::SeqHandler;
use crate::metrics::MEILISEARCH_DEGRADED_SEARCH_REQUESTS;
use crate::routes::indexes::search_analytics::{SearchAggregator, SearchGET, SearchPOST};
use crate::search::{
add_search_rules, perform_search, HybridQuery, MatchingStrategy, RankingScoreThreshold,
RetrieveVectors, SearchKind, SearchQuery, SemanticRatio, DEFAULT_CROP_LENGTH,
@ -225,7 +226,7 @@ pub async fn search_with_url_query(
index_uid: web::Path<String>,
params: AwebQueryParameter<SearchQueryGet, DeserrQueryParamError>,
req: HttpRequest,
analytics: web::Data<dyn Analytics>,
analytics: web::Data<Analytics>,
) -> Result<HttpResponse, ResponseError> {
debug!(parameters = ?params, "Search get");
let index_uid = IndexUid::try_from(index_uid.into_inner())?;
@ -237,7 +238,7 @@ pub async fn search_with_url_query(
add_search_rules(&mut query.filter, search_rules);
}
let mut aggregate = SearchAggregator::from_query(&query, &req);
let mut aggregate = SearchAggregator::<SearchGET>::from_query(&query);
let index = index_scheduler.index(&index_uid)?;
let features = index_scheduler.features();
@ -254,7 +255,7 @@ pub async fn search_with_url_query(
if let Ok(ref search_result) = search_result {
aggregate.succeed(search_result);
}
analytics.get_search(aggregate);
analytics.publish(aggregate, &req);
let search_result = search_result?;
@ -268,7 +269,7 @@ pub async fn search_with_post(
index_uid: web::Path<String>,
params: AwebJson<SearchQuery, DeserrJsonError>,
req: HttpRequest,
analytics: web::Data<dyn Analytics>,
analytics: web::Data<Analytics>,
) -> Result<HttpResponse, ResponseError> {
let index_uid = IndexUid::try_from(index_uid.into_inner())?;
@ -280,7 +281,7 @@ pub async fn search_with_post(
add_search_rules(&mut query.filter, search_rules);
}
let mut aggregate = SearchAggregator::from_query(&query, &req);
let mut aggregate = SearchAggregator::<SearchPOST>::from_query(&query);
let index = index_scheduler.index(&index_uid)?;
@ -302,7 +303,7 @@ pub async fn search_with_post(
MEILISEARCH_DEGRADED_SEARCH_REQUESTS.inc();
}
}
analytics.post_search(aggregate);
analytics.publish(aggregate, &req);
let search_result = search_result?;

485
crates/meilisearch/src/routes/indexes/search_analytics.rs Normal file
View File

@ -0,0 +1,485 @@
use once_cell::sync::Lazy;
use regex::Regex;
use serde_json::{json, Value};
use std::collections::{BTreeSet, BinaryHeap, HashMap};
use meilisearch_types::locales::Locale;
use crate::{
aggregate_methods,
analytics::{Aggregate, AggregateMethod},
search::{
SearchQuery, SearchResult, DEFAULT_CROP_LENGTH, DEFAULT_CROP_MARKER,
DEFAULT_HIGHLIGHT_POST_TAG, DEFAULT_HIGHLIGHT_PRE_TAG, DEFAULT_SEARCH_LIMIT,
DEFAULT_SEMANTIC_RATIO,
},
};
aggregate_methods!(
SearchGET => "Documents Searched GET",
SearchPOST => "Documents Searched POST",
);
#[derive(Default)]
pub struct SearchAggregator<Method: AggregateMethod> {
// requests
total_received: usize,
total_succeeded: usize,
total_degraded: usize,
total_used_negative_operator: usize,
time_spent: BinaryHeap<usize>,
// sort
sort_with_geo_point: bool,
// every time a request has a filter, this field must be incremented by the number of terms it contains
sort_sum_of_criteria_terms: usize,
// every time a request has a filter, this field must be incremented by one
sort_total_number_of_criteria: usize,
// distinct
distinct: bool,
// filter
filter_with_geo_radius: bool,
filter_with_geo_bounding_box: bool,
// every time a request has a filter, this field must be incremented by the number of terms it contains
filter_sum_of_criteria_terms: usize,
// every time a request has a filter, this field must be incremented by one
filter_total_number_of_criteria: usize,
used_syntax: HashMap<String, usize>,
// attributes_to_search_on
// every time a search is done using attributes_to_search_on
attributes_to_search_on_total_number_of_uses: usize,
// q
// The maximum number of terms in a q request
max_terms_number: usize,
// vector
// The maximum number of floats in a vector request
max_vector_size: usize,
// Whether the semantic ratio passed to a hybrid search equals the default ratio.
semantic_ratio: bool,
hybrid: bool,
retrieve_vectors: bool,
// every time a search is done, we increment the counter linked to the used settings
matching_strategy: HashMap<String, usize>,
// List of the unique Locales passed as parameter
locales: BTreeSet<Locale>,
// pagination
max_limit: usize,
max_offset: usize,
finite_pagination: usize,
// formatting
max_attributes_to_retrieve: usize,
max_attributes_to_highlight: usize,
highlight_pre_tag: bool,
highlight_post_tag: bool,
max_attributes_to_crop: usize,
crop_marker: bool,
show_matches_position: bool,
crop_length: bool,
// facets
facets_sum_of_terms: usize,
facets_total_number_of_facets: usize,
// scoring
show_ranking_score: bool,
show_ranking_score_details: bool,
ranking_score_threshold: bool,
marker: std::marker::PhantomData<Method>,
}
impl<Method: AggregateMethod> SearchAggregator<Method> {
#[allow(clippy::field_reassign_with_default)]
pub fn from_query(query: &SearchQuery) -> Self {
let SearchQuery {
q,
vector,
offset,
limit,
page,
hits_per_page,
attributes_to_retrieve: _,
retrieve_vectors,
attributes_to_crop: _,
crop_length,
attributes_to_highlight: _,
show_matches_position,
show_ranking_score,
show_ranking_score_details,
filter,
sort,
distinct,
facets: _,
highlight_pre_tag,
highlight_post_tag,
crop_marker,
matching_strategy,
attributes_to_search_on,
hybrid,
ranking_score_threshold,
locales,
} = query;
let mut ret = Self::default();
ret.total_received = 1;
if let Some(ref sort) = sort {
ret.sort_total_number_of_criteria = 1;
ret.sort_with_geo_point = sort.iter().any(|s| s.contains("_geoPoint("));
ret.sort_sum_of_criteria_terms = sort.len();
}
ret.distinct = distinct.is_some();
if let Some(ref filter) = filter {
static RE: Lazy<Regex> = Lazy::new(|| Regex::new("AND | OR").unwrap());
ret.filter_total_number_of_criteria = 1;
let syntax = match filter {
Value::String(_) => "string".to_string(),
Value::Array(values) => {
if values.iter().map(|v| v.to_string()).any(|s| RE.is_match(&s)) {
"mixed".to_string()
} else {
"array".to_string()
}
}
_ => "none".to_string(),
};
// convert the string to a HashMap
ret.used_syntax.insert(syntax, 1);
let stringified_filters = filter.to_string();
ret.filter_with_geo_radius = stringified_filters.contains("_geoRadius(");
ret.filter_with_geo_bounding_box = stringified_filters.contains("_geoBoundingBox(");
ret.filter_sum_of_criteria_terms = RE.split(&stringified_filters).count();
}
// attributes_to_search_on
if attributes_to_search_on.is_some() {
ret.attributes_to_search_on_total_number_of_uses = 1;
}
if let Some(ref q) = q {
ret.max_terms_number = q.split_whitespace().count();
}
if let Some(ref vector) = vector {
ret.max_vector_size = vector.len();
}
ret.retrieve_vectors |= retrieve_vectors;
if query.is_finite_pagination() {
let limit = hits_per_page.unwrap_or_else(DEFAULT_SEARCH_LIMIT);
ret.max_limit = limit;
ret.max_offset = page.unwrap_or(1).saturating_sub(1) * limit;
ret.finite_pagination = 1;
} else {
ret.max_limit = *limit;
ret.max_offset = *offset;
ret.finite_pagination = 0;
}
ret.matching_strategy.insert(format!("{:?}", matching_strategy), 1);
if let Some(locales) = locales {
ret.locales = locales.iter().copied().collect();
}
ret.highlight_pre_tag = *highlight_pre_tag != DEFAULT_HIGHLIGHT_PRE_TAG();
ret.highlight_post_tag = *highlight_post_tag != DEFAULT_HIGHLIGHT_POST_TAG();
ret.crop_marker = *crop_marker != DEFAULT_CROP_MARKER();
ret.crop_length = *crop_length != DEFAULT_CROP_LENGTH();
ret.show_matches_position = *show_matches_position;
ret.show_ranking_score = *show_ranking_score;
ret.show_ranking_score_details = *show_ranking_score_details;
ret.ranking_score_threshold = ranking_score_threshold.is_some();
if let Some(hybrid) = hybrid {
ret.semantic_ratio = hybrid.semantic_ratio != DEFAULT_SEMANTIC_RATIO();
ret.hybrid = true;
}
ret
}
pub fn succeed(&mut self, result: &SearchResult) {
let SearchResult {
hits: _,
query: _,
processing_time_ms,
hits_info: _,
semantic_hit_count: _,
facet_distribution: _,
facet_stats: _,
degraded,
used_negative_operator,
} = result;
self.total_succeeded = self.total_succeeded.saturating_add(1);
if *degraded {
self.total_degraded = self.total_degraded.saturating_add(1);
}
if *used_negative_operator {
self.total_used_negative_operator = self.total_used_negative_operator.saturating_add(1);
}
self.time_spent.push(*processing_time_ms as usize);
}
}
impl<Method: AggregateMethod> Aggregate for SearchAggregator<Method> {
fn event_name(&self) -> &'static str {
Method::event_name()
}
fn aggregate(mut self: Box<Self>, new: Box<Self>) -> Box<Self> {
let Self {
total_received,
total_succeeded,
mut time_spent,
sort_with_geo_point,
sort_sum_of_criteria_terms,
sort_total_number_of_criteria,
distinct,
filter_with_geo_radius,
filter_with_geo_bounding_box,
filter_sum_of_criteria_terms,
filter_total_number_of_criteria,
used_syntax,
attributes_to_search_on_total_number_of_uses,
max_terms_number,
max_vector_size,
retrieve_vectors,
matching_strategy,
max_limit,
max_offset,
finite_pagination,
max_attributes_to_retrieve,
max_attributes_to_highlight,
highlight_pre_tag,
highlight_post_tag,
max_attributes_to_crop,
crop_marker,
show_matches_position,
crop_length,
facets_sum_of_terms,
facets_total_number_of_facets,
show_ranking_score,
show_ranking_score_details,
semantic_ratio,
hybrid,
total_degraded,
total_used_negative_operator,
ranking_score_threshold,
mut locales,
marker: _,
} = *new;
// request
self.total_received = self.total_received.saturating_add(total_received);
self.total_succeeded = self.total_succeeded.saturating_add(total_succeeded);
self.total_degraded = self.total_degraded.saturating_add(total_degraded);
self.total_used_negative_operator =
self.total_used_negative_operator.saturating_add(total_used_negative_operator);
self.time_spent.append(&mut time_spent);
// sort
self.sort_with_geo_point |= sort_with_geo_point;
self.sort_sum_of_criteria_terms =
self.sort_sum_of_criteria_terms.saturating_add(sort_sum_of_criteria_terms);
self.sort_total_number_of_criteria =
self.sort_total_number_of_criteria.saturating_add(sort_total_number_of_criteria);
// distinct
self.distinct |= distinct;
// filter
self.filter_with_geo_radius |= filter_with_geo_radius;
self.filter_with_geo_bounding_box |= filter_with_geo_bounding_box;
self.filter_sum_of_criteria_terms =
self.filter_sum_of_criteria_terms.saturating_add(filter_sum_of_criteria_terms);
self.filter_total_number_of_criteria =
self.filter_total_number_of_criteria.saturating_add(filter_total_number_of_criteria);
for (key, value) in used_syntax.into_iter() {
let used_syntax = self.used_syntax.entry(key).or_insert(0);
*used_syntax = used_syntax.saturating_add(value);
}
// attributes_to_search_on
self.attributes_to_search_on_total_number_of_uses = self
.attributes_to_search_on_total_number_of_uses
.saturating_add(attributes_to_search_on_total_number_of_uses);
// q
self.max_terms_number = self.max_terms_number.max(max_terms_number);
// vector
self.max_vector_size = self.max_vector_size.max(max_vector_size);
self.retrieve_vectors |= retrieve_vectors;
self.semantic_ratio |= semantic_ratio;
self.hybrid |= hybrid;
// pagination
self.max_limit = self.max_limit.max(max_limit);
self.max_offset = self.max_offset.max(max_offset);
self.finite_pagination += finite_pagination;
// formatting
self.max_attributes_to_retrieve =
self.max_attributes_to_retrieve.max(max_attributes_to_retrieve);
self.max_attributes_to_highlight =
self.max_attributes_to_highlight.max(max_attributes_to_highlight);
self.highlight_pre_tag |= highlight_pre_tag;
self.highlight_post_tag |= highlight_post_tag;
self.max_attributes_to_crop = self.max_attributes_to_crop.max(max_attributes_to_crop);
self.crop_marker |= crop_marker;
self.show_matches_position |= show_matches_position;
self.crop_length |= crop_length;
// facets
self.facets_sum_of_terms = self.facets_sum_of_terms.saturating_add(facets_sum_of_terms);
self.facets_total_number_of_facets =
self.facets_total_number_of_facets.saturating_add(facets_total_number_of_facets);
// matching strategy
for (key, value) in matching_strategy.into_iter() {
let matching_strategy = self.matching_strategy.entry(key).or_insert(0);
*matching_strategy = matching_strategy.saturating_add(value);
}
// scoring
self.show_ranking_score |= show_ranking_score;
self.show_ranking_score_details |= show_ranking_score_details;
self.ranking_score_threshold |= ranking_score_threshold;
// locales
self.locales.append(&mut locales);
self
}
fn into_event(self: Box<Self>) -> serde_json::Value {
let Self {
total_received,
total_succeeded,
time_spent,
sort_with_geo_point,
sort_sum_of_criteria_terms,
sort_total_number_of_criteria,
distinct,
filter_with_geo_radius,
filter_with_geo_bounding_box,
filter_sum_of_criteria_terms,
filter_total_number_of_criteria,
used_syntax,
attributes_to_search_on_total_number_of_uses,
max_terms_number,
max_vector_size,
retrieve_vectors,
matching_strategy,
max_limit,
max_offset,
finite_pagination,
max_attributes_to_retrieve,
max_attributes_to_highlight,
highlight_pre_tag,
highlight_post_tag,
max_attributes_to_crop,
crop_marker,
show_matches_position,
crop_length,
facets_sum_of_terms,
facets_total_number_of_facets,
show_ranking_score,
show_ranking_score_details,
semantic_ratio,
hybrid,
total_degraded,
total_used_negative_operator,
ranking_score_threshold,
locales,
marker: _,
} = *self;
// we get all the values in a sorted manner
let time_spent = time_spent.into_sorted_vec();
// the index of the 99th percentage of value
let percentile_99th = time_spent.len() * 99 / 100;
// We are only interested by the slowest value of the 99th fastest results
let time_spent = time_spent.get(percentile_99th);
json!({
"requests": {
"99th_response_time": time_spent.map(|t| format!("{:.2}", t)),
"total_succeeded": total_succeeded,
"total_failed": total_received.saturating_sub(total_succeeded), // just to be sure we never panics
"total_received": total_received,
"total_degraded": total_degraded,
"total_used_negative_operator": total_used_negative_operator,
},
"sort": {
"with_geoPoint": sort_with_geo_point,
"avg_criteria_number": format!("{:.2}", sort_sum_of_criteria_terms as f64 / sort_total_number_of_criteria as f64),
},
"distinct": distinct,
"filter": {
"with_geoRadius": filter_with_geo_radius,
"with_geoBoundingBox": filter_with_geo_bounding_box,
"avg_criteria_number": format!("{:.2}", filter_sum_of_criteria_terms as f64 / filter_total_number_of_criteria as f64),
"most_used_syntax": used_syntax.iter().max_by_key(|(_, v)| *v).map(|(k, _)| json!(k)).unwrap_or_else(|| json!(null)),
},
"attributes_to_search_on": {
"total_number_of_uses": attributes_to_search_on_total_number_of_uses,
},
"q": {
"max_terms_number": max_terms_number,
},
"vector": {
"max_vector_size": max_vector_size,
"retrieve_vectors": retrieve_vectors,
},
"hybrid": {
"enabled": hybrid,
"semantic_ratio": semantic_ratio,
},
"pagination": {
"max_limit": max_limit,
"max_offset": max_offset,
"most_used_navigation": if finite_pagination > (total_received / 2) { "exhaustive" } else { "estimated" },
},
"formatting": {
"max_attributes_to_retrieve": max_attributes_to_retrieve,
"max_attributes_to_highlight": max_attributes_to_highlight,
"highlight_pre_tag": highlight_pre_tag,
"highlight_post_tag": highlight_post_tag,
"max_attributes_to_crop": max_attributes_to_crop,
"crop_marker": crop_marker,
"show_matches_position": show_matches_position,
"crop_length": crop_length,
},
"facets": {
"avg_facets_number": format!("{:.2}", facets_sum_of_terms as f64 / facets_total_number_of_facets as f64),
},
"matching_strategy": {
"most_used_strategy": matching_strategy.iter().max_by_key(|(_, v)| *v).map(|(k, _)| json!(k)).unwrap_or_else(|| json!(null)),
},
"locales": locales,
"scoring": {
"show_ranking_score": show_ranking_score,
"show_ranking_score_details": show_ranking_score_details,
"ranking_score_threshold": ranking_score_threshold,
},
})
}
}

501
crates/meilisearch/src/routes/indexes/settings.rs
View File

@ -1,15 +1,14 @@
use super::settings_analytics::*;
use actix_web::web::Data;
use actix_web::{web, HttpRequest, HttpResponse};
use deserr::actix_web::AwebJson;
use index_scheduler::IndexScheduler;
use meilisearch_types::deserr::DeserrJsonError;
use meilisearch_types::error::ResponseError;
use meilisearch_types::facet_values_sort::FacetValuesSort;
use meilisearch_types::index_uid::IndexUid;
use meilisearch_types::milli::update::Setting;
use meilisearch_types::settings::{settings, RankingRuleView, SecretPolicy, Settings, Unchecked};
use meilisearch_types::settings::{settings, SecretPolicy, Settings, Unchecked};
use meilisearch_types::tasks::KindWithContent;
use serde_json::json;
use tracing::debug;
use crate::analytics::Analytics;
@ -20,7 +19,7 @@ use crate::Opt;
#[macro_export]
macro_rules! make_setting_route {
($route:literal, $update_verb:ident, $type:ty, $err_ty:ty, $attr:ident, $camelcase_attr:literal, $analytics_var:ident, $analytics:expr) => {
($route:literal, $update_verb:ident, $type:ty, $err_ty:ty, $attr:ident, $camelcase_attr:literal, $analytics:ident) => {
pub mod $attr {
use actix_web::web::Data;
use actix_web::{web, HttpRequest, HttpResponse, Resource};
@ -80,7 +79,7 @@ macro_rules! make_setting_route {
body: deserr::actix_web::AwebJson<Option<$type>, $err_ty>,
req: HttpRequest,
opt: web::Data<Opt>,
$analytics_var: web::Data<dyn Analytics>,
analytics: web::Data<Analytics>,
) -> std::result::Result<HttpResponse, ResponseError> {
let index_uid = IndexUid::try_from(index_uid.into_inner())?;
@ -88,7 +87,10 @@ macro_rules! make_setting_route {
debug!(parameters = ?body, "Update settings");
#[allow(clippy::redundant_closure_call)]
$analytics(&body, &req);
analytics.publish(
$crate::routes::indexes::settings_analytics::$analytics::new(body.as_ref()).into_settings(),
&req,
);
let new_settings = Settings {
$attr: match body {
@ -160,21 +162,7 @@ make_setting_route!(
>,
filterable_attributes,
"filterableAttributes",
analytics,
|setting: &Option<std::collections::BTreeSet<String>>, req: &HttpRequest| {
use serde_json::json;
analytics.publish(
"FilterableAttributes Updated".to_string(),
json!({
"filterable_attributes": {
"total": setting.as_ref().map(|filter| filter.len()).unwrap_or(0),
"has_geo": setting.as_ref().map(|filter| filter.contains("_geo")).unwrap_or(false),
}
}),
Some(req),
);
}
FilterableAttributesAnalytics
);
make_setting_route!(
@ -186,21 +174,7 @@ make_setting_route!(
>,
sortable_attributes,
"sortableAttributes",
analytics,
|setting: &Option<std::collections::BTreeSet<String>>, req: &HttpRequest| {
use serde_json::json;
analytics.publish(
"SortableAttributes Updated".to_string(),
json!({
"sortable_attributes": {
"total": setting.as_ref().map(|sort| sort.len()),
"has_geo": setting.as_ref().map(|sort| sort.contains("_geo")),
},
}),
Some(req),
);
}
SortableAttributesAnalytics
);
make_setting_route!(
@ -212,21 +186,7 @@ make_setting_route!(
>,
displayed_attributes,
"displayedAttributes",
analytics,
|displayed: &Option<Vec<String>>, req: &HttpRequest| {
use serde_json::json;
analytics.publish(
"DisplayedAttributes Updated".to_string(),
json!({
"displayed_attributes": {
"total": displayed.as_ref().map(|displayed| displayed.len()),
"with_wildcard": displayed.as_ref().map(|displayed| displayed.iter().any(|displayed| displayed == "*")),
},
}),
Some(req),
);
}
DisplayedAttributesAnalytics
);
make_setting_route!(
@ -238,40 +198,7 @@ make_setting_route!(
>,
typo_tolerance,
"typoTolerance",
analytics,
|setting: &Option<meilisearch_types::settings::TypoSettings>, req: &HttpRequest| {
use serde_json::json;
analytics.publish(
"TypoTolerance Updated".to_string(),
json!({
"typo_tolerance": {
"enabled": setting.as_ref().map(|s| !matches!(s.enabled, Setting::Set(false))),
"disable_on_attributes": setting
.as_ref()
.and_then(|s| s.disable_on_attributes.as_ref().set().map(|m| !m.is_empty())),
"disable_on_words": setting
.as_ref()
.and_then(|s| s.disable_on_words.as_ref().set().map(|m| !m.is_empty())),
"min_word_size_for_one_typo": setting
.as_ref()
.and_then(|s| s.min_word_size_for_typos
.as_ref()
.set()
.map(|s| s.one_typo.set()))
.flatten(),
"min_word_size_for_two_typos": setting
.as_ref()
.and_then(|s| s.min_word_size_for_typos
.as_ref()
.set()
.map(|s| s.two_typos.set()))
.flatten(),
},
}),
Some(req),
);
}
TypoToleranceAnalytics
);
make_setting_route!(
@ -283,21 +210,7 @@ make_setting_route!(
>,
searchable_attributes,
"searchableAttributes",
analytics,
|setting: &Option<Vec<String>>, req: &HttpRequest| {
use serde_json::json;
analytics.publish(
"SearchableAttributes Updated".to_string(),
json!({
"searchable_attributes": {
"total": setting.as_ref().map(|searchable| searchable.len()),
"with_wildcard": setting.as_ref().map(|searchable| searchable.iter().any(|searchable| searchable == "*")),
},
}),
Some(req),
);
}
SearchableAttributesAnalytics
);
make_setting_route!(
@ -309,20 +222,7 @@ make_setting_route!(
>,
stop_words,
"stopWords",
analytics,
|stop_words: &Option<std::collections::BTreeSet<String>>, req: &HttpRequest| {
use serde_json::json;
analytics.publish(
"StopWords Updated".to_string(),
json!({
"stop_words": {
"total": stop_words.as_ref().map(|stop_words| stop_words.len()),
},
}),
Some(req),
);
}
StopWordsAnalytics
);
make_setting_route!(
@ -334,20 +234,7 @@ make_setting_route!(
>,
non_separator_tokens,
"nonSeparatorTokens",
analytics,
|non_separator_tokens: &Option<std::collections::BTreeSet<String>>, req: &HttpRequest| {
use serde_json::json;
analytics.publish(
"nonSeparatorTokens Updated".to_string(),
json!({
"non_separator_tokens": {
"total": non_separator_tokens.as_ref().map(|non_separator_tokens| non_separator_tokens.len()),
},
}),
Some(req),
);
}
NonSeparatorTokensAnalytics
);
make_setting_route!(
@ -359,20 +246,7 @@ make_setting_route!(
>,
separator_tokens,
"separatorTokens",
analytics,
|separator_tokens: &Option<std::collections::BTreeSet<String>>, req: &HttpRequest| {
use serde_json::json;
analytics.publish(
"separatorTokens Updated".to_string(),
json!({
"separator_tokens": {
"total": separator_tokens.as_ref().map(|separator_tokens| separator_tokens.len()),
},
}),
Some(req),
);
}
SeparatorTokensAnalytics
);
make_setting_route!(
@ -384,20 +258,7 @@ make_setting_route!(
>,
dictionary,
"dictionary",
analytics,
|dictionary: &Option<std::collections::BTreeSet<String>>, req: &HttpRequest| {
use serde_json::json;
analytics.publish(
"dictionary Updated".to_string(),
json!({
"dictionary": {
"total": dictionary.as_ref().map(|dictionary| dictionary.len()),
},
}),
Some(req),
);
}
DictionaryAnalytics
);
make_setting_route!(
@ -409,20 +270,7 @@ make_setting_route!(
>,
synonyms,
"synonyms",
analytics,
|synonyms: &Option<std::collections::BTreeMap<String, Vec<String>>>, req: &HttpRequest| {
use serde_json::json;
analytics.publish(
"Synonyms Updated".to_string(),
json!({
"synonyms": {
"total": synonyms.as_ref().map(|synonyms| synonyms.len()),
},
}),
Some(req),
);
}
SynonymsAnalytics
);
make_setting_route!(
@ -434,19 +282,7 @@ make_setting_route!(
>,
distinct_attribute,
"distinctAttribute",
analytics,
|distinct: &Option<String>, req: &HttpRequest| {
use serde_json::json;
analytics.publish(
"DistinctAttribute Updated".to_string(),
json!({
"distinct_attribute": {
"set": distinct.is_some(),
}
}),
Some(req),
);
}
DistinctAttributeAnalytics
);
make_setting_route!(
@ -458,20 +294,7 @@ make_setting_route!(
>,
proximity_precision,
"proximityPrecision",
analytics,
|precision: &Option<meilisearch_types::settings::ProximityPrecisionView>, req: &HttpRequest| {
use serde_json::json;
analytics.publish(
"ProximityPrecision Updated".to_string(),
json!({
"proximity_precision": {
"set": precision.is_some(),
"value": precision.unwrap_or_default(),
}
}),
Some(req),
);
}
ProximityPrecisionAnalytics
);
make_setting_route!(
@ -483,17 +306,7 @@ make_setting_route!(
>,
localized_attributes,
"localizedAttributes",
analytics,
|rules: &Option<Vec<meilisearch_types::locales::LocalizedAttributesRuleView>>, req: &HttpRequest| {
use serde_json::json;
analytics.publish(
"LocalizedAttributesRules Updated".to_string(),
json!({
"locales": rules.as_ref().map(|rules| rules.iter().flat_map(|rule| rule.locales.iter().cloned()).collect::<std::collections::BTreeSet<_>>())
}),
Some(req),
);
}
LocalesAnalytics
);
make_setting_route!(
@ -505,26 +318,7 @@ make_setting_route!(
>,
ranking_rules,
"rankingRules",
analytics,
|setting: &Option<Vec<meilisearch_types::settings::RankingRuleView>>, req: &HttpRequest| {
use serde_json::json;
analytics.publish(
"RankingRules Updated".to_string(),
json!({
"ranking_rules": {
"words_position": setting.as_ref().map(|rr| rr.iter().position(|s| matches!(s, meilisearch_types::settings::RankingRuleView::Words))),
"typo_position": setting.as_ref().map(|rr| rr.iter().position(|s| matches!(s, meilisearch_types::settings::RankingRuleView::Typo))),
"proximity_position": setting.as_ref().map(|rr| rr.iter().position(|s| matches!(s, meilisearch_types::settings::RankingRuleView::Proximity))),
"attribute_position": setting.as_ref().map(|rr| rr.iter().position(|s| matches!(s, meilisearch_types::settings::RankingRuleView::Attribute))),
"sort_position": setting.as_ref().map(|rr| rr.iter().position(|s| matches!(s, meilisearch_types::settings::RankingRuleView::Sort))),
"exactness_position": setting.as_ref().map(|rr| rr.iter().position(|s| matches!(s, meilisearch_types::settings::RankingRuleView::Exactness))),
"values": setting.as_ref().map(|rr| rr.iter().filter(|s| matches!(s, meilisearch_types::settings::RankingRuleView::Asc(_) | meilisearch_types::settings::RankingRuleView::Desc(_)) ).map(|x| x.to_string()).collect::<Vec<_>>().join(", ")),
}
}),
Some(req),
);
}
RankingRulesAnalytics
);
make_setting_route!(
@ -536,25 +330,7 @@ make_setting_route!(
>,
faceting,
"faceting",
analytics,
|setting: &Option<meilisearch_types::settings::FacetingSettings>, req: &HttpRequest| {
use serde_json::json;
use meilisearch_types::facet_values_sort::FacetValuesSort;
analytics.publish(
"Faceting Updated".to_string(),
json!({
"faceting": {
"max_values_per_facet": setting.as_ref().and_then(|s| s.max_values_per_facet.set()),
"sort_facet_values_by_star_count": setting.as_ref().and_then(|s| {
s.sort_facet_values_by.as_ref().set().map(|s| s.iter().any(|(k, v)| k == "*" && v == &FacetValuesSort::Count))
}),
"sort_facet_values_by_total": setting.as_ref().and_then(|s| s.sort_facet_values_by.as_ref().set().map(|s| s.len())),
},
}),
Some(req),
);
}
FacetingAnalytics
);
make_setting_route!(
@ -566,20 +342,7 @@ make_setting_route!(
>,
pagination,
"pagination",
analytics,
|setting: &Option<meilisearch_types::settings::PaginationSettings>, req: &HttpRequest| {
use serde_json::json;
analytics.publish(
"Pagination Updated".to_string(),
json!({
"pagination": {
"max_total_hits": setting.as_ref().and_then(|s| s.max_total_hits.set()),
},
}),
Some(req),
);
}
PaginationAnalytics
);
make_setting_route!(
@ -591,75 +354,9 @@ make_setting_route!(
>,
embedders,
"embedders",
analytics,
|setting: &Option<std::collections::BTreeMap<String, Setting<meilisearch_types::milli::vector::settings::EmbeddingSettings>>>, req: &HttpRequest| {
analytics.publish(
"Embedders Updated".to_string(),
serde_json::json!({"embedders": crate::routes::indexes::settings::embedder_analytics(setting.as_ref())}),
Some(req),
);
}
EmbeddersAnalytics
);
fn embedder_analytics(
setting: Option<
&std::collections::BTreeMap<
String,
Setting<meilisearch_types::milli::vector::settings::EmbeddingSettings>,
>,
>,
) -> serde_json::Value {
let mut sources = std::collections::HashSet::new();
if let Some(s) = &setting {
for source in s
.values()
.filter_map(|config| config.clone().set())
.filter_map(|config| config.source.set())
{
use meilisearch_types::milli::vector::settings::EmbedderSource;
match source {
EmbedderSource::OpenAi => sources.insert("openAi"),
EmbedderSource::HuggingFace => sources.insert("huggingFace"),
EmbedderSource::UserProvided => sources.insert("userProvided"),
EmbedderSource::Ollama => sources.insert("ollama"),
EmbedderSource::Rest => sources.insert("rest"),
};
}
};
let document_template_used = setting.as_ref().map(|map| {
map.values()
.filter_map(|config| config.clone().set())
.any(|config| config.document_template.set().is_some())
});
let document_template_max_bytes = setting.as_ref().and_then(|map| {
map.values()
.filter_map(|config| config.clone().set())
.filter_map(|config| config.document_template_max_bytes.set())
.max()
});
let binary_quantization_used = setting.as_ref().map(|map| {
map.values()
.filter_map(|config| config.clone().set())
.any(|config| config.binary_quantized.set().is_some())
});
json!(
{
"total": setting.as_ref().map(|s| s.len()),
"sources": sources,
"document_template_used": document_template_used,
"document_template_max_bytes": document_template_max_bytes,
"binary_quantization_used": binary_quantization_used,
}
)
}
make_setting_route!(
"/search-cutoff-ms",
put,
@ -669,14 +366,7 @@ make_setting_route!(
>,
search_cutoff_ms,
"searchCutoffMs",
analytics,
|setting: &Option<u64>, req: &HttpRequest| {
analytics.publish(
"Search Cutoff Updated".to_string(),
serde_json::json!({"search_cutoff_ms": setting }),
Some(req),
);
}
SearchCutoffMsAnalytics
);
macro_rules! generate_configure {
@ -720,7 +410,7 @@ pub async fn update_all(
body: AwebJson<Settings<Unchecked>, DeserrJsonError>,
req: HttpRequest,
opt: web::Data<Opt>,
analytics: web::Data<dyn Analytics>,
analytics: web::Data<Analytics>,
) -> Result<HttpResponse, ResponseError> {
let index_uid = IndexUid::try_from(index_uid.into_inner())?;
@ -729,104 +419,45 @@ pub async fn update_all(
let new_settings = validate_settings(new_settings, &index_scheduler)?;
analytics.publish(
"Settings Updated".to_string(),
json!({
"ranking_rules": {
"words_position": new_settings.ranking_rules.as_ref().set().map(|rr| rr.iter().position(|s| matches!(s, RankingRuleView::Words))),
"typo_position": new_settings.ranking_rules.as_ref().set().map(|rr| rr.iter().position(|s| matches!(s, RankingRuleView::Typo))),
"proximity_position": new_settings.ranking_rules.as_ref().set().map(|rr| rr.iter().position(|s| matches!(s, RankingRuleView::Proximity))),
"attribute_position": new_settings.ranking_rules.as_ref().set().map(|rr| rr.iter().position(|s| matches!(s, RankingRuleView::Attribute))),
"sort_position": new_settings.ranking_rules.as_ref().set().map(|rr| rr.iter().position(|s| matches!(s, RankingRuleView::Sort))),
"exactness_position": new_settings.ranking_rules.as_ref().set().map(|rr| rr.iter().position(|s| matches!(s, RankingRuleView::Exactness))),
"values": new_settings.ranking_rules.as_ref().set().map(|rr| rr.iter().filter(|s| !matches!(s, RankingRuleView::Asc(_) | RankingRuleView::Desc(_)) ).map(|x| x.to_string()).collect::<Vec<_>>().join(", ")),
},
"searchable_attributes": {
"total": new_settings.searchable_attributes.as_ref().set().map(|searchable| searchable.len()),
"with_wildcard": new_settings.searchable_attributes.as_ref().set().map(|searchable| searchable.iter().any(|searchable| searchable == "*")),
},
"displayed_attributes": {
"total": new_settings.displayed_attributes.as_ref().set().map(|displayed| displayed.len()),
"with_wildcard": new_settings.displayed_attributes.as_ref().set().map(|displayed| displayed.iter().any(|displayed| displayed == "*")),
},
"sortable_attributes": {
"total": new_settings.sortable_attributes.as_ref().set().map(|sort| sort.len()),
"has_geo": new_settings.sortable_attributes.as_ref().set().map(|sort| sort.iter().any(|s| s == "_geo")),
},
"filterable_attributes": {
"total": new_settings.filterable_attributes.as_ref().set().map(|filter| filter.len()),
"has_geo": new_settings.filterable_attributes.as_ref().set().map(|filter| filter.iter().any(|s| s == "_geo")),
},
"distinct_attribute": {
"set": new_settings.distinct_attribute.as_ref().set().is_some()
},
"proximity_precision": {
"set": new_settings.proximity_precision.as_ref().set().is_some(),
"value": new_settings.proximity_precision.as_ref().set().copied().unwrap_or_default()
},
"typo_tolerance": {
"enabled": new_settings.typo_tolerance
.as_ref()
.set()
.and_then(|s| s.enabled.as_ref().set())
.copied(),
"disable_on_attributes": new_settings.typo_tolerance
.as_ref()
.set()
.and_then(|s| s.disable_on_attributes.as_ref().set().map(|m| !m.is_empty())),
"disable_on_words": new_settings.typo_tolerance
.as_ref()
.set()
.and_then(|s| s.disable_on_words.as_ref().set().map(|m| !m.is_empty())),
"min_word_size_for_one_typo": new_settings.typo_tolerance
.as_ref()
.set()
.and_then(|s| s.min_word_size_for_typos
.as_ref()
.set()
.map(|s| s.one_typo.set()))
.flatten(),
"min_word_size_for_two_typos": new_settings.typo_tolerance
.as_ref()
.set()
.and_then(|s| s.min_word_size_for_typos
.as_ref()
.set()
.map(|s| s.two_typos.set()))
.flatten(),
},
"faceting": {
"max_values_per_facet": new_settings.faceting
.as_ref()
.set()
.and_then(|s| s.max_values_per_facet.as_ref().set()),
"sort_facet_values_by_star_count": new_settings.faceting
.as_ref()
.set()
.and_then(|s| {
s.sort_facet_values_by.as_ref().set().map(|s| s.iter().any(|(k, v)| k == "*" && v == &FacetValuesSort::Count))
}),
"sort_facet_values_by_total": new_settings.faceting
.as_ref()
.set()
.and_then(|s| s.sort_facet_values_by.as_ref().set().map(|s| s.len())),
},
"pagination": {
"max_total_hits": new_settings.pagination
.as_ref()
.set()
.and_then(|s| s.max_total_hits.as_ref().set()),
},
"stop_words": {
"total": new_settings.stop_words.as_ref().set().map(|stop_words| stop_words.len()),
},
"synonyms": {
"total": new_settings.synonyms.as_ref().set().map(|synonyms| synonyms.len()),
},
"embedders": crate::routes::indexes::settings::embedder_analytics(new_settings.embedders.as_ref().set()),
"search_cutoff_ms": new_settings.search_cutoff_ms.as_ref().set(),
"locales": new_settings.localized_attributes.as_ref().set().map(|rules| rules.iter().flat_map(|rule| rule.locales.iter().cloned()).collect::<std::collections::BTreeSet<_>>()),
}),
Some(&req),
SettingsAnalytics {
ranking_rules: RankingRulesAnalytics::new(new_settings.ranking_rules.as_ref().set()),
searchable_attributes: SearchableAttributesAnalytics::new(
new_settings.searchable_attributes.as_ref().set(),
),
displayed_attributes: DisplayedAttributesAnalytics::new(
new_settings.displayed_attributes.as_ref().set(),
),
sortable_attributes: SortableAttributesAnalytics::new(
new_settings.sortable_attributes.as_ref().set(),
),
filterable_attributes: FilterableAttributesAnalytics::new(
new_settings.filterable_attributes.as_ref().set(),
),
distinct_attribute: DistinctAttributeAnalytics::new(
new_settings.distinct_attribute.as_ref().set(),
),
proximity_precision: ProximityPrecisionAnalytics::new(
new_settings.proximity_precision.as_ref().set(),
),
typo_tolerance: TypoToleranceAnalytics::new(new_settings.typo_tolerance.as_ref().set()),
faceting: FacetingAnalytics::new(new_settings.faceting.as_ref().set()),
pagination: PaginationAnalytics::new(new_settings.pagination.as_ref().set()),
stop_words: StopWordsAnalytics::new(new_settings.stop_words.as_ref().set()),
synonyms: SynonymsAnalytics::new(new_settings.synonyms.as_ref().set()),
embedders: EmbeddersAnalytics::new(new_settings.embedders.as_ref().set()),
search_cutoff_ms: SearchCutoffMsAnalytics::new(
new_settings.search_cutoff_ms.as_ref().set(),
),
locales: LocalesAnalytics::new(new_settings.localized_attributes.as_ref().set()),
dictionary: DictionaryAnalytics::new(new_settings.dictionary.as_ref().set()),
separator_tokens: SeparatorTokensAnalytics::new(
new_settings.separator_tokens.as_ref().set(),
),
non_separator_tokens: NonSeparatorTokensAnalytics::new(
new_settings.non_separator_tokens.as_ref().set(),
),
},
&req,
);
let allow_index_creation = index_scheduler.filters().allow_index_creation(&index_uid);

621
crates/meilisearch/src/routes/indexes/settings_analytics.rs Normal file
View File

@ -0,0 +1,621 @@
//! All the structures used to make the analytics on the settings works.
//! The signatures of the `new` functions are not very rust idiomatic because they must match the types received
//! through the sub-settings route directly without any manipulation.
//! This is why we often use a `Option<&Vec<_>>` instead of a `Option<&[_]>`.
use meilisearch_types::locales::{Locale, LocalizedAttributesRuleView};
use meilisearch_types::milli::update::Setting;
use meilisearch_types::milli::vector::settings::EmbeddingSettings;
use meilisearch_types::settings::{
FacetingSettings, PaginationSettings, ProximityPrecisionView, TypoSettings,
};
use meilisearch_types::{facet_values_sort::FacetValuesSort, settings::RankingRuleView};
use serde::Serialize;
use std::collections::{BTreeMap, BTreeSet, HashSet};
use crate::analytics::Aggregate;
#[derive(Serialize, Default)]
pub struct SettingsAnalytics {
pub ranking_rules: RankingRulesAnalytics,
pub searchable_attributes: SearchableAttributesAnalytics,
pub displayed_attributes: DisplayedAttributesAnalytics,
pub sortable_attributes: SortableAttributesAnalytics,
pub filterable_attributes: FilterableAttributesAnalytics,
pub distinct_attribute: DistinctAttributeAnalytics,
pub proximity_precision: ProximityPrecisionAnalytics,
pub typo_tolerance: TypoToleranceAnalytics,
pub faceting: FacetingAnalytics,
pub pagination: PaginationAnalytics,
pub stop_words: StopWordsAnalytics,
pub synonyms: SynonymsAnalytics,
pub embedders: EmbeddersAnalytics,
pub search_cutoff_ms: SearchCutoffMsAnalytics,
pub locales: LocalesAnalytics,
pub dictionary: DictionaryAnalytics,
pub separator_tokens: SeparatorTokensAnalytics,
pub non_separator_tokens: NonSeparatorTokensAnalytics,
}
impl Aggregate for SettingsAnalytics {
fn event_name(&self) -> &'static str {
"Settings Updated"
}
fn aggregate(self: Box<Self>, new: Box<Self>) -> Box<Self> {
Box::new(Self {
ranking_rules: RankingRulesAnalytics {
words_position: new
.ranking_rules
.words_position
.or(self.ranking_rules.words_position),
typo_position: new.ranking_rules.typo_position.or(self.ranking_rules.typo_position),
proximity_position: new
.ranking_rules
.proximity_position
.or(self.ranking_rules.proximity_position),
attribute_position: new
.ranking_rules
.attribute_position
.or(self.ranking_rules.attribute_position),
sort_position: new.ranking_rules.sort_position.or(self.ranking_rules.sort_position),
exactness_position: new
.ranking_rules
.exactness_position
.or(self.ranking_rules.exactness_position),
values: new.ranking_rules.values.or(self.ranking_rules.values),
},
searchable_attributes: SearchableAttributesAnalytics {
total: new.searchable_attributes.total.or(self.searchable_attributes.total),
with_wildcard: new
.searchable_attributes
.with_wildcard
.or(self.searchable_attributes.with_wildcard),
},
displayed_attributes: DisplayedAttributesAnalytics {
total: new.displayed_attributes.total.or(self.displayed_attributes.total),
with_wildcard: new
.displayed_attributes
.with_wildcard
.or(self.displayed_attributes.with_wildcard),
},
sortable_attributes: SortableAttributesAnalytics {
total: new.sortable_attributes.total.or(self.sortable_attributes.total),
has_geo: new.sortable_attributes.has_geo.or(self.sortable_attributes.has_geo),
},
filterable_attributes: FilterableAttributesAnalytics {
total: new.filterable_attributes.total.or(self.filterable_attributes.total),
has_geo: new.filterable_attributes.has_geo.or(self.filterable_attributes.has_geo),
},
distinct_attribute: DistinctAttributeAnalytics {
set: self.distinct_attribute.set | new.distinct_attribute.set,
},
proximity_precision: ProximityPrecisionAnalytics {
set: self.proximity_precision.set | new.proximity_precision.set,
value: new.proximity_precision.value.or(self.proximity_precision.value),
},
typo_tolerance: TypoToleranceAnalytics {
enabled: new.typo_tolerance.enabled.or(self.typo_tolerance.enabled),
disable_on_attributes: new
.typo_tolerance
.disable_on_attributes
.or(self.typo_tolerance.disable_on_attributes),
disable_on_words: new
.typo_tolerance
.disable_on_words
.or(self.typo_tolerance.disable_on_words),
min_word_size_for_one_typo: new
.typo_tolerance
.min_word_size_for_one_typo
.or(self.typo_tolerance.min_word_size_for_one_typo),
min_word_size_for_two_typos: new
.typo_tolerance
.min_word_size_for_two_typos
.or(self.typo_tolerance.min_word_size_for_two_typos),
},
faceting: FacetingAnalytics {
max_values_per_facet: new
.faceting
.max_values_per_facet
.or(self.faceting.max_values_per_facet),
sort_facet_values_by_star_count: new
.faceting
.sort_facet_values_by_star_count
.or(self.faceting.sort_facet_values_by_star_count),
sort_facet_values_by_total: new
.faceting
.sort_facet_values_by_total
.or(self.faceting.sort_facet_values_by_total),
},
pagination: PaginationAnalytics {
max_total_hits: new.pagination.max_total_hits.or(self.pagination.max_total_hits),
},
stop_words: StopWordsAnalytics {
total: new.stop_words.total.or(self.stop_words.total),
},
synonyms: SynonymsAnalytics { total: new.synonyms.total.or(self.synonyms.total) },
embedders: EmbeddersAnalytics {
total: new.embedders.total.or(self.embedders.total),
sources: match (self.embedders.sources, new.embedders.sources) {
(None, None) => None,
(Some(sources), None) | (None, Some(sources)) => Some(sources),
(Some(this), Some(other)) => Some(this.union(&other).cloned().collect()),
},
document_template_used: match (
self.embedders.document_template_used,
new.embedders.document_template_used,
) {
(None, None) => None,
(Some(used), None) | (None, Some(used)) => Some(used),
(Some(this), Some(other)) => Some(this | other),
},
document_template_max_bytes: match (
self.embedders.document_template_max_bytes,
new.embedders.document_template_max_bytes,
) {
(None, None) => None,
(Some(bytes), None) | (None, Some(bytes)) => Some(bytes),
(Some(this), Some(other)) => Some(this.max(other)),
},
binary_quantization_used: match (
self.embedders.binary_quantization_used,
new.embedders.binary_quantization_used,
) {
(None, None) => None,
(Some(bq), None) | (None, Some(bq)) => Some(bq),
(Some(this), Some(other)) => Some(this | other),
},
},
search_cutoff_ms: SearchCutoffMsAnalytics {
search_cutoff_ms: new
.search_cutoff_ms
.search_cutoff_ms
.or(self.search_cutoff_ms.search_cutoff_ms),
},
locales: LocalesAnalytics { locales: new.locales.locales.or(self.locales.locales) },
dictionary: DictionaryAnalytics {
total: new.dictionary.total.or(self.dictionary.total),
},
separator_tokens: SeparatorTokensAnalytics {
total: new.non_separator_tokens.total.or(self.separator_tokens.total),
},
non_separator_tokens: NonSeparatorTokensAnalytics {
total: new.non_separator_tokens.total.or(self.non_separator_tokens.total),
},
})
}
fn into_event(self: Box<Self>) -> serde_json::Value {
serde_json::to_value(*self).unwrap_or_default()
}
}
#[derive(Serialize, Default)]
pub struct RankingRulesAnalytics {
pub words_position: Option<usize>,
pub typo_position: Option<usize>,
pub proximity_position: Option<usize>,
pub attribute_position: Option<usize>,
pub sort_position: Option<usize>,
pub exactness_position: Option<usize>,
pub values: Option<String>,
}
impl RankingRulesAnalytics {
pub fn new(rr: Option<&Vec<RankingRuleView>>) -> Self {
RankingRulesAnalytics {
words_position: rr.as_ref().and_then(|rr| {
rr.iter()
.position(|s| matches!(s, meilisearch_types::settings::RankingRuleView::Words))
}),
typo_position: rr.as_ref().and_then(|rr| {
rr.iter()
.position(|s| matches!(s, meilisearch_types::settings::RankingRuleView::Typo))
}),
proximity_position: rr.as_ref().and_then(|rr| {
rr.iter().position(|s| {
matches!(s, meilisearch_types::settings::RankingRuleView::Proximity)
})
}),
attribute_position: rr.as_ref().and_then(|rr| {
rr.iter().position(|s| {
matches!(s, meilisearch_types::settings::RankingRuleView::Attribute)
})
}),
sort_position: rr.as_ref().and_then(|rr| {
rr.iter()
.position(|s| matches!(s, meilisearch_types::settings::RankingRuleView::Sort))
}),
exactness_position: rr.as_ref().and_then(|rr| {
rr.iter().position(|s| {
matches!(s, meilisearch_types::settings::RankingRuleView::Exactness)
})
}),
values: rr.as_ref().map(|rr| {
rr.iter()
.filter(|s| {
matches!(
s,
meilisearch_types::settings::RankingRuleView::Asc(_)
| meilisearch_types::settings::RankingRuleView::Desc(_)
)
})
.map(|x| x.to_string())
.collect::<Vec<_>>()
.join(", ")
}),
}
}
pub fn into_settings(self) -> SettingsAnalytics {
SettingsAnalytics { ranking_rules: self, ..Default::default() }
}
}
#[derive(Serialize, Default)]
pub struct SearchableAttributesAnalytics {
pub total: Option<usize>,
pub with_wildcard: Option<bool>,
}
impl SearchableAttributesAnalytics {
pub fn new(setting: Option<&Vec<String>>) -> Self {
Self {
total: setting.as_ref().map(|searchable| searchable.len()),
with_wildcard: setting
.as_ref()
.map(|searchable| searchable.iter().any(|searchable| searchable == "*")),
}
}
pub fn into_settings(self) -> SettingsAnalytics {
SettingsAnalytics { searchable_attributes: self, ..Default::default() }
}
}
#[derive(Serialize, Default)]
pub struct DisplayedAttributesAnalytics {
pub total: Option<usize>,
pub with_wildcard: Option<bool>,
}
impl DisplayedAttributesAnalytics {
pub fn new(displayed: Option<&Vec<String>>) -> Self {
Self {
total: displayed.as_ref().map(|displayed| displayed.len()),
with_wildcard: displayed
.as_ref()
.map(|displayed| displayed.iter().any(|displayed| displayed == "*")),
}
}
pub fn into_settings(self) -> SettingsAnalytics {
SettingsAnalytics { displayed_attributes: self, ..Default::default() }
}
}
#[derive(Serialize, Default)]
pub struct SortableAttributesAnalytics {
pub total: Option<usize>,
pub has_geo: Option<bool>,
}
impl SortableAttributesAnalytics {
pub fn new(setting: Option<&BTreeSet<String>>) -> Self {
Self {
total: setting.as_ref().map(|sort| sort.len()),
has_geo: setting.as_ref().map(|sort| sort.contains("_geo")),
}
}
pub fn into_settings(self) -> SettingsAnalytics {
SettingsAnalytics { sortable_attributes: self, ..Default::default() }
}
}
#[derive(Serialize, Default)]
pub struct FilterableAttributesAnalytics {
pub total: Option<usize>,
pub has_geo: Option<bool>,
}
impl FilterableAttributesAnalytics {
pub fn new(setting: Option<&BTreeSet<String>>) -> Self {
Self {
total: setting.as_ref().map(|filter| filter.len()),
has_geo: setting.as_ref().map(|filter| filter.contains("_geo")),
}
}
pub fn into_settings(self) -> SettingsAnalytics {
SettingsAnalytics { filterable_attributes: self, ..Default::default() }
}
}
#[derive(Serialize, Default)]
pub struct DistinctAttributeAnalytics {
pub set: bool,
}
impl DistinctAttributeAnalytics {
pub fn new(distinct: Option<&String>) -> Self {
Self { set: distinct.is_some() }
}
pub fn into_settings(self) -> SettingsAnalytics {
SettingsAnalytics { distinct_attribute: self, ..Default::default() }
}
}
#[derive(Serialize, Default)]
pub struct ProximityPrecisionAnalytics {
pub set: bool,
pub value: Option<ProximityPrecisionView>,
}
impl ProximityPrecisionAnalytics {
pub fn new(precision: Option<&ProximityPrecisionView>) -> Self {
Self { set: precision.is_some(), value: precision.cloned() }
}
pub fn into_settings(self) -> SettingsAnalytics {
SettingsAnalytics { proximity_precision: self, ..Default::default() }
}
}
#[derive(Serialize, Default)]
pub struct TypoToleranceAnalytics {
pub enabled: Option<bool>,
pub disable_on_attributes: Option<bool>,
pub disable_on_words: Option<bool>,
pub min_word_size_for_one_typo: Option<u8>,
pub min_word_size_for_two_typos: Option<u8>,
}
impl TypoToleranceAnalytics {
pub fn new(setting: Option<&TypoSettings>) -> Self {
Self {
enabled: setting.as_ref().map(|s| !matches!(s.enabled, Setting::Set(false))),
disable_on_attributes: setting
.as_ref()
.and_then(|s| s.disable_on_attributes.as_ref().set().map(|m| !m.is_empty())),
disable_on_words: setting
.as_ref()
.and_then(|s| s.disable_on_words.as_ref().set().map(|m| !m.is_empty())),
min_word_size_for_one_typo: setting
.as_ref()
.and_then(|s| s.min_word_size_for_typos.as_ref().set().map(|s| s.one_typo.set()))
.flatten(),
min_word_size_for_two_typos: setting
.as_ref()
.and_then(|s| s.min_word_size_for_typos.as_ref().set().map(|s| s.two_typos.set()))
.flatten(),
}
}
pub fn into_settings(self) -> SettingsAnalytics {
SettingsAnalytics { typo_tolerance: self, ..Default::default() }
}
}
#[derive(Serialize, Default)]
pub struct FacetingAnalytics {
pub max_values_per_facet: Option<usize>,
pub sort_facet_values_by_star_count: Option<bool>,
pub sort_facet_values_by_total: Option<usize>,
}
impl FacetingAnalytics {
pub fn new(setting: Option<&FacetingSettings>) -> Self {
Self {
max_values_per_facet: setting.as_ref().and_then(|s| s.max_values_per_facet.set()),
sort_facet_values_by_star_count: setting.as_ref().and_then(|s| {
s.sort_facet_values_by
.as_ref()
.set()
.map(|s| s.iter().any(|(k, v)| k == "*" && v == &FacetValuesSort::Count))
}),
sort_facet_values_by_total: setting
.as_ref()
.and_then(|s| s.sort_facet_values_by.as_ref().set().map(|s| s.len())),
}
}
pub fn into_settings(self) -> SettingsAnalytics {
SettingsAnalytics { faceting: self, ..Default::default() }
}
}
#[derive(Serialize, Default)]
pub struct PaginationAnalytics {
pub max_total_hits: Option<usize>,
}
impl PaginationAnalytics {
pub fn new(setting: Option<&PaginationSettings>) -> Self {
Self { max_total_hits: setting.as_ref().and_then(|s| s.max_total_hits.set()) }
}
pub fn into_settings(self) -> SettingsAnalytics {
SettingsAnalytics { pagination: self, ..Default::default() }
}
}
#[derive(Serialize, Default)]
pub struct StopWordsAnalytics {
pub total: Option<usize>,
}
impl StopWordsAnalytics {
pub fn new(stop_words: Option<&BTreeSet<String>>) -> Self {
Self { total: stop_words.as_ref().map(|stop_words| stop_words.len()) }
}
pub fn into_settings(self) -> SettingsAnalytics {
SettingsAnalytics { stop_words: self, ..Default::default() }
}
}
#[derive(Serialize, Default)]
pub struct SynonymsAnalytics {
pub total: Option<usize>,
}
impl SynonymsAnalytics {
pub fn new(synonyms: Option<&BTreeMap<String, Vec<String>>>) -> Self {
Self { total: synonyms.as_ref().map(|synonyms| synonyms.len()) }
}
pub fn into_settings(self) -> SettingsAnalytics {
SettingsAnalytics { synonyms: self, ..Default::default() }
}
}
#[derive(Serialize, Default)]
pub struct EmbeddersAnalytics {
// last
pub total: Option<usize>,
// Merge the sources
pub sources: Option<HashSet<String>>,
// |=
pub document_template_used: Option<bool>,
// max
pub document_template_max_bytes: Option<usize>,
// |=
pub binary_quantization_used: Option<bool>,
}
impl EmbeddersAnalytics {
pub fn new(setting: Option<&BTreeMap<String, Setting<EmbeddingSettings>>>) -> Self {
let mut sources = std::collections::HashSet::new();
if let Some(s) = &setting {
for source in s
.values()
.filter_map(|config| config.clone().set())
.filter_map(|config| config.source.set())
{
use meilisearch_types::milli::vector::settings::EmbedderSource;
match source {
EmbedderSource::OpenAi => sources.insert("openAi".to_string()),
EmbedderSource::HuggingFace => sources.insert("huggingFace".to_string()),
EmbedderSource::UserProvided => sources.insert("userProvided".to_string()),
EmbedderSource::Ollama => sources.insert("ollama".to_string()),
EmbedderSource::Rest => sources.insert("rest".to_string()),
};
}
};
Self {
total: setting.as_ref().map(|s| s.len()),
sources: Some(sources),
document_template_used: setting.as_ref().map(|map| {
map.values()
.filter_map(|config| config.clone().set())
.any(|config| config.document_template.set().is_some())
}),
document_template_max_bytes: setting.as_ref().and_then(|map| {
map.values()
.filter_map(|config| config.clone().set())
.filter_map(|config| config.document_template_max_bytes.set())
.max()
}),
binary_quantization_used: setting.as_ref().map(|map| {
map.values()
.filter_map(|config| config.clone().set())
.any(|config| config.binary_quantized.set().is_some())
}),
}
}
pub fn into_settings(self) -> SettingsAnalytics {
SettingsAnalytics { embedders: self, ..Default::default() }
}
}
#[derive(Serialize, Default)]
#[serde(transparent)]
pub struct SearchCutoffMsAnalytics {
pub search_cutoff_ms: Option<u64>,
}
impl SearchCutoffMsAnalytics {
pub fn new(setting: Option<&u64>) -> Self {
Self { search_cutoff_ms: setting.copied() }
}
pub fn into_settings(self) -> SettingsAnalytics {
SettingsAnalytics { search_cutoff_ms: self, ..Default::default() }
}
}
#[derive(Serialize, Default)]
#[serde(transparent)]
pub struct LocalesAnalytics {
pub locales: Option<BTreeSet<Locale>>,
}
impl LocalesAnalytics {
pub fn new(rules: Option<&Vec<LocalizedAttributesRuleView>>) -> Self {
LocalesAnalytics {
locales: rules.as_ref().map(|rules| {
rules
.iter()
.flat_map(|rule| rule.locales.iter().cloned())
.collect::<std::collections::BTreeSet<_>>()
}),
}
}
pub fn into_settings(self) -> SettingsAnalytics {
SettingsAnalytics { locales: self, ..Default::default() }
}
}
#[derive(Serialize, Default)]
pub struct DictionaryAnalytics {
pub total: Option<usize>,
}
impl DictionaryAnalytics {
pub fn new(dictionary: Option<&BTreeSet<String>>) -> Self {
Self { total: dictionary.as_ref().map(|dictionary| dictionary.len()) }
}
pub fn into_settings(self) -> SettingsAnalytics {
SettingsAnalytics { dictionary: self, ..Default::default() }
}
}
#[derive(Serialize, Default)]
pub struct SeparatorTokensAnalytics {
pub total: Option<usize>,
}
impl SeparatorTokensAnalytics {
pub fn new(separator_tokens: Option<&BTreeSet<String>>) -> Self {
Self { total: separator_tokens.as_ref().map(|separator_tokens| separator_tokens.len()) }
}
pub fn into_settings(self) -> SettingsAnalytics {
SettingsAnalytics { separator_tokens: self, ..Default::default() }
}
}
#[derive(Serialize, Default)]
pub struct NonSeparatorTokensAnalytics {
pub total: Option<usize>,
}
impl NonSeparatorTokensAnalytics {
pub fn new(non_separator_tokens: Option<&BTreeSet<String>>) -> Self {
Self {
total: non_separator_tokens
.as_ref()
.map(|non_separator_tokens| non_separator_tokens.len()),
}
}
pub fn into_settings(self) -> SettingsAnalytics {
SettingsAnalytics { non_separator_tokens: self, ..Default::default() }
}
}

15
crates/meilisearch/src/routes/indexes/similar.rs
View File

@ -13,9 +13,10 @@ use serde_json::Value;
use tracing::debug;
use super::ActionPolicy;
use crate::analytics::{Analytics, SimilarAggregator};
use crate::analytics::Analytics;
use crate::extractors::authentication::GuardedData;
use crate::extractors::sequential_extractor::SeqHandler;
use crate::routes::indexes::similar_analytics::{SimilarAggregator, SimilarGET, SimilarPOST};
use crate::search::{
add_search_rules, perform_similar, RankingScoreThresholdSimilar, RetrieveVectors, SearchKind,
SimilarQuery, SimilarResult, DEFAULT_SEARCH_LIMIT, DEFAULT_SEARCH_OFFSET,
@ -34,13 +35,13 @@ pub async fn similar_get(
index_uid: web::Path<String>,
params: AwebQueryParameter<SimilarQueryGet, DeserrQueryParamError>,
req: HttpRequest,
analytics: web::Data<dyn Analytics>,
analytics: web::Data<Analytics>,
) -> Result<HttpResponse, ResponseError> {
let index_uid = IndexUid::try_from(index_uid.into_inner())?;
let query = params.0.try_into()?;
let mut aggregate = SimilarAggregator::from_query(&query, &req);
let mut aggregate = SimilarAggregator::<SimilarGET>::from_query(&query);
debug!(parameters = ?query, "Similar get");
@ -49,7 +50,7 @@ pub async fn similar_get(
if let Ok(similar) = &similar {
aggregate.succeed(similar);
}
analytics.get_similar(aggregate);
analytics.publish(aggregate, &req);
let similar = similar?;
@ -62,21 +63,21 @@ pub async fn similar_post(
index_uid: web::Path<String>,
params: AwebJson<SimilarQuery, DeserrJsonError>,
req: HttpRequest,
analytics: web::Data<dyn Analytics>,
analytics: web::Data<Analytics>,
) -> Result<HttpResponse, ResponseError> {
let index_uid = IndexUid::try_from(index_uid.into_inner())?;
let query = params.into_inner();
debug!(parameters = ?query, "Similar post");
let mut aggregate = SimilarAggregator::from_query(&query, &req);
let mut aggregate = SimilarAggregator::<SimilarPOST>::from_query(&query);
let similar = similar(index_scheduler, index_uid, query).await;
if let Ok(similar) = &similar {
aggregate.succeed(similar);
}
analytics.post_similar(aggregate);
analytics.publish(aggregate, &req);
let similar = similar?;

235
crates/meilisearch/src/routes/indexes/similar_analytics.rs Normal file
View File

@ -0,0 +1,235 @@
use std::collections::{BinaryHeap, HashMap};
use once_cell::sync::Lazy;
use regex::Regex;
use serde_json::{json, Value};
use crate::{
aggregate_methods,
analytics::{Aggregate, AggregateMethod},
search::{SimilarQuery, SimilarResult},
};
aggregate_methods!(
SimilarPOST => "Similar POST",
SimilarGET => "Similar GET",
);
#[derive(Default)]
pub struct SimilarAggregator<Method: AggregateMethod> {
// requests
total_received: usize,
total_succeeded: usize,
time_spent: BinaryHeap<usize>,
// filter
filter_with_geo_radius: bool,
filter_with_geo_bounding_box: bool,
// every time a request has a filter, this field must be incremented by the number of terms it contains
filter_sum_of_criteria_terms: usize,
// every time a request has a filter, this field must be incremented by one
filter_total_number_of_criteria: usize,
used_syntax: HashMap<String, usize>,
// Whether a non-default embedder was specified
retrieve_vectors: bool,
// pagination
max_limit: usize,
max_offset: usize,
// formatting
max_attributes_to_retrieve: usize,
// scoring
show_ranking_score: bool,
show_ranking_score_details: bool,
ranking_score_threshold: bool,
marker: std::marker::PhantomData<Method>,
}
impl<Method: AggregateMethod> SimilarAggregator<Method> {
#[allow(clippy::field_reassign_with_default)]
pub fn from_query(query: &SimilarQuery) -> Self {
let SimilarQuery {
id: _,
embedder: _,
offset,
limit,
attributes_to_retrieve: _,
retrieve_vectors,
show_ranking_score,
show_ranking_score_details,
filter,
ranking_score_threshold,
} = query;
let mut ret = Self::default();
ret.total_received = 1;
if let Some(ref filter) = filter {
static RE: Lazy<Regex> = Lazy::new(|| Regex::new("AND | OR").unwrap());
ret.filter_total_number_of_criteria = 1;
let syntax = match filter {
Value::String(_) => "string".to_string(),
Value::Array(values) => {
if values.iter().map(|v| v.to_string()).any(|s| RE.is_match(&s)) {
"mixed".to_string()
} else {
"array".to_string()
}
}
_ => "none".to_string(),
};
// convert the string to a HashMap
ret.used_syntax.insert(syntax, 1);
let stringified_filters = filter.to_string();
ret.filter_with_geo_radius = stringified_filters.contains("_geoRadius(");
ret.filter_with_geo_bounding_box = stringified_filters.contains("_geoBoundingBox(");
ret.filter_sum_of_criteria_terms = RE.split(&stringified_filters).count();
}
ret.max_limit = *limit;
ret.max_offset = *offset;
ret.show_ranking_score = *show_ranking_score;
ret.show_ranking_score_details = *show_ranking_score_details;
ret.ranking_score_threshold = ranking_score_threshold.is_some();
ret.retrieve_vectors = *retrieve_vectors;
ret
}
pub fn succeed(&mut self, result: &SimilarResult) {
let SimilarResult { id: _, hits: _, processing_time_ms, hits_info: _ } = result;
self.total_succeeded = self.total_succeeded.saturating_add(1);
self.time_spent.push(*processing_time_ms as usize);
}
}
impl<Method: AggregateMethod> Aggregate for SimilarAggregator<Method> {
fn event_name(&self) -> &'static str {
Method::event_name()
}
/// Aggregate one [SimilarAggregator] into another.
fn aggregate(mut self: Box<Self>, new: Box<Self>) -> Box<Self> {
let Self {
total_received,
total_succeeded,
mut time_spent,
filter_with_geo_radius,
filter_with_geo_bounding_box,
filter_sum_of_criteria_terms,
filter_total_number_of_criteria,
used_syntax,
max_limit,
max_offset,
max_attributes_to_retrieve,
show_ranking_score,
show_ranking_score_details,
ranking_score_threshold,
retrieve_vectors,
marker: _,
} = *new;
// request
self.total_received = self.total_received.saturating_add(total_received);
self.total_succeeded = self.total_succeeded.saturating_add(total_succeeded);
self.time_spent.append(&mut time_spent);
// filter
self.filter_with_geo_radius |= filter_with_geo_radius;
self.filter_with_geo_bounding_box |= filter_with_geo_bounding_box;
self.filter_sum_of_criteria_terms =
self.filter_sum_of_criteria_terms.saturating_add(filter_sum_of_criteria_terms);
self.filter_total_number_of_criteria =
self.filter_total_number_of_criteria.saturating_add(filter_total_number_of_criteria);
for (key, value) in used_syntax.into_iter() {
let used_syntax = self.used_syntax.entry(key).or_insert(0);
*used_syntax = used_syntax.saturating_add(value);
}
self.retrieve_vectors |= retrieve_vectors;
// pagination
self.max_limit = self.max_limit.max(max_limit);
self.max_offset = self.max_offset.max(max_offset);
// formatting
self.max_attributes_to_retrieve =
self.max_attributes_to_retrieve.max(max_attributes_to_retrieve);
// scoring
self.show_ranking_score |= show_ranking_score;
self.show_ranking_score_details |= show_ranking_score_details;
self.ranking_score_threshold |= ranking_score_threshold;
self
}
fn into_event(self: Box<Self>) -> serde_json::Value {
let Self {
total_received,
total_succeeded,
time_spent,
filter_with_geo_radius,
filter_with_geo_bounding_box,
filter_sum_of_criteria_terms,
filter_total_number_of_criteria,
used_syntax,
max_limit,
max_offset,
max_attributes_to_retrieve,
show_ranking_score,
show_ranking_score_details,
ranking_score_threshold,
retrieve_vectors,
marker: _,
} = *self;
// we get all the values in a sorted manner
let time_spent = time_spent.into_sorted_vec();
// the index of the 99th percentage of value
let percentile_99th = time_spent.len() * 99 / 100;
// We are only interested by the slowest value of the 99th fastest results
let time_spent = time_spent.get(percentile_99th);
json!({
"requests": {
"99th_response_time": time_spent.map(|t| format!("{:.2}", t)),
"total_succeeded": total_succeeded,
"total_failed": total_received.saturating_sub(total_succeeded), // just to be sure we never panics
"total_received": total_received,
},
"filter": {
"with_geoRadius": filter_with_geo_radius,
"with_geoBoundingBox": filter_with_geo_bounding_box,
"avg_criteria_number": format!("{:.2}", filter_sum_of_criteria_terms as f64 / filter_total_number_of_criteria as f64),
"most_used_syntax": used_syntax.iter().max_by_key(|(_, v)| *v).map(|(k, _)| json!(k)).unwrap_or_else(|| json!(null)),
},
"vector": {
"retrieve_vectors": retrieve_vectors,
},
"pagination": {
"max_limit": max_limit,
"max_offset": max_offset,
},
"formatting": {
"max_attributes_to_retrieve": max_attributes_to_retrieve,
},
"scoring": {
"show_ranking_score": show_ranking_score,
"show_ranking_score_details": show_ranking_score_details,
"ranking_score_threshold": ranking_score_threshold,
}
})
}
}

1
crates/meilisearch/src/routes/mod.rs
View File

@ -25,6 +25,7 @@ pub mod indexes;
mod logs;
mod metrics;
mod multi_search;
mod multi_search_analytics;
mod snapshot;
mod swap_indexes;
pub mod tasks;

12
crates/meilisearch/src/routes/multi_search.rs
View File

@ -9,7 +9,7 @@ use meilisearch_types::keys::actions;
use serde::Serialize;
use tracing::debug;
use crate::analytics::{Analytics, MultiSearchAggregator};
use crate::analytics::Analytics;
use crate::error::MeilisearchHttpError;
use crate::extractors::authentication::policies::ActionPolicy;
use crate::extractors::authentication::{AuthenticationError, GuardedData};
@ -21,6 +21,8 @@ use crate::search::{
};
use crate::search_queue::SearchQueue;
use super::multi_search_analytics::MultiSearchAggregator;
pub fn configure(cfg: &mut web::ServiceConfig) {
cfg.service(web::resource("").route(web::post().to(SeqHandler(multi_search_with_post))));
}
@ -35,7 +37,7 @@ pub async fn multi_search_with_post(
search_queue: Data<SearchQueue>,
params: AwebJson<FederatedSearch, DeserrJsonError>,
req: HttpRequest,
analytics: web::Data<dyn Analytics>,
analytics: web::Data<Analytics>,
) -> Result<HttpResponse, ResponseError> {
// Since we don't want to process half of the search requests and then get a permit refused
// we're going to get one permit for the whole duration of the multi-search request.
@ -43,7 +45,7 @@ pub async fn multi_search_with_post(
let federated_search = params.into_inner();
let mut multi_aggregate = MultiSearchAggregator::from_federated_search(&federated_search, &req);
let mut multi_aggregate = MultiSearchAggregator::from_federated_search(&federated_search);
let FederatedSearch { mut queries, federation } = federated_search;
@ -87,7 +89,7 @@ pub async fn multi_search_with_post(
multi_aggregate.succeed();
}
analytics.post_multi_search(multi_aggregate);
analytics.publish(multi_aggregate, &req);
HttpResponse::Ok().json(search_result??)
}
None => {
@ -149,7 +151,7 @@ pub async fn multi_search_with_post(
if search_results.is_ok() {
multi_aggregate.succeed();
}
analytics.post_multi_search(multi_aggregate);
analytics.publish(multi_aggregate, &req);
let search_results = search_results.map_err(|(mut err, query_index)| {
// Add the query index that failed as context for the error message.

170
crates/meilisearch/src/routes/multi_search_analytics.rs Normal file
View File

@ -0,0 +1,170 @@
use std::collections::HashSet;
use serde_json::json;
use crate::{
analytics::Aggregate,
search::{FederatedSearch, SearchQueryWithIndex},
};
#[derive(Default)]
pub struct MultiSearchAggregator {
// requests
total_received: usize,
total_succeeded: usize,
// sum of the number of distinct indexes in each single request, use with total_received to compute an avg
total_distinct_index_count: usize,
// number of queries with a single index, use with total_received to compute a proportion
total_single_index: usize,
// sum of the number of search queries in the requests, use with total_received to compute an average
total_search_count: usize,
// scoring
show_ranking_score: bool,
show_ranking_score_details: bool,
// federation
use_federation: bool,
}
impl MultiSearchAggregator {
pub fn from_federated_search(federated_search: &FederatedSearch) -> Self {
let use_federation = federated_search.federation.is_some();
let distinct_indexes: HashSet<_> = federated_search
.queries
.iter()
.map(|query| {
let query = &query;
// make sure we get a compilation error if a field gets added to / removed from SearchQueryWithIndex
let SearchQueryWithIndex {
index_uid,
federation_options: _,
q: _,
vector: _,
offset: _,
limit: _,
page: _,
hits_per_page: _,
attributes_to_retrieve: _,
retrieve_vectors: _,
attributes_to_crop: _,
crop_length: _,
attributes_to_highlight: _,
show_ranking_score: _,
show_ranking_score_details: _,
show_matches_position: _,
filter: _,
sort: _,
distinct: _,
facets: _,
highlight_pre_tag: _,
highlight_post_tag: _,
crop_marker: _,
matching_strategy: _,
attributes_to_search_on: _,
hybrid: _,
ranking_score_threshold: _,
locales: _,
} = query;
index_uid.as_str()
})
.collect();
let show_ranking_score =
federated_search.queries.iter().any(|query| query.show_ranking_score);
let show_ranking_score_details =
federated_search.queries.iter().any(|query| query.show_ranking_score_details);
Self {
total_received: 1,
total_succeeded: 0,
total_distinct_index_count: distinct_indexes.len(),
total_single_index: if distinct_indexes.len() == 1 { 1 } else { 0 },
total_search_count: federated_search.queries.len(),
show_ranking_score,
show_ranking_score_details,
use_federation,
}
}
pub fn succeed(&mut self) {
self.total_succeeded = self.total_succeeded.saturating_add(1);
}
}
impl Aggregate for MultiSearchAggregator {
fn event_name(&self) -> &'static str {
"Documents Searched by Multi-Search POST"
}
/// Aggregate one [MultiSearchAggregator] into another.
fn aggregate(self: Box<Self>, new: Box<Self>) -> Box<Self> {
// write the aggregate in a way that will cause a compilation error if a field is added.
// get ownership of self, replacing it by a default value.
let this = *self;
let total_received = this.total_received.saturating_add(new.total_received);
let total_succeeded = this.total_succeeded.saturating_add(new.total_succeeded);
let total_distinct_index_count =
this.total_distinct_index_count.saturating_add(new.total_distinct_index_count);
let total_single_index = this.total_single_index.saturating_add(new.total_single_index);
let total_search_count = this.total_search_count.saturating_add(new.total_search_count);
let show_ranking_score = this.show_ranking_score || new.show_ranking_score;
let show_ranking_score_details =
this.show_ranking_score_details || new.show_ranking_score_details;
let use_federation = this.use_federation || new.use_federation;
Box::new(Self {
total_received,
total_succeeded,
total_distinct_index_count,
total_single_index,
total_search_count,
show_ranking_score,
show_ranking_score_details,
use_federation,
})
}
fn into_event(self: Box<Self>) -> serde_json::Value {
let Self {
total_received,
total_succeeded,
total_distinct_index_count,
total_single_index,
total_search_count,
show_ranking_score,
show_ranking_score_details,
use_federation,
} = *self;
json!({
"requests": {
"total_succeeded": total_succeeded,
"total_failed": total_received.saturating_sub(total_succeeded), // just to be sure we never panics
"total_received": total_received,
},
"indexes": {
"total_single_index": total_single_index,
"total_distinct_index_count": total_distinct_index_count,
"avg_distinct_index_count": (total_distinct_index_count as f64) / (total_received as f64), // not 0 else returned early
},
"searches": {
"total_search_count": total_search_count,
"avg_search_count": (total_search_count as f64) / (total_received as f64),
},
"scoring": {
"show_ranking_score": show_ranking_score,
"show_ranking_score_details": show_ranking_score_details,
},
"federation": {
"use_federation": use_federation,
}
})
}
}

7
crates/meilisearch/src/routes/snapshot.rs
View File

@ -3,7 +3,6 @@ use actix_web::{web, HttpRequest, HttpResponse};
use index_scheduler::IndexScheduler;
use meilisearch_types::error::ResponseError;
use meilisearch_types::tasks::KindWithContent;
use serde_json::json;
use tracing::debug;
use crate::analytics::Analytics;
@ -17,13 +16,15 @@ pub fn configure(cfg: &mut web::ServiceConfig) {
cfg.service(web::resource("").route(web::post().to(SeqHandler(create_snapshot))));
}
crate::empty_analytics!(SnapshotAnalytics, "Snapshot Created");
pub async fn create_snapshot(
index_scheduler: GuardedData<ActionPolicy<{ actions::SNAPSHOTS_CREATE }>, Data<IndexScheduler>>,
req: HttpRequest,
opt: web::Data<Opt>,
analytics: web::Data<dyn Analytics>,
analytics: web::Data<Analytics>,
) -> Result<HttpResponse, ResponseError> {
analytics.publish("Snapshot Created".to_string(), json!({}), Some(&req));
analytics.publish(SnapshotAnalytics::default(), &req);
let task = KindWithContent::SnapshotCreation;
let uid = get_task_id(&req, &opt)?;

35
crates/meilisearch/src/routes/swap_indexes.rs
View File

@ -8,10 +8,10 @@ use meilisearch_types::error::deserr_codes::InvalidSwapIndexes;
use meilisearch_types::error::ResponseError;
use meilisearch_types::index_uid::IndexUid;
use meilisearch_types::tasks::{IndexSwap, KindWithContent};
use serde_json::json;
use serde::Serialize;
use super::{get_task_id, is_dry_run, SummarizedTaskView};
use crate::analytics::Analytics;
use crate::analytics::{Aggregate, Analytics};
use crate::error::MeilisearchHttpError;
use crate::extractors::authentication::policies::*;
use crate::extractors::authentication::{AuthenticationError, GuardedData};
@ -29,21 +29,36 @@ pub struct SwapIndexesPayload {
indexes: Vec<IndexUid>,
}
#[derive(Serialize)]
struct IndexSwappedAnalytics {
swap_operation_number: usize,
}
impl Aggregate for IndexSwappedAnalytics {
fn event_name(&self) -> &'static str {
"Indexes Swapped"
}
fn aggregate(self: Box<Self>, new: Box<Self>) -> Box<Self> {
Box::new(Self {
swap_operation_number: self.swap_operation_number.max(new.swap_operation_number),
})
}
fn into_event(self: Box<Self>) -> serde_json::Value {
serde_json::to_value(*self).unwrap_or_default()
}
}
pub async fn swap_indexes(
index_scheduler: GuardedData<ActionPolicy<{ actions::INDEXES_SWAP }>, Data<IndexScheduler>>,
params: AwebJson<Vec<SwapIndexesPayload>, DeserrJsonError>,
req: HttpRequest,
opt: web::Data<Opt>,
analytics: web::Data<dyn Analytics>,
analytics: web::Data<Analytics>,
) -> Result<HttpResponse, ResponseError> {
let params = params.into_inner();
analytics.publish(
"Indexes Swapped".to_string(),
json!({
"swap_operation_number": params.len(),
}),
Some(&req),
);
analytics.publish(IndexSwappedAnalytics { swap_operation_number: params.len() }, &req);
let filters = index_scheduler.filters();
let mut swaps = vec![];

129
crates/meilisearch/src/routes/tasks.rs
View File

@ -12,18 +12,17 @@ use meilisearch_types::star_or::{OptionStarOr, OptionStarOrList};
use meilisearch_types::task_view::TaskView;
use meilisearch_types::tasks::{Kind, KindWithContent, Status};
use serde::Serialize;
use serde_json::json;
use time::format_description::well_known::Rfc3339;
use time::macros::format_description;
use time::{Date, Duration, OffsetDateTime, Time};
use tokio::task;
use super::{get_task_id, is_dry_run, SummarizedTaskView};
use crate::analytics::Analytics;
use crate::analytics::{Aggregate, AggregateMethod, Analytics};
use crate::extractors::authentication::policies::*;
use crate::extractors::authentication::GuardedData;
use crate::extractors::sequential_extractor::SeqHandler;
use crate::Opt;
use crate::{aggregate_methods, Opt};
const DEFAULT_LIMIT: u32 = 20;
@ -158,12 +157,69 @@ impl TaskDeletionOrCancelationQuery {
}
}
aggregate_methods!(
CancelTasks => "Tasks Canceled",
DeleteTasks => "Tasks Deleted",
);
#[derive(Serialize)]
struct TaskFilterAnalytics<Method: AggregateMethod> {
filtered_by_uid: bool,
filtered_by_index_uid: bool,
filtered_by_type: bool,
filtered_by_status: bool,
filtered_by_canceled_by: bool,
filtered_by_before_enqueued_at: bool,
filtered_by_after_enqueued_at: bool,
filtered_by_before_started_at: bool,
filtered_by_after_started_at: bool,
filtered_by_before_finished_at: bool,
filtered_by_after_finished_at: bool,
#[serde(skip)]
marker: std::marker::PhantomData<Method>,
}
impl<Method: AggregateMethod + 'static> Aggregate for TaskFilterAnalytics<Method> {
fn event_name(&self) -> &'static str {
Method::event_name()
}
fn aggregate(self: Box<Self>, new: Box<Self>) -> Box<Self> {
Box::new(Self {
filtered_by_uid: self.filtered_by_uid | new.filtered_by_uid,
filtered_by_index_uid: self.filtered_by_index_uid | new.filtered_by_index_uid,
filtered_by_type: self.filtered_by_type | new.filtered_by_type,
filtered_by_status: self.filtered_by_status | new.filtered_by_status,
filtered_by_canceled_by: self.filtered_by_canceled_by | new.filtered_by_canceled_by,
filtered_by_before_enqueued_at: self.filtered_by_before_enqueued_at
| new.filtered_by_before_enqueued_at,
filtered_by_after_enqueued_at: self.filtered_by_after_enqueued_at
| new.filtered_by_after_enqueued_at,
filtered_by_before_started_at: self.filtered_by_before_started_at
| new.filtered_by_before_started_at,
filtered_by_after_started_at: self.filtered_by_after_started_at
| new.filtered_by_after_started_at,
filtered_by_before_finished_at: self.filtered_by_before_finished_at
| new.filtered_by_before_finished_at,
filtered_by_after_finished_at: self.filtered_by_after_finished_at
| new.filtered_by_after_finished_at,
marker: std::marker::PhantomData,
})
}
fn into_event(self: Box<Self>) -> serde_json::Value {
serde_json::to_value(*self).unwrap_or_default()
}
}
async fn cancel_tasks(
index_scheduler: GuardedData<ActionPolicy<{ actions::TASKS_CANCEL }>, Data<IndexScheduler>>,
params: AwebQueryParameter<TaskDeletionOrCancelationQuery, DeserrQueryParamError>,
req: HttpRequest,
opt: web::Data<Opt>,
analytics: web::Data<dyn Analytics>,
analytics: web::Data<Analytics>,
) -> Result<HttpResponse, ResponseError> {
let params = params.into_inner();
@ -172,21 +228,22 @@ async fn cancel_tasks(
}
analytics.publish(
"Tasks Canceled".to_string(),
json!({
"filtered_by_uid": params.uids.is_some(),
"filtered_by_index_uid": params.index_uids.is_some(),
"filtered_by_type": params.types.is_some(),
"filtered_by_status": params.statuses.is_some(),
"filtered_by_canceled_by": params.canceled_by.is_some(),
"filtered_by_before_enqueued_at": params.before_enqueued_at.is_some(),
"filtered_by_after_enqueued_at": params.after_enqueued_at.is_some(),
"filtered_by_before_started_at": params.before_started_at.is_some(),
"filtered_by_after_started_at": params.after_started_at.is_some(),
"filtered_by_before_finished_at": params.before_finished_at.is_some(),
"filtered_by_after_finished_at": params.after_finished_at.is_some(),
}),
Some(&req),
TaskFilterAnalytics::<CancelTasks> {
filtered_by_uid: params.uids.is_some(),
filtered_by_index_uid: params.index_uids.is_some(),
filtered_by_type: params.types.is_some(),
filtered_by_status: params.statuses.is_some(),
filtered_by_canceled_by: params.canceled_by.is_some(),
filtered_by_before_enqueued_at: params.before_enqueued_at.is_some(),
filtered_by_after_enqueued_at: params.after_enqueued_at.is_some(),
filtered_by_before_started_at: params.before_started_at.is_some(),
filtered_by_after_started_at: params.after_started_at.is_some(),
filtered_by_before_finished_at: params.before_finished_at.is_some(),
filtered_by_after_finished_at: params.after_finished_at.is_some(),
marker: std::marker::PhantomData,
},
&req,
);
let query = params.into_query();
@ -214,7 +271,7 @@ async fn delete_tasks(
params: AwebQueryParameter<TaskDeletionOrCancelationQuery, DeserrQueryParamError>,
req: HttpRequest,
opt: web::Data<Opt>,
analytics: web::Data<dyn Analytics>,
analytics: web::Data<Analytics>,
) -> Result<HttpResponse, ResponseError> {
let params = params.into_inner();
@ -223,22 +280,24 @@ async fn delete_tasks(
}
analytics.publish(
"Tasks Deleted".to_string(),
json!({
"filtered_by_uid": params.uids.is_some(),
"filtered_by_index_uid": params.index_uids.is_some(),
"filtered_by_type": params.types.is_some(),
"filtered_by_status": params.statuses.is_some(),
"filtered_by_canceled_by": params.canceled_by.is_some(),
"filtered_by_before_enqueued_at": params.before_enqueued_at.is_some(),
"filtered_by_after_enqueued_at": params.after_enqueued_at.is_some(),
"filtered_by_before_started_at": params.before_started_at.is_some(),
"filtered_by_after_started_at": params.after_started_at.is_some(),
"filtered_by_before_finished_at": params.before_finished_at.is_some(),
"filtered_by_after_finished_at": params.after_finished_at.is_some(),
}),
Some(&req),
TaskFilterAnalytics::<DeleteTasks> {
filtered_by_uid: params.uids.is_some(),
filtered_by_index_uid: params.index_uids.is_some(),
filtered_by_type: params.types.is_some(),
filtered_by_status: params.statuses.is_some(),
filtered_by_canceled_by: params.canceled_by.is_some(),
filtered_by_before_enqueued_at: params.before_enqueued_at.is_some(),
filtered_by_after_enqueued_at: params.after_enqueued_at.is_some(),
filtered_by_before_started_at: params.before_started_at.is_some(),
filtered_by_after_started_at: params.after_started_at.is_some(),
filtered_by_before_finished_at: params.before_finished_at.is_some(),
filtered_by_after_finished_at: params.after_finished_at.is_some(),
marker: std::marker::PhantomData,
},
&req,
);
let query = params.into_query();
let (tasks, _) = index_scheduler.get_task_ids_from_authorized_indexes(

9
crates/meilisearch/src/search/mod.rs
View File

@ -1195,8 +1195,13 @@ impl<'a> HitMaker<'a> {
let vectors_is_hidden = match (&displayed_ids, vectors_fid) {
// displayed_ids is a wildcard, so `_vectors` can be displayed regardless of its fid
(None, _) => false,
// displayed_ids is a finite list, and `_vectors` cannot be part of it because it is not an existing field
(Some(_), None) => true,
// vectors has no fid, so check its explicit name
(Some(_), None) => {
// unwrap as otherwise we'd go to the first one
let displayed_names = index.displayed_fields(rtxn)?.unwrap();
!displayed_names
.contains(&milli::vector::parsed_vectors::RESERVED_VECTORS_FIELD_NAME)
}
// displayed_ids is a finit list, so hide if `_vectors` is not part of it
(Some(map), Some(vectors_fid)) => map.contains(&vectors_fid),
};

1
crates/meilisearch/tests/common/server.rs
View File

@ -386,7 +386,6 @@ pub fn default_settings(dir: impl AsRef<Path>) -> Opt {
db_path: dir.as_ref().join("db"),
dump_dir: dir.as_ref().join("dumps"),
env: "development".to_owned(),
#[cfg(feature = "analytics")]
no_analytics: true,
max_index_size: Byte::from_u64_with_unit(100, Unit::MiB).unwrap(),
max_task_db_size: Byte::from_u64_with_unit(1, Unit::GiB).unwrap(),

5
crates/meilisearch/tests/common/service.rs
View File

@ -9,8 +9,9 @@ use actix_web::test;
use actix_web::test::TestRequest;
use actix_web::web::Data;
use index_scheduler::IndexScheduler;
use meilisearch::analytics::Analytics;
use meilisearch::search_queue::SearchQueue;
use meilisearch::{analytics, create_app, Opt, SubscriberForSecondLayer};
use meilisearch::{create_app, Opt, SubscriberForSecondLayer};
use meilisearch_auth::AuthController;
use tracing::level_filters::LevelFilter;
use tracing_subscriber::Layer;
@ -141,7 +142,7 @@ impl Service {
Data::new(search_queue),
self.options.clone(),
(route_layer_handle, stderr_layer_handle),
analytics::MockAnalytics::new(&self.options),
Data::new(Analytics::no_analytics()),
true,
))
.await

5
crates/meilisearch/tests/logs/mod.rs
View File

@ -7,8 +7,9 @@ use std::str::FromStr;
use actix_web::http::header::ContentType;
use actix_web::web::Data;
use meili_snap::snapshot;
use meilisearch::analytics::Analytics;
use meilisearch::search_queue::SearchQueue;
use meilisearch::{analytics, create_app, Opt, SubscriberForSecondLayer};
use meilisearch::{create_app, Opt, SubscriberForSecondLayer};
use tracing::level_filters::LevelFilter;
use tracing_subscriber::layer::SubscriberExt;
use tracing_subscriber::Layer;
@ -54,7 +55,7 @@ async fn basic_test_log_stream_route() {
Data::new(search_queue),
server.service.options.clone(),
(route_layer_handle, stderr_layer_handle),
analytics::MockAnalytics::new(&server.service.options),
Data::new(Analytics::no_analytics()),
true,
))
.await;

51
crates/meilisearch/tests/search/hybrid.rs
View File

@ -568,6 +568,57 @@ async fn retrieve_vectors() {
]
"###);
// use explicit `_vectors` in displayed attributes
let (response, code) = index
.update_settings(json!({ "displayedAttributes": ["id", "title", "desc", "_vectors"]} ))
.await;
assert_eq!(202, code, "{:?}", response);
index.wait_task(response.uid()).await;
let (response, code) = index
.search_post(
json!({"q": "Captain", "hybrid": {"embedder": "default", "semanticRatio": 0.2}, "retrieveVectors": true}),
)
.await;
snapshot!(code, @"200 OK");
insta::assert_json_snapshot!(response["hits"], {"[]._vectors.default.embeddings" => "[vectors]"}, @r###"
[
{
"title": "Captain Planet",
"desc": "He's not part of the Marvel Cinematic Universe",
"id": "2",
"_vectors": {
"default": {
"embeddings": "[vectors]",
"regenerate": true
}
}
},
{
"title": "Captain Marvel",
"desc": "a Shazam ersatz",
"id": "3",
"_vectors": {
"default": {
"embeddings": "[vectors]",
"regenerate": true
}
}
},
{
"title": "Shazam!",
"desc": "a Captain Marvel ersatz",
"id": "1",
"_vectors": {
"default": {
"embeddings": "[vectors]",
"regenerate": true
}
}
}
]
"###);
// remove `_vectors` from displayed attributes
let (response, code) =
index.update_settings(json!({ "displayedAttributes": ["id", "title", "desc"]} )).await;

47
crates/meilisearch/tests/vector/settings.rs
View File

@ -4,6 +4,53 @@ use crate::common::{GetAllDocumentsOptions, Server};
use crate::json;
use crate::vector::generate_default_user_provided_documents;
#[actix_rt::test]
async fn field_unavailable_for_source() {
let server = Server::new().await;
let index = server.index("doggo");
let (value, code) = server.set_features(json!({"vectorStore": true})).await;
snapshot!(code, @"200 OK");
snapshot!(value, @r###"
{
"vectorStore": true,
"metrics": false,
"logsRoute": false,
"editDocumentsByFunction": false,
"containsFilter": false
}
"###);
let (response, code) = index
.update_settings(json!({
"embedders": { "manual": {"source": "userProvided", "documentTemplate": "{{doc.documentTemplate}}"}},
}))
.await;
snapshot!(code, @"400 Bad Request");
snapshot!(response, @r###"
{
"message": "`.embedders.manual`: Field `documentTemplate` unavailable for source `userProvided` (only available for sources: `huggingFace`, `openAi`, `ollama`, `rest`). Available fields: `source`, `dimensions`, `distribution`, `binaryQuantized`",
"code": "invalid_settings_embedders",
"type": "invalid_request",
"link": "https://docs.meilisearch.com/errors#invalid_settings_embedders"
}
"###);
let (response, code) = index
.update_settings(json!({
"embedders": { "default": {"source": "openAi", "revision": "42"}},
}))
.await;
snapshot!(code, @"400 Bad Request");
snapshot!(response, @r###"
{
"message": "`.embedders.default`: Field `revision` unavailable for source `openAi` (only available for sources: `huggingFace`). Available fields: `source`, `model`, `apiKey`, `documentTemplate`, `dimensions`, `distribution`, `url`, `binaryQuantized`",
"code": "invalid_settings_embedders",
"type": "invalid_request",
"link": "https://docs.meilisearch.com/errors#invalid_settings_embedders"
}
"###);
}
#[actix_rt::test]
async fn update_embedder() {
let server = Server::new().await;

18
crates/milli/Cargo.toml
View File

@ -79,8 +79,8 @@ hf-hub = { git = "https://github.com/dureuill/hf-hub.git", branch = "rust_tls",
] }
tiktoken-rs = "0.5.9"
liquid = "0.26.6"
rhai = { version = "1.19.0", features = ["serde", "no_module", "no_custom_syntax", "no_time", "sync"] }
arroy = { git = "https://github.com/meilisearch/arroy/", rev = "2386594dfb009ce08821a925ccc89fb8e30bf73d" }
rhai = { git = "https://github.com/rhaiscript/rhai", rev = "ef3df63121d27aacd838f366f2b83fd65f20a1e4", features = ["serde", "no_module", "no_custom_syntax", "no_time", "sync"] }
arroy = "0.5.0"
rand = "0.8.5"
tracing = "0.1.40"
ureq = { version = "2.10.0", features = ["json"] }
@ -98,16 +98,7 @@ rand = { version = "0.8.5", features = ["small_rng"] }
[features]
all-tokenizations = [
"charabia/chinese",
"charabia/hebrew",
"charabia/japanese",
"charabia/thai",
"charabia/korean",
"charabia/greek",
"charabia/khmer",
"charabia/vietnamese",
"charabia/swedish-recomposition",
"charabia/german-segmentation",
"charabia/default",
]
# Use POSIX semaphores instead of SysV semaphores in LMDB
@ -146,5 +137,8 @@ german = ["charabia/german-segmentation"]
# force swedish character recomposition
swedish-recomposition = ["charabia/swedish-recomposition"]
# allow turkish specialized tokenization
turkish = ["charabia/turkish"]
# allow CUDA support, see <https://github.com/meilisearch/meilisearch/issues/4306>
cuda = ["candle-core/cuda"]

1
crates/milli/src/error.rs
View File

@ -298,6 +298,7 @@ impl From<arroy::Error> for Error {
arroy::Error::InvalidVecDimension { expected, received } => {
Error::UserError(UserError::InvalidVectorDimensions { expected, found: received })
}
arroy::Error::BuildCancelled => Error::InternalError(InternalError::AbortedIndexation),
arroy::Error::DatabaseFull
| arroy::Error::InvalidItemAppend
| arroy::Error::UnmatchingDistance { .. }

29
crates/milli/src/index.rs
View File

@ -1610,24 +1610,6 @@ impl Index {
.unwrap_or_default())
}
pub fn arroy_readers<'a>(
&'a self,
rtxn: &'a RoTxn<'a>,
embedder_id: u8,
quantized: bool,
) -> impl Iterator<Item = Result<ArroyWrapper>> + 'a {
crate::vector::arroy_db_range_for_embedder(embedder_id).map_while(move |k| {
let reader = ArroyWrapper::new(self.vector_arroy, k, quantized);
// Here we don't care about the dimensions, but we want to know if we can read
// in the database or if its metadata are missing because there is no document with that many vectors.
match reader.dimensions(rtxn) {
Ok(_) => Some(Ok(reader)),
Err(arroy::Error::MissingMetadata(_)) => None,
Err(e) => Some(Err(e.into())),
}
})
}
pub(crate) fn put_search_cutoff(&self, wtxn: &mut RwTxn<'_>, cutoff: u64) -> heed::Result<()> {
self.main.remap_types::<Str, BEU64>().put(wtxn, main_key::SEARCH_CUTOFF, &cutoff)
}
@ -1649,14 +1631,9 @@ impl Index {
let embedding_configs = self.embedding_configs(rtxn)?;
for config in embedding_configs {
let embedder_id = self.embedder_category_id.get(rtxn, &config.name)?.unwrap();
let embeddings = self
.arroy_readers(rtxn, embedder_id, config.config.quantized())
.map_while(|reader| {
reader
.and_then(|r| r.item_vector(rtxn, docid).map_err(|e| e.into()))
.transpose()
})
.collect::<Result<Vec<_>>>()?;
let reader =
ArroyWrapper::new(self.vector_arroy, embedder_id, config.config.quantized());
let embeddings = reader.item_vectors(rtxn, docid)?;
res.insert(config.name.to_owned(), embeddings);
}
Ok(res)

12
crates/milli/src/search/new/vector_sort.rs
View File

@ -1,11 +1,10 @@
use std::iter::FromIterator;
use ordered_float::OrderedFloat;
use roaring::RoaringBitmap;
use super::ranking_rules::{RankingRule, RankingRuleOutput, RankingRuleQueryTrait};
use crate::score_details::{self, ScoreDetails};
use crate::vector::{DistributionShift, Embedder};
use crate::vector::{ArroyWrapper, DistributionShift, Embedder};
use crate::{DocumentId, Result, SearchContext, SearchLogger};
pub struct VectorSort<Q: RankingRuleQueryTrait> {
@ -53,14 +52,9 @@ impl<Q: RankingRuleQueryTrait> VectorSort<Q> {
vector_candidates: &RoaringBitmap,
) -> Result<()> {
let target = &self.target;
let mut results = Vec::new();
for reader in ctx.index.arroy_readers(ctx.txn, self.embedder_index, self.quantized) {
let nns_by_vector =
reader?.nns_by_vector(ctx.txn, target, self.limit, Some(vector_candidates))?;
results.extend(nns_by_vector.into_iter());
}
results.sort_unstable_by_key(|(_, distance)| OrderedFloat(*distance));
let reader = ArroyWrapper::new(ctx.index.vector_arroy, self.embedder_index, self.quantized);
let results = reader.nns_by_vector(ctx.txn, target, self.limit, Some(vector_candidates))?;
self.cached_sorted_docids = results.into_iter();
Ok(())

27
crates/milli/src/search/similar.rs
View File

@ -1,10 +1,9 @@
use std::sync::Arc;
use ordered_float::OrderedFloat;
use roaring::RoaringBitmap;
use crate::score_details::{self, ScoreDetails};
use crate::vector::Embedder;
use crate::vector::{ArroyWrapper, Embedder};
use crate::{filtered_universe, DocumentId, Filter, Index, Result, SearchResult};
pub struct Similar<'a> {
@ -71,23 +70,13 @@ impl<'a> Similar<'a> {
.get(self.rtxn, &self.embedder_name)?
.ok_or_else(|| crate::UserError::InvalidEmbedder(self.embedder_name.to_owned()))?;
let mut results = Vec::new();
for reader in self.index.arroy_readers(self.rtxn, embedder_index, self.quantized) {
let nns_by_item = reader?.nns_by_item(
self.rtxn,
self.id,
self.limit + self.offset + 1,
Some(&universe),
)?;
if let Some(mut nns_by_item) = nns_by_item {
results.append(&mut nns_by_item);
} else {
break;
}
}
results.sort_unstable_by_key(|(_, distance)| OrderedFloat(*distance));
let reader = ArroyWrapper::new(self.index.vector_arroy, embedder_index, self.quantized);
let results = reader.nns_by_item(
self.rtxn,
self.id,
self.limit + self.offset + 1,
Some(&universe),
)?;
let mut documents_ids = Vec::with_capacity(self.limit);
let mut document_scores = Vec::with_capacity(self.limit);

17
crates/milli/src/update/index_documents/mod.rs
View File

@ -689,9 +689,8 @@ where
key: None,
},
)?;
let first_id = crate::vector::arroy_db_range_for_embedder(index).next().unwrap();
let reader =
ArroyWrapper::new(self.index.vector_arroy, first_id, action.was_quantized);
ArroyWrapper::new(self.index.vector_arroy, index, action.was_quantized);
let dim = reader.dimensions(self.wtxn)?;
dimension.insert(name.to_string(), dim);
}
@ -700,6 +699,7 @@ where
for (embedder_name, dimension) in dimension {
let wtxn = &mut *self.wtxn;
let vector_arroy = self.index.vector_arroy;
let cancel = &self.should_abort;
let embedder_index = self.index.embedder_category_id.get(wtxn, &embedder_name)?.ok_or(
InternalError::DatabaseMissingEntry { db_name: "embedder_category_id", key: None },
@ -713,17 +713,8 @@ where
let is_quantizing = embedder_config.map_or(false, |action| action.is_being_quantized);
pool.install(|| {
for k in crate::vector::arroy_db_range_for_embedder(embedder_index) {
let mut writer = ArroyWrapper::new(vector_arroy, k, was_quantized);
if is_quantizing {
writer.quantize(wtxn, k, dimension)?;
}
if writer.need_build(wtxn, dimension)? {
writer.build(wtxn, &mut rng, dimension)?;
} else if writer.is_empty(wtxn, dimension)? {
break;
}
}
let mut writer = ArroyWrapper::new(vector_arroy, embedder_index, was_quantized);
writer.build_and_quantize(wtxn, &mut rng, dimension, is_quantizing, cancel)?;
Result::Ok(())
})
.map_err(InternalError::from)??;

63
crates/milli/src/update/index_documents/transform.rs
View File

@ -990,27 +990,24 @@ impl<'a, 'i> Transform<'a, 'i> {
None
};
let readers: Result<BTreeMap<&str, (Vec<ArroyWrapper>, &RoaringBitmap)>> = settings_diff
let readers: BTreeMap<&str, (ArroyWrapper, &RoaringBitmap)> = settings_diff
.embedding_config_updates
.iter()
.filter_map(|(name, action)| {
if let Some(WriteBackToDocuments { embedder_id, user_provided }) =
action.write_back()
{
let readers: Result<Vec<_>> = self
.index
.arroy_readers(wtxn, *embedder_id, action.was_quantized)
.collect();
match readers {
Ok(readers) => Some(Ok((name.as_str(), (readers, user_provided)))),
Err(error) => Some(Err(error)),
}
let reader = ArroyWrapper::new(
self.index.vector_arroy,
*embedder_id,
action.was_quantized,
);
Some((name.as_str(), (reader, user_provided)))
} else {
None
}
})
.collect();
let readers = readers?;
let old_vectors_fid = settings_diff
.old
@ -1048,34 +1045,24 @@ impl<'a, 'i> Transform<'a, 'i> {
arroy::Error,
> = readers
.iter()
.filter_map(|(name, (readers, user_provided))| {
.filter_map(|(name, (reader, user_provided))| {
if !user_provided.contains(docid) {
return None;
}
let mut vectors = Vec::new();
for reader in readers {
let Some(vector) = reader.item_vector(wtxn, docid).transpose() else {
break;
};
match vector {
Ok(vector) => vectors.push(vector),
Err(error) => return Some(Err(error)),
}
match reader.item_vectors(wtxn, docid) {
Ok(vectors) if vectors.is_empty() => None,
Ok(vectors) => Some(Ok((
name.to_string(),
serde_json::to_value(ExplicitVectors {
embeddings: Some(
VectorOrArrayOfVectors::from_array_of_vectors(vectors),
),
regenerate: false,
})
.unwrap(),
))),
Err(e) => Some(Err(e)),
}
if vectors.is_empty() {
return None;
}
Some(Ok((
name.to_string(),
serde_json::to_value(ExplicitVectors {
embeddings: Some(VectorOrArrayOfVectors::from_array_of_vectors(
vectors,
)),
regenerate: false,
})
.unwrap(),
)))
})
.collect();
@ -1104,11 +1091,9 @@ impl<'a, 'i> Transform<'a, 'i> {
}
// delete all vectors from the embedders that need removal
for (_, (readers, _)) in readers {
for reader in readers {
let dimensions = reader.dimensions(wtxn)?;
reader.clear(wtxn, dimensions)?;
}
for (_, (reader, _)) in readers {
let dimensions = reader.dimensions(wtxn)?;
reader.clear(wtxn, dimensions)?;
}
let grenad_params = GrenadParameters {

57
crates/milli/src/update/index_documents/typed_chunk.rs
View File

@ -673,22 +673,14 @@ pub(crate) fn write_typed_chunk_into_index(
.get(&embedder_name)
.map_or(false, |conf| conf.2);
// FIXME: allow customizing distance
let writers: Vec<_> = crate::vector::arroy_db_range_for_embedder(embedder_index)
.map(|k| ArroyWrapper::new(index.vector_arroy, k, binary_quantized))
.collect();
let writer = ArroyWrapper::new(index.vector_arroy, embedder_index, binary_quantized);
// remove vectors for docids we want them removed
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 {
// Uses invariant: vectors are packed in the first writers.
if !writer.del_item(wtxn, expected_dimension, docid)? {
break;
}
}
writer.del_items(wtxn, expected_dimension, docid)?;
}
// add generated embeddings
@ -716,9 +708,7 @@ pub(crate) fn write_typed_chunk_into_index(
embeddings.embedding_count(),
)));
}
for (embedding, writer) in embeddings.iter().zip(&writers) {
writer.add_item(wtxn, expected_dimension, docid, embedding)?;
}
writer.add_items(wtxn, docid, &embeddings)?;
}
// perform the manual diff
@ -733,51 +723,14 @@ pub(crate) fn write_typed_chunk_into_index(
if let Some(value) = vector_deladd_obkv.get(DelAdd::Deletion) {
let vector: Vec<f32> = pod_collect_to_vec(value);
let mut deleted_index = None;
for (index, writer) in writers.iter().enumerate() {
let Some(candidate) = writer.item_vector(wtxn, docid)? else {
// uses invariant: vectors are packed in the first writers.
break;
};
if candidate == vector {
writer.del_item(wtxn, expected_dimension, docid)?;
deleted_index = Some(index);
}
}
// 🥲 enforce invariant: vectors are packed in the first writers.
if let Some(deleted_index) = deleted_index {
let mut last_index_with_a_vector = None;
for (index, writer) in writers.iter().enumerate().skip(deleted_index) {
let Some(candidate) = writer.item_vector(wtxn, docid)? else {
break;
};
last_index_with_a_vector = Some((index, candidate));
}
if let Some((last_index, vector)) = last_index_with_a_vector {
// unwrap: computed the index from the list of writers
let writer = writers.get(last_index).unwrap();
writer.del_item(wtxn, expected_dimension, docid)?;
writers.get(deleted_index).unwrap().add_item(
wtxn,
expected_dimension,
docid,
&vector,
)?;
}
}
writer.del_item(wtxn, docid, &vector)?;
}
if let Some(value) = vector_deladd_obkv.get(DelAdd::Addition) {
let vector = pod_collect_to_vec(value);
// overflow was detected during vector extraction.
for writer in &writers {
if !writer.contains_item(wtxn, expected_dimension, docid)? {
writer.add_item(wtxn, expected_dimension, docid, &vector)?;
break;
}
}
writer.add_item(wtxn, docid, &vector)?;
}
}

353
crates/milli/src/vector/mod.rs
View File

@ -1,7 +1,7 @@
use std::collections::HashMap;
use std::sync::Arc;
use arroy::distances::{Angular, BinaryQuantizedAngular};
use arroy::distances::{BinaryQuantizedCosine, Cosine};
use arroy::ItemId;
use deserr::{DeserializeError, Deserr};
use heed::{RoTxn, RwTxn, Unspecified};
@ -32,105 +32,243 @@ pub const REQUEST_PARALLELISM: usize = 40;
pub struct ArroyWrapper {
quantized: bool,
index: u16,
embedder_index: u8,
database: arroy::Database<Unspecified>,
}
impl ArroyWrapper {
pub fn new(database: arroy::Database<Unspecified>, index: u16, quantized: bool) -> Self {
Self { database, index, quantized }
pub fn new(
database: arroy::Database<Unspecified>,
embedder_index: u8,
quantized: bool,
) -> Self {
Self { database, embedder_index, quantized }
}
pub fn index(&self) -> u16 {
self.index
pub fn embedder_index(&self) -> u8 {
self.embedder_index
}
fn readers<'a, D: arroy::Distance>(
&'a self,
rtxn: &'a RoTxn<'a>,
db: arroy::Database<D>,
) -> impl Iterator<Item = Result<arroy::Reader<D>, arroy::Error>> + 'a {
arroy_db_range_for_embedder(self.embedder_index).map_while(move |index| {
match arroy::Reader::open(rtxn, index, db) {
Ok(reader) => match reader.is_empty(rtxn) {
Ok(false) => Some(Ok(reader)),
Ok(true) => None,
Err(e) => Some(Err(e)),
},
Err(arroy::Error::MissingMetadata(_)) => None,
Err(e) => Some(Err(e)),
}
})
}
pub fn dimensions(&self, rtxn: &RoTxn) -> Result<usize, arroy::Error> {
let first_id = arroy_db_range_for_embedder(self.embedder_index).next().unwrap();
if self.quantized {
Ok(arroy::Reader::open(rtxn, self.index, self.quantized_db())?.dimensions())
Ok(arroy::Reader::open(rtxn, first_id, self.quantized_db())?.dimensions())
} else {
Ok(arroy::Reader::open(rtxn, self.index, self.angular_db())?.dimensions())
Ok(arroy::Reader::open(rtxn, first_id, self.angular_db())?.dimensions())
}
}
pub fn quantize(
pub fn build_and_quantize<R: rand::Rng + rand::SeedableRng>(
&mut self,
wtxn: &mut RwTxn,
index: u16,
rng: &mut R,
dimension: usize,
quantizing: bool,
cancel: &(impl Fn() -> bool + Sync + Send),
) -> Result<(), arroy::Error> {
if !self.quantized {
let writer = arroy::Writer::new(self.angular_db(), index, dimension);
writer.prepare_changing_distance::<BinaryQuantizedAngular>(wtxn)?;
self.quantized = true;
for index in arroy_db_range_for_embedder(self.embedder_index) {
if self.quantized {
let writer = arroy::Writer::new(self.quantized_db(), index, dimension);
if writer.need_build(wtxn)? {
writer.builder(rng).build(wtxn)?
} else if writer.is_empty(wtxn)? {
break;
}
} else {
let writer = arroy::Writer::new(self.angular_db(), index, dimension);
// If we are quantizing the databases, we can't know from meilisearch
// if the db was empty but still contained the wrong metadata, thus we need
// to quantize everything and can't stop early. Since this operation can
// only happens once in the life of an embedder, it's not very performances
// sensitive.
if quantizing && !self.quantized {
let writer = writer.prepare_changing_distance::<BinaryQuantizedCosine>(wtxn)?;
writer.builder(rng).cancel(cancel).build(wtxn)?;
} else if writer.need_build(wtxn)? {
writer.builder(rng).cancel(cancel).build(wtxn)?;
} else if writer.is_empty(wtxn)? {
break;
}
}
}
Ok(())
}
pub fn need_build(&self, rtxn: &RoTxn, dimension: usize) -> Result<bool, arroy::Error> {
if self.quantized {
arroy::Writer::new(self.quantized_db(), self.index, dimension).need_build(rtxn)
} else {
arroy::Writer::new(self.angular_db(), self.index, dimension).need_build(rtxn)
}
}
pub fn build<R: rand::Rng + rand::SeedableRng>(
/// Overwrite all the embeddings associated with the index and item ID.
/// /!\ It won't remove embeddings after the last passed embedding, which can leave stale embeddings.
/// You should call `del_items` on the `item_id` before calling this method.
/// /!\ Cannot insert more than u8::MAX embeddings; after inserting u8::MAX embeddings, all the remaining ones will be silently ignored.
pub fn add_items(
&self,
wtxn: &mut RwTxn,
rng: &mut R,
dimension: usize,
item_id: arroy::ItemId,
embeddings: &Embeddings<f32>,
) -> Result<(), arroy::Error> {
if self.quantized {
arroy::Writer::new(self.quantized_db(), self.index, dimension).build(wtxn, rng, None)
} else {
arroy::Writer::new(self.angular_db(), self.index, dimension).build(wtxn, rng, None)
let dimension = embeddings.dimension();
for (index, vector) in
arroy_db_range_for_embedder(self.embedder_index).zip(embeddings.iter())
{
if self.quantized {
arroy::Writer::new(self.quantized_db(), index, dimension)
.add_item(wtxn, item_id, vector)?
} else {
arroy::Writer::new(self.angular_db(), index, dimension)
.add_item(wtxn, item_id, vector)?
}
}
Ok(())
}
/// Add one document int for this index where we can find an empty spot.
pub fn add_item(
&self,
wtxn: &mut RwTxn,
dimension: usize,
item_id: arroy::ItemId,
vector: &[f32],
) -> Result<(), arroy::Error> {
if self.quantized {
arroy::Writer::new(self.quantized_db(), self.index, dimension)
.add_item(wtxn, item_id, vector)
self._add_item(wtxn, self.quantized_db(), item_id, vector)
} else {
arroy::Writer::new(self.angular_db(), self.index, dimension)
.add_item(wtxn, item_id, vector)
self._add_item(wtxn, self.angular_db(), item_id, vector)
}
}
pub fn del_item(
fn _add_item<D: arroy::Distance>(
&self,
wtxn: &mut RwTxn,
db: arroy::Database<D>,
item_id: arroy::ItemId,
vector: &[f32],
) -> Result<(), arroy::Error> {
let dimension = vector.len();
for index in arroy_db_range_for_embedder(self.embedder_index) {
let writer = arroy::Writer::new(db, index, dimension);
if !writer.contains_item(wtxn, item_id)? {
writer.add_item(wtxn, item_id, vector)?;
break;
}
}
Ok(())
}
/// Delete all embeddings from a specific `item_id`
pub fn del_items(
&self,
wtxn: &mut RwTxn,
dimension: usize,
item_id: arroy::ItemId,
) -> Result<(), arroy::Error> {
for index in arroy_db_range_for_embedder(self.embedder_index) {
if self.quantized {
let writer = arroy::Writer::new(self.quantized_db(), index, dimension);
if !writer.del_item(wtxn, item_id)? {
break;
}
} else {
let writer = arroy::Writer::new(self.angular_db(), index, dimension);
if !writer.del_item(wtxn, item_id)? {
break;
}
}
}
Ok(())
}
/// Delete one item.
pub fn del_item(
&self,
wtxn: &mut RwTxn,
item_id: arroy::ItemId,
vector: &[f32],
) -> Result<bool, arroy::Error> {
if self.quantized {
arroy::Writer::new(self.quantized_db(), self.index, dimension).del_item(wtxn, item_id)
self._del_item(wtxn, self.quantized_db(), item_id, vector)
} else {
arroy::Writer::new(self.angular_db(), self.index, dimension).del_item(wtxn, item_id)
self._del_item(wtxn, self.angular_db(), item_id, vector)
}
}
fn _del_item<D: arroy::Distance>(
&self,
wtxn: &mut RwTxn,
db: arroy::Database<D>,
item_id: arroy::ItemId,
vector: &[f32],
) -> Result<bool, arroy::Error> {
let dimension = vector.len();
let mut deleted_index = None;
for index in arroy_db_range_for_embedder(self.embedder_index) {
let writer = arroy::Writer::new(db, index, dimension);
let Some(candidate) = writer.item_vector(wtxn, item_id)? else {
// uses invariant: vectors are packed in the first writers.
break;
};
if candidate == vector {
writer.del_item(wtxn, item_id)?;
deleted_index = Some(index);
}
}
// 🥲 enforce invariant: vectors are packed in the first writers.
if let Some(deleted_index) = deleted_index {
let mut last_index_with_a_vector = None;
for index in
arroy_db_range_for_embedder(self.embedder_index).skip(deleted_index as usize)
{
let writer = arroy::Writer::new(db, index, dimension);
let Some(candidate) = writer.item_vector(wtxn, item_id)? else {
break;
};
last_index_with_a_vector = Some((index, candidate));
}
if let Some((last_index, vector)) = last_index_with_a_vector {
let writer = arroy::Writer::new(db, last_index, dimension);
writer.del_item(wtxn, item_id)?;
let writer = arroy::Writer::new(db, deleted_index, dimension);
writer.add_item(wtxn, item_id, &vector)?;
}
}
Ok(deleted_index.is_some())
}
pub fn clear(&self, wtxn: &mut RwTxn, dimension: usize) -> Result<(), arroy::Error> {
if self.quantized {
arroy::Writer::new(self.quantized_db(), self.index, dimension).clear(wtxn)
} else {
arroy::Writer::new(self.angular_db(), self.index, dimension).clear(wtxn)
}
}
pub fn is_empty(&self, rtxn: &RoTxn, dimension: usize) -> Result<bool, arroy::Error> {
if self.quantized {
arroy::Writer::new(self.quantized_db(), self.index, dimension).is_empty(rtxn)
} else {
arroy::Writer::new(self.angular_db(), self.index, dimension).is_empty(rtxn)
for index in arroy_db_range_for_embedder(self.embedder_index) {
if self.quantized {
let writer = arroy::Writer::new(self.quantized_db(), index, dimension);
if writer.is_empty(wtxn)? {
break;
}
writer.clear(wtxn)?;
} else {
let writer = arroy::Writer::new(self.angular_db(), index, dimension);
if writer.is_empty(wtxn)? {
break;
}
writer.clear(wtxn)?;
}
}
Ok(())
}
pub fn contains_item(
@ -139,11 +277,25 @@ impl ArroyWrapper {
dimension: usize,
item: arroy::ItemId,
) -> Result<bool, arroy::Error> {
if self.quantized {
arroy::Writer::new(self.quantized_db(), self.index, dimension).contains_item(rtxn, item)
} else {
arroy::Writer::new(self.angular_db(), self.index, dimension).contains_item(rtxn, item)
for index in arroy_db_range_for_embedder(self.embedder_index) {
let contains = if self.quantized {
let writer = arroy::Writer::new(self.quantized_db(), index, dimension);
if writer.is_empty(rtxn)? {
break;
}
writer.contains_item(rtxn, item)?
} else {
let writer = arroy::Writer::new(self.angular_db(), index, dimension);
if writer.is_empty(rtxn)? {
break;
}
writer.contains_item(rtxn, item)?
};
if contains {
return Ok(contains);
}
}
Ok(false)
}
pub fn nns_by_item(
@ -152,45 +304,108 @@ impl ArroyWrapper {
item: ItemId,
limit: usize,
filter: Option<&RoaringBitmap>,
) -> Result<Option<Vec<(ItemId, f32)>>, arroy::Error> {
) -> Result<Vec<(ItemId, f32)>, arroy::Error> {
if self.quantized {
arroy::Reader::open(rtxn, self.index, self.quantized_db())?
.nns_by_item(rtxn, item, limit, None, None, filter)
self._nns_by_item(rtxn, self.quantized_db(), item, limit, filter)
} else {
arroy::Reader::open(rtxn, self.index, self.angular_db())?
.nns_by_item(rtxn, item, limit, None, None, filter)
self._nns_by_item(rtxn, self.angular_db(), item, limit, filter)
}
}
fn _nns_by_item<D: arroy::Distance>(
&self,
rtxn: &RoTxn,
db: arroy::Database<D>,
item: ItemId,
limit: usize,
filter: Option<&RoaringBitmap>,
) -> Result<Vec<(ItemId, f32)>, arroy::Error> {
let mut results = Vec::new();
for reader in self.readers(rtxn, db) {
let reader = reader?;
let mut searcher = reader.nns(limit);
if let Some(filter) = filter {
searcher.candidates(filter);
}
if let Some(mut ret) = searcher.by_item(rtxn, item)? {
results.append(&mut ret);
} else {
break;
}
}
results.sort_unstable_by_key(|(_, distance)| OrderedFloat(*distance));
Ok(results)
}
pub fn nns_by_vector(
&self,
txn: &RoTxn,
item: &[f32],
rtxn: &RoTxn,
vector: &[f32],
limit: usize,
filter: Option<&RoaringBitmap>,
) -> Result<Vec<(ItemId, f32)>, arroy::Error> {
if self.quantized {
arroy::Reader::open(txn, self.index, self.quantized_db())?
.nns_by_vector(txn, item, limit, None, None, filter)
self._nns_by_vector(rtxn, self.quantized_db(), vector, limit, filter)
} else {
arroy::Reader::open(txn, self.index, self.angular_db())?
.nns_by_vector(txn, item, limit, None, None, filter)
self._nns_by_vector(rtxn, self.angular_db(), vector, limit, filter)
}
}
pub fn item_vector(&self, rtxn: &RoTxn, docid: u32) -> Result<Option<Vec<f32>>, arroy::Error> {
fn _nns_by_vector<D: arroy::Distance>(
&self,
rtxn: &RoTxn,
db: arroy::Database<D>,
vector: &[f32],
limit: usize,
filter: Option<&RoaringBitmap>,
) -> Result<Vec<(ItemId, f32)>, arroy::Error> {
let mut results = Vec::new();
for reader in self.readers(rtxn, db) {
let reader = reader?;
let mut searcher = reader.nns(limit);
if let Some(filter) = filter {
searcher.candidates(filter);
}
results.append(&mut searcher.by_vector(rtxn, vector)?);
}
results.sort_unstable_by_key(|(_, distance)| OrderedFloat(*distance));
Ok(results)
}
pub fn item_vectors(&self, rtxn: &RoTxn, item_id: u32) -> Result<Vec<Vec<f32>>, arroy::Error> {
let mut vectors = Vec::new();
if self.quantized {
arroy::Reader::open(rtxn, self.index, self.quantized_db())?.item_vector(rtxn, docid)
for reader in self.readers(rtxn, self.quantized_db()) {
if let Some(vec) = reader?.item_vector(rtxn, item_id)? {
vectors.push(vec);
} else {
break;
}
}
} else {
arroy::Reader::open(rtxn, self.index, self.angular_db())?.item_vector(rtxn, docid)
for reader in self.readers(rtxn, self.angular_db()) {
if let Some(vec) = reader?.item_vector(rtxn, item_id)? {
vectors.push(vec);
} else {
break;
}
}
}
Ok(vectors)
}
fn angular_db(&self) -> arroy::Database<Angular> {
fn angular_db(&self) -> arroy::Database<Cosine> {
self.database.remap_data_type()
}
fn quantized_db(&self) -> arroy::Database<BinaryQuantizedAngular> {
fn quantized_db(&self) -> arroy::Database<BinaryQuantizedCosine> {
self.database.remap_data_type()
}
}

17
crates/milli/src/vector/settings.rs
View File

@ -417,6 +417,8 @@ impl EmbeddingSettings {
pub const DISTRIBUTION: &'static str = "distribution";
pub const BINARY_QUANTIZED: &'static str = "binaryQuantized";
pub fn allowed_sources_for_field(field: &'static str) -> &'static [EmbedderSource] {
match field {
Self::SOURCE => &[
@ -456,6 +458,13 @@ impl EmbeddingSettings {
EmbedderSource::Rest,
EmbedderSource::UserProvided,
],
Self::BINARY_QUANTIZED => &[
EmbedderSource::HuggingFace,
EmbedderSource::Ollama,
EmbedderSource::OpenAi,
EmbedderSource::Rest,
EmbedderSource::UserProvided,
],
_other => unreachable!("unknown field"),
}
}
@ -470,6 +479,7 @@ impl EmbeddingSettings {
Self::DIMENSIONS,
Self::DISTRIBUTION,
Self::URL,
Self::BINARY_QUANTIZED,
],
EmbedderSource::HuggingFace => &[
Self::SOURCE,
@ -477,6 +487,7 @@ impl EmbeddingSettings {
Self::REVISION,
Self::DOCUMENT_TEMPLATE,
Self::DISTRIBUTION,
Self::BINARY_QUANTIZED,
],
EmbedderSource::Ollama => &[
Self::SOURCE,
@ -486,8 +497,11 @@ impl EmbeddingSettings {
Self::API_KEY,
Self::DIMENSIONS,
Self::DISTRIBUTION,
Self::BINARY_QUANTIZED,
],
EmbedderSource::UserProvided => &[Self::SOURCE, Self::DIMENSIONS, Self::DISTRIBUTION],
EmbedderSource::UserProvided => {
&[Self::SOURCE, Self::DIMENSIONS, Self::DISTRIBUTION, Self::BINARY_QUANTIZED]
}
EmbedderSource::Rest => &[
Self::SOURCE,
Self::API_KEY,
@ -498,6 +512,7 @@ impl EmbeddingSettings {
Self::RESPONSE,
Self::HEADERS,
Self::DISTRIBUTION,
Self::BINARY_QUANTIZED,
],
}
}

21
workloads/search/embeddings-movies-subset-hf.json
View File

@ -77,7 +77,8 @@
"q": "puppy cute comforting movie",
"limit": 100,
"hybrid": {
"semanticRatio": 0.1
"semanticRatio": 0.1,
"embedder": "default"
}
}
},
@ -91,7 +92,8 @@
"q": "puppy cute comforting movie",
"limit": 100,
"hybrid": {
"semanticRatio": 0.5
"semanticRatio": 0.5,
"embedder": "default"
}
}
},
@ -105,7 +107,8 @@
"q": "puppy cute comforting movie",
"limit": 100,
"hybrid": {
"semanticRatio": 0.9
"semanticRatio": 0.9,
"embedder": "default"
}
}
},
@ -119,7 +122,8 @@
"q": "puppy cute comforting movie",
"limit": 100,
"hybrid": {
"semanticRatio": 1.0
"semanticRatio": 1.0,
"embedder": "default"
}
}
},
@ -133,7 +137,8 @@
"q": "shrek",
"limit": 100,
"hybrid": {
"semanticRatio": 1.0
"semanticRatio": 1.0,
"embedder": "default"
}
}
},
@ -147,7 +152,8 @@
"q": "shrek",
"limit": 100,
"hybrid": {
"semanticRatio": 0.5
"semanticRatio": 0.5,
"embedder": "default"
}
}
},
@ -161,7 +167,8 @@
"q": "shrek",
"limit": 100,
"hybrid": {
"semanticRatio": 0.1
"semanticRatio": 0.1,
"embedder": "default"
}
}
},